@article{
 title = {Efficient Roof Selection in Rainwater Harvesting: Hybrid Multi-criteria and Experimental Approach},
 type = {article},
 year = {2025},
 pages = {1567-1586},
 volume = {39},
 websites = {https://link.springer.com/10.1007/s11269-024-04023-3},
 month = {3},
 day = {25},
 id = {1da24b27-8ccb-3d7a-80e0-919ae97f130d},
 created = {2024-11-25T13:50:49.855Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-04-19T11:21:43.383Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Hamidi, Muhammed Nimet and Shitreh, Shayan and Cengiz, Ali Izzet and Ozcelik, Kadir and Eryildiz-Yesir, Bahriye and Ekmekcioğlu, Ömer and Halat, Oguzhan Murat and Demirel, Mehmet Cuneyd and Canberk, Berk and Koyuncu, Ismail and Isik, Onur and Guven, Huseyin and Ozgun, Hale and Ersahin, Mustafa Evren},
 doi = {10.1007/s11269-024-04023-3},
 journal = {Water Resources Management},
 number = {4}
}

@article{
 title = {Effect of different likelihood measures on parameter conditioning and model uncertainty},
 type = {article},
 year = {2025},
 pages = {1091-1108},
 volume = {39},
 websites = {https://link.springer.com/10.1007/s00477-025-02909-1},
 month = {3},
 day = {24},
 id = {de331ccb-4e8e-3a9a-859a-5f50c5252676},
 created = {2025-01-31T08:16:43.689Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-04-19T11:21:43.378Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Baig, Faisal and Demirel, Mehmet Cuneyd and Taseer, Muhammad Yousaf Raza and Kassem, Assaad and Sherif, Mohsen},
 doi = {10.1007/s00477-025-02909-1},
 journal = {Stochastic Environmental Research and Risk Assessment},
 number = {3}
}

@misc{
 title = {Modeling the combined effects of the 2023 Türkiye-Syria Earthquake and an Atmospheric River event on landslide hazard},
 type = {misc},
 year = {2025},
 source = {Natural Hazards and Earth System Sciences (NHESS)},
 volume = {(under rev},
 websites = {https://egusphere.copernicus.org/preprints/2025/egusphere-2025-3011/},
 month = {7},
 day = {1},
 id = {dc0b0c8b-8faa-35f7-afc2-85c197d7abc5},
 created = {2025-07-01T18:26:09.026Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-09-19T11:49:17.149Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Abstract. This study investigates the landslide hazards resulting from the compound effects of the February 6, 2023 Türkiye-Syria earthquakes and a subsequent atmospheric river (AR) event that delivered up to 183 mm of rainfall across the earthquake-impacted region. Using the open-source Landlab modeling toolkit, we integrate global satellite datasets to simulate shallow landslide hazard at a regional scale. Our landslide hazard model incorporates earthquake legacy effects, a seismic driver accounting for post-seismic hillslope weakening, and rainfall drivers into a probabilistic implementation of the infinite slope stability theorem through a Monte Carlo approach. Model validation using landslide inventories and satellite-derived surface change metrics confirms improved performance for rainfall-driven landslide hazards when legacy effects are included. The legacy model reveals an approximately 13° reduction in critical slope angle and identifies high-hazard zones consistent with observed and inferred failures. Additionally, we analyze how the sequence of extreme seismic and rainfall events influences landslide hazard. We find that the scenario where the AR event precedes the earthquakes produces the greatest hazard, with median critical slopes up to 7° lower than other models in high-probability bins (probability of failure, P(F) > 0.6) and nearly double the number of grid cells exceeding P(F) > 0.8 compared to the next closest scenario. We demonstrate how using historical extreme rainfall records can effectively replicate post-seismic landslide hazard maps that use real-time data, offering a rapid approach for hazard forecasting in tectonically active and climate-sensitive regions.},
 bibtype = {misc},
 author = {Jimenez, Hunter N. and Istanbulluoglu, Erkan and Gorum, Tolga and Stanley, Thomas A. and Amatya, Pukar M. and Tanyas, Hakan and Demirel, Mehmet C. and Akgun, Aykut and Bozkurt, Deniz},
 doi = {10.5194/egusphere-2025-3011}
}

Abstract. This study investigates the landslide hazards resulting from the compound effects of the February 6, 2023 Türkiye-Syria earthquakes and a subsequent atmospheric river (AR) event that delivered up to 183 mm of rainfall across the earthquake-impacted region. Using the open-source Landlab modeling toolkit, we integrate global satellite datasets to simulate shallow landslide hazard at a regional scale. Our landslide hazard model incorporates earthquake legacy effects, a seismic driver accounting for post-seismic hillslope weakening, and rainfall drivers into a probabilistic implementation of the infinite slope stability theorem through a Monte Carlo approach. Model validation using landslide inventories and satellite-derived surface change metrics confirms improved performance for rainfall-driven landslide hazards when legacy effects are included. The legacy model reveals an approximately 13° reduction in critical slope angle and identifies high-hazard zones consistent with observed and inferred failures. Additionally, we analyze how the sequence of extreme seismic and rainfall events influences landslide hazard. We find that the scenario where the AR event precedes the earthquakes produces the greatest hazard, with median critical slopes up to 7° lower than other models in high-probability bins (probability of failure, P(F) > 0.6) and nearly double the number of grid cells exceeding P(F) > 0.8 compared to the next closest scenario. We demonstrate how using historical extreme rainfall records can effectively replicate post-seismic landslide hazard maps that use real-time data, offering a rapid approach for hazard forecasting in tectonically active and climate-sensitive regions.

@article{
 title = {Effects of Model Spatial Structure and Basin Characteristics on the Performance of Three Hydrologic Models},
 type = {article},
 year = {2025},
 volume = {(accepted)},
 websites = {https://link.springer.com/10.1007/s11269-025-04308-1},
 month = {7},
 day = {23},
 id = {5d7795fd-6bbe-3a16-9bbf-452ff68c8efd},
 created = {2025-07-23T13:23:24.910Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-07-23T13:25:46.288Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Kacar, F. Sencer and Bayhan, Kayhan and Gassner, Andreas and Ergun, Enes and Halat, Oguzhan Murat and Balov, Mustafa Nuri and Demirel, Mahmud Sami and Avcuoglu, Muhammet Bahattin and Babagiray, Salih and Calli, Suleyman Selim and Ghasempour, Roghayeh and Kirca, V. S. Ozgur and Demirel, Mehmet Cuneyd and Booij, Martijn J.},
 doi = {10.1007/s11269-025-04308-1},
 journal = {Water Resources Management}
}

@article{
 title = {Efficiency of multi-layer greywater and rainwater treatment for sustainable water management through water reuse in irrigation},
 type = {article},
 year = {2025},
 pages = {119158},
 volume = {13},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S2213343725038540},
 month = {10},
 id = {6d2fe721-bab4-3f9c-8459-299d02d13062},
 created = {2025-09-19T11:48:23.339Z},
 file_attached = {true},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-10-23T10:58:08.379Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Guven, Huseyin and Turkoz, Seda Nur and Ozcelik, Kadir and Nalbant, Berk and Demirel, Mehmet Cuneyd and Ekmekcioğlu, Omer and Canberk, Berk and Koyuncu, Ismail and Ersahin, Mustafa Evren and Ozgun, Hale and Isik, Onur},
 doi = {10.1016/j.jece.2025.119158},
 journal = {Journal of Environmental Chemical Engineering},
 number = {5}
}

@article{
 title = {Cost Efficiency Assessment of Four Pressure Management Methods in Water Distribution Systems},
 type = {article},
 year = {2024},
 volume = {150},
 websites = {https://ascelibrary.org/doi/10.1061/JWRMD5.WRENG-5984},
 month = {3},
 id = {0c9f36eb-7e07-3cb4-945e-a2ed9b4c3879},
 created = {2023-10-05T05:48:47.940Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2023-12-21T05:52:04.050Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Koşucu, Mehmet Melih and Demirel, Mehmet Cüneyd},
 doi = {10.1061/JWRMD5.WRENG-5984},
 journal = {Journal of Water Resources Planning and Management},
 number = {3}
}

@article{
 title = {Incorporating Spatio-Temporal Changes of Well Irrigation into a Distributed Hydrologic Model to Improve Groundwater Anomaly Estimations for Basins with Expanding Agricultural Lands},
 type = {article},
 year = {2024},
 pages = {3471-3487},
 volume = {38},
 websites = {https://doi.org/10.1007/s11269-024-03826-8,https://link.springer.com/10.1007/s11269-024-03826-8},
 month = {7},
 day = {22},
 id = {a3e1f0ac-894b-3557-8014-43a9428f90bb},
 created = {2024-03-23T05:31:40.278Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-04-20T19:19:58.168Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 source_type = {JOUR},
 private_publication = {false},
 abstract = {This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change.},
 bibtype = {article},
 author = {Koycegiz, Cihangir and Demirel, Mehmet Cuneyd and Sen, Omer Lutfi and Buyukyildiz, Meral},
 doi = {10.1007/s11269-024-03826-8},
 journal = {Water Resources Management},
 number = {9}
}

This paper seeks to address the deficiency of utilizing satellite-based GRACE observations and model-based GLDAS water budget components in estimating the changes in the groundwater storage in Konya Endorheic Basin (KEB), a basin experiencing considerable land use land cover (LULC) change, primarily agricultural expansion. Cereal cultivation in the basin has a slight decreasing trend, however, the cultivation of crops with high water consumption, such as maize and sunflower, is increasing substantially. And total agricultural areas are increasing. GRACE-GLDAS approach does not accurately give the long-term groundwater decline in the basin, mainly because the land surface models employed in GLDAS cannot realistically simulate variations in water budget components as they do not consider the changes in LULC and do not possess an elaborated irrigation scheme. Here, we used a fully-distributed mesoscale hydrologic model, mHM, that can handle multiple LULC maps from different years. The model was modified to incorporate the spatio-temporal changes of agricultural fields in KEB and an explicit irrigation scheme since we hypothesized that the groundwater depletion is mainly caused by well irrigation. mHM was calibrated against streamflow observations for the period 2004–2019. The simulations show that the use of mHM with the incorporated features gives groundwater storage changes that are more consistent with the well-based observations than those obtained from the GRACE-GLDAS approach. On the other hand, the mHM simulation with a static LULC map, as in GLDAS models but with a better representation of irrigated fields, provides groundwater anomaly changes that are more consistent with the GRACE-GLDAS results, a further justification of insufficiency of the GLDAS-based approach in estimating groundwater variations for basins with considerable landscape change.

@article{
 title = {Tradeoffs Between Temporal and Spatial Pattern Calibration and Their Impacts on Robustness and Transferability of Hydrologic Model Parameters to Ungauged Basins},
 type = {article},
 year = {2024},
 volume = {60},
 websites = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022WR034193},
 month = {1},
 day = {8},
 id = {69d3b9f2-2977-38c6-8733-32346f360a7b},
 created = {2024-04-26T12:25:56.355Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-04-29T10:45:45.764Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi‐objective and transferability studies by exploring the value of both multi‐basin and spatial pattern calibration of distributed hydrologic models as compared to single‐basin and single‐objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns. Several model validation experiments are performed through combinations of single‐ (temporal evaluation through discharge) and multi‐objective (temporal and spatial evaluation through discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi‐basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets.},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Koch, Julian and Rakovec, Oldrich and Kumar, Rohini and Mai, Juliane and Müller, Sebastian and Thober, Stephan and Samaniego, Luis and Stisen, Simon},
 doi = {10.1029/2022WR034193},
 journal = {Water Resources Research},
 number = {1}
}

Optimization of spatially consistent parameter fields is believed to increase the robustness of parameter estimation and its transferability to ungauged basins. The current paper extends previous multi‐objective and transferability studies by exploring the value of both multi‐basin and spatial pattern calibration of distributed hydrologic models as compared to single‐basin and single‐objective model calibrations, with respect to tradeoffs, performance and transferability. The mesoscale Hydrological Model (mHM) is used across six large central European basins. Model simulations are evaluated against streamflow observations at the basin outlets and remotely sensed evapotranspiration patterns. Several model validation experiments are performed through combinations of single‐ (temporal evaluation through discharge) and multi‐objective (temporal and spatial evaluation through discharge and spatial evapotranspiration patterns) calibrations with holdout experiments saving alternating basins for model evaluation. The study shows that there are very minimal tradeoffs between spatial and temporal performance objectives and that a joint calibration of multiple basins using multiple objective functions provides the most robust estimations of parameter fields that perform better when transferred to ungauged basins. The study indicates that particularly the multi‐basin calibration approach is key for robust parametrizations, and that the addition of an objective function tailored for matching spatial patterns of ET fields alters the spatial parameter fields while significantly improving the spatial pattern performance without any tradeoffs with discharge performance. In light of model equifinality, the minimal tradeoff between spatial and temporal performance shows that adding spatial pattern evaluation to the traditional temporal evaluation of hydrological models can assist in identifying optimal parameter sets.

@article{
 title = {Toward robust pattern similarity metric for distributed model evaluation},
 type = {article},
 year = {2024},
 pages = {4007-4025},
 volume = {38},
 websites = {https://link.springer.com/10.1007/s00477-024-02790-4},
 month = {10},
 day = {2},
 id = {b9c42cb0-c845-3d48-9ea4-8fa51fcec958},
 created = {2024-08-01T09:29:51.955Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-10-12T16:10:39.315Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Yorulmaz, Eymen Berkay and Kartal, Elif and Demirel, Mehmet Cüneyd},
 doi = {10.1007/s00477-024-02790-4},
 journal = {Stochastic Environmental Research and Risk Assessment},
 number = {10}
}

@article{
 title = {Combined Drought Index Using High-Resolution Hydrological Models and Explainable Artificial Intelligence Techniques in Türkiye},
 type = {article},
 year = {2024},
 keywords = {SHAP,XGBoost,agricultural drought,combined drought indices,crop yield},
 pages = {3799},
 volume = {16},
 websites = {https://www.mdpi.com/2072-4292/16/20/3799/htm,https://www.mdpi.com/2072-4292/16/20/3799},
 month = {10},
 publisher = {Multidisciplinary Digital Publishing Institute},
 day = {12},
 id = {542b749b-19e8-36d0-8547-d36d7c38a298},
 created = {2024-10-12T15:22:24.290Z},
 accessed = {2024-10-12},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2025-09-19T11:49:17.139Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {54f9a1cb-cd85-43bf-81c7-692f1856eaa8},
 private_publication = {false},
 abstract = {We developed a combined drought index to better monitor agricultural drought events. To develop the index, different combinations of the temperature condition index, precipitation condition index, vegetation condition index, soil moisture condition index, gross primary productivity, and normalized difference water index were used to obtain a single drought severity index. To obtain more effective results, a mesoscale hydrologic model was used to obtain soil moisture values. The SHapley Additive exPlanations (SHAP) algorithm was used to calculate the weights for the combined index. To provide input to the SHAP model, crop yield was predicted using a machine learning model, with the training set yielding a correlation coefficient (R) of 0.8, while the test set values were calculated to be 0.68. The representativeness of the new index in drought situations was compared with established indices, including the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Self-Calibrated Palmer Drought Severity Index (scPDSI). The index showed the highest correlation with an R-value of 0.82, followed by the SPEI with 0.7 and scPDSI with 0.48. This study contributes a different perspective for effective detection of agricultural drought events. The integration of an increased volume of data from remote sensing systems with technological advances could facilitate the development of significantly more efficient agricultural drought monitoring systems.},
 bibtype = {article},
 author = {Başakın, Eyyup Ensar and Stoy, Paul C. and Demirel, Mehmet Cüneyd and Ozdogan, Mutlu and Otkin, Jason A.},
 doi = {10.3390/rs16203799},
 journal = {Remote Sensing},
 number = {20}
}

We developed a combined drought index to better monitor agricultural drought events. To develop the index, different combinations of the temperature condition index, precipitation condition index, vegetation condition index, soil moisture condition index, gross primary productivity, and normalized difference water index were used to obtain a single drought severity index. To obtain more effective results, a mesoscale hydrologic model was used to obtain soil moisture values. The SHapley Additive exPlanations (SHAP) algorithm was used to calculate the weights for the combined index. To provide input to the SHAP model, crop yield was predicted using a machine learning model, with the training set yielding a correlation coefficient (R) of 0.8, while the test set values were calculated to be 0.68. The representativeness of the new index in drought situations was compared with established indices, including the Standardized Precipitation-Evapotranspiration Index (SPEI) and the Self-Calibrated Palmer Drought Severity Index (scPDSI). The index showed the highest correlation with an R-value of 0.82, followed by the SPEI with 0.7 and scPDSI with 0.48. This study contributes a different perspective for effective detection of agricultural drought events. The integration of an increased volume of data from remote sensing systems with technological advances could facilitate the development of significantly more efficient agricultural drought monitoring systems.

@article{
 title = {Spatiotemporal Variability of Gross Primary Productivity in Türkiye: A Multi-Source and Multi-Method Assessment},
 type = {article},
 year = {2024},
 pages = {1994},
 volume = {16},
 websites = {https://www.mdpi.com/2072-4292/16/11/1994},
 month = {5},
 day = {31},
 id = {d8026f39-715b-318f-adcf-aaa8f5becd40},
 created = {2024-10-12T15:48:22.177Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-10-12T15:48:22.177Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over Türkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal–Wallis and Mann–Whitney U methods, and long-term trends were analyzed using Modified Mann–Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of Türkiye (χ2 values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest ‘greening’ for Türkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of Türkiye.},
 bibtype = {article},
 author = {Başakın, Eyyup Ensar and Stoy, Paul C. and Demirel, Mehmet Cüneyd and Pham, Quoc Bao},
 doi = {10.3390/rs16111994},
 journal = {Remote Sensing},
 number = {11}
}

We investigated the spatiotemporal variability of remotely sensed gross primary productivity (GPP) over Türkiye based on MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2 GPP products. The differences in various GPP products were assessed using Kruskal–Wallis and Mann–Whitney U methods, and long-term trends were analyzed using Modified Mann–Kendall (MMK), innovative trend analysis (ITA), and empirical mode decomposition (EMD). Our results show that at least one GPP product significantly differs from the others over the seven geographic regions of Türkiye (χ2 values of 50.8, 21.9, 76.9, 42.6, 149, 34.5, and 168; p < 0.05), and trend analyses reveal a significant increase in GPP from all satellite-based products over the latter half of the study period. Throughout the year, the average number of months in which each dataset showed significant increases across all study regions are 6.7, 8.1, 5.9, 9.6, and 8.7 for MODIS, TL-LUE, GOSIF, MuSyQ, and PMLV2, respectively. The ITA and EMD methods provided additional insight into the MMK test in both visualizing and detecting trends due to their graphical techniques. Overall, the GPP products investigated here suggest ‘greening’ for Türkiye, consistent with the findings from global studies, but the use of different statistical approaches and satellite-based GPP estimates creates different interpretations of how these trends have emerged. Ground stations, such as eddy covariance towers, can help further improve our understanding of the carbon cycle across the diverse ecosystem of Türkiye.

@article{
 title = {On the use of distributed hydrologic model for filling large gaps at different parts of the streamflow data},
 type = {article},
 year = {2023},
 pages = {101321},
 volume = {37},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S2215098622002300},
 month = {1},
 id = {6aa838c4-2486-3fa4-a8f6-457467907453},
 created = {2022-12-30T20:04:52.858Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2023-04-02T09:06:18.987Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {Ergun2023},
 private_publication = {false},
 bibtype = {article},
 author = {Ergün, Enes and Demirel, Mehmet Cüneyd},
 doi = {10.1016/j.jestch.2022.101321},
 journal = {Engineering Science and Technology, an International Journal}
}

@inproceedings{
 title = {Spatial pattern-oriented optimization of regional scale hydrological models (EGU23-7955)},
 type = {inproceedings},
 year = {2023},
 websites = {https://www.egu23.eu},
 publisher = {Copernicus GmbH},
 city = {Vienna, Austria},
 id = {280a00ab-5da2-3aa2-8c52-9fde3eb34c45},
 created = {2023-01-28T00:21:58.180Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-01-02T12:06:10.707Z},
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 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
 private_publication = {false},
 abstract = {Regional scale hydrological models are often constrained by a group of observation stations, typically for discharge, which each represent a lumped catchment response. While multi-station calibration greatly improves model fidelity, other sources of data and different calibration objectives are often required to improve models for other variables and increase robustness for ungauged areas. Satellite data has often been utilized as an additional source of information for multi-objective optimization. However, in many cases satellite-based data for other variables, such as soil moisture, AET, snow cover, storage change etc. has been applied as timeseries of catchment averages, thereby limiting the unique spatial pattern information they carry. In a series of studies a simple alternative approach has been developed to capitalize on the benefits of combining spatial pattern information from satellite data with classical discharge and groundwater head observations. By limiting the constraint by the satellite data to pattern information only a very limited tradeoff with other observations is achieved. Meanwhile, the approach ensures realistic spatial patterns of parameter fields and simulations leading to improved transferability to ungauged basins. In light of equifinality, often encountered for regional scale models constrained by multiple discharge stations, the approach can as such also be seen as an efficient way of identifying spatially consistent solutions among a large range of possible parameter sets. Here we present two cases, one across six central-European basins using a mesoscale hydrological model (mHM) and another using a national scale groundwater-surface model (MIKE-SHE).},
 bibtype = {inproceedings},
 author = {Stisen, Simon and Demirel, Mehmet Cüneyd and Soltani, Mohsen and Koch, Julian},
 booktitle = {EGU General Assembly}
}

Regional scale hydrological models are often constrained by a group of observation stations, typically for discharge, which each represent a lumped catchment response. While multi-station calibration greatly improves model fidelity, other sources of data and different calibration objectives are often required to improve models for other variables and increase robustness for ungauged areas. Satellite data has often been utilized as an additional source of information for multi-objective optimization. However, in many cases satellite-based data for other variables, such as soil moisture, AET, snow cover, storage change etc. has been applied as timeseries of catchment averages, thereby limiting the unique spatial pattern information they carry. In a series of studies a simple alternative approach has been developed to capitalize on the benefits of combining spatial pattern information from satellite data with classical discharge and groundwater head observations. By limiting the constraint by the satellite data to pattern information only a very limited tradeoff with other observations is achieved. Meanwhile, the approach ensures realistic spatial patterns of parameter fields and simulations leading to improved transferability to ungauged basins. In light of equifinality, often encountered for regional scale models constrained by multiple discharge stations, the approach can as such also be seen as an efficient way of identifying spatially consistent solutions among a large range of possible parameter sets. Here we present two cases, one across six central-European basins using a mesoscale hydrological model (mHM) and another using a national scale groundwater-surface model (MIKE-SHE).

@article{
 title = {Effect of Dynamic PET Scaling with LAI and Aspect on the Spatial Performance of a Distributed Hydrologic Model},
 type = {article},
 year = {2023},
 pages = {534},
 volume = {13},
 websites = {https://www.mdpi.com/2073-4395/13/2/534},
 id = {42d16b87-1536-3525-9946-ffc56b7a0ff4},
 created = {2023-02-09T18:22:52.384Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2023-02-13T06:54:25.668Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on the soil properties and crop-vegetation dynamics. Mostly coarse-scale meteorological forcing is used to estimate only the water balance at the catchment outlet. The mesoscale Hydrologic Model (mHM) is one of the rare models that incorporate remote sensing data, i.e., leaf area index (LAI) and aspect, to improve the actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduce a new weight parameter, “alphax”, that allows the user to incorporate both LAI and aspect together for potential evapotranspiration (PET) scaling. With the mHM code enhancement, the modeler also has the option of using raw PET with no scaling. In this study, streamflow and AET are simulated using the mHM in The Main Basin (Germany) for the period of 2002–2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using the Optimization Software Toolkit (OSTRICH). For calibration and evaluation, the KGE metric is used for water balance, and the SPAEF metric is used for evaluating spatial patterns of AET. Our results show that the AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. This is key for agronomic studies like crop yield estimations and irrigation water use. The additional “alphax” parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain.},
 bibtype = {article},
 author = {Demirci, Utku and Demirel, Mehmet Cüneyd},
 doi = {10.3390/agronomy13020534},
 journal = {Agronomy},
 number = {2}
}

The spatial heterogeneity in hydrologic simulations is a key difference between lumped and distributed models. Not all distributed models benefit from pedo-transfer functions based on the soil properties and crop-vegetation dynamics. Mostly coarse-scale meteorological forcing is used to estimate only the water balance at the catchment outlet. The mesoscale Hydrologic Model (mHM) is one of the rare models that incorporate remote sensing data, i.e., leaf area index (LAI) and aspect, to improve the actual evapotranspiration (AET) simulations and water balance together. The user can select either LAI or aspect to scale PET. However, herein we introduce a new weight parameter, “alphax”, that allows the user to incorporate both LAI and aspect together for potential evapotranspiration (PET) scaling. With the mHM code enhancement, the modeler also has the option of using raw PET with no scaling. In this study, streamflow and AET are simulated using the mHM in The Main Basin (Germany) for the period of 2002–2014. The additional value of PET scaling with LAI and aspect for model performance is investigated using Moderate Resolution Imaging Spectroradiometer (MODIS) AET and LAI products. From 69 mHM parameters, 26 parameters are selected for calibration using the Optimization Software Toolkit (OSTRICH). For calibration and evaluation, the KGE metric is used for water balance, and the SPAEF metric is used for evaluating spatial patterns of AET. Our results show that the AET performance of the mHM is highest when using both LAI and aspect indicating that LAI and aspect contain valuable spatial heterogeneity information from topography and canopy (e.g., forests, grasslands, and croplands) that should be preserved during modeling. This is key for agronomic studies like crop yield estimations and irrigation water use. The additional “alphax” parameter makes the model physically more flexible and robust as the model can decide the weights according to the study domain.

@inproceedings{
 title = {Tussle Between Spatial Metrics: Assessing the Convergence Performance of Commonly Used Metrics in Hydrology},
 type = {inproceedings},
 year = {2023},
 websites = {https://www.newyorkcongress2022.com},
 publisher = {BZT Academy},
 city = {Istanbul (Online)},
 id = {15f10d2f-8b67-34e5-be36-41a87513b342},
 created = {2023-02-18T18:14:42.762Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-01-02T12:06:10.944Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
 private_publication = {false},
 abstract = {Hydrologic model calibration is a process of testing different parameter sets to reach the best performance based on the modeler’s objective such as water balance, groundwater and actual evapotranspiration (AET). Achieving the water balance is the main and usually the only goal in conventional hydrological model calibration. In the modern approach, satellite-based remote sensing data is used as well as gauge discharge time series. So that evaporation, snow cover, soil moisture and groundwater can also be included in the parameter estimation (model calibration or optimization). Appropriate objective functions are designed to evaluate the status and distribution of these variables. At this point, the unit difference becomes an issue to tackle. For example, the evapotranspiration variable, which is a combination of evaporation and transpiration from satellite-derived products has a unit of J/m2 whereas hydrological models based on water balance simulate AET in mm/day. The spatial pattern-oriented bias-insensitive SPAtial Efficiency (SPAEF) metric is among the most frequently used metrics in evaluating the pattern match of such variables. The aim of this study is to improve SPAEF and to increase SPAEF’s discriminative power by replacing the third component i.e. “histogram match” with other statistical indices such as kurtosis and earth mover’s distance, or by adding a fourth or even fifth component to make it less tolerant (sharp). We also compare the newly proposed versions of SPAEF with other spatial pattern metrics used in the literature to assess their converging performance. The mesoscale Hydrologic Model (mHM), a physically-based fully distributed model, was used to simulate the streamflow and AET of the Moselle River basin. The two-source energy balance (TSEB) AET during the growing season is used as monthly reference maps and was compared to the model outputs. MODIS-based leaf area index (LAI) is utilized by the mHM via pedo-transfer functions and a multi-scale parameter regionalization (MPR) approach to scale the potential ET. In addition to the long-term monthly average AET maps, we also used a synthetically true AET map simulated with a known mHM parameter set for a randomly selected day. The use of a synthetic case is necessary for reproducibility and to have full control of the calibration process. The results show that the newly proposed four-component metric i.e. SPAtial Count Density (SPACD), slightly outperforms the conventional three-component metric SPAEF (6% better). However, SPACD significantly outperforms the other existing metrics i.e. 11% better than SSIM and 2% better than SPEM. We expect that the SPACD metric will be welcomed not only by the hydrological modeling community but also used in other fields such as remote sensing, image processing and object detection.},
 bibtype = {inproceedings},
 author = {Yorulmaz, Eymen Berkay and Demirel, Mehmet Cüneyd},
 editor = {Köni, Hasan and Maree, Kobus and Nile, Mrudul},
 booktitle = {7th International New York Academic Research Congress on Life, Engineering, and Applied Sciences (18-20 Feb)}
}

Hydrologic model calibration is a process of testing different parameter sets to reach the best performance based on the modeler’s objective such as water balance, groundwater and actual evapotranspiration (AET). Achieving the water balance is the main and usually the only goal in conventional hydrological model calibration. In the modern approach, satellite-based remote sensing data is used as well as gauge discharge time series. So that evaporation, snow cover, soil moisture and groundwater can also be included in the parameter estimation (model calibration or optimization). Appropriate objective functions are designed to evaluate the status and distribution of these variables. At this point, the unit difference becomes an issue to tackle. For example, the evapotranspiration variable, which is a combination of evaporation and transpiration from satellite-derived products has a unit of J/m2 whereas hydrological models based on water balance simulate AET in mm/day. The spatial pattern-oriented bias-insensitive SPAtial Efficiency (SPAEF) metric is among the most frequently used metrics in evaluating the pattern match of such variables. The aim of this study is to improve SPAEF and to increase SPAEF’s discriminative power by replacing the third component i.e. “histogram match” with other statistical indices such as kurtosis and earth mover’s distance, or by adding a fourth or even fifth component to make it less tolerant (sharp). We also compare the newly proposed versions of SPAEF with other spatial pattern metrics used in the literature to assess their converging performance. The mesoscale Hydrologic Model (mHM), a physically-based fully distributed model, was used to simulate the streamflow and AET of the Moselle River basin. The two-source energy balance (TSEB) AET during the growing season is used as monthly reference maps and was compared to the model outputs. MODIS-based leaf area index (LAI) is utilized by the mHM via pedo-transfer functions and a multi-scale parameter regionalization (MPR) approach to scale the potential ET. In addition to the long-term monthly average AET maps, we also used a synthetically true AET map simulated with a known mHM parameter set for a randomly selected day. The use of a synthetic case is necessary for reproducibility and to have full control of the calibration process. The results show that the newly proposed four-component metric i.e. SPAtial Count Density (SPACD), slightly outperforms the conventional three-component metric SPAEF (6% better). However, SPACD significantly outperforms the other existing metrics i.e. 11% better than SSIM and 2% better than SPEM. We expect that the SPACD metric will be welcomed not only by the hydrological modeling community but also used in other fields such as remote sensing, image processing and object detection.

@article{
 title = {Analysis of spatiotemporal variations of drought and its correlations with remote sensing-based indices via wavelet analysis and clustering methods},
 type = {article},
 year = {2022},
 pages = {175-192},
 volume = {53},
 websites = {https://iwaponline.com/hr/article/53/1/175/85804/Analysis-of-spatiotemporal-variations-of-drought},
 month = {1},
 day = {1},
 id = {f68bc67d-744e-39bf-9f9d-887346cd886f},
 created = {2021-12-12T17:30:44.059Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2023-01-12T18:22:51.569Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Beside in situ observations, satellite-based products can provide an ideal data source for spatiotemporal monitoring of drought. In this study, the spatiotemporal pattern of drought was investigated for the northwest part of Iran using ground- and satellite-based datasets. First, the Standardized Precipitation Index series were calculated via precipitation data of 29 sites located in the selected area and the CPC Merged Analysis of Precipitation satellite. The Maximal Overlap Discrete Wavelet Transform (MODWT) was used for obtaining the temporal features of time series, and further decomposition was performed using Ensemble Empirical Mode Decomposition (EEMD) to have more stationary time series. Then, multiscale zoning was done based on subseries energy values via two clustering methods, namely the self-organizing map and K-means. The results showed that the MODWT–EEMD–K-means method successfully identified homogenous drought areas. On the other hand, correlation between the satellite sensor data (i.e. the Normalized Difference Vegetation Index, the Vegetation Condition Index, the Vegetation Healthy Index, and the Temperature Condition Index) was evaluated. The possible links between central stations of clusters and satellite-based indices were assessed via the wavelet coherence method. The results revealed that all applied satellite-based indices had significant statistical correlations with the ground-based drought index within a certain period.},
 bibtype = {article},
 author = {Ghasempour, Roghayeh and Roushangar, Kiyoumars and Ozgur Kirca, V. S. and Demirel, Mehmet Cüneyd},
 doi = {10.2166/nh.2021.104},
 journal = {Hydrology Research},
 number = {1}
}

Beside in situ observations, satellite-based products can provide an ideal data source for spatiotemporal monitoring of drought. In this study, the spatiotemporal pattern of drought was investigated for the northwest part of Iran using ground- and satellite-based datasets. First, the Standardized Precipitation Index series were calculated via precipitation data of 29 sites located in the selected area and the CPC Merged Analysis of Precipitation satellite. The Maximal Overlap Discrete Wavelet Transform (MODWT) was used for obtaining the temporal features of time series, and further decomposition was performed using Ensemble Empirical Mode Decomposition (EEMD) to have more stationary time series. Then, multiscale zoning was done based on subseries energy values via two clustering methods, namely the self-organizing map and K-means. The results showed that the MODWT–EEMD–K-means method successfully identified homogenous drought areas. On the other hand, correlation between the satellite sensor data (i.e. the Normalized Difference Vegetation Index, the Vegetation Condition Index, the Vegetation Healthy Index, and the Temperature Condition Index) was evaluated. The possible links between central stations of clusters and satellite-based indices were assessed via the wavelet coherence method. The results revealed that all applied satellite-based indices had significant statistical correlations with the ground-based drought index within a certain period.

@article{
 title = {Climate Normalized Spatial Patterns of Evapotranspiration Enhance the Calibration of a Hydrological Model},
 type = {article},
 year = {2022},
 keywords = {climate normalization,evapotranspiration,hydrological,model evaluation,modeling,remote sensing,spatial patterns},
 pages = {315},
 volume = {14},
 websites = {https://www.mdpi.com/2072-4292/14/2/315},
 month = {1},
 day = {11},
 id = {f3924d1d-3d31-3b3b-bdbc-5e49127a1f6a},
 created = {2022-01-11T11:42:34.547Z},
 file_attached = {true},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2022-01-12T13:00:24.149Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated patterns. To address this, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as a modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. We apply the mesoscale Hydrological Model (mHM) to model the hydrological cycle of the Senegal River basin. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. As objective functions we applied the Kling-Gupta-Efficiency (KGE) for Q and the Spatial Efficiency (SPAEF) for ET. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial pattern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern, i.e., a 30% decrease in SPAEF. Both calibrations reached comparable performance of Q, i.e., KGE around 0.7. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.},
 bibtype = {article},
 author = {Koch, Julian and Demirel, Mehmet Cüneyd and Stisen, Simon},
 doi = {10.3390/rs14020315},
 journal = {Remote Sensing},
 number = {2}
}

Spatial pattern-oriented evaluations of distributed hydrological models have contributed towards an improved realism of hydrological simulations. This advancement has been supported by the broad range of readily available satellite-based datasets of key hydrological variables, such as evapotranspiration (ET). At larger scale, spatial patterns of ET are often driven by underlying climate gradients, and with this study, we argue that gradient dominated patterns may hamper the potential of spatial pattern-oriented evaluation frameworks. We hypothesize that the climate control of spatial patterns of ET overshadows the effect model parameters have on the simulated patterns. To address this, we propose a climate normalization strategy. This is demonstrated for the Senegal River basin as a modeling case study, where the dominant north-south precipitation gradient is the main driver of the observed hydrological variability. We apply the mesoscale Hydrological Model (mHM) to model the hydrological cycle of the Senegal River basin. Two multi-objective calibration experiments investigate the effect of climate normalization. Both calibrations utilize observed discharge (Q) in combination with remote sensing ET data, where one is based on the original ET pattern and the other utilizes the normalized ET pattern. As objective functions we applied the Kling-Gupta-Efficiency (KGE) for Q and the Spatial Efficiency (SPAEF) for ET. We identify parameter sets that balance the tradeoffs between the two independent observations and find that the calibration using the normalized ET pattern does not compromise the spatial pattern performance of the original pattern. However, vice versa, this is not necessarily the case, since the calibration using the original ET pattern showed a poorer performance for the normalized pattern, i.e., a 30% decrease in SPAEF. Both calibrations reached comparable performance of Q, i.e., KGE around 0.7. With this study, we identified a general shortcoming of spatial pattern-oriented model evaluations using ET in basins dominated by a climate gradient, but we argue that this also applies to other variables such as, soil moisture or land surface temperature.

@article{
 title = {Effect of data length, spin-up period and spatial model resolution on fully distributed hydrological model calibration in the Moselle basin},
 type = {article},
 year = {2022},
 pages = {759-772},
 volume = {67},
 websites = {https://www.tandfonline.com/doi/full/10.1080/02626667.2022.2046754},
 month = {4},
 day = {4},
 id = {ce5f14cf-b974-3341-b915-cd64d0144dcb},
 created = {2022-01-29T17:56:24.043Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2022-04-26T11:09:08.412Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 citation_key = {10.1080/02626667.2022.2046754},
 source_type = {article},
 private_publication = {false},
 abstract = {Subjective decisions in hydrologic model calibration can have drastic impacts on our understanding of basin processes and simulated fluxes. Here, we present a multi-case calibration approach for determining three pillars of an appropriate hydrological model configuration: calibration data length, spin-up period and spatial resolution of the hydrological model of the Moselle River. We used spatially distributed meso-scale Hydrological Model (mHM) together with Dynamically Dimensioned Search (DDS) algorithm, and Nash Sutcliffe Efficiency (NSE) to test 105 cases each representing different combinations of the three pillars. The results show that a 10-year calibration data length, 2-year spin-up period and a 4 km model resolution are appropriate for the Moselle basin to reduce the computational burden while simulating streamflow at a descent performance. Although the conclusions are drawn for Moselle basin, analyzing the combined effects further allowed us to understand the interactions of these three usually overlooked pillars in the mHM configuration.},
 bibtype = {article},
 author = {Ekmekcioğlu, Ömer and Demirel, Mehmet Cüneyd and Booij, Martijn J},
 doi = {10.1080/02626667.2022.2046754},
 journal = {Hydrological Sciences Journal},
 number = {5}
}

Subjective decisions in hydrologic model calibration can have drastic impacts on our understanding of basin processes and simulated fluxes. Here, we present a multi-case calibration approach for determining three pillars of an appropriate hydrological model configuration: calibration data length, spin-up period and spatial resolution of the hydrological model of the Moselle River. We used spatially distributed meso-scale Hydrological Model (mHM) together with Dynamically Dimensioned Search (DDS) algorithm, and Nash Sutcliffe Efficiency (NSE) to test 105 cases each representing different combinations of the three pillars. The results show that a 10-year calibration data length, 2-year spin-up period and a 4 km model resolution are appropriate for the Moselle basin to reduce the computational burden while simulating streamflow at a descent performance. Although the conclusions are drawn for Moselle basin, analyzing the combined effects further allowed us to understand the interactions of these three usually overlooked pillars in the mHM configuration.

@article{
 title = {Smart pressure management extension for EPANET: source code enhancement with a dynamic pressure reducing valve model},
 type = {article},
 year = {2022},
 pages = {642-658},
 volume = {24},
 websites = {https://iwaponline.com/jh/article/doi/10.2166/hydro.2022.172/87798/Smart-pressure-management-extension-for-EPANET,https://iwaponline.com/jh/article/24/3/642/87798/Smart-pressure-management-extension-for-EPANET},
 month = {5},
 day = {1},
 id = {80338cf6-64fb-3f35-902f-563383e0b6ee},
 created = {2022-03-16T22:49:06.542Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2022-05-31T10:18:50.620Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Applying pressure management reduces lost water and excessive hydraulic pressures in water distribution networks (WDNs). There are currently four different types of pressure management in the literature, i.e. fixed outlet, time modulated, flow modulated, and remote node modulated. The primary device used in pressure management is the pressure reducing valve (PRV) that dynamically controls the outlet pressure by moving up and down its main valve element. In this study, we firstly introduce the dynamic PRV model with four different pressure management types to the source code of EPANET v3.1 software and assess the effect of different valve opening schemes on pressure graphs and leakage quantities. The results showed that dynamic PRV significantly reduces lost water amounts and excessive hydraulic pressures in the WDN when valve opening is continuously adjusted. Our smart PM extension implemented into EPANET v3.1 software is publicly available in Zenodo repositories (https://zenodo.org/record/6243078).},
 bibtype = {article},
 author = {Koşucu, Mehmet Melih and Demirel, Mehmet Cüneyd},
 doi = {10.2166/hydro.2022.172},
 journal = {Journal of Hydroinformatics},
 number = {3}
}

Applying pressure management reduces lost water and excessive hydraulic pressures in water distribution networks (WDNs). There are currently four different types of pressure management in the literature, i.e. fixed outlet, time modulated, flow modulated, and remote node modulated. The primary device used in pressure management is the pressure reducing valve (PRV) that dynamically controls the outlet pressure by moving up and down its main valve element. In this study, we firstly introduce the dynamic PRV model with four different pressure management types to the source code of EPANET v3.1 software and assess the effect of different valve opening schemes on pressure graphs and leakage quantities. The results showed that dynamic PRV significantly reduces lost water amounts and excessive hydraulic pressures in the WDN when valve opening is continuously adjusted. Our smart PM extension implemented into EPANET v3.1 software is publicly available in Zenodo repositories (https://zenodo.org/record/6243078).

@article{
 title = {Extending EPANET hydraulic solver capacity with rigid water column global gradient algorithm},
 type = {article},
 year = {2022},
 pages = {31-43},
 volume = {42},
 websites = {https://linkinghub.elsevier.com/retrieve/pii/S1570644322000211},
 month = {5},
 id = {9ba7ce2b-69a0-3a5c-90ca-be2481271a1e},
 created = {2022-03-22T08:00:48.325Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2023-08-24T11:49:30.669Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {54f9a1cb-cd85-43bf-81c7-692f1856eaa8},
 private_publication = {false},
 abstract = {EPANET is one of the most commonly used open source programs in hydraulic modeling of water distribution networks (WDNs), based on steady state and extended period simulation approaches. These approaches are effective for estimating flow capacity and average pressures in networks, however; EPANET is not yet fully effective in modeling incompressible unsteady flows in WDNs. In this study, the hydraulic solver capacity of EPANET 3 is extended with Rigid Water Column Global Gradient Algorithm (RWC-GGA) to model incompressible unsteady flow hydraulics in WDNs. Moreover, we incorporated dynamically more accurate valve expressions than the existing ones in the default EPANET code and introduced a new global convergence algorithm Convergence Tracking Control Method (CTCM) in the solver code. The RWC-GGA, CTCM, and valve expressions are tested and validated in three different WDNs varying from simple to sophisticated set-ups. The results show that incompressible unsteady flows can be modeled with RWC-CGA and dynamic valve representations. Finally, the convergence problem due to the valve motion and the pressure-dependent algorithm (PDA) is solved by the implemented global convergence algorithm i.e. CTCM.},
 bibtype = {article},
 author = {Melih Koşucu, Mehmet and Albay, Enes and Demirel, Mehmet Cüneyd},
 doi = {10.1016/j.jher.2022.04.002},
 journal = {Journal of Hydro-environment Research}
}

EPANET is one of the most commonly used open source programs in hydraulic modeling of water distribution networks (WDNs), based on steady state and extended period simulation approaches. These approaches are effective for estimating flow capacity and average pressures in networks, however; EPANET is not yet fully effective in modeling incompressible unsteady flows in WDNs. In this study, the hydraulic solver capacity of EPANET 3 is extended with Rigid Water Column Global Gradient Algorithm (RWC-GGA) to model incompressible unsteady flow hydraulics in WDNs. Moreover, we incorporated dynamically more accurate valve expressions than the existing ones in the default EPANET code and introduced a new global convergence algorithm Convergence Tracking Control Method (CTCM) in the solver code. The RWC-GGA, CTCM, and valve expressions are tested and validated in three different WDNs varying from simple to sophisticated set-ups. The results show that incompressible unsteady flows can be modeled with RWC-CGA and dynamic valve representations. Finally, the convergence problem due to the valve motion and the pressure-dependent algorithm (PDA) is solved by the implemented global convergence algorithm i.e. CTCM.

@article{
 title = {Hidrolojik Model Kalibrasyonunda Uydu Tabanlı Aylık Buharlaşma ve LAI Verilerinin Kullanılması},
 type = {article},
 year = {2022},
 keywords = {MODIS,mHM,model calibration,non-measured basins,real evaporation,remote sensing},
 pages = {13013-13035},
 volume = {33},
 websites = {https://dergipark.org.tr/tr/doi/10.18400/tekderg.1067466,http://dergipark.org.tr/tr/doi/10.18400/tekderg.1067466},
 month = {11},
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 abstract = {Hidrolojik model parametreleri geleneksel yaklaşımda havza çıkışındaki akım gözlem istasyonlarından (AGİ) elde edilen günlük akım verileriyle tahmin edilmeye çalışılır. Modern yaklaşımda ise akım verileri yanında açık erişimli uydu tabanlı uzaktan algılama verilerinden de faydalanılır. Uzaktan algılama verilerinin kullanıldığı yöntem ile sadece akım verisiyle elde edilen noktasal iyileştirme sonuçlarının yanında alana yayılı kar örtüsü, gerçek buharlaşma, yaprak alan indeksi, toprak nemi ve yer altı suyu beslenmesi gibi akı değerlerinin de daha tutarlı ve güvenilir olması sağlanır. Bu çalışmamızın amacı uzaktan algılama yöntemleriyle elde edilmiş MODIS aylık gerçek evapotranspirasyon (AET) verileri ile yaprak alan indeksi (LAI) haritalarının hidrolojik model kalibrasyonuna etkilerini araştırmaktır. Benzeşim deneylerimiz için Vienne (Fransa) havzası seçilmiştir. Fizik tabanlı tam yayılı mHM hidrolojik modeli bu havza için çalıştırılmış ve 6 senaryo için kalibrasyonlar yapılmıştır. Modelin akım benzeşim performansı Kling-Gupta (KGE) metriği ile modelin yayılı evapotranspirasyon performansı ise SPAEF metriği ile ortaya konmuştur. Sonuçlara göre, sadece havza çıkışındaki AGİ verilerine göre kalibre edilen model KGE 0.91’ye ulaşırken (maksimum 1), SPAEF buharlaşma performansı düşüktür. Havzaya yayılmış 4 AGİ’li kalibrasyonda ortlama KGE 0.37 iken SPAEF kısmen iyileşmiştir. Tek AGİ ve MODIS-AET birlikte kalibrasyonda kullanıldığında KGE 0.90 SPAEF ~0.70 olmuştur. Dördüncü senaryomuzda model sadece MODIS-AET ile kalibre edilmiş SPAEF 0.60’e ulaşmıştır. Öte yandan su dengesi tutturulamamıştır (KGE -0.24). Beşinci senaryoda, model sadece 12 adet akım verisi ve MODIS-AET ile kalibre edilmiş ve KGE 0.67 iken SPAEF 0.75 gibi yüksek değerler almıştır. Altıncı son senaryoda sadece bir yıl günlük akım gözlemi yapıldığı varsayımı yapılarak MODIS-AET’nin de dahil edildiği model kalibrasyonu yapıldığında KGE 0.72 ve SPAEF yine 0.75 dolaylarında yüksek değerler almıştır. Bu altı senaryolu model kalibrasyon çalışmamızın sonuçları akım ölçümleri eksik havzalar için ümit vericidir. Öyle ki; uydu verilerinden elde edilen gerçek evapotranspirasyon (AET) ile birlikte sadece bir yıl günlük veya bir yılın her ayından bir debi ölçümü toplamda 12 debi değeri ile dahi yeterli su dengesi sağlanabilmektedir.},
 bibtype = {article},
 author = {Avcuoğlu, Muhammet Bahattin and Demirel, Mehmet Cüneyd},
 doi = {10.18400/tekderg.1067466},
 journal = {Teknik Dergi},
 number = {6}
}

Hidrolojik model parametreleri geleneksel yaklaşımda havza çıkışındaki akım gözlem istasyonlarından (AGİ) elde edilen günlük akım verileriyle tahmin edilmeye çalışılır. Modern yaklaşımda ise akım verileri yanında açık erişimli uydu tabanlı uzaktan algılama verilerinden de faydalanılır. Uzaktan algılama verilerinin kullanıldığı yöntem ile sadece akım verisiyle elde edilen noktasal iyileştirme sonuçlarının yanında alana yayılı kar örtüsü, gerçek buharlaşma, yaprak alan indeksi, toprak nemi ve yer altı suyu beslenmesi gibi akı değerlerinin de daha tutarlı ve güvenilir olması sağlanır. Bu çalışmamızın amacı uzaktan algılama yöntemleriyle elde edilmiş MODIS aylık gerçek evapotranspirasyon (AET) verileri ile yaprak alan indeksi (LAI) haritalarının hidrolojik model kalibrasyonuna etkilerini araştırmaktır. Benzeşim deneylerimiz için Vienne (Fransa) havzası seçilmiştir. Fizik tabanlı tam yayılı mHM hidrolojik modeli bu havza için çalıştırılmış ve 6 senaryo için kalibrasyonlar yapılmıştır. Modelin akım benzeşim performansı Kling-Gupta (KGE) metriği ile modelin yayılı evapotranspirasyon performansı ise SPAEF metriği ile ortaya konmuştur. Sonuçlara göre, sadece havza çıkışındaki AGİ verilerine göre kalibre edilen model KGE 0.91’ye ulaşırken (maksimum 1), SPAEF buharlaşma performansı düşüktür. Havzaya yayılmış 4 AGİ’li kalibrasyonda ortlama KGE 0.37 iken SPAEF kısmen iyileşmiştir. Tek AGİ ve MODIS-AET birlikte kalibrasyonda kullanıldığında KGE 0.90 SPAEF ~0.70 olmuştur. Dördüncü senaryomuzda model sadece MODIS-AET ile kalibre edilmiş SPAEF 0.60’e ulaşmıştır. Öte yandan su dengesi tutturulamamıştır (KGE -0.24). Beşinci senaryoda, model sadece 12 adet akım verisi ve MODIS-AET ile kalibre edilmiş ve KGE 0.67 iken SPAEF 0.75 gibi yüksek değerler almıştır. Altıncı son senaryoda sadece bir yıl günlük akım gözlemi yapıldığı varsayımı yapılarak MODIS-AET’nin de dahil edildiği model kalibrasyonu yapıldığında KGE 0.72 ve SPAEF yine 0.75 dolaylarında yüksek değerler almıştır. Bu altı senaryolu model kalibrasyon çalışmamızın sonuçları akım ölçümleri eksik havzalar için ümit vericidir. Öyle ki; uydu verilerinden elde edilen gerçek evapotranspirasyon (AET) ile birlikte sadece bir yıl günlük veya bir yılın her ayından bir debi ölçümü toplamda 12 debi değeri ile dahi yeterli su dengesi sağlanabilmektedir.

@inproceedings{
 title = {The Effects of Different Potential Evapotranspiration Data on the Performance of Two Hydrologic Models for the Konya Closed Basin in Turkey},
 type = {inproceedings},
 year = {2022},
 websites = {https://igrs.itu.edu.tr},
 publisher = {ITU - LEE},
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 booktitle = {INTERNATIONAL GRADUATE RESEARCH SYMPOSIUM IGRS'22. 1-3 June 2022 Istanbul – TURKEY.}
}

@inproceedings{
 title = {Calibration of a Distributed Hydrologic Model for Konya Closed Basin Using Multi Gauge Discharge Data},
 type = {inproceedings},
 year = {2022},
 websites = {https://igrs.itu.edu.tr},
 publisher = {ITU - LEE},
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 author = {Ergün, Enes and Demirel, Mehmet Cüneyd},
 booktitle = {INTERNATIONAL GRADUATE RESEARCH SYMPOSIUM IGRS'22. 1-3 June 2022 Istanbul – TURKEY.}
}

@inproceedings{
 title = {Hydrological Model Structure and Calibration Algorithm Effect on Discharge Simulation Performance},
 type = {inproceedings},
 year = {2022},
 websites = {https://igrs.itu.edu.tr},
 publisher = {ITU - LEE},
 city = {İstanbul},
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@inproceedings{
 title = {mHM DAĞILIMLI HİDROLOJİK MODEL PARAMETRELERİNİN DDS OPTİMİZASYON ALGORİTMASI KULLANILARAK KALİBRASYONU: SUSURLUK HAVZASI ÖRNEĞİ},
 type = {inproceedings},
 year = {2022},
 websites = {http://uhk.gantep.edu.tr},
 city = {Gaziantep},
 id = {7cff9a7b-7192-355a-8e43-013033804d97},
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 abstract = {Hidrolojik modeller, son yıllarda dikkat çeken taşkın ve kuraklık gibi doğal afetlerin analizinde önemli bir araç olarak kullanılmaktadır. Havza bazında kurulan hidrolojik modellerin güvenilirliği için model parametrelerinin kalibrasyonu ile en iyi parametre setinin elde edilmesi oldukça önemlidir. Bu çalışma kapsamında, fiziksel tabanlı, dağılımlı ve orta ölçekli bir hidrolojik model olan mHM (mesoscale Hydrologic Model) kullanılarak Susurluk Havzası yağış-akış ilişkisi 2000-2015 yılları arasında günlük zaman adımında modellenmiştir. mHM toprak tipi, bitki örtüsü ve jeolojik özellikler gibi havzanın fiziksel temsiliyetini sağlayan girdilerin yanı sıra sıcaklık ve yağış gibi meteorolojik girdileri kullanarak modelleme yapabilme kabiliyetine sahiptir. Bu girdiler kullanılarak akış ve evapotranspirasyon gibi çıktıların zamansal değişkenliği Susurluk Havzası için ortaya konulmuştur. Çalışmanın devamında, modelin kendi içerisinde sunduğu otomatik kalibrasyon aracı ile gözlenmiş akım çıktılarına göre parametrelerin optimizasyonu gerçekleştirilmiştir. Bunun için DDS (Dynamically Dimensioned Search) optimizasyon algoritması tercih edilmiştir. Karar metriği olarak seçilen NSE (Nash-Sutcliffe Efficiency) ve KGE (Kling-Gupta Efficiency) değerleri kalibrasyon ve validasyon periyotları için sırası ile 0.90 ve 0.70 üzeri elde edilerek modelin kabul edilebilir sonuçlar verdiğini göstermiştir. Çalışma sonucunda, Susurluk Havzası için kalibre edilmiş güvenilir bir hidrolojik model gelecek çalışmalarda kullanılmak üzere oluşturulmuştur.},
 bibtype = {inproceedings},
 author = {Sadak, Derya and Peker, İsmail Bilal and Demirel, Mehmet Cüneyd and Doğan, Emrah},
 booktitle = {11. Ulusal Hidroloji Kongresi}
}

Hidrolojik modeller, son yıllarda dikkat çeken taşkın ve kuraklık gibi doğal afetlerin analizinde önemli bir araç olarak kullanılmaktadır. Havza bazında kurulan hidrolojik modellerin güvenilirliği için model parametrelerinin kalibrasyonu ile en iyi parametre setinin elde edilmesi oldukça önemlidir. Bu çalışma kapsamında, fiziksel tabanlı, dağılımlı ve orta ölçekli bir hidrolojik model olan mHM (mesoscale Hydrologic Model) kullanılarak Susurluk Havzası yağış-akış ilişkisi 2000-2015 yılları arasında günlük zaman adımında modellenmiştir. mHM toprak tipi, bitki örtüsü ve jeolojik özellikler gibi havzanın fiziksel temsiliyetini sağlayan girdilerin yanı sıra sıcaklık ve yağış gibi meteorolojik girdileri kullanarak modelleme yapabilme kabiliyetine sahiptir. Bu girdiler kullanılarak akış ve evapotranspirasyon gibi çıktıların zamansal değişkenliği Susurluk Havzası için ortaya konulmuştur. Çalışmanın devamında, modelin kendi içerisinde sunduğu otomatik kalibrasyon aracı ile gözlenmiş akım çıktılarına göre parametrelerin optimizasyonu gerçekleştirilmiştir. Bunun için DDS (Dynamically Dimensioned Search) optimizasyon algoritması tercih edilmiştir. Karar metriği olarak seçilen NSE (Nash-Sutcliffe Efficiency) ve KGE (Kling-Gupta Efficiency) değerleri kalibrasyon ve validasyon periyotları için sırası ile 0.90 ve 0.70 üzeri elde edilerek modelin kabul edilebilir sonuçlar verdiğini göstermiştir. Çalışma sonucunda, Susurluk Havzası için kalibre edilmiş güvenilir bir hidrolojik model gelecek çalışmalarda kullanılmak üzere oluşturulmuştur.

@inproceedings{
 title = {ERA5 VERİSİNİN GR4J MODEL ÇIKTISI ÜZERİNDEKİ ETKİSİ},
 type = {inproceedings},
 year = {2022},
 websites = {http://uhk.gantep.edu.tr},
 city = {Gaziantep},
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 abstract = {Hidrolojik modeller, gün geçtikçe önem kazanan iklimsel ekstrem koşullar ve su kaynaklarının yönetimi gibi konulara yönelik çalışmalarda yol gösterici bir araç olarak kullanılmaktadır. Hidrolojik modellerin girdileri, model çıktısı olan debinin doğru bir biçimde elde edilmesi açısından büyük önem taşımaktadır. Bu çalışmada, GR4J hidrolojik modeli kurulmuş, model girdisi olarak Ege Bölgesinde Gediz Havzası’nın membaında yer alan Acısu alt Havzası için Meteoroloji Genel Müdürlüğü’ne (MGM) ait yağış ve sıcaklık ölçüm verileri ve alternatif olarak ERA5 kaynaklı tahmine dayalı yağış ve sıcaklık verileri kullanılmıştır. Mekânsal çözünürlüğüne göre toplu hidrolojik model sınıfına giren GR4J modeli, girdileri tüm havzayı temsil eden zaman serileri ile tanımlamaktadır. Bu sebeple havzaya etkisi bulunabilecek MGM ölçüm istasyonlarına ait veriler Thiessen poligonu yöntemi, ERA5 kaynaklı 30 km çözünürlüğe sahip tahmin verileri ise havza sınırları içerisinde alansal ağırlıklı ortalamaları alınarak modele uygun şekilde tanımlanmıştır. Model girdisi olarak ihtiyaç duyulan potansiyel evapotranspirasyon değerleri iki veri seti için de Hargreaves-Samani yöntemi kullanılarak elde edilmiştir. Buna ek olarak GR4J modeli Covariance Matrix Adoption Evolution Strategy (CMAES) algoritması kullanılarak kalibre edilmiştir. Çalışma çerçevesinde, model girdilerindeki değişimin debi performansını ne ölçüde ve nasıl etkilediği incelenmiş ve değerlendirilmiştir.},
 bibtype = {inproceedings},
 author = {Alp, Harun and Aşıkoğlu, Ömer Levend and Demirel, Mehmet Cüneyd},
 booktitle = {11. Ulusal Hidroloji Kongresi}
}

Hidrolojik modeller, gün geçtikçe önem kazanan iklimsel ekstrem koşullar ve su kaynaklarının yönetimi gibi konulara yönelik çalışmalarda yol gösterici bir araç olarak kullanılmaktadır. Hidrolojik modellerin girdileri, model çıktısı olan debinin doğru bir biçimde elde edilmesi açısından büyük önem taşımaktadır. Bu çalışmada, GR4J hidrolojik modeli kurulmuş, model girdisi olarak Ege Bölgesinde Gediz Havzası’nın membaında yer alan Acısu alt Havzası için Meteoroloji Genel Müdürlüğü’ne (MGM) ait yağış ve sıcaklık ölçüm verileri ve alternatif olarak ERA5 kaynaklı tahmine dayalı yağış ve sıcaklık verileri kullanılmıştır. Mekânsal çözünürlüğüne göre toplu hidrolojik model sınıfına giren GR4J modeli, girdileri tüm havzayı temsil eden zaman serileri ile tanımlamaktadır. Bu sebeple havzaya etkisi bulunabilecek MGM ölçüm istasyonlarına ait veriler Thiessen poligonu yöntemi, ERA5 kaynaklı 30 km çözünürlüğe sahip tahmin verileri ise havza sınırları içerisinde alansal ağırlıklı ortalamaları alınarak modele uygun şekilde tanımlanmıştır. Model girdisi olarak ihtiyaç duyulan potansiyel evapotranspirasyon değerleri iki veri seti için de Hargreaves-Samani yöntemi kullanılarak elde edilmiştir. Buna ek olarak GR4J modeli Covariance Matrix Adoption Evolution Strategy (CMAES) algoritması kullanılarak kalibre edilmiştir. Çalışma çerçevesinde, model girdilerindeki değişimin debi performansını ne ölçüde ve nasıl etkilediği incelenmiş ve değerlendirilmiştir.

@inproceedings{
 title = {SU DAĞITIM ŞEBEKESİNİN HİDROLİK MODELİNDE FARKLI BASINÇ YÖNETİMİ METOTLARININ SİMÜLASYONU},
 type = {inproceedings},
 year = {2022},
 keywords = {Basınç Yönetimi,Hidrolik Modelleme,Su Dağıtım Şebekeleri},
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 abstract = {Su dağıtım şebekelerinde sistematik basınç yönetimi uygulamak kayıp suyu ve yüksek hidrolik basınçları azaltır. Sistematik yaklaşıma göre basınç yönetimi önce gerçek şebekenin dijital ikizinin (digital twin) bilgisayar ortamında kurulması ile başlar. Ardından literatürdeki algoritmaya dayalı basınç yönetimi türleri kullanılarak şebekenin hidrolik modeli farklı konfigürasyonlar için test edilir ve en ideali seçilerek aparatları ile birlikte gerçek şebekede uygulanır. Literatürde şu anda dört farklı basınç yönetimi türü vardır, bunlar sabit çıkışlı, zaman ayarlı, debi ayarlı ve kritik nokta ayarlı basınç yönetimi metotlarıdır. Basınç yönetiminde kullanılan esas cihaz, vananın ana elemanını yukarı ve aşağı hareket ettirerek çıkış basıncını dinamik olarak kontrol eden Basınç Düşürücü Vanadır (PRV). Açık kaynak kodlu bir yazılım olan EPANET’in mevcut versiyonlarında PRV’nin tanımı statik olarak yapılmıştır. Bu durum PRV dinamiğini gereğince modelleyebilmenin ve PRV ile farklı basınç yönetimi metotlarını simüle edebilmenin önünde bir engel teşkil etmektedir. Bu sebeple EPANET 3 yazılımının kaynak koduna PRV’nin çalışma prensiplerini fiziksel olarak hassas bir şekilde simüle edebilen Dinamik PRV modeli eklenmiştir. Böylece EPANET 3 ile su dağıtım şebekelerinde sabit çıkışlı, zaman ayarlı, debi ayarlı ve kritik nokta ayarlı basınç yönetimi metotlarının hidrolik analizinin yapılabilmesi sağlanmıştır. EPANET 3‘e eklenen basınç yönetimi uzantısının kodları, Zenodo adlı platformda araştırmacıların, mühendislerin ve kod geliştiricilerinin istifadesine açık hale getirilmiştir (https://zenodo.org/record/6243078).},
 bibtype = {inproceedings},
 author = {Koşucu, Mehmet Melih and Demirel, Mehmet Cüneyd},
 editor = {Bahram, Bahri},
 booktitle = {14. Uluslararası Bilimsel Araştırmalar Kongresi ANKARA/TÜRKİYE 20 - 21 AĞUSTOS}
}

Su dağıtım şebekelerinde sistematik basınç yönetimi uygulamak kayıp suyu ve yüksek hidrolik basınçları azaltır. Sistematik yaklaşıma göre basınç yönetimi önce gerçek şebekenin dijital ikizinin (digital twin) bilgisayar ortamında kurulması ile başlar. Ardından literatürdeki algoritmaya dayalı basınç yönetimi türleri kullanılarak şebekenin hidrolik modeli farklı konfigürasyonlar için test edilir ve en ideali seçilerek aparatları ile birlikte gerçek şebekede uygulanır. Literatürde şu anda dört farklı basınç yönetimi türü vardır, bunlar sabit çıkışlı, zaman ayarlı, debi ayarlı ve kritik nokta ayarlı basınç yönetimi metotlarıdır. Basınç yönetiminde kullanılan esas cihaz, vananın ana elemanını yukarı ve aşağı hareket ettirerek çıkış basıncını dinamik olarak kontrol eden Basınç Düşürücü Vanadır (PRV). Açık kaynak kodlu bir yazılım olan EPANET’in mevcut versiyonlarında PRV’nin tanımı statik olarak yapılmıştır. Bu durum PRV dinamiğini gereğince modelleyebilmenin ve PRV ile farklı basınç yönetimi metotlarını simüle edebilmenin önünde bir engel teşkil etmektedir. Bu sebeple EPANET 3 yazılımının kaynak koduna PRV’nin çalışma prensiplerini fiziksel olarak hassas bir şekilde simüle edebilen Dinamik PRV modeli eklenmiştir. Böylece EPANET 3 ile su dağıtım şebekelerinde sabit çıkışlı, zaman ayarlı, debi ayarlı ve kritik nokta ayarlı basınç yönetimi metotlarının hidrolik analizinin yapılabilmesi sağlanmıştır. EPANET 3‘e eklenen basınç yönetimi uzantısının kodları, Zenodo adlı platformda araştırmacıların, mühendislerin ve kod geliştiricilerinin istifadesine açık hale getirilmiştir (https://zenodo.org/record/6243078).

@inproceedings{
 title = {SU DAĞITIM ŞEBEKESİ HİDROLİĞİNİN DEĞİŞKEN AKIM ALGORİTMASIYLA ANALİZİ},
 type = {inproceedings},
 year = {2022},
 keywords = {Değişken Akımların Hidroliği,Hidrolik Modelleme,Su Dağıtım Şebekeleri},
 websites = {https://www.ubaksymposium.org},
 city = {Ankara},
 id = {35af99e6-b8b6-3bcd-a437-adec8d8c9faa},
 created = {2022-08-26T08:36:56.882Z},
 file_attached = {true},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
 private_publication = {false},
 abstract = {EPANET, su dağıtım şebekelerinin hidrolik modellemesinde en yaygın kullanılan açık kaynaklı programlardan biridir. Bu program, kararlı akım ve genişletilmiş dönem simülasyonu yaklaşımlarıyla analiz yapmaktadır. Bu yaklaşımlar, şebekelerdeki akımların ortalama debi ve basınçlarını etkin bir şekilde hesaplayabilmektedir. Ancak EPANET’in mevcut versiyonlarında, su dağıtım şebekelerinde sıkıştırılamaz değişken akımların simüle edilebilme imkanı bulunmamaktadır. Halbuki vanaların açılma-kapanma hareketleri ile su tüketiminin hızlı bir şekilde değişmesi gibi olgular ancak değişken akım algoritmalarıyla modellenebilmektedir. Bu sebeple bu çalışmada, EPANET 3'ün hidrolik çözücü kapasitesi, su dağıtım şebekelerinde sıkıştırılamaz değişken akım hidroliğini modellemek için Rijit Su Sütunu Küresel Gradyan Algoritması (RWC-GGA) ile genişletilmiştir. EPANET 3 kaynak kodunda yapılan bu değişikliğin hidrolik açıdan anlamlı sonuçlar ürettiği, bir su dağıtım şebekesi üzerinde yapılan simülasyonla gösterilmiştir.},
 bibtype = {inproceedings},
 author = {Koşucu, Mehmet Melih and Demirel, Mehmet Cüneyd},
 editor = {Bahram, Bahri},
 booktitle = {14. Uluslararası Bilimsel Araştırmalar Kongresi ANKARA/TÜRKİYE 20 - 21 AĞUSTOS}
}

EPANET, su dağıtım şebekelerinin hidrolik modellemesinde en yaygın kullanılan açık kaynaklı programlardan biridir. Bu program, kararlı akım ve genişletilmiş dönem simülasyonu yaklaşımlarıyla analiz yapmaktadır. Bu yaklaşımlar, şebekelerdeki akımların ortalama debi ve basınçlarını etkin bir şekilde hesaplayabilmektedir. Ancak EPANET’in mevcut versiyonlarında, su dağıtım şebekelerinde sıkıştırılamaz değişken akımların simüle edilebilme imkanı bulunmamaktadır. Halbuki vanaların açılma-kapanma hareketleri ile su tüketiminin hızlı bir şekilde değişmesi gibi olgular ancak değişken akım algoritmalarıyla modellenebilmektedir. Bu sebeple bu çalışmada, EPANET 3'ün hidrolik çözücü kapasitesi, su dağıtım şebekelerinde sıkıştırılamaz değişken akım hidroliğini modellemek için Rijit Su Sütunu Küresel Gradyan Algoritması (RWC-GGA) ile genişletilmiştir. EPANET 3 kaynak kodunda yapılan bu değişikliğin hidrolik açıdan anlamlı sonuçlar ürettiği, bir su dağıtım şebekesi üzerinde yapılan simülasyonla gösterilmiştir.

@article{
 title = {Effect of Model Structure and Calibration Algorithm on Discharge Simulation in the Acısu Basin, Turkey},
 type = {article},
 year = {2022},
 pages = {196},
 volume = {10},
 websites = {https://www.mdpi.com/2225-1154/10/12/196},
 month = {12},
 day = {8},
 id = {d173d071-56e0-3b5d-96fd-ef3e7517de00},
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 abstract = {In this study, the Acısu Basin—viz., the headwater of the Gediz Basin—in Turkey, was modelled using three types of hydrological models and three different calibration algorithms. A well-known lumped model (GR4J), a commonly used semi-distributed (SWAT+) model, and a skillful distributed (mHM) hydrological model were built and integrated with the Parameter Estimation Tool (PEST). PEST is a model-independent calibration tool including three algorithms—namely, Levenberg Marquardt (L-M), Shuffled Complex Evolution (SCE), and Covariance Matrix Adoption Evolution Strategy (CMA-ES). The calibration period was 1991–2000, and the validation results were obtained for 2002–2005. The effect of the model structure and calibration algorithm selection on the discharge simulation was evaluated via comparison of nine different model-algorithm combinations. Results have shown that mHM and CMA-ES combination performed the best discharge simulation according to NSE values (calibration: 0.67, validation: 0.60). Although statistically the model results were classified as acceptable, the models mostly missed the peak values in the hydrograph. This problem may be related to the interventions made in 2000–2001 and may be overcome by changing the calibration and validation periods, increasing the number of iterations, or using the naturalized gauge data.},
 bibtype = {article},
 author = {Alp, Harun and Demirel, Mehmet Cüneyd and Aşıkoğlu, Ömer Levend},
 doi = {10.3390/cli10120196},
 journal = {Climate},
 number = {12}
}

In this study, the Acısu Basin—viz., the headwater of the Gediz Basin—in Turkey, was modelled using three types of hydrological models and three different calibration algorithms. A well-known lumped model (GR4J), a commonly used semi-distributed (SWAT+) model, and a skillful distributed (mHM) hydrological model were built and integrated with the Parameter Estimation Tool (PEST). PEST is a model-independent calibration tool including three algorithms—namely, Levenberg Marquardt (L-M), Shuffled Complex Evolution (SCE), and Covariance Matrix Adoption Evolution Strategy (CMA-ES). The calibration period was 1991–2000, and the validation results were obtained for 2002–2005. The effect of the model structure and calibration algorithm selection on the discharge simulation was evaluated via comparison of nine different model-algorithm combinations. Results have shown that mHM and CMA-ES combination performed the best discharge simulation according to NSE values (calibration: 0.67, validation: 0.60). Although statistically the model results were classified as acceptable, the models mostly missed the peak values in the hydrograph. This problem may be related to the interventions made in 2000–2001 and may be overcome by changing the calibration and validation periods, increasing the number of iterations, or using the naturalized gauge data.

@inbook{
 type = {inbook},
 year = {2021},
 pages = {101-124},
 websites = {https://link.springer.com/10.1007/978-981-33-4295-8_5},
 publisher = {Springer Nature},
 city = {Singapore},
 id = {1d1c70fe-065d-39eb-80fa-3b55cdeda025},
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 author = {Rezaei, Hossein and Bozorg-Haddad, Omid and Demirel, Mehmet Cüneyd},
 editor = {Bozorg-Haddad, Omid},
 doi = {10.1007/978-981-33-4295-8_5},
 chapter = {Remote Sensing Application in Water Resources Planning},
 title = {Essential Tools for Water Resources Analysis, Planning, and Management}
}

@article{
 title = {Hybrid point and interval prediction approaches for drought modeling using ground-based and remote sensing data},
 type = {article},
 year = {2021},
 websites = {https://iwaponline.com/hr/article/doi/10.2166/nh.2021.028/82635/Hybrid-point-and-interval-prediction-approaches},
 month = {6},
 day = {18},
 id = {98069636-f825-36f0-9ec8-38a2227766f5},
 created = {2021-06-18T21:25:00.546Z},
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 read = {true},
 starred = {false},
 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 abstract = {Drought as a severe natural disaster has devastating effects on the environment; therefore, reliable drought prediction is an important issue. In the current study, based on lower upper bound estimation, hybrid models including data preprocessing, permutation entropy, and artificial intelligence (AI) methods were used for point and interval predictions of short- to long-term series of Standardized Precipitation Index in the Northwest of Iran. Ground-based and remote sensing precipitation data were used covering the period of 1983–2017. In the modeling process, first, the data processing capability via variational mode decomposition (VMD), ensemble empirical mode decomposition, and permutation entropy (PE) was investigated in drought point prediction. Then, interval prediction was applied for tolerating increased uncertainty and providing more details for practical operation decisions. The simulation results demonstrated that the proposed integrated models could achieve significantly better performance compared to single models. Hybrid PE models increased the modeling accuracy up to 40 and 55%. Finally, the efficiency of developed models was verified for Normalized Difference Vegetation Index prediction. Results demonstrated that the proposed methodology based on remote sensing data and VMD–PE–AI approaches could be successfully used for drought modeling, especially in limited or non-gauged areas.},
 bibtype = {article},
 author = {Roushangar, Kiyoumars and Ghasempour, Roghayeh and Kirca, V. S. Ozgur and Demirel, Mehmet Cüneyd},
 doi = {10.2166/nh.2021.028},
 journal = {Hydrology Research}
}

Drought as a severe natural disaster has devastating effects on the environment; therefore, reliable drought prediction is an important issue. In the current study, based on lower upper bound estimation, hybrid models including data preprocessing, permutation entropy, and artificial intelligence (AI) methods were used for point and interval predictions of short- to long-term series of Standardized Precipitation Index in the Northwest of Iran. Ground-based and remote sensing precipitation data were used covering the period of 1983–2017. In the modeling process, first, the data processing capability via variational mode decomposition (VMD), ensemble empirical mode decomposition, and permutation entropy (PE) was investigated in drought point prediction. Then, interval prediction was applied for tolerating increased uncertainty and providing more details for practical operation decisions. The simulation results demonstrated that the proposed integrated models could achieve significantly better performance compared to single models. Hybrid PE models increased the modeling accuracy up to 40 and 55%. Finally, the efficiency of developed models was verified for Normalized Difference Vegetation Index prediction. Results demonstrated that the proposed methodology based on remote sensing data and VMD–PE–AI approaches could be successfully used for drought modeling, especially in limited or non-gauged areas.

@article{
 title = {Comparison of conventional and differential evolution-based parameter estimation methods on the flood frequency analysis},
 type = {article},
 year = {2021},
 pages = {1887-1900},
 volume = {69},
 websites = {https://link.springer.com/10.1007/s11600-021-00645-y},
 month = {10},
 day = {6},
 id = {d534ebfd-b948-3a88-a23b-482e5b477769},
 created = {2021-08-06T09:39:11.090Z},
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 authored = {true},
 confirmed = {true},
 hidden = {false},
 private_publication = {false},
 bibtype = {article},
 author = {Yilmaz, Muhammet and Tosunoglu, Fatih and Demirel, Mehmet Cüneyd},
 doi = {10.1007/s11600-021-00645-y},
 journal = {Acta Geophysica},
 number = {5}
}

@inproceedings{
 title = {Hidrolik Modellemeyle DMA Odası Konumunun Belirlenmesi},
 type = {inproceedings},
 year = {2021},
 pages = {Tam metin - Sözlü sunum},
 websites = {https://umuh.bilmescongress.com/arsiv/},
 id = {1c946798-53a4-3b25-8e04-f1d8ada542fd},
 created = {2021-12-29T13:46:39.763Z},
 file_attached = {false},
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 confirmed = {true},
 hidden = {false},
 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
 private_publication = {false},
 bibtype = {inproceedings},
 author = {Kıran, Samet and Sağ, A.B. and Koşucu, M.M. and Demirel, Mehmet Cüneyd},
 booktitle = {4. Ulusal Mühendislikte Bilimsel ve Mesleki Çalışmalar (UMUH-BİLMES)}
}

@inproceedings{
 title = {Su Dağıtım Şebekesi Hidrolik Modelinde Türbin ile Enerji Üretimi},
 type = {inproceedings},
 year = {2021},
 pages = {Tam metin - Sözlü sunum},
 websites = {https://umuh.bilmescongress.com/arsiv/},
 id = {b7795854-7449-39f4-8dd5-e43d6cc0ebd4},
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 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
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 bibtype = {inproceedings},
 author = {Alp, H and Koşucu, M.M. and Kıran, Samet and Demirel, Mehmet Cüneyd},
 booktitle = {4. Ulusal Mühendislikte Bilimsel ve Mesleki Çalışmalar (UMUH-BİLMES)}
}

@article{
 title = {Water leakage reduction in the water distribution network with real time pressure management},
 type = {article},
 year = {2021},
 volume = {32},
 id = {ca752b91-2258-3d95-b5e8-b4c4b6dc831d},
 created = {2024-05-13T21:26:55.987Z},
 file_attached = {false},
 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
 last_modified = {2024-05-13T21:26:55.987Z},
 read = {false},
 starred = {false},
 authored = {true},
 confirmed = {false},
 hidden = {false},
 private_publication = {true},
 abstract = {Reducing water leakages in water distribution systems is essential in terms of water, energy, treatment and time savings. However, the reduction of water leakages can only be realized effectively by pressure management with the help of a hydraulic model. When attempting to do this task with pressure reducing valves with constant pressure output, it is possible that either the critical point will fall below the minimum pressure value or that the desired efficiency cannot be obtained from the pressure management. For this reason, pressure management by real-time control method is very beneficial especially in large cities where the water consumption pattern shows large oscillations. Two important activities were carried out in this study. The first one is to perform a sensitivity analysis by performing Real Time pressure management under different water loss scenarios in a hypothetical network. The second is to demonstrate that this method is successful in reducing water losses by applying Real Time pressure management in the hydraulic model of a real network.},
 bibtype = {article},
 author = {Kosucu, M.M. and Sari, O. and Demirel, M.C. and Kiran, S. and Yilmaz, A. and Aybakan, A. and Albay, E. and Ozgur Kirca, V.S.},
 doi = {10.18400/TEKDERG.658870},
 journal = {Teknik Dergi/Technical Journal of Turkish Chamber of Civil Engineers},
 number = {1}
}

Reducing water leakages in water distribution systems is essential in terms of water, energy, treatment and time savings. However, the reduction of water leakages can only be realized effectively by pressure management with the help of a hydraulic model. When attempting to do this task with pressure reducing valves with constant pressure output, it is possible that either the critical point will fall below the minimum pressure value or that the desired efficiency cannot be obtained from the pressure management. For this reason, pressure management by real-time control method is very beneficial especially in large cities where the water consumption pattern shows large oscillations. Two important activities were carried out in this study. The first one is to perform a sensitivity analysis by performing Real Time pressure management under different water loss scenarios in a hypothetical network. The second is to demonstrate that this method is successful in reducing water losses by applying Real Time pressure management in the hydraulic model of a real network.

@article{
 title = {Effect of Using Multi-Year Land Use Land Cover and Monthly LAI Inputs on the Calibration of a Distributed Hydrologic Model},
 type = {article},
 year = {2021},
 keywords = {CORINE,Hydrologic Modeling,LULC,MODIS.,mHM},
 pages = {1538},
 volume = {13},
 websites = {https://www.mdpi.com/1130950,https://www.mdpi.com/2073-4441/13/11/1538},
 month = {5},
 publisher = {Multidisciplinary Digital Publishing Institute},
 day = {30},
 id = {bdd4f462-b20f-3973-9ad6-6094121ff1b7},
 created = {2025-05-29T04:59:42.299Z},
 accessed = {2021-05-31},
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 profile_id = {f04515b8-7bd9-3ff6-8226-72a3fe741d01},
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 citation_key = {Busari2021},
 source_type = {JOUR},
 folder_uuids = {20001051-c7d5-4fd4-926e-b73bceb5e8ae,54f9a1cb-cd85-43bf-81c7-692f1856eaa8},
 private_publication = {false},
 abstract = {Effective management of water resources entails the understanding of spatiotemporal changes in hydrologic fluxes with variation in land use, especially with a growing trend of urbanization, agricultural lands and non-stationarity of climate. This study explores the use of satellite-based Land Use Land Cover (LULC) data while simultaneously correcting potential evapotranspiration (PET) input with Leaf Area Index (LAI) to increase the performance of a physically distributed hydrologic model. The mesoscale hydrologic model (mHM) was selected for this purpose due to its unique features. Since LAI input informs the model about vegetation dynamics, we incorporated the LAI based PET correction option together with multi-year LULC data. The Globcover land cover data was selected for the single land cover cases, and hybrid of CORINE (coordination of information on the environment) and MODIS (Moderate Resolution Imaging Spectroradiometer) land cover datasets were chosen for the cases with multiple land cover datasets. These two datasets complement each other since MODIS has no separate forest class but more frequent (yearly) observations than CORINE. Calibration period spans from 1990 to 2006 and corresponding NSE (Nash-Sutcliffe Efficiency) values varies between 0.23 and 0.42, while the validation period spans from 2007 to 2010 and corresponding NSE values are between 0.13 and 0.39. The results revealed that the best performance is obtained when multiple land cover datasets are provided to the model and LAI data is used to correct PET, instead of default aspect-based PET correction in mHM. This study suggests that to minimize errors due to parameter uncertainties in physically distributed hydrologic models, adequate information can be supplied to the model with care taken to avoid over-parameterizing the model.},
 bibtype = {article},
 author = {Busari, Ibrahim Olayode and Demirel, Mehmet Cüneyd and Newton, Alice},
 doi = {10.3390/w13111538},
 journal = {Water},
 number = {11}
}

Effective management of water resources entails the understanding of spatiotemporal changes in hydrologic fluxes with variation in land use, especially with a growing trend of urbanization, agricultural lands and non-stationarity of climate. This study explores the use of satellite-based Land Use Land Cover (LULC) data while simultaneously correcting potential evapotranspiration (PET) input with Leaf Area Index (LAI) to increase the performance of a physically distributed hydrologic model. The mesoscale hydrologic model (mHM) was selected for this purpose due to its unique features. Since LAI input informs the model about vegetation dynamics, we incorporated the LAI based PET correction option together with multi-year LULC data. The Globcover land cover data was selected for the single land cover cases, and hybrid of CORINE (coordination of information on the environment) and MODIS (Moderate Resolution Imaging Spectroradiometer) land cover datasets were chosen for the cases with multiple land cover datasets. These two datasets complement each other since MODIS has no separate forest class but more frequent (yearly) observations than CORINE. Calibration period spans from 1990 to 2006 and corresponding NSE (Nash-Sutcliffe Efficiency) values varies between 0.23 and 0.42, while the validation period spans from 2007 to 2010 and corresponding NSE values are between 0.13 and 0.39. The results revealed that the best performance is obtained when multiple land cover datasets are provided to the model and LAI data is used to correct PET, instead of default aspect-based PET correction in mHM. This study suggests that to minimize errors due to parameter uncertainties in physically distributed hydrologic models, adequate information can be supplied to the model with care taken to avoid over-parameterizing the model.

@inproceedings{
 title = {Classification System Drives Disagreement Among Brazilian Vegetation Maps at a Sample Area of the Semiarid Caatinga},
 type = {inproceedings},
 year = {2020},
 pages = {499-504},
 websites = {https://ieeexplore.ieee.org/document/9165656/},
 month = {3},
 publisher = {IEEE},
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 author = {Bontempo, E. and Demirel, Mehmet Cüneyd and Corsini, C. and Martins, F. and Valeriano, D.},
 doi = {10.1109/LAGIRS48042.2020.9165656},
 booktitle = {2020 IEEE Latin American GRSS & ISPRS Remote Sensing Conference (LAGIRS)}
}

@article{
 title = {Correction: Hydrodynamic and hydrographie modeling of Istanbul Strait. [Processes (2019), 7, 710] doi: 10.3390/pr7100710},
 type = {article},
 year = {2020},
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 abstract = {We were not aware of an error made in the proofreading phase; therefore, we wish to make the following correction to Figure 7b from this paper.},
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 author = {Koşucu, M.M. and Demirel, M.C. and Kirca, V.S.O. and Özger, M.},
 doi = {10.3390/pr8020205},
 journal = {Processes},
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}

We were not aware of an error made in the proofreading phase; therefore, we wish to make the following correction to Figure 7b from this paper.

@article{
 title = {Selection of multi-model ensemble of general circulation models for the simulation of precipitation and maximum and minimum temperature based on spatial assessment metrics},
 type = {article},
 year = {2019},
 pages = {4803-4824},
 volume = {23},
 websites = {https://www.hydrol-earth-syst-sci-discuss.net/hess-2018-585/,https://www.hydrol-earth-syst-sci.net/23/4803/2019/},
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@inproceedings{
 title = {Calibration of Conceptual Hydrological Model Parameters using Heuristic Algorithms},
 type = {inproceedings},
 year = {2019},
 pages = {730-741},
 websites = {www.dokapsempozyum.org},
 city = {Tokat, Türkiye},
 id = {6e744829-afcb-342c-9e42-924149114590},
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 abstract = {Canlı yaşamında büyük öneme sahip olan tatlı suyun zaman içerisinde gösterdiği değişikliğin tespit edilmesi, hidrolojide en çok çalışılan konular arasındadır. Bilhassa akarsu kaynaklarının potansiyeli üzerinde çalışan araştırmacılar fiziksel (kavramsal) tabanlı ve veri güdümlü olmak üzere iki model etrafında çalışmalarına devam etmektedir. Fiziksel modeller, bir yağış-akış sürecinin coğrafi ve fiziksel parametreler yardımıyla açıklanmasını içermektedir. Veri güdümlü modeller ise yalnızca eldeki akış verilerini kullanarak hiçbir fiziksel kurala bağlı kalmaksızın, gelecekteki akış değerini tahmin etmek için kullanılır. Bu çalışmada fiziksel tabanlı, Hydrologiska Byråns Vattenbalansavdelning (HBV) modelinin parametrelerinin tahmini (eniyilenmesi) için sezgisel algoritmaların performansları karıştırılmıştır. Çalışma alanı olarak Ren Nehri havzası seçilmiştir. Bu havzaya ait günlük yağış (P), potansiyel evapotranspirasyon (PET) ve akış (Q) değerleri kullanılarak model kalibre edilmeye çalışılmıştır. HBV modeli yapısı gereği akış benzeşimi gerçekleştirmek için 8 parametre kullanmaktadır. Bu parametreler geniş bir aralıkta değerler almakta olup, her havza için farklı değerlerde en iyi temsil sağlanmaktadır. En iyi benzeşimi sağlayan parametre değerlerinin bulunması için Parameter Estimation Tool (PEST), Genetik Algoritma (GA), Parçacık Sürü Optimizasyonu (PSO) ve Benzetim Tavlama gibi arama algoritmaları kullanılmıştır. Amaç fonksiyonu olarak Nash-Sutcliffe (NSE) katsayısı kullanılan çalışmada, GA az bir farkla en iyi sonucu vermekte olup diğer tüm algoritmalar birbirine yakın sonuçlar vermiştir. Algoritmalar arasındaki en temel fark ise global minimuma ulaşma süreleri olmuştur. GA ve PSO en hızlı algoritmalar olurken PEST (Levenberg-Marquardt) en yavaş algoritma olarak tespit edilmiştir.},
 bibtype = {inproceedings},
 author = {Başakın, E E and Sağ, A B and Kartal, Elif and Avcuoğlu, M B and Demirel, Mehmet Cüneyd},
 editor = {Gül, Mustafa and Acungil, Y and Bozdoğan, D and Şimşek, Ü},
 booktitle = {3. International UNIDOKAP Black Sea Symposium (ISBN 978-605-80568-1-7)},
 keywords = {Tokat}
}

Canlı yaşamında büyük öneme sahip olan tatlı suyun zaman içerisinde gösterdiği değişikliğin tespit edilmesi, hidrolojide en çok çalışılan konular arasındadır. Bilhassa akarsu kaynaklarının potansiyeli üzerinde çalışan araştırmacılar fiziksel (kavramsal) tabanlı ve veri güdümlü olmak üzere iki model etrafında çalışmalarına devam etmektedir. Fiziksel modeller, bir yağış-akış sürecinin coğrafi ve fiziksel parametreler yardımıyla açıklanmasını içermektedir. Veri güdümlü modeller ise yalnızca eldeki akış verilerini kullanarak hiçbir fiziksel kurala bağlı kalmaksızın, gelecekteki akış değerini tahmin etmek için kullanılır. Bu çalışmada fiziksel tabanlı, Hydrologiska Byråns Vattenbalansavdelning (HBV) modelinin parametrelerinin tahmini (eniyilenmesi) için sezgisel algoritmaların performansları karıştırılmıştır. Çalışma alanı olarak Ren Nehri havzası seçilmiştir. Bu havzaya ait günlük yağış (P), potansiyel evapotranspirasyon (PET) ve akış (Q) değerleri kullanılarak model kalibre edilmeye çalışılmıştır. HBV modeli yapısı gereği akış benzeşimi gerçekleştirmek için 8 parametre kullanmaktadır. Bu parametreler geniş bir aralıkta değerler almakta olup, her havza için farklı değerlerde en iyi temsil sağlanmaktadır. En iyi benzeşimi sağlayan parametre değerlerinin bulunması için Parameter Estimation Tool (PEST), Genetik Algoritma (GA), Parçacık Sürü Optimizasyonu (PSO) ve Benzetim Tavlama gibi arama algoritmaları kullanılmıştır. Amaç fonksiyonu olarak Nash-Sutcliffe (NSE) katsayısı kullanılan çalışmada, GA az bir farkla en iyi sonucu vermekte olup diğer tüm algoritmalar birbirine yakın sonuçlar vermiştir. Algoritmalar arasındaki en temel fark ise global minimuma ulaşma süreleri olmuştur. GA ve PSO en hızlı algoritmalar olurken PEST (Levenberg-Marquardt) en yavaş algoritma olarak tespit edilmiştir.

@article{
 title = {Hydrodynamic and Hydrographic Modeling of Istanbul Strait},
 type = {article},
 year = {2019},
 pages = {710},
 volume = {7},
 websites = {https://www.mdpi.com/2227-9717/7/10/710},
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 abstract = {The aim of this study is to model the hydrodynamic processes of the Istanbul Strait with its stratified flow characteristics, and calibrate the most important parameters using local and global search algorithms. For that, two open boundary conditions are defined, which are in the northern and southern parts of the Strait. Observed bathymetric, hydrographic, meteorological, and water-level data are used to set up the Delft3D-FLOW model. First, the sensitivities of the model parameters on the numerical model outputs are assessed using Parameter EStimation Tool (PEST) toolbox. Then, the model is calibrated based on the objective functions, focusing on the flow rates of the upper and lower layers. The salinity and temperature profiles of the strait are only used for model validation. The results show that the calibrated model outputs of the Istanbul Strait are reliable and consistent with the in situ measurements. The sensitivity analysis reveals that the spatial low-pass filter coefficient, horizontal eddy viscosity, Prandtl–Schmidt number, slope in log–log spectrum, and Manning roughness coefficient are most sensitive parameters affecting the flow rate performance of the model. The agreement between observed salinity profiles and simulated model outputs is promising, whereas the match between observed and simulated temperature profiles is weak, showing that the model can be improved, particularly for simulating the mixing layer.},
 bibtype = {article},
 author = {Koşucu, Mehmet Melih and Demirel, Mehmet Cüneyd and Kirca, VS O and Özger, Mehmet},
 doi = {10.3390/pr7100710},
 journal = {Processes},
 number = {10}
}

The aim of this study is to model the hydrodynamic processes of the Istanbul Strait with its stratified flow characteristics, and calibrate the most important parameters using local and global search algorithms. For that, two open boundary conditions are defined, which are in the northern and southern parts of the Strait. Observed bathymetric, hydrographic, meteorological, and water-level data are used to set up the Delft3D-FLOW model. First, the sensitivities of the model parameters on the numerical model outputs are assessed using Parameter EStimation Tool (PEST) toolbox. Then, the model is calibrated based on the objective functions, focusing on the flow rates of the upper and lower layers. The salinity and temperature profiles of the strait are only used for model validation. The results show that the calibrated model outputs of the Istanbul Strait are reliable and consistent with the in situ measurements. The sensitivity analysis reveals that the spatial low-pass filter coefficient, horizontal eddy viscosity, Prandtl–Schmidt number, slope in log–log spectrum, and Manning roughness coefficient are most sensitive parameters affecting the flow rate performance of the model. The agreement between observed salinity profiles and simulated model outputs is promising, whereas the match between observed and simulated temperature profiles is weak, showing that the model can be improved, particularly for simulating the mixing layer.

@article{
 title = {The changing characteristics of groundwater sustainability in Pakistan from 2002 to 2016},
 type = {article},
 year = {2019},
 pages = {2485-2496},
 volume = {27},
 websites = {http://link.springer.com/10.1007/s10040-019-02023-x},
 month = {11},
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 journal = {Hydrogeology Journal},
 number = {7}
}

@article{
 title = {Additional Value of Using Satellite-Based Soil Moisture and Two Sources of Groundwater Data for Hydrological Model Calibration},
 type = {article},
 year = {2019},
 keywords = {bitirme projesi},
 pages = {2083},
 volume = {11},
 websites = {https://www.mdpi.com/2073-4441/11/10/2083/htm,https://www.mdpi.com/2073-4441/11/10/2083},
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 abstract = {Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model’s physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Özen, Alparslan and Orta, Selen and Toker, Emir and Demir, Hatice Kübra and Ekmekcioğlu, Ömer and Tayşi, Hüsamettin and Eruçar, Sinan and Sağ, Ahmet Bilal and Sarı, Ömer and Tuncer, Ecem and Hancı, Hayrettin and Özcan, Türkan İrem and Erdem, Hilal and Koşucu, Mehmet Melih and Başakın, Eyyup Ensar and Ahmed, Kamal and Anwar, Awat and Avcuoğlu, Muhammet Bahattin and Vanlı, Ömer and Stisen, Simon and Booij, Martijn J.},
 doi = {10.3390/w11102083},
 journal = {Water},
 number = {10}
}

Although the complexity of physically-based models continues to increase, they still need to be calibrated. In recent years, there has been an increasing interest in using new satellite technologies and products with high resolution in model evaluations and decision-making. The aim of this study is to investigate the value of different remote sensing products and groundwater level measurements in the temporal calibration of a well-known hydrologic model i.e., Hydrologiska Bryåns Vattenbalansavdelning (HBV). This has rarely been done for conceptual models, as satellite data are often used in the spatial calibration of the distributed models. Three different soil moisture products from the European Space Agency Climate Change Initiative Soil Measure (ESA CCI SM v04.4), The Advanced Microwave Scanning Radiometer on the Earth Observing System (EOS) Aqua satellite (AMSR-E), soil moisture active passive (SMAP), and total water storage anomalies from Gravity Recovery and Climate Experiment (GRACE) are collected and spatially averaged over the Moselle River Basin in Germany and France. Different combinations of objective functions and search algorithms, all targeting a good fit between observed and simulated streamflow, groundwater and soil moisture, are used to analyze the contribution of each individual source of information. Firstly, the most important parameters are selected using sensitivity analysis, and then these parameters are included in a subsequent model calibration. The results of our multi-objective calibration reveal a substantial contribution of remote sensing products to the lumped model calibration, even if their spatially-distributed information is lost during the spatial aggregation. Inclusion of new observations, such as groundwater levels from wells and remotely sensed soil moisture to the calibration improves the model’s physical behavior, while it keeps a reasonable water balance that is the key objective of every hydrologic model.

@article{
 title = {Spatial Pattern Oriented Multicriteria Sensitivity Analysis of a Distributed Hydrologic Model},
 type = {article},
 year = {2018},
 keywords = {GLUE,actual evapotranspiration,mHM,remote sensing,sensitivity analysis,spatial pattern},
 pages = {1188},
 volume = {10},
 websites = {http://www.mdpi.com/2073-4441/10/9/1188},
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 abstract = {Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represent an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity typically do not reflect other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). The Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definitions based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis.},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Koch, Julian and Mendiguren, Gorka and Stisen, Simon},
 doi = {10.3390/w10091188},
 journal = {Water},
 number = {9}
}

Hydrologic models are conventionally constrained and evaluated using point measurements of streamflow, which represent an aggregated catchment measure. As a consequence of this single objective focus, model parametrization and model parameter sensitivity typically do not reflect other aspects of catchment behavior. Specifically for distributed models, the spatial pattern aspect is often overlooked. Our paper examines the utility of multiple performance measures in a spatial sensitivity analysis framework to determine the key parameters governing the spatial variability of predicted actual evapotranspiration (AET). The Latin hypercube one-at-a-time (LHS-OAT) sampling strategy with multiple initial parameter sets was applied using the mesoscale hydrologic model (mHM) and a total of 17 model parameters were identified as sensitive. The results indicate different parameter sensitivities for different performance measures focusing on temporal hydrograph dynamics and spatial variability of actual evapotranspiration. While spatial patterns were found to be sensitive to vegetation parameters, streamflow dynamics were sensitive to pedo-transfer function (PTF) parameters. Above all, our results show that behavioral model definitions based only on streamflow metrics in the generalized likelihood uncertainty estimation (GLUE) type methods require reformulation by incorporating spatial patterns into the definition of threshold values to reveal robust hydrologic behavior in the analysis.

@article{
 title = {The SPAtial EFficiency metric (SPAEF): multiple-component evaluation of spatial patterns for optimization of hydrological models},
 type = {article},
 year = {2018},
 pages = {1873-1886},
 volume = {11},
 websites = {https://gmd.copernicus.org/articles/11/1873/2018/,https://www.geosci-model-dev-discuss.net/gmd-2017-238/,https://www.geosci-model-dev.net/11/1873/2018/},
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@article{
 title = {Combining satellite data and appropriate objective functions for improved spatial pattern performance of a distributed hydrologic model},
 type = {article},
 year = {2018},
 pages = {1299-1315},
 volume = {22},
 websites = {https://hess.copernicus.org/articles/22/1299/2018/,https://www.hydrol-earth-syst-sci.net/22/1299/2018/,https://www.hydrol-earth-syst-sci.net/22/1299/2018/hess-22-1299-2018.pdf},
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 abstract = {Abstract. Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Mai, Juliane and Mendiguren, Gorka and Koch, Julian and Samaniego, Luis and Stisen, Simon},
 doi = {10.5194/hess-22-1299-2018},
 journal = {Hydrol. Earth Syst. Sci.},
 number = {2}
}

Abstract. Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.

@inproceedings{
 title = {Calibration of a distributed hydrologic model for six European catchments using remote sensing data},
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 booktitle = {American Geophysical Union Fall Meeting}
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@article{
 title = {Medium-Range Low Flow Forecasts in the Lobith, River Rhine},
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 year = {2017},
 pages = {139-148},
 volume = {22},
 websites = {http://dergipark.gov.tr/doi/10.17482/uumfd.338785},
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 journal = {Uludağ University Journal of The Faculty of Engineering},
 number = {2}
}

@article{
 title = {A comparative assessment of projected meteorological and hydrological droughts: Elucidating the role of temperature},
 type = {article},
 year = {2017},
 pages = {785-797},
 volume = {553},
 websites = {http://linkinghub.elsevier.com/retrieve/pii/S002216941730584X,https://linkinghub.elsevier.com/retrieve/pii/S002216941730584X},
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 bibtype = {article},
 author = {Ahmadalipour, Ali and Moradkhani, Hamid and Demirel, Mehmet Cüneyd},
 doi = {10.1016/j.jhydrol.2017.08.047},
 journal = {Journal of Hydrology}
}

@inproceedings{
 title = {Integrating satellite actual evapotranspiration patterns into distributed model parametrization and evaluation for a mesoscale catchment},
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 year = {2016},
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 booktitle = {American Geophysical Union Fall Meeting}
}

@article{
 title = {Assessing the impact of CMIP5 climate multi-modeling on estimating the precipitation seasonality and timing},
 type = {article},
 year = {2016},
 pages = {357-372},
 volume = {135},
 websites = {http://link.springer.com/10.1007/s10584-015-1559-z},
 month = {3},
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 journal = {Climatic Change},
 number = {2}
}

@inproceedings{
 title = {On the Value of Climate Elasticity Indices to Assess the Impact of Climate Change on Streamflow Projection using an ensemble of bias corrected CMIP5 dataset},
 type = {inproceedings},
 year = {2015},
 pages = {EGU2015-6881},
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 doi = {10.13140/RG.2.2.12609.15200},
 booktitle = {EGU General Assembly}
}

@article{
 title = {The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models},
 type = {article},
 year = {2015},
 pages = {275-291},
 volume = {19},
 websites = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921346683&partnerID=40&md5=261ee50d14696a3a752e0a3c9d5b3987,http://www.hydrol-earth-syst-sci.net/19/275/2015/hess-19-275-2015.pdf,http://www.hydrol-earth-syst-sci.net/19/275/2015/,https://hess.copernic},
 month = {1},
 publisher = {Copernicus GmbH},
 day = {16},
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 language = {English},
 notes = {<b>From Duplicate 1 (<i>The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models</i> - Demirel, M C; Booij, M J; Hoekstra, A Y)<br/></b><br/>Cited By :1<br/><br/>Export Date: 11 September 2016},
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 private_publication = {false},
 abstract = {Abstract. This paper investigates the skill of 90-day low-flow forecasts using two conceptual hydrological models and one data-driven model based on Artificial Neural Networks (ANNs) for the Moselle River. The three models, i.e. HBV, GR4J and ANN-Ensemble (ANN-E), all use forecasted meteorological inputs (precipitation P and potential evapotranspiration PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low-flow forecasts for five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the models. The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the models are compared based on their skill of low-flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90-day-ahead low flows in the very dry year 2003 without precipitation data. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Booij, M J. and Hoekstra, A Y.},
 doi = {10.5194/hess-19-275-2015},
 journal = {Hydrology and Earth System Sciences},
 number = {1}
}

Abstract. This paper investigates the skill of 90-day low-flow forecasts using two conceptual hydrological models and one data-driven model based on Artificial Neural Networks (ANNs) for the Moselle River. The three models, i.e. HBV, GR4J and ANN-Ensemble (ANN-E), all use forecasted meteorological inputs (precipitation P and potential evapotranspiration PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low-flow forecasts for five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the models. The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the models are compared based on their skill of low-flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict runoff during low-flow periods using ensemble seasonal meteorological forcing. The largest range for 90-day low-flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90-day-ahead low flows in the very dry year 2003 without precipitation data. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low-flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.

@inproceedings{
 title = {The effect of multi-model averaging of climate model outputs on the seasonality of rainfall over the Columbia River Basin.},
 type = {inproceedings},
 year = {2014},
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 doi = {10.13140/2.1.4778.4322},
 booktitle = {5th Annual Pacific Northwest Climate Science Conference}
}

@inproceedings{
 title = {Impacts of climate change on the seasonality of extremes in the Columbia River Basin},
 type = {inproceedings},
 year = {2014},
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 booktitle = {American Geophysical Union Fall Meeting}
}

@article{
 title = {Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations},
 type = {article},
 year = {2013},
 pages = {4241-4257},
 volume = {17},
 websites = {http://www.hydrol-earth-syst-sci.net/17/4241/2013/},
 month = {10},
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 journal = {Hydrology and Earth System Sciences},
 number = {10}
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@article{
 title = {Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times},
 type = {article},
 year = {2013},
 keywords = {River Rhine,appropriate modelling,correlation analysis,lag,low flows,temporal resolution},
 pages = {2742-2758},
 volume = {27},
 websites = {http://dx.doi.org/10.1002/hyp.9402,http://doi.wiley.com/10.1002/hyp.9402},
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@article{
 title = {Effect of different uncertainty sources on the skill of 10 day ensemble low flow forecasts for two hydrological models},
 type = {article},
 year = {2013},
 keywords = {1812 Drought,1816 Estimation and forecasting,1847 Modeling,1873 Uncertainty assessment,GLUE,GR4J,HBV,Moselle River,low flows,uncertainty analysis},
 pages = {4035-4053},
 volume = {49},
 websites = {http://doi.wiley.com/10.1002/wrcr.20294},
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 doi = {10.1002/wrcr.20294},
 journal = {Water Resources Research},
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@inproceedings{
 title = {Wavelets Transform Applied to Hydrological Time Series (HIC-1A1-DM6)},
 type = {inproceedings},
 year = {2009},
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 bibtype = {inproceedings},
 author = {Rivera, D and Lillo, M and Arumi, J and Demirel, Mehmet Cüneyd},
 booktitle = {Proceedings of the 8th International Conference on Hydroinformatics}
}

@inproceedings{
 title = {Identification of an appropriate low flow forecast model for the Meuse River (Oral presentation, full text)},
 type = {inproceedings},
 year = {2009},
 keywords = {so:78691},
 pages = {296-303},
 volume = {331},
 issue = {331},
 websites = {http://doc.utwente.nl/78691/},
 publisher = {IAHS Press},
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 abstract = {This study investigates the selection of an appropriate low flow forecast model for the Meuse River based on the comparison of output uncertainties of different models. For this purpose, three data driven models have been developed for the Meuse River: a multivariate ARMAX model, a linear regression model and an Artificial Neural Network (ANN) model. The uncertainty in these three models is assumed to be represented by the difference between observed and simulated discharge. The results show that the ANN low flow forecast model with one or two input variables(s) performed slightly better than the other statistical models when forecasting low flows for a lead time of seven days. The approach for the selection of an appropriate low flow forecast model adopted in this study can be used for other lead times and river basins as well.},
 bibtype = {inproceedings},
 author = {Demirel, Mehmet Cüneyd and Booij, Martijn J M.J.},
 editor = {Cluckie, Ian and Chen, Yangbo and Babovic, Vladan and Konikow, Lenny and Mynett, Arthur and Demuth, Siegfried and Savic, Dragan A},
 booktitle = {Hydroinformatics in hydrology, hydrogeology and water resources}
}

This study investigates the selection of an appropriate low flow forecast model for the Meuse River based on the comparison of output uncertainties of different models. For this purpose, three data driven models have been developed for the Meuse River: a multivariate ARMAX model, a linear regression model and an Artificial Neural Network (ANN) model. The uncertainty in these three models is assumed to be represented by the difference between observed and simulated discharge. The results show that the ANN low flow forecast model with one or two input variables(s) performed slightly better than the other statistical models when forecasting low flows for a lead time of seven days. The approach for the selection of an appropriate low flow forecast model adopted in this study can be used for other lead times and river basins as well.

@article{
 title = {Discussion of "hydrologic regionalization of watersheds in Turkey" by Sabahattin Isik and Vijay P. Singh},
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 year = {2009},
 volume = {14},
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 author = {Demirel, M.C. and Kahya, E. and Rivera, D.},
 doi = {10.1061/(ASCE)HE.1943-5584.0000036},
 journal = {Journal of Hydrologic Engineering},
 number = {7}
}

@article{
 title = {Discussion of “Clustering On Dissimilarity Representations for Detecting Mislabelled Seismic Signals at Nevado Del Ruiz Volcano” by Mauricio Orozco-Alzate, and César Germán Castellanos-Domínguez},
 type = {article},
 year = {2008},
 pages = {265-268},
 volume = {12},
 websites = {http://www.scielo.org.co/scielo.php?script=sci_arttext&pid=S1794-61902008000200008},
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 citation_key = {Demirel2008b},
 source_type = {Journal Article},
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 private_publication = {false},
 bibtype = {article},
 author = {Demirel, Mehmet Cüneyd and Kahya, Ercan and Rivera, Diego},
 journal = {Earth Sciences Research Journal},
 number = {2}
}

@inproceedings{
 title = {Impact of waste water discharges in Ria Formosa Coastal Lagoon (Portugal)},
 type = {inproceedings},
 year = {2008},
 websites = {http://www.mwwd.org/images/mwwd2008/downloads/Summary_Demirel.pdf,http://www.mwwd.org/wp-content/uploads/2014/04/web list 2008.xlsx},
 city = {Cavtat-Croatia},
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 source_type = {Conference Proceedings},
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 private_publication = {false},
 bibtype = {inproceedings},
 author = {Demirel, Mehmet Cüneyd and Kahya, Ercan},
 editor = {Avanzini, Carlo},
 booktitle = {Proceedings of the MWWD 2008 – 5th International Conference on Marine Waste Water Discharges and Coastal Environment},
 keywords = {ISBN: 978-9944-5566-3-7}
}

@inproceedings{
 title = {Seasonal and long-term prediction of low flows in the Rhine Basin (Poster presentation, full text)},
 type = {inproceedings},
 year = {2008},
 pages = {54-55},
 websites = {http://doc.utwente.nl/67892/},
 city = {Dalfsen, the Netherlands},
 id = {72cd457b-657b-38cf-89d6-e86f897c9443},
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 source_type = {Conference Paper},
 folder_uuids = {620eeb49-e26b-4729-8ee9-eb8b6c95ab75},
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 abstract = {The aim of this paper is to give information about a new project on the Rhine River. In this project we intent to identify appropriate low flow prediction models for the seasonal and long term by comparing uncertainties in low flows predicted by different pre-selected models.},
 bibtype = {inproceedings},
 author = {Demirel, Mehmet Cüneyd and Booij, M J and Hoekstra, A Y},
 editor = {Erdbrink, C D and Os van, A G},
 booktitle = {NCR-days 2008},
 keywords = {so:67892}
}

The aim of this paper is to give information about a new project on the Rhine River. In this project we intent to identify appropriate low flow prediction models for the seasonal and long term by comparing uncertainties in low flows predicted by different pre-selected models.

@article{
 title = {Hydrologic homogeneous regions using monthly streamflow in Turkey},
 type = {article},
 year = {2008},
 keywords = {Cluster analysis,Homogeneous region,Regionalization,Streamflow,Turkey,Ward's method},
 pages = {181-193},
 volume = {12},
 id = {1fc23685-6171-3d3d-9f31-0461ef6fed65},
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 citation_key = {Kahya2008},
 source_type = {Journal Article},
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 private_publication = {false},
 abstract = {Cluster analysis of gauged streamflow records into homogeneous and robust regions is an important tool for the characterization of hydrologic systems. In this paper we applied the hierarchical cluster analysis to the task of objectively classifying streamflow data into regions encompassing similar streamflow patterns over Turkey. The performance of three standardization techniques was also tested, and standardizing by range was found better than standardizing with zero mean and unit variance. Clustering was carried out using Ward's minimum variance method which became prominent in managing water resources with squared Euclidean dissimilarity measures on 80 streamflow stations. The stations have natural flow regimes where no intensive river regulation had occurred. A general conclusion drawn is that the zones having similar streamflow pattern were not be overlapped well with the conventional climate zones of Turkey; however, they are coherent with the climate zones of Turkey recently redefined by the cluster analysis to total precipitation data as well as homogenous streamflow zones of Turkey determined by the rotated principal component analysis. The regional streamflow information in this study can significantly improve the accuracy of flow predictions in ungauged watersheds.},
 bibtype = {article},
 author = {Kahya, Ercan and Demirel, Mehmet Cüneyd and Beg, Osman A O.A.},
 journal = {Earth Sciences Research Journal},
 number = {2}
}

Cluster analysis of gauged streamflow records into homogeneous and robust regions is an important tool for the characterization of hydrologic systems. In this paper we applied the hierarchical cluster analysis to the task of objectively classifying streamflow data into regions encompassing similar streamflow patterns over Turkey. The performance of three standardization techniques was also tested, and standardizing by range was found better than standardizing with zero mean and unit variance. Clustering was carried out using Ward's minimum variance method which became prominent in managing water resources with squared Euclidean dissimilarity measures on 80 streamflow stations. The stations have natural flow regimes where no intensive river regulation had occurred. A general conclusion drawn is that the zones having similar streamflow pattern were not be overlapped well with the conventional climate zones of Turkey; however, they are coherent with the climate zones of Turkey recently redefined by the cluster analysis to total precipitation data as well as homogenous streamflow zones of Turkey determined by the rotated principal component analysis. The regional streamflow information in this study can significantly improve the accuracy of flow predictions in ungauged watersheds.

@inproceedings{
 title = {Erasmus Mundus Scholar's Perspective on Water and Coastal Management Education in Europe},
 type = {inproceedings},
 year = {2007},
 websites = {http://www.dsi.gov.tr/english/congress2007/chapter_1/06.pdf},
 city = {Antalya , Turkey},
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 author = {Ganapuram, S and Hamidov, A and Demirel, Mehmet Cüneyd and Bozkurt, E and Kindap, U and Newton, A},
 booktitle = {International Congress - River Basin Management}
}

@inproceedings{
 title = {Türkiye verilerinin genel hidroklimatolojik davranışları: İklim değişikliği nabzının teşhisi.},
 type = {inproceedings},
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 author = {Kahya, E. and Kalaycı, S. and Karabörk, M Ç. and Martı, A I . and Demirel, Mehmet Cüneyd and Partal, T.},
 booktitle = {Global Climate Change and Its Environmental Impacts: Regional and Local Dimensions, 18-20 October, Konya, Turkey.}
}

@inproceedings{
 title = {Hydrological determination of hierarchical clustering scheme by using small experimental matrix},
 type = {inproceedings},
 year = {2007},
 pages = {161-168},
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 author = {Demirel, Mehmet Cüneyd and Kahya, Ercan},
 booktitle = {27th AGU Hydrology Days}
}

@inproceedings{
 title = {Implementation of Web Mapping Tools for Monitoring Water Quality in Ria Formosa Coastal Lagoon using UMN MapServer},
 type = {inproceedings},
 year = {2006},
 websites = {http://www.cmos.ca/CongressAbstracts/cong4006.pdf},
 city = {Toronto, Canada},
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 author = {Demirel, Mehmet Cüneyd and Martins, F and Galvao, P and Saraiva, S},
 booktitle = {40th CMOS CONGRESS, Weather, Oceans and Climate, Exploring the Connections}
}

@inproceedings{
 title = {A Comparison of Low Flow Clustering Methods: Streamflow Grouping},
 type = {inproceedings},
 year = {2006},
 volume = {8, 01373},
 websites = {http://www.cosis.net/abstracts/EGU06/01373/EGU06-J-01373-2.pdf},
 publisher = {Geophysical Research Abstracts},
 city = {Vienna , Austria},
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 author = {Demirel, Mehmet Cüneyd and Karaca, M and Martins, F and Kahya, E},
 booktitle = {EGU General Assembly}
}

@inproceedings{
 title = {Turkiye Yagis ve Akim Verilerinin Kume Analizi Yontemi ile Siniflandirilmasi},
 type = {inproceedings},
 year = {2005},
 city = {İzmir},
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 bibtype = {inproceedings},
 author = {Demirel, Mehmet Cüneyd and Kahya, E. and Karaca, M. and Kindap, T.},
 booktitle = {II. Ulusal Su Muhendisligi Sempozyumu, DSI Gumuldur Izmir}
}

@inproceedings{
 title = {Determination of Rainfall Time Distributions of Turkey by Using Cluster Analysis},
 type = {inproceedings},
 year = {2005},
 websites = {http://www.cosis.net/abstracts/EMS05/00182/EMS05-A-00182-5.pdf},
 city = {Utrecht, the Netherlands},
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 bibtype = {inproceedings},
 author = {Gunel, M. Sinan and Demirel, Mehmet Cüneyd and Kucuk, Murat and Agiralioglu, Necati},
 booktitle = {Fifth Annual Meeting of the European Meteorological Society}
}

@inproceedings{
 title = {Turkiye Genelindeki Mevsimlik Akim Verilerinin Kume Analizi ile Bolgelere Ayrilmasi},
 type = {inproceedings},
 year = {2004},
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 author = {Demirel, Mehmet Cüneyd and Kahya, E. and Karacuha, G.},
 booktitle = {I. Ulusal Barajlar ve Hidroelektrik Santrallar Sempozyumu, DSI Genel Mudurlugu, Ankara}
}

@phdthesis{
 title = {Cluster analysis of streamflow data over Turkey},
 type = {phdthesis},
 year = {2004},
 pages = {104},
 publisher = {Istanbul Technical University},
 city = {Istanbul},
 institution = {Istanbul Technical University},
 department = {Institute of Science and Technology},
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 author = {Demirel, Mehmet Cüneyd and Kahya, Ercan},
 doi = {10.13140/2.1.3944.2249}
}