@article{yu_impacts_2022,
	title = {Impacts of the {Scale} of {Representation} of {Heterogeneity} on {Simulated} {Salinity} and {Saltwater} {Circulation} in {Coastal} {Aquifers}},
	volume = {58},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2020WR029523},
	doi = {https://doi.org/10.1029/2020WR029523},
	abstract = {Abstract Numerical models of variable-density groundwater flow and salt transport are a primary tool for predicting salinity distributions in coastal aquifers and estimating submarine groundwater discharge (SGD). Models are particularly useful to estimate the saline component of SGD, which can occur far offshore and is difficult to measure directly. Depending on the system and application, the level of geologic detail represented can range from homogeneous or layered to fully heterogeneous hydraulic conductivity fields. These features strongly affect model results, limiting understanding of subsurface salinity distributions and associated density-driven saltwater circulation along coasts worldwide. In this study, the impact of the scale of representation of heterogeneity on salinity distributions and SGD was investigated using numerical simulations. Upscaling hydraulic conductivity can significantly modify salinity distributions and flow paths, resulting in unpredictable variations in simulated SGD, though the values for homogeneous fields with equivalent hydraulic conductivity show consistent trends. Simulated density distributions control both the rate and direction of subsurface saltwater circulation. The length of the mixing zone perimeter, a measure of salinity distribution complexity, is shown to correlate with both the rate of subsurface saltwater circulation and the amount of groundwater circulating in the reverse direction from homogeneous cases. Overall, the results demonstrate a strong dependence of salinity distributions and saltwater circulation on the scale and distribution of geologic heterogeneity represented in numerical models. This suggests that numerical models with simplified geologic structure may substantially underestimate saltwater circulation, and attempts to calibrate them using salinity distributions or SGD measurements may be problematic.},
	number = {1},
	journal = {Water Resources Research},
	author = {Yu, Xuan and Michael, Holly A.},
	year = {2022},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2020WR029523},
	keywords = {geologic heterogeneity, groundwater modeling, saltwater circulation, scale-dependence, submarine groundwater discharge},
	pages = {e2020WR029523},
}

Abstract Numerical models of variable-density groundwater flow and salt transport are a primary tool for predicting salinity distributions in coastal aquifers and estimating submarine groundwater discharge (SGD). Models are particularly useful to estimate the saline component of SGD, which can occur far offshore and is difficult to measure directly. Depending on the system and application, the level of geologic detail represented can range from homogeneous or layered to fully heterogeneous hydraulic conductivity fields. These features strongly affect model results, limiting understanding of subsurface salinity distributions and associated density-driven saltwater circulation along coasts worldwide. In this study, the impact of the scale of representation of heterogeneity on salinity distributions and SGD was investigated using numerical simulations. Upscaling hydraulic conductivity can significantly modify salinity distributions and flow paths, resulting in unpredictable variations in simulated SGD, though the values for homogeneous fields with equivalent hydraulic conductivity show consistent trends. Simulated density distributions control both the rate and direction of subsurface saltwater circulation. The length of the mixing zone perimeter, a measure of salinity distribution complexity, is shown to correlate with both the rate of subsurface saltwater circulation and the amount of groundwater circulating in the reverse direction from homogeneous cases. Overall, the results demonstrate a strong dependence of salinity distributions and saltwater circulation on the scale and distribution of geologic heterogeneity represented in numerical models. This suggests that numerical models with simplified geologic structure may substantially underestimate saltwater circulation, and attempts to calibrate them using salinity distributions or SGD measurements may be problematic.

@article{yang_large_2022,
	title = {Large increase in {CH4} emission following conversion of coastal marsh to aquaculture ponds caused by changing gas transport pathways},
	doi = {10.1016/j.watres.2022.118882},
	journal = {Water Research},
	author = {Yang, Ping and Lai, Derrick Y.F. and Yang, Hong and Yongxin, Lin and Tong, Chuan and Hong, Yan and Tian, Yalan and Tang, Chen and Tang, Kam},
	month = aug,
	year = {2022},
	pages = {118882},
}

@article{hou_impacts_2022,
	title = {Impacts of {Coastal} {Shrimp} {Ponds} on {Saltwater} {Intrusion} and {Submarine} {Groundwater} {Discharge}},
	volume = {58},
	issn = {0043-1397},
	url = {https://doi.org/10.1029/2021WR031866},
	doi = {10.1029/2021WR031866},
	abstract = {Abstract Shrimp aquaculture has expanded rapidly in coastal zones worldwide over the past few decades. Saline water stored in shrimp farm ponds can infiltrate into the underlying aquifer causing groundwater salinization and increased submarine groundwater discharge (SGD) to coastal water. However, little research has assessed salinization resulting from these shrimp ponds. To understand the impacts of shrimp farm irrigation on groundwater salinization and SGD, we numerically simulated a series of aquaculture management scenarios in a two-dimensional conceptual coastal aquifer using a coupled surface-subsurface approach. We characterized sensitivities to pond water salinity, pond water depth, and farm width. Salinization was assessed by three indicators (salinized area, infiltrated salt mass, and recovery rate), and three SGD indicators were evaluated (fresh SGD, saline SGD, and saltwater circulation rate). Our results show that pond water depth is the primary control on the mass of saltwater infiltration while farm width is the primary control for recovery rate. Pond water salinity and depth affect both fresh and saline SGD. We show that aquaculture is a previously unrecognized mechanism of salinization affecting coastal aquifer vulnerability and SGD. A regional graphical information system analysis shows transformation into aquacultural ponds could introduce considerable SGD variability spatially and temporally. These findings will enable coastal managers to better evaluate groundwater vulnerability in regions with expanding onshore aquaculture and demonstrates the impact of aquaculture on coastal groundwater resources and the need for further study to understand the impact of aquaculture across Asia and the globe.},
	number = {7},
	urldate = {2022-08-28},
	journal = {Water Resources Research},
	author = {Hou, Yuxuan and Yang, Jie and Russoniello, Christopher J. and Zheng, Tianyuan and Wu, Mei-lin and Yu, Xuan},
	month = jul,
	year = {2022},
	note = {Publisher: John Wiley \& Sons, Ltd},
	keywords = {aquaculture, salinization, saltwater intrusion, shrimp pond, submarine groundwater discharge},
	pages = {e2021WR031866},
}

Abstract Shrimp aquaculture has expanded rapidly in coastal zones worldwide over the past few decades. Saline water stored in shrimp farm ponds can infiltrate into the underlying aquifer causing groundwater salinization and increased submarine groundwater discharge (SGD) to coastal water. However, little research has assessed salinization resulting from these shrimp ponds. To understand the impacts of shrimp farm irrigation on groundwater salinization and SGD, we numerically simulated a series of aquaculture management scenarios in a two-dimensional conceptual coastal aquifer using a coupled surface-subsurface approach. We characterized sensitivities to pond water salinity, pond water depth, and farm width. Salinization was assessed by three indicators (salinized area, infiltrated salt mass, and recovery rate), and three SGD indicators were evaluated (fresh SGD, saline SGD, and saltwater circulation rate). Our results show that pond water depth is the primary control on the mass of saltwater infiltration while farm width is the primary control for recovery rate. Pond water salinity and depth affect both fresh and saline SGD. We show that aquaculture is a previously unrecognized mechanism of salinization affecting coastal aquifer vulnerability and SGD. A regional graphical information system analysis shows transformation into aquacultural ponds could introduce considerable SGD variability spatially and temporally. These findings will enable coastal managers to better evaluate groundwater vulnerability in regions with expanding onshore aquaculture and demonstrates the impact of aquaculture on coastal groundwater resources and the need for further study to understand the impact of aquaculture across Asia and the globe.

@article{zheng_assess_2021,
	title = {Assess hydrological responses to a warming climate at the {Lysina} {Critical} {Zone} {Observatory} in {Central} {Europe}},
	volume = {35},
	issn = {0885-6087},
	url = {https://doi.org/10.1002/hyp.14281},
	doi = {10.1002/hyp.14281},
	abstract = {Abstract Climate warming is having profound effects on the hydrological cycle by increasing atmospheric demand, changing water availability, and snow seasonality. Europe suffered three distinct heat waves in 2019, and 11 of the 12 hottest years ever recorded took place in the past two decades, which will potentially change seasonal streamflow patterns and long-term trends. Central Europe exhibited six dry years in a row since 2014. This study uses data from a well-documented headwater catchment in Central Europe (Lysina) to explore hydrological responses to a warming climate. We applied a lumped parameter hydrologic model Brook90 and a distributed model Penn State Integrated Hydrologic Model (PIHM) to simulate long-term hydrological change under future climate scenarios. Both models performed well on historic streamflow and in agreement with each other according to the catchment water budget. In addition, PIHM was able to simulate lateral groundwater redistribution within the catchment validated by the groundwater table dynamics. The long-term trends in runoff and low flow were captured by PIHM only. We applied different EURO-CORDEX models with two emission scenarios (Representative Concentration Pathways RCP 4.5, 8.5) and found significant impacts on runoff and evapotranspiration (ET) for the period of 2071?2100. Results from both models suggested reduced runoff and increased ET, while the monthly distribution of runoff was different. We used this catchment study to understand the importance of subsurface processes in projection of hydrologic response to a warming climate.},
	number = {9},
	urldate = {2022-08-28},
	journal = {Hydrological Processes},
	author = {Zheng, Wenjuan and Lamačová, Anna and Yu, Xuan and Krám, Pavel and Hruška, Jakub and Zahradníček, Pavel and Štěpánek, Petr and Farda, Aleš},
	month = sep,
	year = {2021},
	note = {Publisher: John Wiley \& Sons, Ltd},
	keywords = {Brook90, Lysina, PIHM, climate change scenario, critical zone observatory, process-based hydrological model},
	pages = {e14281},
}

Abstract Climate warming is having profound effects on the hydrological cycle by increasing atmospheric demand, changing water availability, and snow seasonality. Europe suffered three distinct heat waves in 2019, and 11 of the 12 hottest years ever recorded took place in the past two decades, which will potentially change seasonal streamflow patterns and long-term trends. Central Europe exhibited six dry years in a row since 2014. This study uses data from a well-documented headwater catchment in Central Europe (Lysina) to explore hydrological responses to a warming climate. We applied a lumped parameter hydrologic model Brook90 and a distributed model Penn State Integrated Hydrologic Model (PIHM) to simulate long-term hydrological change under future climate scenarios. Both models performed well on historic streamflow and in agreement with each other according to the catchment water budget. In addition, PIHM was able to simulate lateral groundwater redistribution within the catchment validated by the groundwater table dynamics. The long-term trends in runoff and low flow were captured by PIHM only. We applied different EURO-CORDEX models with two emission scenarios (Representative Concentration Pathways RCP 4.5, 8.5) and found significant impacts on runoff and evapotranspiration (ET) for the period of 2071?2100. Results from both models suggested reduced runoff and increased ET, while the monthly distribution of runoff was different. We used this catchment study to understand the importance of subsurface processes in projection of hydrologic response to a warming climate.

@article{yu_capturing_2021,
	title = {Capturing hotspots of fresh submarine groundwater discharge using a coupled surface–subsurface model},
	volume = {598},
	issn = {0022-1694},
	url = {https://www.sciencedirect.com/science/article/pii/S0022169421004030},
	doi = {https://doi.org/10.1016/j.jhydrol.2021.126356},
	abstract = {Submarine groundwater discharge (SGD) contributes to the physical and chemical characters of coastal waters by discharging nutrients and contaminants, significantly impacting regional marine ecosystems and contributing to ocean chemical budgets. However, such groundwater discharge varies dramatically across scales and is often not comparable due to different model assumptions and field designs. We used a hydrologic model with integration of fundamental surface and subsurface processes to simulate the coastline level fresh SGD for the Crete Island in the Mediterranean Sea. The modeled hydrological processes suggested that fresh SGD substantially contributes to water flow entering the Mediterranean Sea (2.3 × 108 m3/yr), amounting to 31\% of river discharge and 14\% of precipitation. Spatially, fresh SGD varied from 2.4 m3/yr/m to 13.4 × 104 m3/yr/m, with an average of 2.6 × 103 m3/yr/m. The local maxima were commonly associated with river mouths reflecting larger hydraulic gradients and higher permeable structures. Temporally, fresh SGD was impacted by episodic precipitation in a delayed and prolonged pattern. We found that fresh SGD variability at the coastline segment level was compared to point measurements and fresh SGD magnitudes summered up to the catchment level were consistent with global products. Our results suggest the coupled surface–subsurface hydrologic modeling approach is a promising strategy to quantify and partition large-scale water budgets down to point observations that typically do not capture the full range of fresh SGD dynamics.},
	journal = {Journal of Hydrology},
	author = {Yu, Xuan and Xu, Zexuan and Moraetis, Daniel and Nikolaidis, Nikolaos P. and Schwartz, Franklin W. and Zhang, Yu and Shu, Lele and Duffy, Christopher J. and Liu, Bingjun},
	year = {2021},
	keywords = {Coupled surface–subsurface model, PIHM, River runoff, Submarine groundwater discharge, Surface water-groundwater interaction},
	pages = {126356},
}

Submarine groundwater discharge (SGD) contributes to the physical and chemical characters of coastal waters by discharging nutrients and contaminants, significantly impacting regional marine ecosystems and contributing to ocean chemical budgets. However, such groundwater discharge varies dramatically across scales and is often not comparable due to different model assumptions and field designs. We used a hydrologic model with integration of fundamental surface and subsurface processes to simulate the coastline level fresh SGD for the Crete Island in the Mediterranean Sea. The modeled hydrological processes suggested that fresh SGD substantially contributes to water flow entering the Mediterranean Sea (2.3 × 108 m3/yr), amounting to 31% of river discharge and 14% of precipitation. Spatially, fresh SGD varied from 2.4 m3/yr/m to 13.4 × 104 m3/yr/m, with an average of 2.6 × 103 m3/yr/m. The local maxima were commonly associated with river mouths reflecting larger hydraulic gradients and higher permeable structures. Temporally, fresh SGD was impacted by episodic precipitation in a delayed and prolonged pattern. We found that fresh SGD variability at the coastline segment level was compared to point measurements and fresh SGD magnitudes summered up to the catchment level were consistent with global products. Our results suggest the coupled surface–subsurface hydrologic modeling approach is a promising strategy to quantify and partition large-scale water budgets down to point observations that typically do not capture the full range of fresh SGD dynamics.

@article{guimond_physical-biogeochemical_2020,
	title = {A physical-biogeochemical mechanism for negative feedback between marsh crabs and carbon storage},
	volume = {15},
	issn = {1748-9326},
	url = {http://dx.doi.org/10.1088/1748-9326/ab60e2},
	doi = {10.1088/1748-9326/ab60e2},
	abstract = {Tidal marshes are valuable global carbon sinks, yet large uncertainties in coastal marsh carbon budgets and mediating mechanisms limit our ability to estimate fluxes and predict feedbacks with global change. To improve mechanistic understanding, we assess how net carbon storage is influenced by interactions between crab activity, water movement, and biogeochemistry. We show that crab burrows enhance carbon loss from tidal marsh sediments by physical and chemical feedback processes. Burrows increase near-creek sediment permeability in the summer by an order of magnitude compared to the winter crab dormancy period, promoting carbon-rich fluid exchange between the marsh and creek. Burrows also enhance vertical exchange by increasing the depth of the strongly carbon-oxidizing zone and reducing the capacity for carbon sequestration. Results reveal the mechanism through which crab burrows mediate the movement of carbon through tidal wetlands and highlight the importance of considering burrowing activity when making budget projections across temporal and spatial scales.},
	number = {3},
	journal = {Environmental Research Letters},
	author = {Guimond, Julia A and Seyfferth, Angelia L and Moffett, Kevan B and Michael, Holly A},
	year = {2020},
	note = {Publisher: IOP Publishing},
	pages = {034024},
}

Tidal marshes are valuable global carbon sinks, yet large uncertainties in coastal marsh carbon budgets and mediating mechanisms limit our ability to estimate fluxes and predict feedbacks with global change. To improve mechanistic understanding, we assess how net carbon storage is influenced by interactions between crab activity, water movement, and biogeochemistry. We show that crab burrows enhance carbon loss from tidal marsh sediments by physical and chemical feedback processes. Burrows increase near-creek sediment permeability in the summer by an order of magnitude compared to the winter crab dormancy period, promoting carbon-rich fluid exchange between the marsh and creek. Burrows also enhance vertical exchange by increasing the depth of the strongly carbon-oxidizing zone and reducing the capacity for carbon sequestration. Results reveal the mechanism through which crab burrows mediate the movement of carbon through tidal wetlands and highlight the importance of considering burrowing activity when making budget projections across temporal and spatial scales.

@article{guimond_using_2020,
	title = {Using {Hydrological}-{Biogeochemical} {Linkages} to {Elucidate} {Carbon} {Dynamics} in {Coastal} {Marshes} {Subject} to {Relative} {Sea} {Level} {Rise}},
	volume = {56},
	doi = {10.1029/2019WR026302},
	abstract = {Abstract Coastal marshes are an important component of the global carbon cycle, yet our understanding of how these ecosystems will respond to sea level rise (SLR) is limited. Coastal marsh hydrology varies based on elevation, distance from channel, and hydraulic properties, resulting in zones of unique water level oscillation patterns. These zones impact ecology and geochemistry and correspond to differences in carbon accumulation rates. These physical-biogeochemical linkages enable use of a hydrological model to predict changes in marsh zonation, and in turn carbon accumulation, as well as groundwater-surface water exchange under SLR. Here, we developed a calibrated hydrological model of a Delaware coastal marsh using HydroGeoSphere. We simulated three scenarios each of SLR, sediment accretion, and upland hydrologic response, and we quantified changes in the spatial coverage of different hydrologic zonations and groundwater-surface water exchange. Results show that relative SLR reduces marsh area, carbon burial, and lateral water fluxes. However, the magnitudes of change are linked to the terrestrial groundwater table response as well as relative SLR. In scenarios where the upland water table does not change with SLR, the magnitude of decline in marsh area and carbon accumulation is reduced compared to scenarios where the upland water table keeps pace with SLR. In contrast, the reduction in lateral water flux is minimized in scenarios with an upland water table rise equal to SLR compared to scenarios where the upland water table is held at present-day levels. This study highlights the importance of regional hydrologic setting in the fate of coastal marsh dynamics.},
	number = {2},
	journal = {Water Resources Research},
	author = {Guimond, Julia A. and Yu, Xuan and Seyfferth, Angelia L. and Michael, Holly A.},
	year = {2020},
	keywords = {carbon budgets, coastal wetlands, estuaries, groundwater modeling, groundwater-surface water interaction, sea level rise},
	pages = {e2019WR026302},
}

Abstract Coastal marshes are an important component of the global carbon cycle, yet our understanding of how these ecosystems will respond to sea level rise (SLR) is limited. Coastal marsh hydrology varies based on elevation, distance from channel, and hydraulic properties, resulting in zones of unique water level oscillation patterns. These zones impact ecology and geochemistry and correspond to differences in carbon accumulation rates. These physical-biogeochemical linkages enable use of a hydrological model to predict changes in marsh zonation, and in turn carbon accumulation, as well as groundwater-surface water exchange under SLR. Here, we developed a calibrated hydrological model of a Delaware coastal marsh using HydroGeoSphere. We simulated three scenarios each of SLR, sediment accretion, and upland hydrologic response, and we quantified changes in the spatial coverage of different hydrologic zonations and groundwater-surface water exchange. Results show that relative SLR reduces marsh area, carbon burial, and lateral water fluxes. However, the magnitudes of change are linked to the terrestrial groundwater table response as well as relative SLR. In scenarios where the upland water table does not change with SLR, the magnitude of decline in marsh area and carbon accumulation is reduced compared to scenarios where the upland water table keeps pace with SLR. In contrast, the reduction in lateral water flux is minimized in scenarios with an upland water table rise equal to SLR compared to scenarios where the upland water table is held at present-day levels. This study highlights the importance of regional hydrologic setting in the fate of coastal marsh dynamics.

@article{yu_data_2020,
	title = {Data rescue in manuscripts: a hydrological modelling study example},
	volume = {65},
	issn = {0262-6667},
	url = {https://doi.org/10.1080/02626667.2019.1614593},
	doi = {10.1080/02626667.2019.1614593},
	number = {5},
	journal = {Hydrological Sciences Journal},
	author = {Yu, Xuan and Lamačová, Anna and Shu, Lele and Duffy, Christopher and Krám, Pavel and Hruška, Jakub and White, Tim and Lin, Kairong},
	year = {2020},
	pages = {763--769},
}

@article{yu_flow_2020,
	title = {Flow, {Transport}, and {Reactions} in {Coastal} {Aquifers}},
	volume = {2020},
	issn = {1468-8115},
	url = {https://doi.org/10.1155/2020/3539052},
	doi = {10.1155/2020/3539052},
	journal = {Geofluids},
	author = {Yu, Xuan and Russoniello, Christopher J. and Morgan, Leanne K. and Massmann, Gudrun and Wang, Guizhi},
	year = {2020},
	note = {Publisher: Hindawi},
	pages = {3539052},
}

@article{yu_mechanisms_2019,
	title = {Mechanisms, configuration typology, and vulnerability of pumping-induced seawater intrusion in heterogeneous aquifers},
	url = {https://doi.org/10.1016/j.advwatres.2019.04.013},
	doi = {10.1016/j.advwatres.2019.04.013},
	journal = {Advances in Water Resources},
	author = {Yu, Xuan and Michael, Holly A.},
	year = {2019},
	keywords = {Coastal water resources, Geostatistics, Groundwater, Heterogeneity, Saltwater intrusion, Vulnerability},
}

@article{yu_coupled_2019,
	title = {A coupled surface-subsurface hydrologic model to assess groundwater flood risk spatially and temporally},
	volume = {114},
	issn = {1364-8152},
	url = {http://www.sciencedirect.com/science/article/pii/S1364815218309204},
	doi = {10.1016/j.envsoft.2019.01.008},
	abstract = {Floods introduced by rainfall events are responsible for tremendous economic and property losses. It is important to delineate flood prone areas to minimize flood damages and make mitigation plans. Recently, there has been recognition of the need to understand the risk from groundwater flooding caused by the emergence of groundwater at the ground surface. Mapping groundwater flood risk is more challenging compared to river flooding, especially in karst systems, where subsurface preferential flowpaths can affect groundwater flow. We developed a coupled surface-subsurface modelling framework resolving spatial information and hydrologic data to assess the groundwater flood risk at a karstic watershed: Koiliaris River Basin, Greece. The simulated groundwater table was used to delineate groundwater flooding. Modelled results revealed the role of faults in groundwater flooding generation. We anticipate the coupled surface-subsurface approach to be a starting point for more sophisticated flooding risk assessment, including magnitude and temporal duration of groundwater flooding.},
	journal = {Environmental Modelling \& Software},
	author = {Yu, Xuan and Moraetis, Daniel and Nikolaidis, Nikolaos P. and Li, Bailing and Duffy, Christopher and Liu, Bingjun},
	year = {2019},
	keywords = {Coupled surface-subsurface model, Critical zone observatory, Groundwater flooding, Koiliaris river basin, PIHM, Risk assessment},
	pages = {129 -- 139},
}

Floods introduced by rainfall events are responsible for tremendous economic and property losses. It is important to delineate flood prone areas to minimize flood damages and make mitigation plans. Recently, there has been recognition of the need to understand the risk from groundwater flooding caused by the emergence of groundwater at the ground surface. Mapping groundwater flood risk is more challenging compared to river flooding, especially in karst systems, where subsurface preferential flowpaths can affect groundwater flow. We developed a coupled surface-subsurface modelling framework resolving spatial information and hydrologic data to assess the groundwater flood risk at a karstic watershed: Koiliaris River Basin, Greece. The simulated groundwater table was used to delineate groundwater flooding. Modelled results revealed the role of faults in groundwater flooding generation. We anticipate the coupled surface-subsurface approach to be a starting point for more sophisticated flooding risk assessment, including magnitude and temporal duration of groundwater flooding.

@article{yu_offshore_2019,
	title = {Offshore pumping impacts onshore groundwater resources and land subsidence},
	url = {https://onlinelibrary.wiley.com/doi/abs/10.1029/2019GL081910},
	doi = {10.1029/2019GL081910},
	journal = {Geophysical Research Letters},
	author = {Yu, Xuan and Michael, Holly A.},
	year = {2019},
}

@article{yang_impact_2018,
	title = {Impact of hydrogeological factors on groundwater salinization due to ocean-surge inundation},
	url = {https://doi.org/10.1016/j.advwatres.2017.11.017},
	doi = {10.1016/j.advwatres.2017.11.017},
	journal = {Advances in Water Resources},
	author = {Yang, Jie and Zhang, Huichen and Yu, Xuan and Graf, Thomas and Michael, Holly A.},
	year = {2018},
}

@article{crow_spatial_2018,
	title = {Spatial and {Temporal} {Variability} of {Root}-{Zone} {Soil} {Moisture} {Acquired} {From} {Hydrologic} {Modeling} and {AirMOSS} {P}-{Band} {Radar}},
	url = {https://doi.org/10.1109/JSTARS.2018.2865251},
	doi = {10.1109/JSTARS.2018.2865251},
	journal = {IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
	author = {Crow, Wade T. and Milak, Sushil and Moghaddam, Mahta and Tabatabaeenejad, Alireza and Jaruwatanadilok, Sermsak and Yu, Xuan and Shi, Yuning and Reichle, Rolf H. and Hagimoto, Yutaka and Cuenca, Richard H.},
	year = {2018},
}

@article{yu_watershed_2018,
	title = {Watershed {Hydrology}: {Scientific} {Advances} and {Environmental} {Assessments}},
	volume = {10},
	issn = {2073-4441},
	url = {http://www.mdpi.com/2073-4441/10/3/288},
	doi = {10.3390/w10030288},
	abstract = {The watershed is a fundamental concept in hydrology and is the basis for understanding hydrologic processes and for the planning and management of water resources. Storage and movement of water at a watershed scale is complicated due to the coupled processes which act over multiple spatial and temporal scales. In addition, climate change and human activities increase the complexity of these processes driving hydrologic change. Scientific advances in the field of watershed hydrology is now making use of the latest methods and technologies to achieve responsible management of water resources to meet the needs of rising populations and the protection of important ecosystems. The selected papers cover a wide range of issues that are relevant to watershed hydrology and have motivated model development, application, parameterization, uncertainty estimation, environment assessment, and management. Continued technological advances grounded in modern environmental science are necessary to meet these challenges. This will require a greater emphasis on disciplinary collaboration and integrated approaches to problem solving founded on science-driven innovations in technology, socio-economics, and public policy.},
	number = {3},
	journal = {Water},
	author = {Yu, Xuan and Duffy, Christopher J.},
	year = {2018},
}

The watershed is a fundamental concept in hydrology and is the basis for understanding hydrologic processes and for the planning and management of water resources. Storage and movement of water at a watershed scale is complicated due to the coupled processes which act over multiple spatial and temporal scales. In addition, climate change and human activities increase the complexity of these processes driving hydrologic change. Scientific advances in the field of watershed hydrology is now making use of the latest methods and technologies to achieve responsible management of water resources to meet the needs of rising populations and the protection of important ecosystems. The selected papers cover a wide range of issues that are relevant to watershed hydrology and have motivated model development, application, parameterization, uncertainty estimation, environment assessment, and management. Continued technological advances grounded in modern environmental science are necessary to meet these challenges. This will require a greater emphasis on disciplinary collaboration and integrated approaches to problem solving founded on science-driven innovations in technology, socio-economics, and public policy.

@article{michael_geologic_2016,
	title = {Geologic influence on groundwater salinity drives large seawater circulation through the continental shelf},
	volume = {43},
	url = {http://dx.doi.org/10.1002/2016GL070863},
	doi = {10.1002/2016GL070863},
	number = {20},
	journal = {Geophysical Research Letters},
	author = {Michael, Holly A. and Scott, Kaileigh C. and Koneshloo, Mohammad and Yu, Xuan and Khan, Mahfuzur R. and Li, Katie},
	year = {2016},
}

@article{yu_hydrological_2016,
	title = {Hydrological model uncertainty due to spatial evapotranspiration estimation methods},
	url = {http://dx.doi.org/10.1016/j.cageo.2015.05.006},
	doi = {10.1016/j.cageo.2015.05.006},
	abstract = {Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03′N, 12°40′E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.},
	journal = {Computers \& Geosciences},
	author = {Yu, Xuan and Lamačová, Anna and Duffy, Christopher and Krám, Pavel and Hruška, Jakub},
	year = {2016},
}

Evapotranspiration (ET) continues to be a difficult process to estimate in seasonal and long-term water balances in catchment models. Approaches to estimate ET typically use vegetation parameters (e.g., leaf area index [LAI], interception capacity) obtained from field observation, remote sensing data, national or global land cover products, and/or simulated by ecosystem models. In this study we attempt to quantify the uncertainty that spatial evapotranspiration estimation introduces into hydrological simulations when the age of the forest is not precisely known. The Penn State Integrated Hydrologic Model (PIHM) was implemented for the Lysina headwater catchment, located 50°03′N, 12°40′E in the western part of the Czech Republic. The spatial forest patterns were digitized from forest age maps made available by the Czech Forest Administration. Two ET methods were implemented in the catchment model: the Biome-BGC forest growth sub-model (1-way coupled to PIHM) and with the fixed-seasonal LAI method. From these two approaches simulation scenarios were developed. We combined the estimated spatial forest age maps and two ET estimation methods to drive PIHM. A set of spatial hydrologic regime and streamflow regime indices were calculated from the modeling results for each method. Intercomparison of the hydrological responses to the spatial vegetation patterns suggested considerable variation in soil moisture and recharge and a small uncertainty in the groundwater table elevation and streamflow. The hydrologic modeling with ET estimated by Biome-BGC generated less uncertainty due to the plant physiology-based method. The implication of this research is that overall hydrologic variability induced by uncertain management practices was reduced by implementing vegetation models in the catchment models.

@article{gil_towards_2016,
	title = {Towards the {Geoscience} {Paper} of the {Future}: {Best} {Practices} for {Documenting} and {Sharing} {Research} from {Data} to {Software} to {Provenance}},
	issn = {2333-5084},
	url = {http://dx.doi.org/10.1002/2015EA000136},
	doi = {10.1002/2015EA000136},
	journal = {Earth and Space Science},
	author = {Gil, Yolanda and David, Cédric H. and Demir, Ibrahim and Essawy, Bakinam T. and Fulweiler, Robinson W. and Goodall, Jonathan L. and Karlstrom, Leif and Lee, Huikyo and Mills, Heath J. and Oh, Ji-Hyun and Pierce, Suzanne A and Pope, Allen and Tzeng, Mimi W. and Villamizar, Sandra R. and Yu, Xuan},
	year = {2016},
	keywords = {0520 Data analysis: algorithms and implementation, 0525 Data management, 1912 Data management, preservation, rescue, 1978 Software re-use, 1998 Workflow, Data sharing, Geoscience paper of the future, Provenance, Reproducibility, Software reuse, Workflow},
	pages = {2015EA000136},
}

@article{yu_virtual_2016,
	title = {Virtual {Experiments} {Guide} {Calibration} {Strategies} for a {Real}-{World} {Watershed} {Application} of {Coupled} {Surface}-{Subsurface} {Modeling}},
	url = {http://dx.doi.org/10.1061/(ASCE)HE.1943-5584.0001431},
	doi = {10.1061/(ASCE)HE.1943-5584.0001431},
	journal = {Journal of Hydrologic Engineering},
	author = {Yu, Xuan and Duffy, C. J. and Zhang, Yu and Bhatt, Gopal and Shi, Yuning},
	year = {2016},
}

@article{yu_impact_2016,
	title = {Impact of {Topography} on {Groundwater} {Salinization} {Due} to {Ocean} {Surge} {Inundation}},
	url = {http://dx.doi.org/10.1002/2016WR018814},
	doi = {10.1002/2016WR018814},
	journal = {Water Resources Research},
	author = {Yu, Xuan and Yang, Jie and Graf, Thomas and Koneshloo, Mohammad and O’Neal, Michael A. and Michael, Holly A.},
	year = {2016},
}

@article{yu_open_2016,
	title = {Open science in practice: learning integrated modeling of coupled surface-subsurface flow processes from scratch},
	volume = {3},
	url = {http://dx.doi.org/10.1002/2015EA000155},
	doi = {10.1002/2015EA000155},
	abstract = {Integrated modeling of coupled surface-subsurface flow and ensuing role in diverse earth system processes is of current research interest to characterize nonlinear rainfall-runoff response, and also to understand land-surface energy balances, biogeochemical processes, geomorphological dynamics, etc. A growing number of complex models have been developed for water-related research, and many of these are made available to the Earth science community. However, relatively few resources have been made accessible to the potentially large group of Earth science and engineering users. New users have to invest an extraordinary effort to study the models. To provide a stimulating experience focusing on the learning curve of integrated modeling of coupled surface-subsurface flow, we describe use cases of an open-source model, the Penn State Integrated Hydrologic Model, PIHM. New users were guided through data processing and model application by reproducing a numerical benchmark problem and a real-world watershed simulation. Specifically, we document the PIHM application and its computational workflow to enable intuitive understanding of coupled surface-subsurface flow processes. In addition, we describe the user experience as important evidence of the significance of reusability. The interaction shows that documentation of data, software, and computational workflow in research papers is a promising method to foster open scientific collaboration and reuse. This study demonstrates how open science practice in research papers would promote the utility of open source software. Addressing such open science practice in publications would promote the utility of journal papers. Further popularization of such practice will require coordination among research communities, funding agencies and journals. This article is protected by copyright. All rights reserved.},
	number = {5},
	journal = {Earth and Space Science},
	author = {Yu, Xuan and Duffy, Christopher J. and Rousseau, Alain N. and Bhatt, Gopal and Pardo Álvarez, Álvaro and Charron, Dominique},
	year = {2016},
	pages = {190--206},
}

Integrated modeling of coupled surface-subsurface flow and ensuing role in diverse earth system processes is of current research interest to characterize nonlinear rainfall-runoff response, and also to understand land-surface energy balances, biogeochemical processes, geomorphological dynamics, etc. A growing number of complex models have been developed for water-related research, and many of these are made available to the Earth science community. However, relatively few resources have been made accessible to the potentially large group of Earth science and engineering users. New users have to invest an extraordinary effort to study the models. To provide a stimulating experience focusing on the learning curve of integrated modeling of coupled surface-subsurface flow, we describe use cases of an open-source model, the Penn State Integrated Hydrologic Model, PIHM. New users were guided through data processing and model application by reproducing a numerical benchmark problem and a real-world watershed simulation. Specifically, we document the PIHM application and its computational workflow to enable intuitive understanding of coupled surface-subsurface flow processes. In addition, we describe the user experience as important evidence of the significance of reusability. The interaction shows that documentation of data, software, and computational workflow in research papers is a promising method to foster open scientific collaboration and reuse. This study demonstrates how open science practice in research papers would promote the utility of open source software. Addressing such open science practice in publications would promote the utility of journal papers. Further popularization of such practice will require coordination among research communities, funding agencies and journals. This article is protected by copyright. All rights reserved.

@article{shi_simulating_2015,
	title = {Simulating high‐resolution soil moisture patterns in the {Shale} {Hills} watershed using a land surface hydrologic model},
	volume = {29},
	url = {http://dx.doi.org/10.1002/hyp.10593},
	doi = {10.1002/hyp.10593},
	abstract = {Soil moisture is a critical variable in the water and energy cycles. The prediction of soil moisture patterns, especially at high spatial resolution, is challenging. This study tests the ability of a land surface hydrologic model (Flux-PIHM) to simulate high-resolution soil moisture patterns in the Shale Hills watershed (0.08 km2) in central Pennsylvania. Locally measured variables including a soil map, soil parameters, a tree map, and lidar topographic data, all have been synthesized into Flux-PIHM to provide model inputs. The predicted 10-cm soil moisture patterns for 15 individual days encompassing seven months in 2009 are compared with the observations from 61 soil moisture monitoring sites. Calibrated using only watershed-scale and a few point-based measurements, and driven by spatially uniform meteorological forcing, Flux-PIHM is able to simulate the observed macro spatial pattern of soil moisture at {\textasciitilde}10-m resolution (spatial correlation coefficient {\textasciitilde} 0.6) and the day-to-day variation of this soil moisture pattern, although it underestimates the amplitude of the spatial variability and the mean soil moisture. Results show that the spatial distribution of soil hydraulic parameters has the dominant effect on the soil moisture spatial pattern. The surface topography and depth to bedrock also affect the soil moisture patterns in this watershed. Using the National Land Cover Database (NLCD) in place of a local tree survey map makes a negligible difference. Field measured soil type maps and soil type-specific hydraulic parameters significantly improve the predicted soil moisture pattern as compared to the most detailed national soils database (Soil Survey Geographic Database, or SSURGO, 30-m resolution).},
	number = {21},
	journal = {Hydrological Processes},
	author = {Shi, Yuning and Baldwin, Douglas C. and Davis, Kenneth J. and Yu, Xuan and Duffy, Christopher J. and Lin, Henry},
	year = {2015},
	pages = {4624--4637},
}

Soil moisture is a critical variable in the water and energy cycles. The prediction of soil moisture patterns, especially at high spatial resolution, is challenging. This study tests the ability of a land surface hydrologic model (Flux-PIHM) to simulate high-resolution soil moisture patterns in the Shale Hills watershed (0.08 km2) in central Pennsylvania. Locally measured variables including a soil map, soil parameters, a tree map, and lidar topographic data, all have been synthesized into Flux-PIHM to provide model inputs. The predicted 10-cm soil moisture patterns for 15 individual days encompassing seven months in 2009 are compared with the observations from 61 soil moisture monitoring sites. Calibrated using only watershed-scale and a few point-based measurements, and driven by spatially uniform meteorological forcing, Flux-PIHM is able to simulate the observed macro spatial pattern of soil moisture at ~10-m resolution (spatial correlation coefficient ~ 0.6) and the day-to-day variation of this soil moisture pattern, although it underestimates the amplitude of the spatial variability and the mean soil moisture. Results show that the spatial distribution of soil hydraulic parameters has the dominant effect on the soil moisture spatial pattern. The surface topography and depth to bedrock also affect the soil moisture patterns in this watershed. Using the National Land Cover Database (NLCD) in place of a local tree survey map makes a negligible difference. Field measured soil type maps and soil type-specific hydraulic parameters significantly improve the predicted soil moisture pattern as compared to the most detailed national soils database (Soil Survey Geographic Database, or SSURGO, 30-m resolution).

@article{shi_parameter_2015,
	title = {Parameter estimation of a physically-based land surface hydrologic model using an ensemble {Kalman} filter: {A} multivariate real-data experiment},
	volume = {83},
	url = {http://dx.doi.org/10.1016/j.advwatres.2015.06.009},
	doi = {10.1016/j.advwatres.2015.06.009},
	abstract = {The capability of an ensemble Kalman filter (EnKF) to simultaneously estimate multiple parameters in a physically-based land surface hydrologic model using multivariate field observations is tested at a small watershed (0.08 km2). Multivariate, high temporal resolution, in situ measurements of discharge, water table depth, soil moisture, and sensible and latent heat fluxes encompassing five months of 2009 are assimilated. It is found that, for five out of the six parameters, the EnKF estimated parameter values from different test cases converge strongly, and the estimates after convergence are close to the manually calibrated parameter values. The EnKF estimated parameters and manually calibrated parameters yield similar model performance, but the EnKF sequential method significantly decreases the time and labor required for calibration. The results demonstrate that, given a limited number of multi-state, site-specific observations, an automated sequential calibration method (EnKF) can be used to optimize physically-based land surface hydrologic models.},
	journal = {Advances in Water Resources},
	author = {Shi, Yuning and Davis, Kenneth J. and Zhang, Fuqing and Duffy, Christopher J. and Yu, Xuan},
	year = {2015},
	pages = {421--427},
}

The capability of an ensemble Kalman filter (EnKF) to simultaneously estimate multiple parameters in a physically-based land surface hydrologic model using multivariate field observations is tested at a small watershed (0.08 km2). Multivariate, high temporal resolution, in situ measurements of discharge, water table depth, soil moisture, and sensible and latent heat fluxes encompassing five months of 2009 are assimilated. It is found that, for five out of the six parameters, the EnKF estimated parameter values from different test cases converge strongly, and the estimates after convergence are close to the manually calibrated parameter values. The EnKF estimated parameters and manually calibrated parameters yield similar model performance, but the EnKF sequential method significantly decreases the time and labor required for calibration. The results demonstrate that, given a limited number of multi-state, site-specific observations, an automated sequential calibration method (EnKF) can be used to optimize physically-based land surface hydrologic models.

@article{yu_modeling_2015,
	title = {Modeling the long term water yield effects of forest management in a {Norway} spruces forest},
	url = {http://dx.doi.org/10.1080/02626667.2014.897406},
	doi = {10.1080/02626667.2014.897406},
	abstract = {Intensive forest management is one of the main land cover changes over the last century in Central Europe, resulting in forest monoculture. It has been proposed that these monoculture stands impact hydrological processes, water yield, water quality and ecosystem services. At the Lysina Critical Zone Observatory, a forest catchment in the western Czech Republic, a distributed physics-based hydrologic model, Penn State Integrated Hydrologic Model (PIHM), was used to simulate long-term hydrological change under different forest management practices, and to evaluate the comparative scenarios of the hydrological consequences of changing land cover. Stand-age-adjusted LAI (leaf area index) curves were generated from an empirical relationship to represent changes in seasonal tree growth. By consideration of age-adjusted LAI, the spatially-distributed model was able to successfully simulate the integrated hydrological response from snowmelt, recharge, evapotranspiration, groundwater levels, soil moisture and streamflow, as well as spatial patterns of each state and flux. Simulation scenarios of forest management (historical management, unmanaged, clear cutting to cropland) were compared. One of the critical findings of the study indicates that selective (patch) forest cutting results in a modest increase in runoff (water yield) as compared to the simulated unmanaged (no cutting) scenario over a 29-year period at Lysina, suggesting the model is sensitive to selective cutting practices. A simulation scenario of cropland or complete forest cutting leads to extreme increases in annual water yield and peak flow. The model sensitivity to forest management practices examined here suggests the utility of models and scenario development to future management strategies for assessing sustainable water resources and ecosystem services.},
	urldate = {2013-05-23},
	journal = {Hydrological Sciences Journal},
	author = {Yu, X. and Lamačová, Anna and Duffy, C. J and Krám, P. and Hruška, J. and White, T. and Bhatt, Gopal},
	year = {2015},
}

Intensive forest management is one of the main land cover changes over the last century in Central Europe, resulting in forest monoculture. It has been proposed that these monoculture stands impact hydrological processes, water yield, water quality and ecosystem services. At the Lysina Critical Zone Observatory, a forest catchment in the western Czech Republic, a distributed physics-based hydrologic model, Penn State Integrated Hydrologic Model (PIHM), was used to simulate long-term hydrological change under different forest management practices, and to evaluate the comparative scenarios of the hydrological consequences of changing land cover. Stand-age-adjusted LAI (leaf area index) curves were generated from an empirical relationship to represent changes in seasonal tree growth. By consideration of age-adjusted LAI, the spatially-distributed model was able to successfully simulate the integrated hydrological response from snowmelt, recharge, evapotranspiration, groundwater levels, soil moisture and streamflow, as well as spatial patterns of each state and flux. Simulation scenarios of forest management (historical management, unmanaged, clear cutting to cropland) were compared. One of the critical findings of the study indicates that selective (patch) forest cutting results in a modest increase in runoff (water yield) as compared to the simulated unmanaged (no cutting) scenario over a 29-year period at Lysina, suggesting the model is sensitive to selective cutting practices. A simulation scenario of cropland or complete forest cutting leads to extreme increases in annual water yield and peak flow. The model sensitivity to forest management practices examined here suggests the utility of models and scenario development to future management strategies for assessing sustainable water resources and ecosystem services.

@article{yu_cyber-innovated_2015,
	title = {Cyber-{Innovated} {Watershed} {Research} at the {Shale} {Hills} {Critical} {Zone} {Observatory}},
	volume = {PP},
	issn = {1932-8184},
	url = {http://dx.doi.org/10.1109/JSYST.2015.2484219},
	doi = {10.1109/JSYST.2015.2484219},
	abstract = {Cyberinfrastructure is enabling ever more integrative and transformative science. Technological advances in cyberinfrastructure have allowed deeper understanding of watershed hydrology by improved integration of data, information, and models. The synthesis of all sources of hydrologic variables (historical, real time, future scenarios, observed, and modeled) requires advanced data acquisition, data storage, data management, data integration, data mining, and data visualization. In this context, cyber-innovated hydrologic research was implemented to carry out watershed-based historical climate simulations at the Shale Hills Critical Zone Observatory. The simulations were based on the assimilation of data from a hydrologic monitoring network into a multiphysics hydrologic model (the Penn State Integrated Hydrology Model). We documented workflows for the model application and applied the model to short-time hyporheic exchange flow study and long-term climate scenario analysis. The effort reported herein demonstrates that advances in cyberscience allows innovative research that improves our ability to access and share data; to allow collective development of science hypotheses; and to support building models via team participation. We simplified communications between model developers and community scientists, software professionals, students, and decision makers, which in the long term will improve the utilization of hydrologic models for science and societal applications.},
	number = {99},
	journal = {Systems Journal, IEEE},
	author = {Yu, X. and Duffy, C. and Gil, Y. and Leonard, L. and Bhatt, G. and Thomas, E.},
	year = {2015},
	keywords = {Analytical models, Biological system modeling, Critical zone observatories (CZOs), Data models, Data visualization, Hydrology, Observatories, Software, cyberinfrastructure, data analytics, penn state integrated hydrologic model (PIHM), shale hills, watershed, web services},
	pages = {1--12},
}

Cyberinfrastructure is enabling ever more integrative and transformative science. Technological advances in cyberinfrastructure have allowed deeper understanding of watershed hydrology by improved integration of data, information, and models. The synthesis of all sources of hydrologic variables (historical, real time, future scenarios, observed, and modeled) requires advanced data acquisition, data storage, data management, data integration, data mining, and data visualization. In this context, cyber-innovated hydrologic research was implemented to carry out watershed-based historical climate simulations at the Shale Hills Critical Zone Observatory. The simulations were based on the assimilation of data from a hydrologic monitoring network into a multiphysics hydrologic model (the Penn State Integrated Hydrology Model). We documented workflows for the model application and applied the model to short-time hyporheic exchange flow study and long-term climate scenario analysis. The effort reported herein demonstrates that advances in cyberscience allows innovative research that improves our ability to access and share data; to allow collective development of science hypotheses; and to support building models via team participation. We simplified communications between model developers and community scientists, software professionals, students, and decision makers, which in the long term will improve the utilization of hydrologic models for science and societal applications.

@article{yu_coupled_2015,
	title = {A coupled surface–subsurface modeling framework to assess the impact of climate change on freshwater wetlands},
	volume = {66},
	issn = {0936-577X, 1616-1572},
	url = {http://www.int-res.com/abstracts/cr/v66/n3/p211-228/},
	doi = {10.3354/cr01348},
	abstract = {The Susquehanna River Basin (SRB) lies in the northeastern United States and contains a mosaic of wetlands that are susceptible to future climate change. This study develops a coupled surface–subsurface modeling framework to assess the prospects for the SRB wetlands under modified hydrologic processes induced by climate change. We selected 7 watersheds ranging in size from 163 to 902 km2, representing the major landscapes of the SRB. We explored the broad spatial and temporal patterns across these watersheds between climate and wetland water levels by applying a coupled surface–subsurface model: Penn State Integrated Hydrologic Model (PIHM) with 7-yr hourly weather records from the North American Land Data Assimilation System. In the model calibration, we employed both streamflow and the spatial distribution of wetlands to constrain the model parameters. The possible effects of climate change on wetland hydrology were investigated by creating historical and future climate scenarios based on the output of one global climate model from Phase 3 of the Coupled Model Intercomparison Project (CMIP). We selected the best climate model based on historical performance to force the PIHM simulation of historical and future scenarios. The hydrologic scenarios suggested that water tables would fall, with greater declines in upland regions than in wetland areas. A key result of this study is that a high-resolution spatial and temporal model can resolve the heterogeneous wetland dynamics in the context of distributed mesoscale watershed modeling.},
	language = {en},
	number = {3},
	urldate = {2015-12-03},
	journal = {Climate Research},
	author = {Yu, X. and Bhatt, G. and Duffy, C. J. and Wardrop, D. H. and Najjar, R. G. and Ross, A. C. and Rydzik, M.},
	month = dec,
	year = {2015},
	pages = {211--228},
}

The Susquehanna River Basin (SRB) lies in the northeastern United States and contains a mosaic of wetlands that are susceptible to future climate change. This study develops a coupled surface–subsurface modeling framework to assess the prospects for the SRB wetlands under modified hydrologic processes induced by climate change. We selected 7 watersheds ranging in size from 163 to 902 km2, representing the major landscapes of the SRB. We explored the broad spatial and temporal patterns across these watersheds between climate and wetland water levels by applying a coupled surface–subsurface model: Penn State Integrated Hydrologic Model (PIHM) with 7-yr hourly weather records from the North American Land Data Assimilation System. In the model calibration, we employed both streamflow and the spatial distribution of wetlands to constrain the model parameters. The possible effects of climate change on wetland hydrology were investigated by creating historical and future climate scenarios based on the output of one global climate model from Phase 3 of the Coupled Model Intercomparison Project (CMIP). We selected the best climate model based on historical performance to force the PIHM simulation of historical and future scenarios. The hydrologic scenarios suggested that water tables would fall, with greater declines in upland regions than in wetland areas. A key result of this study is that a high-resolution spatial and temporal model can resolve the heterogeneous wetland dynamics in the context of distributed mesoscale watershed modeling.

@article{zheng_considering_2015,
	title = {Considering {Surface} {Roughness} {Effects} in a {Triangular} {Pore} {Space} {Model} for {Unsaturated} {Hydraulic} {Conductivity}},
	volume = {14},
	url = {http://dx.doi.org/10.2136/vzj2014.09.0121},
	doi = {10.2136/vzj2014.09.0121},
	abstract = {Quantifying the unsaturated hydraulic conductivity of a porous medium has been a great interest in the fields of hydrology, environmental engineering, and petroleum engineering. Previous research has shown that rough surfaces enhance liquid retention and conductance of flow in the form of liquid film. We present a pore-scale-based water retention and hydraulic conductivity model considering surface roughness effects. In the proposed model, a porous medium is simplified as a bundle of statistically distributed capillaries with triangular cross-sections. Surface roughness effects are characterized by a roughness factor, which accounts for increased film thickness under relatively wet conditions due to capillary effects and increased film area under relatively dry conditions. The model significantly improved the prediction of hydraulic conductivity across the entire range of matric potentials for the illustrative soils compared with the van Genuchten–Mualem model (VGM), while maintaining the same number of adjustable parameters. The improved performance of the proposed model demonstrates the advantage of incorporating surface roughness in the pore-scale-based models. Furthermore, sandy soils and loams showed distinct roughness factors and pore-size distribution functions. Sandy soils tended to have smaller roughness factors and greater mean pore sizes than loams.},
	language = {English},
	number = {7},
	journal = {Vadose Zone Journal},
	author = {Zheng, Wenjuan and Yu, Xuan and Jin, Yan},
	year = {2015},
}

Quantifying the unsaturated hydraulic conductivity of a porous medium has been a great interest in the fields of hydrology, environmental engineering, and petroleum engineering. Previous research has shown that rough surfaces enhance liquid retention and conductance of flow in the form of liquid film. We present a pore-scale-based water retention and hydraulic conductivity model considering surface roughness effects. In the proposed model, a porous medium is simplified as a bundle of statistically distributed capillaries with triangular cross-sections. Surface roughness effects are characterized by a roughness factor, which accounts for increased film thickness under relatively wet conditions due to capillary effects and increased film area under relatively dry conditions. The model significantly improved the prediction of hydraulic conductivity across the entire range of matric potentials for the illustrative soils compared with the van Genuchten–Mualem model (VGM), while maintaining the same number of adjustable parameters. The improved performance of the proposed model demonstrates the advantage of incorporating surface roughness in the pore-scale-based models. Furthermore, sandy soils and loams showed distinct roughness factors and pore-size distribution functions. Sandy soils tended to have smaller roughness factors and greater mean pore sizes than loams.

@article{yu_watershed_2014,
	title = {Watershed {Reanalysis} of {Water} and {Carbon} {Cycle} {Models} at a {Critical} {Zone} {Observatory}},
	volume = {206},
	url = {http://dx.doi.org/10.1002/9781118872086.ch31},
	doi = {10.1002/9781118872086.ch31},
	abstract = {This chapter compares the physics-based watershed model Penn State Integrated Hydrologic Model (PIHM) and an ecophysiological model BioGeochemical Cycles (Biome-BGC) to gain insight into the strengths and weakness of each in the context of a new watershed sensor and reanalysis data set. To bring in correspondence with the intensive regional observation, the chapter focuses on model evaluation and assessment of coupling with primary objectives to (a) demonstrate how hydrological and biogeochemical models could resolve the multiple sources of high-resolution regional observation, (b) determine how coupled models could help with the interpretation of interaction between water and carbon cycles, and (c) how these, in turn, influence the evolution and design of process-based coupling in the future generations of integrated environmental models.},
	journal = {Remote Sensing of the Terrestrial Water Cycle},
	author = {Yu, Xuan and Duffy, Christopher and Kaye, Jason and Crow, Wade and Bhatt, Gopal and Shi, Yuning},
	year = {2014},
	pages = {493},
}

This chapter compares the physics-based watershed model Penn State Integrated Hydrologic Model (PIHM) and an ecophysiological model BioGeochemical Cycles (Biome-BGC) to gain insight into the strengths and weakness of each in the context of a new watershed sensor and reanalysis data set. To bring in correspondence with the intensive regional observation, the chapter focuses on model evaluation and assessment of coupling with primary objectives to (a) demonstrate how hydrological and biogeochemical models could resolve the multiple sources of high-resolution regional observation, (b) determine how coupled models could help with the interpretation of interaction between water and carbon cycles, and (c) how these, in turn, influence the evolution and design of process-based coupling in the future generations of integrated environmental models.

@article{yu_role_2014,
	title = {The role of macropores and multi-resolution soil survey datasets for distributed surface–subsurface flow modeling},
	url = {http://dx.doi.org/10.1016/j.jhydrol.2014.02.055},
	doi = {10.1016/j.jhydrol.2014.02.055},
	abstract = {Distributed watershed-scale modeling is often used as a framework for exploring the heterogeneity of runoff response and hydrologic performance of the catchment. The objective of this study is to apply this framework to characterizing the impacts of soil hydraulic properties at multiple scales on moisture storage and distributed runoff generation in a forested catchment. The physics-based and fully-coupled Penn State Integrated Hydrologic Model (PIHM) is employed to test a priori and field-measured properties in the modeling of watershed hydrology. PIHM includes an approximate representation of macropore flow that preserves the water holding capacity of the soil matrix while still allowing rapid flow through the macroporous soil under wet conditions. Both phenomena are critical to the overall hydrologic performance of the catchment. Soils data at different scales were identified: Case I STATSGO soils data (uniform or single soil type), Case II STATSGO soils data with macropore effect, and Case III field-based hydropedologic experiment revised distributed soil hydraulic properties and macropore property estimation. Our results showed that the Case I had difficulties in simulating the timing and peakflow of the runoff responses. Case II performed satisfactorily for peakflow at the outlet and internal weir locations. The distributed soils data in Case III demonstrated the model ability of predicting groundwater levels. The analysis suggests the important role of macropore flow to setting the threshold for recharge and runoff response, while still preserving the water holding capability of the soil and plant water availability. The spatial variability in soil hydraulic properties represented by Case III introduces an additional improvement in distributed catchment flow modeling, especially as it relates to subsurface lateral flow. Comparison of the three cases suggests the value of high-resolution soil survey mapping combined with a macropore parameterization can improve distributed watershed models.},
	journal = {Journal of Hydrology},
	author = {Yu, Xuan and Duffy, Christopher and Baldwin, Doug C. and Lin, Henry},
	year = {2014},
}

Distributed watershed-scale modeling is often used as a framework for exploring the heterogeneity of runoff response and hydrologic performance of the catchment. The objective of this study is to apply this framework to characterizing the impacts of soil hydraulic properties at multiple scales on moisture storage and distributed runoff generation in a forested catchment. The physics-based and fully-coupled Penn State Integrated Hydrologic Model (PIHM) is employed to test a priori and field-measured properties in the modeling of watershed hydrology. PIHM includes an approximate representation of macropore flow that preserves the water holding capacity of the soil matrix while still allowing rapid flow through the macroporous soil under wet conditions. Both phenomena are critical to the overall hydrologic performance of the catchment. Soils data at different scales were identified: Case I STATSGO soils data (uniform or single soil type), Case II STATSGO soils data with macropore effect, and Case III field-based hydropedologic experiment revised distributed soil hydraulic properties and macropore property estimation. Our results showed that the Case I had difficulties in simulating the timing and peakflow of the runoff responses. Case II performed satisfactorily for peakflow at the outlet and internal weir locations. The distributed soils data in Case III demonstrated the model ability of predicting groundwater levels. The analysis suggests the important role of macropore flow to setting the threshold for recharge and runoff response, while still preserving the water holding capability of the soil and plant water availability. The spatial variability in soil hydraulic properties represented by Case III introduces an additional improvement in distributed catchment flow modeling, especially as it relates to subsurface lateral flow. Comparison of the three cases suggests the value of high-resolution soil survey mapping combined with a macropore parameterization can improve distributed watershed models.

@article{shi_parameter_2014,
	title = {Parameter estimation of a physically based land surface hydrologic model using the ensemble {Kalman} filter: {A} synthetic experiment},
	volume = {50},
	url = {http://dx.doi.org/10.1002/2013WR014070},
	doi = {10.1002/2013WR014070},
	abstract = {This paper presents multiple parameter estimation using multivariate observations via the ensemble Kalman filter (EnKF) for a physically based land surface hydrologic model. A data assimilation system is developed for a coupled physically based land surface hydrologic model (Flux-PIHM) by incorporating EnKF for model parameter and state estimation. Synthetic data experiments are performed at a first-order watershed, the Shale Hills watershed (0.08 km2). Six model parameters are estimated. Observations of discharge, water table depth, soil moisture, land surface temperature, sensible and latent heat fluxes, and transpiration are assimilated into the system. The results show that, given a limited number of site-specific observations, the EnKF can be used to estimate Flux-PIHM model parameters. All the estimated parameter values are very close to their true values, with the true values inside the estimated uncertainty range (1 standard deviation spread). The estimated parameter values are not affected by the initial guesses. It is found that discharge, soil moisture, and land surface temperature (or sensible and latent heat fluxes) are the most critical observations for the estimation of those six model parameters. The assimilation of multivariate observations applies strong constraints to parameter estimation, and provides unique parameter solutions. Model results reveal strong interaction between the van Genuchten parameters α and β, and between land surface and subsurface parameters. The EnKF data assimilation system provides a new approach for physically based hydrologic model calibration using multivariate observations. It can be used to provide guidance for observational system designs, and is promising for real-time probabilistic flood and drought forecasting.},
	number = {1},
	journal = {Water Resources Research},
	author = {Shi, Yuning and Davis, Kenneth J. and Zhang, Fuqing and Duffy, Christopher J. and Yu, Xuan},
	year = {2014},
	pages = {706--724},
}

This paper presents multiple parameter estimation using multivariate observations via the ensemble Kalman filter (EnKF) for a physically based land surface hydrologic model. A data assimilation system is developed for a coupled physically based land surface hydrologic model (Flux-PIHM) by incorporating EnKF for model parameter and state estimation. Synthetic data experiments are performed at a first-order watershed, the Shale Hills watershed (0.08 km2). Six model parameters are estimated. Observations of discharge, water table depth, soil moisture, land surface temperature, sensible and latent heat fluxes, and transpiration are assimilated into the system. The results show that, given a limited number of site-specific observations, the EnKF can be used to estimate Flux-PIHM model parameters. All the estimated parameter values are very close to their true values, with the true values inside the estimated uncertainty range (1 standard deviation spread). The estimated parameter values are not affected by the initial guesses. It is found that discharge, soil moisture, and land surface temperature (or sensible and latent heat fluxes) are the most critical observations for the estimation of those six model parameters. The assimilation of multivariate observations applies strong constraints to parameter estimation, and provides unique parameter solutions. Model results reveal strong interaction between the van Genuchten parameters α and β, and between land surface and subsurface parameters. The EnKF data assimilation system provides a new approach for physically based hydrologic model calibration using multivariate observations. It can be used to provide guidance for observational system designs, and is promising for real-time probabilistic flood and drought forecasting.

@article{yu_parameterization_2013,
	title = {Parameterization for distributed watershed modeling using national data and evolutionary algorithm},
	volume = {58},
	issn = {0098-3004},
	url = {http://www.sciencedirect.com/science/article/pii/S0098300413001349},
	doi = {10.1016/j.cageo.2013.04.025},
	abstract = {Distributed hydrologic models supported by national soil survey, geology, topography and vegetation data products can provide valuable information about the watershed hydrologic cycle. However numerical simulation of the multi-state, multi-process system is structurally complex and computationally intensive. This presents a major difficulty in model calibration using traditional techniques. This paper presents an efficient calibration strategy for the physics-based, fully coupled, distributed hydrologic model Penn State Integrated Hydrologic Model (PIHM) with the support of national data products. PIHM uses a semi-discrete Finite Volume Method (FVM) formulation of the system of coupled ordinary differential equations (e.g. canopy interception, transpiration, soil evaporation) and partial differential equations (e.g. groundwater-surface water, overland flow, infiltration, channel flow, etc.). The matrix of key parameters to be estimated in the optimization process was partitioned into two groups according to the sensitivity to difference in time scales. The first group of parameters generally describes hydrologic processes influenced by hydrologic events (event-scale group: EG), which are sensitive to short time runoff generation, while the second group of parameters is largely influenced by seasonal changes in energy (seasonal time scale group: SG). The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is used to optimize the EG parameters in Message Passing Interface (MPI) environment, followed by the estimation of parameters in the SG. The calibration strategy was applied at three watersheds in central PA: a small upland catchment (8.4 ha), a watershed in the Appalachian Plateau (231 km2) and the Valley and Ridge of central Pennsylvania (843 km2). A partition calibration enabled a fast and efficient estimation of parameters.},
	number = {0},
	journal = {Computers \& Geosciences},
	author = {Yu, Xuan and Bhatt, Gopal and Duffy, Christopher and Shi, Yuning},
	month = aug,
	year = {2013},
	keywords = {Calibration, Little Juniata river, PIHM, Physics-based hydrological modeling, SSHCZO, Young Womans creek},
	pages = {80--90},
}

Distributed hydrologic models supported by national soil survey, geology, topography and vegetation data products can provide valuable information about the watershed hydrologic cycle. However numerical simulation of the multi-state, multi-process system is structurally complex and computationally intensive. This presents a major difficulty in model calibration using traditional techniques. This paper presents an efficient calibration strategy for the physics-based, fully coupled, distributed hydrologic model Penn State Integrated Hydrologic Model (PIHM) with the support of national data products. PIHM uses a semi-discrete Finite Volume Method (FVM) formulation of the system of coupled ordinary differential equations (e.g. canopy interception, transpiration, soil evaporation) and partial differential equations (e.g. groundwater-surface water, overland flow, infiltration, channel flow, etc.). The matrix of key parameters to be estimated in the optimization process was partitioned into two groups according to the sensitivity to difference in time scales. The first group of parameters generally describes hydrologic processes influenced by hydrologic events (event-scale group: EG), which are sensitive to short time runoff generation, while the second group of parameters is largely influenced by seasonal changes in energy (seasonal time scale group: SG). The Covariance Matrix Adaptation Evolution Strategy (CMA-ES) is used to optimize the EG parameters in Message Passing Interface (MPI) environment, followed by the estimation of parameters in the SG. The calibration strategy was applied at three watersheds in central PA: a small upland catchment (8.4 ha), a watershed in the Appalachian Plateau (231 km2) and the Valley and Ridge of central Pennsylvania (843 km2). A partition calibration enabled a fast and efficient estimation of parameters.

@article{shi_development_2013,
	title = {Development of a {Coupled} {Land} {Surface} {Hydrologic} {Model} and {Evaluation} at a {Critical} {Zone} {Observatory}},
	url = {http://dx.doi.org/10.1175/JHM-D-12-0145.1},
	doi = {10.1175/JHM-D-12-0145.1},
	abstract = {A fully coupled land surface hydrologic model, Flux-PIHM, is developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater at spatial resolutions sufficient to resolve upland stream networks, Flux-PIHM is able to represent heterogeneities due to topography and soils at high resolution, including spatial structure in the link between groundwater and the surface energy balance (SEB). Flux-PIHM has been implemented at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Multistate observations of discharge, water table depth, soil moisture, soil temperature, and sensible and latent heat fluxes in June and July 2009 are used to manually calibrate Flux-PIHM at hourly temporal resolution. Model predictions from 1 March to 1 December 2009 are evaluated. Both hydrologic predictions and SEB predictions show good agreement with observations. Comparisons of model predictions between Flux-PIHM and the original PIHM show that the inclusion of the complex SEB simulation only brings slight improvement in hourly model discharge predictions. Flux-PIHM adds the ability of simulating SEB to PIHM and does improve the prediction of hourly evapotranspiration, the prediction of total runoff (discharge), and the predictions of some peak discharge events, especially after extended dry periods. Model results reveal that annual average sensible and latent heat fluxes are strongly correlated with water table depth, and the correlation is especially strong for the model grids near the stream.},
	number = {2013},
	journal = {Journal of Hydrometeorology},
	author = {Shi, Yuning and Davis, Kenneth J. and Duffy, Christopher J. and Yu, Xuan},
	year = {2013},
}

A fully coupled land surface hydrologic model, Flux-PIHM, is developed by incorporating a land surface scheme into the Penn State Integrated Hydrologic Model (PIHM). The land surface scheme is adapted from the Noah land surface model. Because PIHM is capable of simulating lateral water flow and deep groundwater at spatial resolutions sufficient to resolve upland stream networks, Flux-PIHM is able to represent heterogeneities due to topography and soils at high resolution, including spatial structure in the link between groundwater and the surface energy balance (SEB). Flux-PIHM has been implemented at the Shale Hills watershed (0.08 km2) in central Pennsylvania. Multistate observations of discharge, water table depth, soil moisture, soil temperature, and sensible and latent heat fluxes in June and July 2009 are used to manually calibrate Flux-PIHM at hourly temporal resolution. Model predictions from 1 March to 1 December 2009 are evaluated. Both hydrologic predictions and SEB predictions show good agreement with observations. Comparisons of model predictions between Flux-PIHM and the original PIHM show that the inclusion of the complex SEB simulation only brings slight improvement in hourly model discharge predictions. Flux-PIHM adds the ability of simulating SEB to PIHM and does improve the prediction of hourly evapotranspiration, the prediction of total runoff (discharge), and the predictions of some peak discharge events, especially after extended dry periods. Model results reveal that annual average sensible and latent heat fluxes are strongly correlated with water table depth, and the correlation is especially strong for the model grids near the stream.

@inproceedings{duffy_watershed_2011,
	title = {Watershed {Reanalysis}: {Towards} a {National} {Strategy} for {Model}-{Data} {Integration}},
	isbn = {1-4673-0026-8},
	url = {http://dx.doi.org/10.1109/eScienceW.2011.32},
	doi = {10.1109/eScienceW.2011.32},
	abstract = {Reanalysis or retrospective analysis is the process of re-analyzing and assimilating climate and weather observations with the current modeling context. Reanalysis is an objective, quantitative method of synthesizing all sources of information (historical and real-time observations) within a unified framework. In this context, we propose a prototype for automated and virtualized web services software using national data products for climate reanalysis, soils, geology, terrain and land cover for the purpose of water resource simulation, prediction, data assimilation, calibration and archival. The prototype for model-data integration focuses on creating tools for fast data storage from selected national databases, as well as the computational resources necessary for a dynamic, distributed watershed prediction anywhere in the continental US. In the future implementation of virtualized services will benefit from the development of a cloud cyber infrastructure as the prototype evolves to data and model intensive computation for continental scale water resource predictions.},
	booktitle = {e-{Science} {Workshops} ({eScienceW}), 2011 {IEEE} {Seventh} {International} {Conference} on},
	publisher = {IEEE},
	author = {Duffy, Christopher and Leonard, Lorne and Bhatt, Gopal and Yu, Xuan and Giles, Lee},
	year = {2011},
	pages = {61--65},
}

Reanalysis or retrospective analysis is the process of re-analyzing and assimilating climate and weather observations with the current modeling context. Reanalysis is an objective, quantitative method of synthesizing all sources of information (historical and real-time observations) within a unified framework. In this context, we propose a prototype for automated and virtualized web services software using national data products for climate reanalysis, soils, geology, terrain and land cover for the purpose of water resource simulation, prediction, data assimilation, calibration and archival. The prototype for model-data integration focuses on creating tools for fast data storage from selected national databases, as well as the computational resources necessary for a dynamic, distributed watershed prediction anywhere in the continental US. In the future implementation of virtualized services will benefit from the development of a cloud cyber infrastructure as the prototype evolves to data and model intensive computation for continental scale water resource predictions.

@inproceedings{xuan_ndvi-based_2009,
	title = {An {NDVI}-based precipitation interpolation to improve hydrology simulation in the {Upper} {Reaches} of the {Yangtze} {River}.},
	isbn = {1-907161-07-4},
	url = {http://iahs.info/uploads/dms/iahs_335_0009.pdf},
	abstract = {Spatially interpolated rainfall estimates from rain gauges are widely used as input to hydrological models, but there is no universally suitable interpolation method. In southwest China there are very few rain gauges. Therefore, geographical information related to rainfall needs to be used in spatial interpolation methods. Among elevation, longitude, latitude, slope, and the normalized difference vegetation index (NDVI), NDVI is found to be the most optimum geographical information indicator for precipitation in the upper reaches of the Yangtze River in China, after careful analysis. Accordingly, a gradient plus reverse distance squared method based on NDVI was developed and applied in the upper reaches of the Yangtze River from 1956 to 2000. The interpolation result was compared with the result of Countrywide Water Resources Planning. The difference was not too much and the result of the interpolation showed a reasonable precipitation distribution in the mountainous areas, which was greatly improved compared to the direct use of the inverse-distance weighted method (IDW). And then the interpolation result was input to the Water and Energy transfer Process (WEP) model to simulate the hydrological cycle of the basin. The simulation of the hydrological processes show that water quantity balance errors are less than 5\% and the Nash-Sutcliffe efficiency coefficient is above 0.7, which proved that the interpolation method presented in this paper is credible.},
	booktitle = {Hydrological modelling and integrated water resources management in ungauged mountainous watersheds. {Proceedings} of a symposium held at {Chengdu}, {China}, {November} 2008.},
	publisher = {IAHS Press},
	author = {Xuan, Yu and Hao, Wang and DengHua, Yan and YangWen, Jia and CunWen, Niu},
	year = {2009},
	pages = {9--17},
}

Spatially interpolated rainfall estimates from rain gauges are widely used as input to hydrological models, but there is no universally suitable interpolation method. In southwest China there are very few rain gauges. Therefore, geographical information related to rainfall needs to be used in spatial interpolation methods. Among elevation, longitude, latitude, slope, and the normalized difference vegetation index (NDVI), NDVI is found to be the most optimum geographical information indicator for precipitation in the upper reaches of the Yangtze River in China, after careful analysis. Accordingly, a gradient plus reverse distance squared method based on NDVI was developed and applied in the upper reaches of the Yangtze River from 1956 to 2000. The interpolation result was compared with the result of Countrywide Water Resources Planning. The difference was not too much and the result of the interpolation showed a reasonable precipitation distribution in the mountainous areas, which was greatly improved compared to the direct use of the inverse-distance weighted method (IDW). And then the interpolation result was input to the Water and Energy transfer Process (WEP) model to simulate the hydrological cycle of the basin. The simulation of the hydrological processes show that water quantity balance errors are less than 5% and the Nash-Sutcliffe efficiency coefficient is above 0.7, which proved that the interpolation method presented in this paper is credible.

@article{ahrens_synthesis_2008,
	title = {A synthesis of nitrogen transformations and transfers from land to the sea in the {Yaqui} {Valley} agricultural region of northwest {Mexico}},
	volume = {44},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2007WR006661},
	doi = {https://doi.org/10.1029/2007WR006661},
	abstract = {Intensification of agricultural systems represents one of the most significant land use changes of the last century. High fertilizer inputs have been a key component of intensification and have contributed to increases in crop yield in most areas, but they can also cause profound alterations in the biogeochemical functioning of the soil, water, and air resources of these systems, particularly with regard to the nutrient nitrogen (N). Comprehensive studies linking field-scale fertilization with regional N fates and consequences for water resources are surprisingly sparse, particularly in the rapidly developing tropics and subtropics. Here we synthesize 15 years of research in wheat fields, drainage canals, estuaries, and coastal waters of the Yaqui Valley region of Sonora, Mexico. Although a relatively low proportion ({\textless}4\%) of total N inputs are exported via surface water to the coast, the episodic nature of these losses can have significant ecological consequences. For instance, gaseous and dissolved N fluxes from agricultural fields are among the highest observed, and N-rich runoff from the Yaqui Valley fuels phytoplankton blooms in coastal waters. Reductions in N losses with improved timing of fertilizer application relative to crop demand are possible without negatively affecting crop yield or quality and may help to move this and similar regions closer to sustainability.},
	number = {7},
	journal = {Water Resources Research},
	author = {Ahrens, T. D. and Beman, J. M. and Harrison, J. A. and Jewett, P. K. and Matson, P. A.},
	year = {2008},
	note = {\_eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2007WR006661},
	keywords = {agroecosystems, greenhouse gases, leaching, nitrogen, nitrogen export, watersheds},
}

Intensification of agricultural systems represents one of the most significant land use changes of the last century. High fertilizer inputs have been a key component of intensification and have contributed to increases in crop yield in most areas, but they can also cause profound alterations in the biogeochemical functioning of the soil, water, and air resources of these systems, particularly with regard to the nutrient nitrogen (N). Comprehensive studies linking field-scale fertilization with regional N fates and consequences for water resources are surprisingly sparse, particularly in the rapidly developing tropics and subtropics. Here we synthesize 15 years of research in wheat fields, drainage canals, estuaries, and coastal waters of the Yaqui Valley region of Sonora, Mexico. Although a relatively low proportion (\textless4%) of total N inputs are exported via surface water to the coast, the episodic nature of these losses can have significant ecological consequences. For instance, gaseous and dissolved N fluxes from agricultural fields are among the highest observed, and N-rich runoff from the Yaqui Valley fuels phytoplankton blooms in coastal waters. Reductions in N losses with improved timing of fertilizer application relative to crop demand are possible without negatively affecting crop yield or quality and may help to move this and similar regions closer to sustainability.