Upscaling Tracer‐Aided Ecohydrological Modeling to Larger Catchments: Implications for Process Representation and Heterogeneity in Landscape Organization. Yang, X., Tetzlaff, D., Müller, C., Knöller, K., Borchardt, D., & Soulsby, C. Water Resources Research, 59(3):e2022WR033033, March, 2023.
Upscaling Tracer‐Aided Ecohydrological Modeling to Larger Catchments: Implications for Process Representation and Heterogeneity in Landscape Organization [link]Paper  doi  abstract   bibtex   
Abstract Stable isotopes of water are ideal tracers to integrate into process‐based models, advancing ecohydrological understanding. Current tracer‐aided ecohydrological modeling is mostly conducted in relatively small‐scale catchments, due to limited tracer data availability and often highly damped stream isotope signals in larger catchments (\textgreater100 km 2 ). Recent model developments have prioritized better spatial representation, offering new potential for advancing upscaling in tracer‐aided modeling. Here, we adapted the fully distributed EcH 2 O‐iso model to the Selke catchment (456 km 2 , Germany), incorporating monthly sampled isotopes from seven sites between 2012 and 2017. Parameter sensitivity analysis indicated that the information content of isotope data was generally complementary to discharge and more sensitive to runoff partitioning, soil water and energy dynamics. Multi‐criteria calibrations revealed that inclusion of isotopes could significantly improve discharge performance during validations and isotope simulations, resulting in more reasonable estimates of the seasonality of stream water ages. However, capturing isotopic signals of highly non‐linear near‐surface processes remained challenging for the upscaled model, but still allowed for plausible simulation of water ages reflecting non‐stationarity in transport and mixing. The detailed modeling also helped unravel spatio‐temporally varying patterns of water storage‐flux‐age interactions and their interplay under severe drought conditions. Embracing the upscaling challenges, this study demonstrated that even coarsely sampled isotope data can be of value in aiding ecohydrological modeling and consequent process representation in larger catchments. The derived innovative insights into ecohydrological functioning at scales commensurate with management decision making, are of particular importance for guiding science‐based measures for tackling environmental changes. , Key Points Process‐based tracer‐aided ecohydrological modeling is upscaled to \textgreater100 km 2 catchments using stable water isotopes Isotopes benefit large‐scale modeling in substantially improving model robustness and reliability of water age estimates Larger‐scale water partitioning and drought responses are controlled by heterogeneity in catchment organization
@article{yang_upscaling_2023,
	title = {Upscaling {Tracer}‐{Aided} {Ecohydrological} {Modeling} to {Larger} {Catchments}: {Implications} for {Process} {Representation} and {Heterogeneity} in {Landscape} {Organization}},
	volume = {59},
	issn = {0043-1397, 1944-7973},
	shorttitle = {Upscaling {Tracer}‐{Aided} {Ecohydrological} {Modeling} to {Larger} {Catchments}},
	url = {https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022WR033033},
	doi = {10.1029/2022WR033033},
	abstract = {Abstract
            
              Stable isotopes of water are ideal tracers to integrate into process‐based models, advancing ecohydrological understanding. Current tracer‐aided ecohydrological modeling is mostly conducted in relatively small‐scale catchments, due to limited tracer data availability and often highly damped stream isotope signals in larger catchments ({\textgreater}100 km
              2
              ). Recent model developments have prioritized better spatial representation, offering new potential for advancing upscaling in tracer‐aided modeling. Here, we adapted the fully distributed EcH
              2
              O‐iso model to the Selke catchment (456 km
              2
              , Germany), incorporating monthly sampled isotopes from seven sites between 2012 and 2017. Parameter sensitivity analysis indicated that the information content of isotope data was generally complementary to discharge and more sensitive to runoff partitioning, soil water and energy dynamics. Multi‐criteria calibrations revealed that inclusion of isotopes could significantly improve discharge performance during validations and isotope simulations, resulting in more reasonable estimates of the seasonality of stream water ages. However, capturing isotopic signals of highly non‐linear near‐surface processes remained challenging for the upscaled model, but still allowed for plausible simulation of water ages reflecting non‐stationarity in transport and mixing. The detailed modeling also helped unravel spatio‐temporally varying patterns of water storage‐flux‐age interactions and their interplay under severe drought conditions. Embracing the upscaling challenges, this study demonstrated that even coarsely sampled isotope data can be of value in aiding ecohydrological modeling and consequent process representation in larger catchments. The derived innovative insights into ecohydrological functioning at scales commensurate with management decision making, are of particular importance for guiding science‐based measures for tackling environmental changes.
            
          , 
            Key Points
            
              
                
                  
                    Process‐based tracer‐aided ecohydrological modeling is upscaled to {\textgreater}100 km
                    2
                    catchments using stable water isotopes
                  
                
                
                  Isotopes benefit large‐scale modeling in substantially improving model robustness and reliability of water age estimates
                
                
                  Larger‐scale water partitioning and drought responses are controlled by heterogeneity in catchment organization},
	language = {en},
	number = {3},
	urldate = {2024-11-15},
	journal = {Water Resources Research},
	author = {Yang, Xiaoqiang and Tetzlaff, Doerthe and Müller, Christin and Knöller, Kay and Borchardt, Dietrich and Soulsby, Chris},
	month = mar,
	year = {2023},
	pages = {e2022WR033033},
}

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