Linking hydrologic signatures to hydrologic processes: A review

McMillan, Hilary

doi:10.1002/hyp.13632

Cited by 123 publications

(112 citation statements)

References 108 publications

(192 reference statements)

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“…They are designed to extract relevant information about hydrological behavior of the system as each metric is designed to quantify underlying process that is linked with a particular hydrologic signature. Due to this ability to capture and quantify hydrologic behavior (McMillan, 2019), hydrologic signatures have many applications. Here, we applied signatures to evaluate whether simulations accurately represent watershed behavior and to link dominant model parameters with hydrologic signatures using sensitivity analysis.…”

Section: Methodsmentioning

confidence: 99%

Time‐Varying Sensitivity Analysis Reveals Relationships Between Watershed Climate and Variations in Annual Parameter Importance in Regions With Strong Interannual Variability

Basijokaite

Kelleher

2021

Water Resources Research

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As weather and climate extremes continue to set new records (WMO, 2017), it is becoming increasingly important to study the effects of these extremes on hydrologic cycles (Bates et al., 2008) as well as our ability to simulate these changes within hydrologic models (Nijssen et al., 2001; Xu, 1999). In the United States, Cal-Abstract Climate change impacts on hydroclimatology are becoming increasingly apparent around the world. It is unknown how annual variations in precipitation and air temperature alter the modelinferred importance of hydrological processes and how this varies across watersheds. To examine this, we used parsimonious rainfall-runoff model and applied time-varying sensitivity analysis across 30 Californian watersheds for a 33-year period (1981-2014). We calculated annual total order sensitivity indices for five performance metrics: Kling-Gupta Efficiency (KGE) and model error in simulating hydrologic signatures (runoff ratio, slope of flow duration curve, baseflow index, and timing of streamflow centroid). Sensitivity of hydrological signatures to the parameters differed by signature, while parameter importance with respect to KGE was much more spatially and temporally variable. Variations in parameter sensitivity with respect to KGE were either correlated with air temperature (snow-dominated sites in the Sierra Nevada) or precipitation (lower elevation sites < 1,300 m). Across error metrics and signatures, parameter sensitivity strongly differed between wet and dry years for a subset of our study sites. While parameter importance varied through time, parameter sensitivity variations across watersheds were much more pronounced. This suggests that parameter controls on model performance are much more a reflection of watershed properties as opposed to being dominantly shaped by shifts in precipitation and air temperature. These findings emphasize the importance of understanding simulated watershed responses to fluctuating annual conditions, as this conceptual knowledge is necessary to anticipate similarities and differences in response across even relatively proximal watersheds in the face of growing extreme conditions. Plain Language Summary Computer models are useful tools that can be used to analyze what inputs matter most to ensuring that model output is similar to observed conditions. In order to understand how very wet years versus very dry years impact which model inputs (called parameters) are most important to matching good predictions, we simulated streamflow using a simple mathematical model many thousands of times. We used these outputs to determine how variations in predictions of streamflow (output from the model) are related to variations in model parameters, to identify which parameters are most important for ensuring reasonable model predictions. We focused on watersheds that are close together, but that may experience different average conditions and interannual variability. We found that which parameters are important varied across different watersheds and also varied with total a...

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Section: Methodsmentioning

confidence: 99%

Time‐Varying Sensitivity Analysis Reveals Relationships Between Watershed Climate and Variations in Annual Parameter Importance in Regions With Strong Interannual Variability

Basijokaite

Kelleher

2021

Water Resources Research

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“…Signatures are helpful to systematically characterize the behavior of a hydrological system (Jothityangkoon et al., 2001; McMillan, 2020; Sawicz, et al., 2011). For the conceptualization of a karst‐influenced hydro‐system, we have to solve problems of intercatchment groundwater flow (IGF) that result in differences between topographic and subsurface domains.…”

Section: Methodsmentioning

confidence: 99%

Assessing Streamflow Sensitivity to Precipitation Variability in Karst‐Influenced Catchments With Unclosed Water Balances

Liu

Wagener

Hartmann

2021

Water Resources Research

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Karst water resources are estimated to provide drinking water to 10%-25% of the world's population (Ford & Williams, 2007; Stevanović, 2019). In some countries and regions, for example, Austria and Slovenia, karst water resources account for approximately half of the total water supply (Hartmann, Goldscheider, et al., 2014; Stevanović, 2019). Chemical weathering of carbonate rock results in a strong subsurface heterogeneity in karstic areas, which leads to groundwater recharge and storage behavior substantially different from the nonkarstic regions (Bakalowicz, 2005; Hartmann & Baker, 2017). Climate projections suggest strong changes of temperature and precipitation in almost all karstic regions in the world (Christensen et al., 2007). Climate change will affect hydrological dynamics and water availability in karstic regions by an unknown extent. New approaches to understanding the impact of climate change on karstic regions are therefore of great importance. Recent achievements in karst research include the creation of a karst spring discharge database to promote data availability for karstic regions (Olarinoye et al., 2020), relating soil moisture networks to karst groundwater storage and flow (Berthelin et al., 2020), using tracer experiments to detect fast and slow pathways and the connectivity of conduit systems (

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“…Moving forwards, it is important to consider commensurability while applying machine learning in this context. 8) Consider comparing models against hydrologic signatures -indices that provide insight into the functional behavior of the system under study (Wagener et al, 2007;McMilan, 2020). The direct comparison of simulated and observed variables through statistical https://doi.org/10.5194/gmd-2021-97 Preprint.…”

Section: Observation-based Model Evaluationmentioning

confidence: 99%

GMD Perspective: the quest to improve the evaluation of groundwater representation in continental to global scale models

Gleeson

Wagener

Döll

et al. 2021

Preprint

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Abstract. Continental- to global-scale hydrologic and land surface models increasingly include representations of the groundwater system. Such large-scale models are essential for examining, communicating, and understanding the dynamic interactions between the Earth System above and below the land surface as well as the opportunities and limits of groundwater resources. We argue that both large-scale and regional-scale groundwater models have utility, strengths and limitations so continued modeling at both scales is essential and mutually beneficial. A crucial quest is how to evaluate the realism, capabilities and performance of large-scale groundwater models given their modeling purpose of addressing large-scale science or sustainability questions as well as limitations in data availability and commensurability. Evaluation should identify if, when or where large-scale models achieve their purpose or where opportunities for improvements exists so that such models better achieve their purpose. We suggest that reproducing the spatio-temporal details of regional-scale models and matching local data is not a relevant goal. Instead, it is important to decide on reasonable model expectations regarding when a large scale model is performing “well enough” in the context of its specific purpose. The decision of reasonable expectations is necessarily subjective even if the evaluation criteria is quantitative. Our objective is to provide recommendations for improving the evaluation of groundwater representation in continental- to global-scale models. We describe current modeling strategies and evaluation practices, and subsequently discuss the value of three evaluation strategies: 1) comparing model outputs with available observations of groundwater levels or other state or flux variables (observation-based evaluation); 2) comparing several models with each other with or without reference to actual observations (model-based evaluation); and 3) comparing model behavior with expert expectations of hydrologic behaviors in particular regions or at particular times (expert-based evaluation). Based on evolving practices in model evaluation as well as innovations in observations, machine learning and expert elicitation, we argue that combining observation-, model-, and expert-based model evaluation approaches, while accounting for commensurability issues, may significantly improve the realism of groundwater representation in large-scale models. Thus advancing our ability for quantification, understanding, and prediction of crucial Earth science and sustainability problems. We encourage greater community-level communication and cooperation on this quest, including among global hydrology and land surface modelers, local to regional hydrogeologists, and hydrologists focused on model development and evaluation.

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Linking hydrologic signatures to hydrologic processes: A review

Cited by 123 publications

References 108 publications

Time‐Varying Sensitivity Analysis Reveals Relationships Between Watershed Climate and Variations in Annual Parameter Importance in Regions With Strong Interannual Variability

Time‐Varying Sensitivity Analysis Reveals Relationships Between Watershed Climate and Variations in Annual Parameter Importance in Regions With Strong Interannual Variability

Assessing Streamflow Sensitivity to Precipitation Variability in Karst‐Influenced Catchments With Unclosed Water Balances

GMD Perspective: the quest to improve the evaluation of groundwater representation in continental to global scale models

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