Consistency between hydrological models and field observations: linking processes at the hillslope scale to hydrological responses at the watershed scale

Clark, Martyn P.; Rupp, David E.; Woods, Ross; Meerveld, H. J. Tromp-van; Peters, Norman E.; Freer, J. E.

doi:10.1002/hyp.7154

Cited by 141 publications

(280 citation statements)

References 43 publications

(75 reference statements)

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“…This scatter reduction in recession plots might improve model fit and has been applied in a number of studies (e.g. Clark et al, 2009;Palmroth et al, 2010;Ajami et al, 2011;Staudinger et al, 2011).…”

Section: Roles Of Extraction Procedures and Parameterization Methodsmentioning

confidence: 99%

“…Beyond that, RAMs are often used to estimate recession behavior over different scales (e.g. hillslopes, catchment size) (Clark et al, 2009;Wang, 2011) or to characterize storage capacity (Sayama et al, 2011) or recession timescales (Aksoy and Wittenberg, 2011;Krakauer and Temimi, 2011). In these applications, the choice of RAM will directly influence the estimated properties of water availability.…”

Section: The Effect Of Different Rams To Distinguish Catchments' Recementioning

confidence: 99%

“…Fixed slopes of approximately b = 1.5 have been suggested to calibrate parameter a and to regionalize non-linear storage-outflow (Wittenberg, 1999), but one should note that for the RAMs in this study the slopes differ notably between 1 and 2. Some studies have linked slopes b to the spatial scale and found that a linear relationship for storage-outflow (b = 1) was suitable for hillslopes but turned more and more into non-linear behavior (b > 1) with increasing catchment scale and catchment heterogeneity (Clark et al, 2009;Harman et al, 2009). We found no systematic pattern between slopes b and catchment area (not shown), although area often has been identified as a catchment characteristic for regional low-flow regression models (Eng and Milly, 2007).…”

Section: The Effect Of Different Rams To Distinguish Catchments' Recementioning

confidence: 99%

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Are streamflow recession characteristics really characteristic?

Stoelzle

Stahl

Weiler

2013

Hydrol. Earth Syst. Sci.

108

134

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Abstract. Streamflow recession has been investigated by a variety of methods, often involving the fit of a model to empirical recession plots to parameterize a non-linear storageoutflow relationship based on the dQ/dt-Q method. Such recession analysis methods (RAMs) are used to estimate hydraulic conductivity, storage capacity, or aquifer thickness and to model streamflow recession curves for regionalization and prediction at the catchment scale. Numerous RAMs have been published, but little is known about how comparably the resulting recession models distinguish characteristic catchment behavior. In this study we combined three established recession extraction methods with three different parameter-fitting methods to the power-law storage-outflow model to compare the range of recession characteristics that result from the application of these different RAMs. Resulting recession characteristics including recession time and corresponding storage depletion were evaluated for 20 mesoscale catchments in Germany. We found plausible ranges for model parameterization; however, calculated recession characteristics varied over two orders of magnitude. While recession characteristics of the 20 catchments derived with the different methods correlate strongly, particularly for the RAMs that use the same extraction method, not all rank the catchments consistently, and the differences among some of the methods are larger than among the catchments. To elucidate this variability we discuss the ambiguous roles of recession extraction procedures and the parameterization of the storage-outflow model and the limitations of the presented recession plots. The results suggest strong limitations to the comparability of recession characteristics derived with different methods, not only in the model parameters but also in the relative characterization of different catchments. A multiple-methods approach to investigating streamflow recession characteristics should be considered for applications whenever possible.

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Section: Roles Of Extraction Procedures and Parameterization Methodsmentioning

confidence: 99%

Section: The Effect Of Different Rams To Distinguish Catchments' Recementioning

confidence: 99%

Section: The Effect Of Different Rams To Distinguish Catchments' Recementioning

confidence: 99%

See 1 more Smart Citation

Are streamflow recession characteristics really characteristic?

Stoelzle

Stahl

Weiler

2013

Hydrol. Earth Syst. Sci.

108

134

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show abstract

“…Multivariate and multiscale diagnostic metrics of model behavior should provide insight into both the individual processes within a model as well as how interlinked processes combine to produce the system-scale response at larger spatial scales Luo et al, 2012]. For example, analysis of recession behavior can provide more information on model weaknesses than analysis of summary metrics of model performance such as the Nash-Sutcliffe score [Yilmaz et al, 2008;Clark et al, 2009]. Essentially, models need to reproduce both realistic temporal hydrologic behavior (i.e., high frequency and low frequency) and realistic spatial patterns of variability across a hierarchy of scales.…”

Section: Process-based Model Evaluationmentioning

confidence: 99%

Improving the representation of hydrologic processes in Earth System Models

Clark

Fan

Lawrence

et al. 2015

Water Resources Research

452

404

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Many of the scientific and societal challenges in understanding and preparing for global environmental change rest upon our ability to understand and predict the water cycle change at large river basin, continent, and global scales. However, current large-scale land models (as a component of Earth System Models, or ESMs) do not yet reflect the best hydrologic process understanding or utilize the large amount of hydrologic observations for model testing. This paper discusses the opportunities and key challenges to improve hydrologic process representations and benchmarking in ESM land models, suggesting that (1) land model development can benefit from recent advances in hydrology, both through incorporating key processes (e.g., groundwater-surface water interactions) and new approaches to describe multiscale spatial variability and hydrologic connectivity; (2) accelerating model advances requires comprehensive hydrologic benchmarking in order to systematically evaluate competing alternatives, understand model weaknesses, and prioritize model development needs, and (3) stronger collaboration is needed between the hydrology and ESM modeling communities, both through greater engagement of hydrologists in ESM land model development, and through rigorous evaluation of ESM hydrology performance in research watersheds or Critical Zone Observatories. Such coordinated efforts in advancing hydrology in ESMs have the potential to substantially impact energy, carbon, and nutrient cycle prediction capabilities through the fundamental role hydrologic processes play in regulating these cycles.

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“…Several studies also illustrated the non-uniqueness of the response of discharge to storage. For instance, Clark et al (2009) illustrated for a mountain watershed in Georgia (USA) that the recession relationships of (dQ/dt) and Q is approximately consistent with a linear reservoir at a hillslope scale and deviation from linearity becomes progressively larger with increasing spatial scale, and Myrabø (1997), Beven (2006), Ewen and Birkinshaw (2007), Spence et al (2010), Martina et al (2011) and Fovet et al (2015 reported hysteresis in discharge-storage relationships. Furthermore, Teuling et al…”

mentioning

confidence: 99%