TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks

Müller, Marc F.; Thompson, Sally

doi:10.5194/hess-19-2925-2015

Cited by 21 publications

(12 citation statements)

References 43 publications

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“…They often use a limited number of physically meaningful parameters, with low computational burden, to mechanistically link the drivers, state and hydrologic response of the catchment [Müller and Thompson, 2015]. process-based models can also be applied in the absence of long term discharge time series, as they require minimal or no calibration [Doulatyari et al, 2015].…”

Section: Introductionmentioning

confidence: 99%

Patterns of streamflow regimes along the river network: The case of the Thur river

Doulatyari

Betterle

Radny

et al. 2017

Environmental Modelling & Software

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A modeling framework for point-wise prediction of the probability density function and flow duration curve of streamflows along complex river networks is presented. The predictions are based on catchment-scale climatic and morphological features, without calibration on observed discharge time-series. The framework was applied to a test basin in northeastern Switzerland, and relevant flow statistics were validated at six subcatchment outlets with satisfactory results. Spatial patterns of flow regime exhibit a strong climatic signature, mostly driven by reduced rainfall depths and increasing effective rainfall frequency in the downstream areas. The increasing non-linearity of the catchment response with contributing area is reflected by the observed increase in the recession parameters along the main river channel. This framework offers a novel approach for assessing the spatial patterns of streamflows based on limited information, which is important for evaluation of human and ecological functions in riverine systems.

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Section: Introductionmentioning

confidence: 99%

Patterns of streamflow regimes along the river network: The case of the Thur river

Doulatyari

Betterle

Radny

et al. 2017

Environmental Modelling & Software

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“…Drainage area can have a significant influence on model performance [69]. This phenomenon became apparent here when we divided the study basins into three groups according to their drainage area (each group having 10 study basins) and then viewed the NSE DB s and NSE IDW s in box plots (Figure 8).…”

Section: The Effect Of Drainage Area On Model Performancementioning

confidence: 94%

Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India

Nag

Biswal

2019

Hydrology

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Construction of flow duration curves (FDCs) is a challenge for hydrologists as most streams and rivers worldwide are ungauged. Regionalization methods are commonly followed to solve the problem of discharge data scarcity by transforming hydrological information from gauged basins to ungauged basins. As a consequence, regionalization-based FDC predictions are not very reliable where discharge data are scarce quantitatively and/or qualitatively. In such a scenario, it is perhaps more meaningful to use a calibration-free rainfall‒runoff model that can exploit easily available meteorological information to predict FDCs in ungauged basins. This hypothesis is tested in this study by comparing a well-known regionalization-based model, the inverse distance weighting (IDW) model, with the recently proposed calibration-free dynamic Budyko model (DB) in a region where discharge observations are not only insufficient quantitatively but also show apparent signs of observational errors. The DB model markedly outperformed the IDW model in the study region. Furthermore, the IDW model’s performance sharply declined when we randomly removed discharge gauging stations to test the model in a variety of data availability scenarios. The analysis here also throws some light on how errors in observational datasets and drainage area influence model performance and thus provides a better picture of the relative strengths of the two models. Overall, the results of this study support the notion that a calibration-free rainfall‒runoff model can be chosen to predict FDCs in discharge data-scarce regions. On a philosophical note, our study highlights the importance of process understanding for the development of meaningful hydrological models.

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“…The corresponding contributing areas can be either “nested” (if one catchment is embedded into a larger one) or “non‐nested” (i.e., if the intersection between the two contributing areas is null). The nested/non‐nested nature of river basins can strongly influence the relationship between their hydrographs (e.g., Müller & Thompson, 2015; Skøien & Blöschl, 2007). In fact, while two nested outlets are physically connected by routing processes, non‐nested catchments lack a direct physical link (Betterle, Schirmer, & Botter, 2017).…”

Section: Introductionmentioning

confidence: 99%

“…2015). In fact, catchment nestedness is commonly considered as a proxy of hydrological similarity (Gottschalk et al., 2006, 2011; Müller & Thompson, 2015; Skøien et al., 2006). However, non‐nested catchments can also display similar flow dynamics owing to common hydrological drivers.…”

Section: Introductionmentioning

confidence: 99%

Does Catchment Nestedness Enhance Hydrological Similarity?

Betterle

Botter

2021

Geophysical Research Letters

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The topology of river networks defines the hierarchical organization of the landscape and controls the drainage pathways triggered by precipitation. This study investigates how the structure of channel networks influences spatial patterns of flow regimes by focusing on the hydrograph observed at the outlet of nested and non‐nested basins. An extensive data set spanning diverse geomorphoclimatic conditions is used to show that – when inter‐catchment distance increases – nested catchments exhibit a more pronounced decrease of streamflow correlation as compared to non‐nested sites. Thus, non‐nested basins have more correlated hydrologic responses at large distances. This unexpected behavior is explained by a geometrical model, which reveals that inter‐catchment differences in size and elevation are larger in nested sites, thereby increasing the spatial heterogeneity of key hydrological processes that shape the hydrograph. This study provides clues to critically reinterpret the hydrological response on nested versus non‐nested catchments, with relevant implications for hydrology and ecology.

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TopREML: a topological restricted maximum likelihood approach to regionalize trended runoff signatures in stream networks

Cited by 21 publications

References 43 publications

Patterns of streamflow regimes along the river network: The case of the Thur river

Patterns of streamflow regimes along the river network: The case of the Thur river

Can a Calibration-Free Dynamic Rainfall‒Runoff Model Predict FDCs in Data-Scarce Regions? Comparing the IDW Model with the Dynamic Budyko Model in South India

Does Catchment Nestedness Enhance Hydrological Similarity?

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