Toward improved identification of hydrological models: A diagnostic evaluation of the “<i>abcd</i>” monthly water balance model for the conterminous United States

Martínez, Guillermo; Gupta, H. V.

doi:10.1029/2009wr008294

Cited by 148 publications

(141 citation statements)

References 96 publications

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“…This model including more than 20 parameters is likely the most complex model among the existing MWBMs (Hughes, 2013). In 1981, Thomas (1981) proposed a four-parameter ''abcd" water balance model based on Thornthwaite's (1948) conceptual framework, while this model incorporates a more realistic representation of the infiltration process (Martinez and Gupta, 2010). As the concern regarding http://dx.doi.org/10.1016/j.jhydrol.2015.09.015 0022-1694/Ó 2015 Elsevier B.V. All rights reserved.…”

Section: Introductionmentioning

confidence: 99%

Comparison of performance of twelve monthly water balance models in different climatic catchments of China

Bai

Liu

Liang

et al. 2015

Journal of Hydrology

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Keywords: Monthly water balance model Model comparison Model selection a b s t r a c tMulti-model comparison can provide useful information for model selection and improvement. In this study, twelve monthly water balance models with different structures and various degree of complexity are compared in 153 catchments with different climatic conditions in China. Generally, the GR5M model has the best performance, followed by the GR2M and WBM model. We investigate the relations between model performance and catchment characteristics and find that the climatic characteristic of a catchment is the most important factor impacting model performance. The models have better performance in wet catchments than in dry catchments. Large differences of model performance exist in dry catchments and model users should pay attention to model selection in dry catchments. In addition, we analyze the model performances among different models and conclude that increasing the model complexity does not guarantee a better model performance. Simple models can achieve comparable or even better performance than complex models. For the monthly simulation of hydrological processes, a two-parameter model is sufficient to achieve a good result. Moreover, by comparing the impacts of evapotranspiration simulation and runoff generation simulation on model performance, we find that evapotranspiration simulation has limited influence on the model performance. We suggest model builders focus on runoff generation process rather than evapotranspiration process to improve the performance of a monthly hydrological model.

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Section: Introductionmentioning

confidence: 99%

Comparison of performance of twelve monthly water balance models in different climatic catchments of China

Bai

Liu

Liang

et al. 2015

Journal of Hydrology

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“…We then selected 2 additional input variables for an extended Gaussian process regression (EGPR) model, potential evaporation and NDVI. Potential evaporation is one of the main external drivers of land surface water partitioning [53], and therefore has been widely used as an input or internal variable in hydrologic models for streamflow simulation (e.g., [54][55][56]). Vegetation coverage, which is represented by NDVI, has also shown controlling effects on intra-annual streamflow in previous studies (e.g., [13,26]).…”

Section: Data-driven Methodsmentioning

confidence: 99%

“…Therefore, to improve the model robustness of PHM, we focused on these watersheds with weak positive or negative correlation between precipitation and surface runoff. These watersheds are strongly affected by snow processes [56].…”

Section: Model Performance Comparisonmentioning

confidence: 99%

Monthly Rainfall-Runoff Modeling at Watershed Scale: A Comparative Study of Data-Driven and Theory-Driven Approaches

Chang

Chen

2018

Water

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Data-driven machine learning approaches have been rapidly developed in the past 10 to 20 years and applied to various problems in the field of hydrology. To investigate the capability of data-driven approaches in rainfall-runoff modeling in comparison to theory-driven models, we conducted a comparative study of simulated monthly surface runoff at 203 watersheds across the contiguous USA using a conceptual model, the proportionality hydrologic model, and a data-driven Gaussian process regression model. With the same input variables of precipitation and mean monthly aridity index, the two models showed similar performance. We then introduced two more input variables in the data-driven model: potential evaporation and the normalized difference vegetation index (NDVI), which were selected based on hydrologic knowledge. The modified data-driven model performed much better than either the conceptual or original data-driven model. A sensitivity analysis was conducted on all three models tested in this study, which showed that surface runoff responded positively to increased precipitation. However, a confounding effect on surface runoff sensitivity was found among mean monthly aridity index, potential evaporation, and NDVI. This confounding was caused by complex interconnections among energy supply, vegetation coverage, and climate seasonality of the watershed system. We also conducted an uncertainty analysis on the two data-driven models, which showed that both models had reasonable predictability within the 95% confidence interval. With the additional two input variables, the modified data-driven model had lower prediction uncertainty and higher prediction accuracy.

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confidence: 99%

Spatial Heterogeneity in Sensitivity of Evapotranspiration to Climate Change

Wang¹,

Zhang²,

Cui³

et al. 2017

Pol. J. Environ. Stud.

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A long-term estimation of water balance is very important to: 1) understand the hydrological cycles over large temporal scales, 2) describe the dynamics of hydrological systems, and 3) predict the rapidly changing trends of hydro-climatic variables [1]. Water balance is a most basic and important concept for catchment hydrology. Moreover, it is a common concept for studying hydrological behaviors [2][3][4][5]. One of the core questions for estimating long-term water balance is the partition of mean annual precipitation into mean annual evapotranspiration and mean annual streamflow [6]. Until now, none of the methods has been developed for directly measuring evapotranspiration on a large spatial scale [2].In recent times, climate change and human activities have led to a large change in hydrological processes and water availability in many regions of the world [7][8][9][10]. The link between climate change and hydrological response is one of the main questions to be researched in the past and even today in hydrology. Many attempts have been made to formulate the mean annual water-energy balance [11][12][13][14]. Budyko (1974) assumed that the actual evapotranspiration is a function of the aridity index and precipitation, and it can be expressed as E/P=f(E 0 /P) [15].The energy-based theoretical equations, which describe the climate and the water balance, have been developed and applied in a "top-down" fashion [16][17][18]. The developments of Budyko (1974) andFu' (1981) [19] Pol. J. Environ. Stud. Vol. 26, No. 5 (2017) AbstractLong-term water-energy balance is a major concern in hydrology and water resource management. Evapotranspiration is a key factor for achieving water-energy balance. In this study, we used a simple water and energy balance equation to compare the effects of precipitation and potential evapotranspiration on actual evapotranspiration -mathematically and theoretically. The results showed that, in Baiyangdian catchment, a 1 mm or 10% increase in precipitation would lead to a 0.51 mm or 6.6% in actual evapotranspiration, and a 1 mm or 10% increase in potential evapotranspiration would lead to a 0.14 mm or 3.4% in actual evapotranspiration. The regional differences in the 10 regions of China showed that the effects of climate on actual evapotranspiration were significantly influenced by the aridity index. The changes of potential evapotranspiration will lead to more changes in actual evapotranspiration in humid regions, and the changes of precipitation will lead to more changes in actual evapotranspiration in arid regions.

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Toward improved identification of hydrological models: A diagnostic evaluation of the “abcd” monthly water balance model for the conterminous United States

Cited by 148 publications

References 96 publications

Comparison of performance of twelve monthly water balance models in different climatic catchments of China

Comparison of performance of twelve monthly water balance models in different climatic catchments of China

Monthly Rainfall-Runoff Modeling at Watershed Scale: A Comparative Study of Data-Driven and Theory-Driven Approaches

Spatial Heterogeneity in Sensitivity of Evapotranspiration to Climate Change

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