Global S&T Development Trend Analysis Platform of Resources and Environment
DOI | 10.1029/2020WR027340 |
Exploring Hydrologic Model Process Connectivity at the Continental Scale through An Information Theory Approach | |
Goutam Konapala; Shih‐; Chieh Kao; Nans Addor | |
2020-10-03 | |
发表期刊 | Water Resources Research
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出版年 | 2020 |
英文摘要 | Exploring water fluxes between hydrological model (HM) components is essential to assess and improve model realism. Many classical metrics for HM diagnosis rely solely on streamflow and hence provide limited insights into model performance across processes. This study applies an information theory measure known as “transfer entropy” (TE) to systematically quantify the transfer of information among major HM components. To test and demonstrate the benefits of TE, we use the Framework for Understanding Structural Errors (FUSE) to mimic and compare four commonly used HM structures, VIC, PRMS, SACRAMENTO, and TOPMODEL, across 671 catchments spanning a variety of hydrologic regimes in the conterminous United States. We explore connections between HM components and catchment landscape characteristics (e.g., climate, topography, soil and vegetation) and characterize their nonlinear associations using distance correlation and Spearman correlation coefficients. Our results indicate that while the information transferred from precipitation to runoff is similar across model structures (likely as a result of calibration), the information transferred among other components can vary significantly from a FUSE structure to the next. We find that aridity, precipitation duration and frequency, snow fraction, mean elevation, forest area, and leaf area index are often significantly associated with TE between the main HM components. We propose that the presence of meaningful nonlinear associations can be used to diagnose process representation in HMs. Our results highlight the necessity to enhance the conventional streamflow‐only calibration approach for a more realistic representation of water dynamics in models. |
领域 | 资源环境 |
URL | 查看原文 |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://119.78.100.173/C666/handle/2XK7JSWQ/297882 |
专题 | 资源环境科学 |
推荐引用方式 GB/T 7714 | Goutam Konapala,Shih‐,Chieh Kao,et al. Exploring Hydrologic Model Process Connectivity at the Continental Scale through An Information Theory Approach[J]. Water Resources Research,2020. |
APA | Goutam Konapala,Shih‐,Chieh Kao,&Nans Addor.(2020).Exploring Hydrologic Model Process Connectivity at the Continental Scale through An Information Theory Approach.Water Resources Research. |
MLA | Goutam Konapala,et al."Exploring Hydrologic Model Process Connectivity at the Continental Scale through An Information Theory Approach".Water Resources Research (2020). |
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