Entropy-Based Index for Spatiotemporal Analysis of Streamflow, Precipitation, and Land-Cover
Entropy-Based Index for Spatiotemporal Analysis of Streamflow, Precipitation, and Land-Cover
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DOI：
10.1061/(asce)he.1943-5584.0001429
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发表时间：
2016-11-01
影响因子：
2.4
通讯作者：
Singh, Vijay P.
中科院分区：
文献类型：
--
作者：
Djebou, Dagbegnon C. Sohoulande;Singh, Vijay P.
流域的水文行为受多种因素的影响，这些因素在时间和空间上相互作用。这些相互作用的洞察力对于推进水资源管理至关重要。本文讨论了一种方法，需要一个基于熵的无序指数的时空模式分析。通过实例分析，说明了该指标对流域水文要素分析的针对性。具体而言，该方法研究的时空格局的径流，降水量和土地覆盖整个流域。事实上，这三个变量中的每一个都是随时间变化的，在陆地水文学中起着决定性的作用。然而，它们的联合功能更复杂的阐明，即使这些变量经常显示有意义的变化在时间和空间。在这一背景下的框架内，应用基于熵的指数揭示了突出的信号，是有用的水资源评估。此外，使用基于熵的指数的分析提供了现实的见解，这些水文因素之间的相互作用，在流域尺度上的相互作用。
The hydrological behavior of a watershed is influenced by a multitude of factors that interact differently in time and space. The perspicacity of these interactions is critical for advancing water resource management. This article discusses an approach that entails an entropy-based disorder index for spatio-temporal pattern analysis. Based on a case study, the article reported the pertinence of the index for analyzing the hydrologic components of the watershed. Specifically, the approach examines the spatio-temporal patterns of streamflow, precipitation, and land-cover across the watershed. Indeed, each of these three variables is time-dependent and plays a determinant role in terrestrial hydrology. However, their joint functionality is more complex to elucidate, even though these variables frequently display meaningful variability in time and space. Within this contextual frame, application of the entropy-based index reveals prominent signals that are useful for water resources assessment. Moreover, the analysis using the entropy-based index provides realistic insights into the interactions between these hydrologic factors that interplay at the watershed scale.