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GRACE: Gravity Recovery and Climate Experiment long-term trend investigation over the Nile River Basin: Spatial variability drivers
Journal of Hydrology ( IF 6.4 ) Pub Date : 2020-07-01 , DOI: 10.1016/j.jhydrol.2020.124870
Emad Hasan , Aondover Tarhule

Abstract GRACE (Gravity Recovery and Climate Experiment) long-term terrestrial water storage anomaly (TWSA) is attributed to the complex interaction of climatic, physical and anthropogenic drivers. This paper, therefore, explores how different hydroclimatic and anthropogenic processes interact and combine over “space” to produce the mass variations that GRACE-TWSA detects. Using the Nile River Basin (NRB) as a case study, it explicitly analyzes nine hydroclimatic and anthropogenic processes, as well as their relationship to the TWSA in different climatic zones. The analytic method employed the long-term trends derived for both the dependent (TWSA) and independent (explanatory) variables via applying two geographically multiple regression (GMR) approaches: (i) an ordinary least square regression (OLS) model in which the contributions of all variables to TWSA variability are deemed equal at all locations; and (ii) a geographically weighted regression (GWR) which assigns a weight to each variable at different locations based on clustering occurrences. The models’ efficacy was investigated using standard goodness of fit diagnostics. The OLS explains that the basin at large TWSA spatial variability significantly attributed to five variables, i.e., precipitation, runoff, surface water storage, soil moisture storage, and population density, (p

中文翻译:

GRACE:尼罗河流域重力恢复和气候实验长期趋势调查:空间变异性驱动因素

摘要 GRACE(重力恢复和气候实验)长期陆地储水异常(TWSA)归因于气候、物理和人为驱动因素的复杂相互作用。因此,本文探讨了不同的水文气候和人为过程如何在“空间”上相互作用和结合以产生 GRACE-TWSA 检测到的质量变化。使用尼罗河流域 (NRB) 作为案例研究,它明确分析了九个水文气候和人为过程,以及它们与不同气候带中 TWSA 的关系。分析方法通过应用两种地理多元回归 (GMR) 方法,采用了从因变量 (TWSA) 和独立(解释性)变量得出的长期趋势:(i) 普通最小二乘回归 (OLS) 模型,其中所有变量对 TWSA 变异性的贡献在所有位置均视为相等;(ii) 地理加权回归 (GWR),它根据聚类发生情况为不同位置的每个变量分配权重。使用标准拟合优度诊断来研究模型的功效。OLS 解释说,大 TWSA 空间变异性的流域显着归因于五个变量,即降水、径流、地表水储存、土壤水分储存和人口密度,(p 使用标准拟合优度诊断来研究模型的功效。OLS 解释说,大 TWSA 空间变异性的流域显着归因于五个变量,即降水、径流、地表水储存、土壤水分储存和人口密度,(p 使用标准拟合优度诊断来研究模型的功效。OLS 解释说,大 TWSA 空间变异性的流域显着归因于五个变量,即降水、径流、地表水储存、土壤水分储存和人口密度,(p
更新日期:2020-07-01
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