Downscaled-GRACE Data Reveal Anthropogenic and Climate-Induced Water Storage Decline Across the Indus Basin

IF 4.6 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES Water Resources Research Pub Date : 2024-07-15 DOI:10.1029/2023wr035882
Arfan Arshad, Ali Mirchi, Saleh Taghvaeian, Amir AghaKouchak
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Abstract

GRACE (Gravity Recovery and Climate Experiment) has been widely used to evaluate terrestrial water storage (TWS) and groundwater storage (GWS). However, the coarse-resolution of GRACE data has limited the ability to identify local vulnerabilities in water storage changes associated with climatic and anthropogenic stressors. This study employs high-resolution (1 km2) GRACE data generated through machine learning (ML) based statistical downscaling to illuminate TWS and GWS dynamics across twenty sub-regions in the Indus Basin. Monthly TWS and GWS anomalies obtained from a geographically weighted random forest (RFgw) model maintained good consistency with original GRACE data at the 25 km2 grid scale. The downscaled data at 1 km2 resolution illustrate the spatial heterogeneity of TWS and GWS depletion within each sub-region. Comparison with in-situ GWS from 2,200 monitoring wells shows that downscaling of GRACE data significantly improves agreement with in-situ data, evidenced by higher Kling-Gupta Efficiency (0.50–0.85) and correlation coefficients (0.60–0.95). Hotspots with the highest TWS and GWS decline rate between 2002 and 2023 were Dehli Doab (−442, −585 mm/year), BIST Doab (−367, −556 mm/year), Rajasthan (−242, −381 mm/year), and BARI (−188, −333 mm/year). Based on a general additive model, 47%–83% of the TWS decline was associated with anthropogenic stressors mainly due to increasing trends of crop sown area, water consumption, and human settlements. The decline rate of TWS and GWS anomalies was lower (i.e., −25 to −75 mm/year) in upstream sub-regions (e.g., Yogo, Gilgit, Khurmong, Kabul) where climatic factors (downward shortwave radiations, air temperature, and sea surface temperature) explained 72%–91% of TWS/GWS changes. The relative influences of climatic and anthropogenic stressors varied across sub-regions, underscoring the complex interplay of natural-human activities in the basin. These findings inform place-based water resource management in the Indus Basin by advancing the understanding of local vulnerabilities.
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缩小尺度--GRACE 数据揭示整个印度河流域人为和气候导致的蓄水量下降
GRACE(重力恢复与气候实验)已被广泛用于评估陆地蓄水量(TWS)和地下水蓄水量(GWS)。然而,GRACE 数据的粗分辨率限制了识别与气候和人为压力因素相关的蓄水变化的局部脆弱性的能力。本研究利用通过基于机器学习 (ML) 的统计降尺度生成的高分辨率(1 平方公里)GRACE 数据来阐明印度河流域 20 个次区域的 TWS 和 GWS 动态。从地理加权随机森林(RFgw)模型中获得的 TWS 和 GWS 月度异常与 25 平方公里网格尺度的 GRACE 原始数据保持了良好的一致性。1 平方公里分辨率下的降尺度数据说明了每个子区域内 TWS 和 GWS 消耗的空间异质性。与来自 2,200 口监测井的原位 GWS 相比,GRACE 数据的降尺度处理大大提高了与原位数据的一致性,更高的 Kling-Gupta 效率(0.50-0.85)和相关系数(0.60-0.95)证明了这一点。2002 年至 2023 年 TWS 和 GWS 下降率最高的热点地区是 Dehli Doab(-442、-585 毫米/年)、BIST Doab(-367、-556 毫米/年)、Rajasthan(-242、-381 毫米/年)和 BARI(-188、-333 毫米/年)。根据一般加和模型,47%-83%的 TWS 下降与人为压力因素有关,主要是由于作物播种面积、耗水量和人类居住区的增加趋势。上游次区域(如 Yogo、Gilgit、Khurmong、Kabul)的 TWS 和 GWS 异常值下降率较低(即-25 至-75 毫米/年),其中气候因素(向下的短波辐射、气温和海面温度)解释了 72% 至 91% 的 TWS/GWS 变化。气候和人为压力因素的相对影响因次区域而异,凸显了流域内自然与人类活动之间复杂的相互作用。这些发现为印度河流域以地方为基础的水资源管理提供了信息,促进了对地方脆弱性的了解。
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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