Arshad Arfan, Mirchi Ali, Samimi Maryam, Ahmad Bashir
Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK, USA; Department of Irrigation and Drainage, Faculty of Agricultural Engineering and Technology, University of Agriculture Faisalabad, Faisalabad, Pakistan.
Department of Biosystems and Agricultural Engineering, Oklahoma State University, Stillwater, OK, USA.
Sci Total Environ. 2022 Sep 10;838(Pt 2):156044. doi: 10.1016/j.scitotenv.2022.156044. Epub 2022 May 20.
The growth of agricultural production systems is a major driver of groundwater depletion worldwide. Balancing groundwater supply and food production requires localized understanding of groundwater storage and depletion variations in response to diverse cropping systems and surface water availability for irrigation. While advances through Gravity Recovery and Climate Experiment (GRACE) have facilitated estimating the groundwater storage (GWS) changes in recent years, the coarse resolution of GRACE data hinders the characterization of GWS variation hotspots. Herein, we present a novel spatial water balance approach to improve the distributed estimation of groundwater storage and depletion changes at a spatial scale that can detect the hotspots of GWS variation. We used a mixed geographically weighted regression (MGWR) model to downscale GRACE Level-3 data from coarse resolution (1° × 1°) to fine scale (1 km × 1 km) based on high resolution environmental variables. We then combined the downscaled GRACE-based GWS variations with results from a calibrated Soil and Water Assessment Tool (SWAT) model. We demonstrate an application of the approach in the Irrigated Indus Basin (IIB). Between 2002 and 2019, total loss of groundwater reserves varied in the IIB's 55 canal command areas with the highest loss observed in Dehli Doab by >50 km followed by 7.8-49 km in the upstream, and 0.77-7.77 km in the downstream canal command areas. GWS declined by -325.55 mm/year at Dehli Doab, followed by -186.86 mm/year at BIST Doab, -119.20 mm/year at BARI Doab, and -100.82 mm/year at JECH Doab. The rate of groundwater depletion is increasing in the canal command areas of Delhi Doab and BIST Doab by 0.21-0.35 m/year. Larger groundwater depletion in some canal command areas (e.g., RACHNA, BIST Doab, and Delhi Doab) is associated with the rice-wheat cropping system, low rainfall, and low flows from tributaries.
农业生产系统的发展是全球地下水消耗的主要驱动因素。平衡地下水供应和粮食生产需要对地下水储量以及因不同种植系统和灌溉地表水可利用量而导致的消耗变化有局部性的了解。虽然近年来通过重力恢复与气候实验（GRACE）取得的进展有助于估算地下水储量（GWS）的变化，但GRACE数据的粗分辨率阻碍了对GWS变化热点的特征描述。在此，我们提出一种新颖的空间水平衡方法，以改进在能够检测GWS变化热点的空间尺度上对地下水储量和消耗变化的分布式估算。我们使用混合地理加权回归（MGWR）模型，基于高分辨率环境变量将GRACE三级数据从粗分辨率（1°×1°）降尺度到细尺度（1千米×1千米）。然后，我们将基于GRACE降尺度后的GWS变化与经过校准的土壤和水资源评估工具（SWAT）模型的结果相结合。我们展示了该方法在印度河灌溉流域（IIB）的应用。在2002年至2019年期间，IIB的55个运河灌区的地下水储量总损失各不相同，其中德里多布损失最大，超过50千米，其次是上游的7.8 - 49千米，以及下游运河灌区的0.77 - 7.77千米。德里多布的GWS每年下降 - 325.55毫米，其次是比斯塔多布每年下降 - 186.86毫米，巴里多布每年下降 - 119.20毫米，杰赫多布每年下降 - 100.82毫米。德里多布和比斯塔多布运河灌区的地下水消耗速率每年增加0.21 - 0.35米。一些运河灌区（如拉奇纳、比斯塔多布和德里多布）较大的地下水消耗与稻麦种植系统、低降雨量以及支流低流量有关。
