Spatiotemporal Analysis of Extracted Groundwater Volumes Estimated from Electricity Consumption. Issue 6 (6th May 2020)

• Record Type: Journal Article
• Authors: Chu, Hone‐Jay; Lin, Cheng‐Wei; Burbey, Thomas J.; Ali, Muhammad Zeeshan
• Is Part Of: Ground water. Volume 58:Issue 6(2020)
• Page Start: 962
• Page End: 972
• Publication Date: 2020-05-06
• Subjects: Groundwater -- Periodicals; Wells -- Periodicals; Eau souterraine -- Périodiques; Puits -- Périodiques; Grondwater; Eau souterraine; Puits; Electronic journals; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 551.49
• DOI: 10.1111/gwat.13008
• Languages: English
• ISSNs: 0017-467X

Abstract

Abstract: Land subsidence caused by groundwater overexploitation is a serious global problem. The acquisition of spatiotemporal pumping rates and volumes is a first step for water managers to develop a strategic plan for mitigating land subsidence. This study investigates an empirical formulation to estimate the monthly maximum pumped volume over a 10‐year period based on electric power consumption data. A spatiotemporal variability analysis of monthly pumped volume is developed to provide an improved understanding of seasonal pumping patterns and the role of irrigation type. The analysis of regional pumped volume provides an approximation of the spatiotemporal patterns of the variations in pumped volume. Results show the effects of climate, seasonal changes in pumping from irrigation, and the local differences in pumping caused to crop types. A seasonal pumped volume peak occurs annually, with the highest and least pumped volumes occurring in March (highest peak) and September (lowest peak), respectively. However, the majority of the historical maximum pumped volumes have occurred during the last few years. Extracted volumes continue to increase in some locations. The analysis reveals increasing trends in pumping, thereby possibly providing the locations where increased effective stresses may lead to land subsidence. Abstract : Article impact statement : The study provides the spatiotemporal patterns in pumped volume estimated from electricity consumption data, especially maximum pumped volumes.