Groundwater Storage Change Estimation Using Grace Satellite Data In Indus Basin

Muhammad Salam (), Muhammad Jehanzeb Masud Cheema, Wanchang Zhang, Saddam Hussain, Azeem Khan, Muhammad Bilal, Arfan Arshad, Sikandar Ali and Muhammad Awais Zaman
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Muhammad Salam: Department of Irrigation and Drainage, University of Agriculture Faisalabad, Pakistan
Muhammad Jehanzeb Masud Cheema: Faculty of Agricultural Engineering and Technology, PMAS-Arid Agriculture University, Rawalpindi, Pakistan.
Wanchang Zhang: Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100049, China
Saddam Hussain: Applied Agricultural Remote Sensing Centre (AARSC), School of Science and Technology, University of New England, Armidale NSW 2351, Australia
Azeem Khan: Department of Irrigation and Drainage, University of Agriculture Faisalabad, Pakistan
Muhammad Bilal: Department of Soil Science, University of Agriculture, Faisalabad, Pakistan
Arfan Arshad: University of Chinese Academy of Sciences, Beijing 100049, China
Sikandar Ali: Department of Irrigation and Drainage, University of Agriculture Faisalabad, Pakistan
Muhammad Awais Zaman: Department of Civil Engineering, University of Nottingham, England

Big Data In Water Resources Engineering (BDWRE), 2020, vol. 1, issue 1, 10-15

Abstract: Over exploitation of Ground Water (GW) has resulted in lowering of water table in the Indus Basin. While waterlogging, salinity and seawater intrusion has resulted in rising of water table in Indus Basin. The sparse piezometer network cannot provide sufficient data to map groundwater changes spatially. To estimate groundwater change in this region, data from Gravity Recovery and Climate Experiment (GRACE) satellite was used. GRACE measures (Total Water Storage) TWS and used to estimate groundwater storage change. Net change in storage of groundwater was estimated from the change in TWS by including the additional components such as Soil Moisture (SM), Surface water storage (Qs) and snowpack equivalent water (SWE). For the estimation of these components Global Land Data Assimilation system (GLDAS) Land Surface Models (LSMs) was used. Both GRACE and GLDAS produce results for the Indus Basin for the period of April 2010 to January 2017. The monitoring well water-level records from the Scarp Monitoring Organization (SMO) and the Punjab Irrigation and Drainage Authority (PIDA) from April 2009 to December 2016 were used. The groundwater results from different combinations of GRACE products GFZ (GeoforschungsZentrum Potsdam) CSR (Center for Space Research at University of Texas, Austin) JPL (Jet Propulsion Laboratory) and GLDAS LSMs (CLM, NOAH and VIC) are calibrated (April 2009-2014) and validated (April 2015-April 2016) with in-situ measurements. For yearly scale, their correlation coefficient reaches 0.71 with Nash-Sutcliffe Efficiency (NSE) 0.82. It was estimated that net loss in groundwater storage is at mean rate of 85.01 mm per year and 118,668.16 Km3 in the 7 year of study period (April 2010-Jan 2017). GRACE TWS data were also able to pick up the signals from the large-scale flooding events observed in 2010 and 2014. These flooding events played a significant role in the replenishment of the groundwater system in the Indus Basin. Our study indicates that the GRACE based estimation of groundwater storage changes is skillful enough to provide monthly updates on the trend of the groundwater storage changes for resource managers and policy makers of Indus Basin.

Keywords: GRACE; GLDAS; Indus Basin; groundwater. (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:zib:zbdwre:v:1:y:2020:i:1:p:10-15

DOI: 10.26480/bdwre.01.2020.10.15

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