journal article·2020-07-28Open access

Modelling Groundwater Hydraulics to Design a Groundwater Level Monitoring Network for Sustainable Management of Fresh Groundwater Lens in Lower Indus Basin, Pakistan

Waqas Ahmed, Zulfiqar Ali Rahimoon, Carlos Anthony Oroza, Salman Sarwar, Abdul Latif Qureshi, Jehangir Framroze Punthakey, Muhammad Arfan

Applied Sciences· Volume 10· Issue 15

Abstract

The over-extraction of groundwater from thin fresh groundwater lenses is a threat to the livelihood of farmers in the Lower Indus Basin (LIB). It is essential to monitor and regulate this pumping to sustain fresh groundwater lenses. In this study, we applied a modelling approach in combination with geostatistical analysis to identify the critical locations to monitor the groundwater levels for sustaining fresh groundwater in the LIB. Our approach included four steps: (i) simulating temporal heads using a calibrated hydrogeological model; (ii) sampling monitoring locations using a hexagonal pattern of sampling; (iii) applying principal component analysis (PCA) of the temporal head observations, and selecting high scoring locations from the PCA; and (iv) minimizing the observation points to represent the water level contours. The calibrated model was able to replicate the hydro-dynamic behavior of the study area, with a root mean square of 0.95 and an absolute residual mean of 0.74 m. The hexagonal pattern of spatial sampling resulted in a 195 point network, but PCA reduced this network to 135 points and contour classification reduced it even further to 59 points. The 195, 135, and 59 point networks represented the water levels with average standard errors of 0.098, 0.318, and 0.610 m, respectively. Long-term simulations with increased pumping showed that the water levels would best be assessed by 195 monitoring points, although 135 and 59 points would represent the depleting area but would not capture the water logging area.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Hydrology and Watershed Management Studies · Hydrological Forecasting Using AI · Hydrology and Drought Analysis

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

US Pakistan Center for Advanced Studies in Water, Mehran University of Engineering and Technology, Jamshoro 76020, Pakistan

Department of Civil and Environmental Engineering, University of Utah, Salt Lake City, UT 84102, USA

Ecoseal Developments Pty Ltd., Roseville, NSW 2069, Australia

Funding

Higher Education Commission, Pakistan · Australian Centre for International Agricultural Research

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