Modelling Groundwater Hydraulics to Design a Groundwater Level Monitoring Network for Sustainable Management of Fresh Groundwater Lens in Lower Indus Basin, Pakistan
| Autor: | Carlos A. Oroza, Salman Sarwar, A. L. Qureshi, Zulfiqar Ali Rahimoon, Waqas Ahmed, Muhammad Arfan, Jehangir F Punthakey |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
010504 meteorology & atmospheric sciences
Hydraulics principal component analysis 0207 environmental engineering 02 engineering and technology Structural basin Residual 01 natural sciences lcsh:Technology law.invention groundwater monitoring lcsh:Chemistry sustainable water use law General Materials Science freshwater lens 020701 environmental engineering Instrumentation lcsh:QH301-705.5 0105 earth and related environmental sciences Fluid Flow and Transfer Processes Hydrology Hydrogeology lcsh:T Process Chemistry and Technology General Engineering Sampling (statistics) lcsh:QC1-999 interpolation Computer Science Applications Water level lcsh:Biology (General) lcsh:QD1-999 lcsh:TA1-2040 hexagonal pattern of sampling Principal component analysis Environmental science flow simulation lcsh:Engineering (General). Civil engineering (General) Groundwater lcsh:Physics |
| Zdroj: | Applied Sciences Volume 10 Issue 15 Applied Sciences, Vol 10, Iss 5200, p 5200 (2020) |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app10155200 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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