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Title

A FRAMEWORK TO ESTIMATION OF AQUIFER SUBSIDENCE POTENTIAL USING GENETIC ALGORITHM

Pages

 Start Page 174 | End Page 185

Abstract

 Land subsidence is often triggered by over abstraction of groundwater due to increased agriculture, industry and domestic demands. This problem is investigated in SHABESTAR PLAIN formulating a framework to estimate SUBSIDENCE POTENTIALs and the outcome is compared with measured values with the lowest subsidence threshold value of 30 cm. The research put together seven hydrogeological and geological factors affecting land subsidence, which comprised groundwater level decline, AQUIFER media, recharge, groundwater withdrawal, land use, AQUIFER thickness, and distance to faults. The resulting maps for vulnerability to subsidence were then validated with results from satellite images. Although the primary results were also acceptable, the GENETIC ALGORITHM (GA) was used to optimize weights and to improve the correlation between calculated indices and their corresponding measured subsidence values. Results confirmed the improvement and further showed that the southern and southeastern areas in SHABESTAR PLAIN have the most SUBSIDENCE POTENTIALs. As such management plans are essential to meet the local demands and yet to protect the land against subsidence and other adverse impacts.

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