Monitoring and Measuring Surface Water in Semi-Arid Environment Using Satellite Data: A Case Study of Karachi Pages 484-491

Monitoring and Measuring Surface Water in Semi-Arid Environment Using Satellite Data: A Case Study of Karachi
Pages 484-491
Lubna Ghazal and Syed Jamil H. Kazmi

DOI: http://dx.doi.org/10.6000/1927-5129.2014.10.64

Published: 11 November 2014

Abstract: Water is a dynamic and precious resource for all living creatures. Its significance is imperative for different sectors of economy at global and regional level. Sustainable use of land resources such as water is vital to carryout fundamental chores and has become an important area of investigation in developing and developed countries. Pakistan is an under developing country with agro-based economy and it is among the top of those countries which are facing acute water scarcity. World Bank has projected that by 2025 severe food shortage could be caused in Pakistan due to water scarcity.

Karachi is the most populous city of Pakistan with high consumption of water and food but semi arid climate conditions and drastic variability in rainfall pattern make it prone to desertification and drought. In Karachi Hydrological drought is closely associated with agricultural drought. Hence, monitoring, quantification and mapping of water is vital for better planning.

This Study is aimed at monitoring spatio-temporal variation of surface water in Karachi using Geoinformatic techniques. For this purpose four satellite images of Landsat -7 ETM + were used. Through NDWI spatial distribution of water and its seasonal variation was observed and maps of water availability in each Union council of Karachi using software ArcMap 10.1 were also developed for the quick and better interpration. Use of modern state of the art Remote sensing data coupled with GIS for the monitoring of land resources has proved very significant for evaluating the potential of resources in different administrative units for planning and decision making.

Keywords: Water Scarcity, NDWI, Hydrological Drought, Spatio-Temporal Data, Quantification, Landsat-7 ETM+