Identifikasi lahan pertanian rawan kekeringan dengan metode sistem informasi geografis

Abstract

Drought is an event where rainfall is very low for long time period. Drought is a common natural phenomenon in Indonesia. It affects a wide variety of events, one of which is crop failure. This study aims to determine the drought prone of an area in Indramayu using GIS methods based on several bio-physic parameters, to determine the distribution and characteristics of drought prone area in Indramayu district, and to see the difference in the distribution of drought prone area by using different or the equal weights of parameter in annual rainfall or monthly rainfall (dry season). The study consists of several phases namely preparation, collection of base maps and create thematic map, satellite imagery interpretation, analysis and making drought-vulnerable, and presentation of research results. The bio-physic parameters used in this study were rainfall, landforms, land cover, drainage, slope, and stream buffers. All parameters are combined in a GIS analysis using different weighting and equal weighting with annual rainfall and dry season rainfall. The most influential parameter will get the highest value of weight and parameters with small influence will be given a low weight value. Modeling bio-physic parameter with different weights to the annual rainfall resulted in two vulnerable classes, less vulnerable 77.24%, and vulnerable 22.76%, while for the dry season rainfall resulted three classes including not vulnerable 0.74%, less vulnerable 85.20%, and vulnerable 14.06%. Maps with the equal weighting parameters for the annual rainfall resulted in four classes including not vulnerable 0.07%, less vulnerable 76.26%, vulnerable 23.56% and very vulnerable 0.11%. For the dry season rainfall also resulted in four classes: not vulnerable 0.47%, less vulnerable 84.12%, and vulnerable 15.28%, and the very vulnerable classes 0.12%. The subdistrict that potentially effected by drought prone area are Trisi subdistrict and Gantar subdistrict.