AGRICULTURAL DROUGHT ASSESSMENT BASED ON RAINFALL AND REMOTE SENSING DATA IN UPPER BENGAWAN SOLO WATERSHED
Mochamad Yusuf, Prof. Dr. Sudibyakto, M.S.
2014 | Tesis | S2 Geo-Informasi untuk Manajemen Bencana-
This include in Bengaw Agricultural drought tend to occur in some part of Indonesia during dry period. Eventhough Indonesia is a humid tropical country, drought still occur in several watershed. an Solo Watershed that comprise several municipalities from Central Java to East Java Province. Since meteorological-based drought assessment in form of meteorological indices is lack of spatial detail, remote sensing based drought index is proposed to represent agricultural drought. To apply hydro-meteorological and remote sensing based indices, the application of Standard Precipitation Index (SPI) and Vegetation Temperature Condition Index (VTCI) are used. In order to know the reliability of both indices the result of both indices are overlayed to know how detail both indices in representing agricultural drought. Lastly VTCI is compared to maize productivity in order to know how reliable the index in representing drought impact on maize productivity during dry period. Drought assessment is done for July – August as the months are considered as dry period The result of drought assessment based on SPI and VTCI show different result. Based on SPI the most severe drought is on August 2011 and September 2012, while based on VTCI the most severe drought is on September 2011 and July 2012. Moreover, the overlay of both indices show that VTCI give more detail pixels separationon normal and drought condition than SPI since SPI generally only indicate near normal condition during all period. VTCI is also preferably chosen by agricultural department in the study area since gives better detail on their municipality. Vulnerability model built to know drought impact on maize productivity show that VTCI and maize productivity is best correlated in two order polynomial. Furthermore, the average VTCI of July to September 2012 is best correlated with agricultural productivity fluctuation.
Kata Kunci : Drought, Remote Sensing, SPI, VTCI, agricultural productivity
