DROUGHT ASSESSMENT USING EDI AND RAINFALL VARIABILITY WITH GIS TOOLS

Abstract

Droughts are undesirable like any other hazards and natural calamities it is a hurdle in agricultural management. Drought is a multidisciplinary concept having furious impacts on areas under threat majorly impacting ecological, agricultural, and socio-economic spheres. Marathwada, a region in the state of Maharashtra, India is a region comprising eight districts namely Aurangabad, Beed, Hingoli, Jalna, Latur, Nanded, Osmanabad and Parbhani. This region has been drought-prone from quite a time and serves as the paramount area for the study. It is essential to assess and monitor the characteristics of droughts to efficiently cope up with its occurrence and neutralize any harsh effects. The research work focuses on study and prediction of drought in the Marathwada region using GIS and remote sensing techniques (from 1980 to 2018). Marathwada region is a drought prone area that faces frequent drought events. The consequences of the events are drastic. Transportation of water to one of the districts of the Marathwada region ‘Latur’ through Jal Dut express trail indicates how largely the drought events affect the region. Marathwada region of Maharashtra state does not have well established agricultural irrigation system across its entire area. Marathwada region total gross irrigated area was 9459 ha and total net irrigated area was 7540 ha in 1999-2000. Area under well irrigation was 5982 ha in 1999-2000 well irrigated area has increased due to recent development but is not enough.The region contributes to nearly one-third of the total agricultural output of the Mharashtra state. The region is known for its sugarcane crop. A crop that demands high volume of water for better results but due to anthropogenic activities like extraction of ground water done by humans leading to its depletion at the rate of 4cm/year, which results into the increase in extremity of natural drought events. So there was a need of accurate monitoring and gathering information of spatio-temporal distribution of drought using space-based technology like remote sensing in combination with AI which holds immense potential in extracting the pattern of drought and enabling hands-on measures for effective drought management.