Drought characterization under climate change for sustainable crop planning in marathwada region

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Date
2018-04-24
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Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani
Abstract
Drought is caused due to sudden and significant deficiency in precipitation, resulting in acute water scarcity, remarkable shortage of soil moisture and reduced crop yields. Droughts cannot be avoided, but they can be predicted and monitored to alleviate their adverse impacts. Droughts are classified into meteorological, agricultural, hydrological, and socioeconomic droughts. While meteorological drought occurs mainly due to deficient precipitation, agricultural drought is developed due to the impact of meteorological and hydrological droughts.Severity, duration and spatial extent of agricultural droughts vary from place to place and time to time depending on varios other factors such as late arrival and/or early retreat of the monsoon, duration of dry spell and lack of irrigation water. A comprehensive analysis of the spatial and temporal extension of droughts can help to develop drought-monitoring signals based on relevant drought indices. Rainfall is one of the important climatic variables that largely determine the occurrence of drought and also influences the growth and development of vegetation reflecting in NDVI. In the present study an attempt has been made to analyse rainfall pattern of Marathwada region comprising of 46 stations on annual and monthly basis using historical meteorological data for the years 1981 to 2016. The trend analysis of rainfall and evaporation of study area was performed on annual and monthly basis using Mann Kendall Test and Sen’s slope estimator. The meteorological drought indices namely SPI, NMI, Deciles, ND and PN were determined by analysing daily rainfall data. The probability analysis of SPI as drought indicator was carried out by using different probability distribution functions to identify the best fit probability distribution. The drought frequency and return period were estimated using Weibull’s method.Remote sensing based drought indices can be used for classification of agricultural drought since they give better synoptic view for understanding drought affected area in the study region.In order to evaluate overall vegetation condition in the study area, aagricultural drought assessment was carried out by using remote sensing based drought indices such as NDVI, VCI, TCI and VHI.The spatiotemporal variation of agricultural drought indices and drought severity were detected. The drought severity maps were developed by using IDW interpolation method in GIS for better synoptic view of drought condition in Marathwada. Results showed a large scale temporal and spatial variation of annual rainfall between 18 to 33% during June - October in Marathwada. Trend analysis of rainfall at most of the stations in Marathwada showed a mixed trend pattern except few wherein Kannad station showed significantly increasing trend of annual rainfall whereas Khultabad, Nanded, Biloli and Degloor showed decreasing trend. Drought classification based on various meteorological drought indices namely; SPI, NMI, Deciles, ND and PN indicated that majority of the stations in Marathwada suffered from extreme to severe drought conditions for 2 to 3 times during 36 years of study period. The mild drought and wet drought were more frequent among all the locations of Marathwada. Based on probability analysis the Normal distribution was found to be the best fitted for SPI followed by Gumbel distribution in the study area. The drought frequency analysis based on SPI indicated that frequency of occurrence of moderate and severe drought was more than the extreme drought; however the frequency of occurrence of mild drought was the highest. The results obtained remote sensing based indices NDVI, VCI, TCI and VHI show close agreement with the ground based precipitation indices. The drought severity maps indicate that Marathwada region can be classified into extreme, severe, moderate and mild drought affected area. Hence, agricultural drought assessment using satellite data are found to be of great importance in order to assess the past and the current agricultural drought conditions and generate baseline information. This will help to monitor real time situation in future for different adaptation options for large geographical area of Marathwada region with repetitive time scale coverage.
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