Faculty Publications
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Item Assessment of agricultural drought by remote sensing technique(SPIE spie@spie.org, 2018) Pathak, A.A.; Dodamani, B.M.Drought is commonly occurring natural hazard. It has vicious impact on agricultural production as well as on socioeconomic status of an area. Meteorological drought will induce with the deficit of rainfall and leads to agricultural drought as it prolongs. Rainfall is crucial parameter to assess meteorological drought and NDVI based indices can capture agricultural drought satisfactorily. The present study aims to assess meteorological and agricultural drought in the Ghataprabha river basin using Standardized Precipitation Index (SPI) and Vegetation Condition Index (VCI). Monitoring of SPI and VCI will benefits to mitigate drought impacts with the proper water resources managements. Ghataprabha river basin is the sub basin of river Krishna, in India and is agriculturally dominated. Major portion of the basin is semiarid and rainfall is the major sources of water for agriculture. Average annual rainfall of the basin varies from 600 mm to 2000 mm. Gridded rainfall data was procured from the Indian Meteorological Department for the period of forty three years (1970-2013) and considered same as input for SPI. To calculate SPI with multiple time scale, two parameter gamma distribution was implemented. MODIS NDVI products from 2000-2013 was considered for calculation of VCI. Significant number of meteorological drought episodes were observed during the study period while severe agricultural drought was observed during 2001-2003 and in 2012. SPI and VCI were compared to quantify variation of VCI with respect to SPI. Good agreement between SPI and VCI was observed during drought and non-drought periods. Results indicates that eastern part of the basin was more prone to severe droughts as compare to other part of the basin. This study assistances to formulate drought mitigation strategies and to establish effective water resources policies in the study region. © SPIE. Downloading of the abstract is permitted for personal use only.Item Application of remotely sensed NDVI and soil moisture to monitor long-term agricultural drought(SPIE spie@spie.org, 2019) Pathak, A.A.; Dodamani, B.M.The present study aims to assess agricultural drought using remote sensing based NDVI and soil moisture products in a drought prone river basin of India. The study is conducted in the Ghataprabha river basin which is a sub basin of river Krishna, in India and is agriculturally dominated. Major portion of the basin is semiarid and rainfall is the major sources of water for agriculture. Gridded soil moisture data from Modern-Era Retrospective analysis for Research and Applications (MERRA) from 1980 to 2015 is considered to derive Standardized Soil moisture Index (SSI) at different time scales. The Vegetation Condition Index (VCI) was calculated from MODIS NDVI products from 2000-2013. The results of VCI and SSI indicated significant number of drought episodes during the study period while severe agricultural drought was observed during 2001-2003. A Good agreement between SSI and VCI was observed during drought year. © 2019 SPIE.Item Connection between Meteorological and Groundwater Drought with Copula-Based Bivariate Frequency Analysis(American Society of Civil Engineers (ASCE), 2021) Pathak, A.A.; Dodamani, B.M.Groundwater is a major resource of freshwater that provides additional resilience to agricultural drought during rainfall deficit and also helps in understanding the nature of the hydrological drought risk of an area. This study investigated the response of groundwater drought to meteorological drought and local aquifer properties by considering monthly groundwater levels of a tropical river basin in India. Further, bivariate frequency analysis was carried out for groundwater drought to develop severity-duration-frequency curves by considering the copula function. Long-term monthly groundwater levels were procured, and cluster analysis was performed on groundwater observations to classify the wells. Standardized Groundwater level Index (SGI) was used to evaluate groundwater drought for each cluster, and the same was compared with the meteorological drought of different association periods. The cluster analysis conveyed that wells can be grouped into three clusters optimally. Based on the comparison of groundwater drought with meteorological drought, it was inferred that SGI is well harmonized with the Standardized Precipitation Index (SPI) and Standardized Precipitation Evapotranspiration Index (SPEI) in humid and semiarid regions, respectively. Analysis of hydraulic diffusivity with the autocorrelation structure of SGI emphasizes the crucial role of aquifer characteristics in local groundwater droughts. The results of joint and conditional return periods obtained from bivariate frequency analysis conveyed that high severity and high-duration droughts were more frequent in the well of Clusters 1 as well as Cluster 3 and comparatively less for the well of Cluster 2. The outcome of the study will be helpful to design proactive drought mitigation and preparedness strategies by considering conjunctive use of surface and groundwater. It also provides a framework to evaluate groundwater drought risk in other parts of the world. © 2021 American Society of Civil Engineers.