Informations et ressources scientifiques
sur le développement des zones arides et semi-arides

Titre : Assessment of impacts of agro climatological droughts using remote sensing and geo spatial technologies

Auteur : Kulkarni, Sneha Shrinivas

Université de soutenance : Indian Institute of Technology Bombay

Grade : Doctor of Philosophy (PhD) 2022

Résumé partiel
Drought is one of the highest destructive climate-based hazards, which is generally considered as a long-term absence of rainfall. It affects nearly all climatic zones worldwide and millions of people every year. Concerning food security and society’s need, agro-climatic drought is probably the most important key aspect of the drought. Impacts of droughts are usually the first to occur over agriculture. Land degradation problems are often aggravated by stress due to inadequate or absent vegetation cover over an area. Therefore, agro-climatological drought studies play an essential role in overall drought monitoring. Meteorology-dependent agricultural drought analysis is mostly a point-based study, which fails to explain the overall spatio-temporal impact of drought. To overcome this problem, remote sensing-based analysis is a fast way to monitor and evaluate stress conditions. Therefore, this study is based on geospatial technologies for drought monitoring. The present study is a part of the five-year drought assessment project for one of the most drought prone regions of India, i.e., ‘Marathwada,’ Maharashtra. In the initial stage, we have analysed the changing trends in rainfall, temperature, and other different drought indices (SPI, SPEI, SRI, VCI, SSI, etc.) for the period 1901 to 2018 (or the available). The spatio-temporal analysis highlighted 1971-72, 1985-86, 2015-16 as persistent server drought years in the study area. In the next objective, we worked on developing a combined drought monitoring index for the Marathwada region. In India, operational agricultural drought assessment methods mainly depend on a single input parameter such as precipitation and are based on sparsely located in-situ measurements, limiting monitoring precision. Therefore, as the second objective of this study, we have addressed this need by developing an integrated agro-climatological drought-monitoring approach, i.e., a combined drought indicator for Marathwada (CDI_M). In this objective, satellite and model-based input parameters (i.e., standardized precipitation index (SPI-3), land surface temperature (LST), soil moisture (SM), and normalized difference vegetation index (NDVI)) were analysed at a monthly scale from 2001 to 2018. Two quantitative methods were tested to combine the input parameters for developing the CDI_M. These methods included an expert judgment based weight of each parameter (Method-I) and a principal component analysis (PCA)-based weighting approach (Method-II). Secondary data for major types of crop yields in Marathwada were utilized to assess the CDI_M results for the study period. CDI_M maps depict moderate to extreme drought cases in the historic drought years of 2002, 2009, and 2015–2016. This study found a significant increase in drought intensities (p ≤ 0.05) and drought frequency from 2001 to 2018, especially in the Latur, Jalna, and Parbhani districts. In comparison to Method-I (r ≥ 0.4), PCA-based (Method-II) CDI_M showed a higher correlation (r ≥ 0.60) with crop yields in both harvesting seasons (Kharif and Rabi). In particular, crop yields during the drier years showed a more significant association (r > 0.65) with CDI_M over Marathwada. Hence, the results from the second objective illustrated the effectiveness of CDI_M to monitor agricultural drought in India and provide improved information to support agricultural drought management practices.

Présentation et version intégrale (Shodhganga)