A Systematic Review of Meteorological Drought Indices Using Geospatial Techniques.

Drought is a complex natural disaster with significant implications for agriculture, water resources, and socioeconomic development. Accurate and timely assessment of meteorological drought is crucial for effective management and mitigation strategies. This systematic review analyzes and evaluates meteorological drought indices and their associated techniques in drought monitoring and assessment. The review involved an exhaustive search of peer-reviewed literature, conference papers, and technical reports from reputable databases. A robust selection criterion was applied to identify relevant studies on meteorological drought indices, methodologies, and their performance in different regions and climatic conditions. A wide array of meteorological drought indices was identified and classified into three major categories: rainfall-based, temperature-based, and combined indices. The most commonly used rainfall-based indices were the Standardized Precipitation Index (SPI) and the Palmer Drought Severity Index (PDSI), which effectively capture meteorological droughts with varying lead times and durations. Temperature-based indices, such as the Standardized Precipitation Evapotranspiration Index (SPEI) and the Thornthwaite Moisture Index (TMI), provide valuable insights into the impact of temperature on drought conditions. Several studies focused on developing combined indices that integrate precipitation and temperature data to offer a more holistic representation of meteorological droughts. The Composite Drought Index (CDI) and the Joint Drought Index (JDI) were widely used due to their ability to account for multiple climatic variables. The review emphasizes the importance of considering the specific characteristics of the study region and the intended application when selecting an appropriate drought index. It also highlights the need for continuous advancements in drought assessment techniques to address emerging challenges, such as climate change impacts and data sparsity in certain regions.