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• A new multi-sensor remote sensing based index is developed for drought monitoring. • The new drought index compares favorably with other commonly used drought indices. • The new drought index has a good performance for drought monitoring across different climate regions. • The performance of the new drought index is insensitive to environmental factors. Remote sensing data are frequently incorporated into drought indices used widely by research and management communities to assess and diagnose current and historic drought events. The integrated drought indices combine multiple indicators and reflect drought conditions from a range of perspectives (i.e., hydrological, agricultural, meteorological). However, the success of most remote sensing based drought indices is constrained by geographic regions since their performance strongly depends on environmental factors such as land cover type, temperature, and soil moisture. To address this limitation, we propose a framework for a new integrated drought index that performs well across diverse climate regions. Our framework uses a geographically weighted regression model and principal component analysis to composite a range of vegetation and meteorological indices derived from multiple remote sensing platforms and in-situ drought indices developed from meteorological station data. Our new index, which we call the station-enabled Geographically Independent Integrated Drought Index (GIIDI_station), compared favorably with other common drought indices such as Microwave Integrated Drought Index (MIDI), Optimized Meteorological Drought Index (OMDI), Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI), and Vegetation Condition Index (VCI). Using Pearson correlation analyses between remote sensing and in-situ drought indices during the growing season (April to October) from 2002 to 2011, we show that GIIDI_station had the best correlations with in-situ drought indices. Across the entire study region of the continental United States, the performance of GIIDI_station was not affected by common environmental factors such as precipitation, temperature, land cover and soil conditions. Taken together, our results suggest that GIIDI_station has considerable potential to improve our ability of monitoring drought at regional scales, provided local meteorological station data are available. [ABSTRACT FROM AUTHOR]

Drought is a complex and poorly understood natural hazard in complex terrain and plains lie in foothills of Hindukush-Himalaya-Karakoram region of Central and South Asia. Few research studied climate change scenarios in the transboundary Chitral Kabul River Basin (CKRB) despite its vulnerability to global warming and importance as a region inhabited with more than 10 million people where no treaty on use of water exists between Afghanistan and Pakistan. This study examines the meteorological and agricultural drought between 2000 and 2018 and their future trends from 2020 to 2030 in the CKRB. To study meteorological and agricultural drought comprehensively, various single drought indices such as Precipitation Condition Index (PCI), Temperature Condition Index (TCI), Soil Moisture Condition Index (SMCI) and Vegetation Condition Index (VCI), and combined drought indices such as Scaled Drought Condition Index (SDCI) and Microwave Integrated Drought Index (MIDI) were utilized. As non-microwave data were used in MIDI, this index was given a new name as Non-Microwave Integrated Drought Index (NMIDI). Our research has found that 2000 was the driest year in the monsoon season followed by 2004 that experienced both meteorological and agricultural drought between 2000 and 2018. Results also indicate that though there exists spatial variation in the agricultural and meteorological drought, but temporally there has been a decreasing trend observed from 2000 to 2018 for both types of droughts. This trend is projected to continue in the future drought projections between 2020 and 2030. The overall study results indicate that drought can be properly assessed by integration of different data sources and therefore management plans can be developed to address the risk and signing new treaties. [ABSTRACT FROM AUTHOR]