Estimation of Regional Drought Index Considering the Climate and Land Surface Changes over a Large River Basin in India

The regional hydrologic change is a central part of the global climate change. To better understand the hydrological cycle intensification in the future, we need to accurately estimate major components of hydrological budget at regional scales. At basin scale, Evapotranspiration (ET) is the largest water flux next to rainfall, which is a prominent hydrological component and represents the atmospheric water demand. Essentially, ET is a more involved process influenced by the regional climate, land use changes due to human interventions, water withdrawals from the rivers for agricultural practices etc. It is essential to distinguish and study the impact of each of these components by individual, particularly for a regional water resources system. Further, the changes in ET will have an immediate effect on runoff, frequency and intensity of floods and droughts, soil moisture and crop production of a drainage basin. Among the extreme events, droughts are the most widespread and slowly developing hydro-meteorological events remain for a long duration affecting natural resources, environment and the people. It is very difficult to objectively quantify their characteristics in terms of intensity, magnitude, duration, and spatial extent. For this reason, much effort has been devoted in developing techniques for drought analysis and monitoring. Few studies included reference evapotranspiration to account for climatic water availability in drought characterization such as Standardized Precipitation–Evapotranspiration Index (SPEI). However, a drought prediction model should consider the actual evapotranspiration to include the physical water availability and land surface changes of a region. The present study aims at assessing the observed variability of the Standardized Precipitation–Actual Evapotranspiration Index (SPAEI) at regional scale. The Budyko curve is used to estimate the actual evapotranspiration as a function of the aridity index. The SPAEI is based on the probability distribution of the difference between precipitation and Actual Evapotranspiration (AET), which represents the measure of the water surplus or deficit for a particular month. The gridded daily precipitation data from India Meteorological Department (IMD) available for the period of 1901 to 2015 at 0.25^o X 0.25^o resolution is used in the study as precipitation observational dataset. The gridded daily average temperature at a resolution of 1^o X 1^o resolution is used in the study as temperature observational data sets. The regional drought prediction model developed in the study is applied on Krishna River basin in India. The monthly PET is estimated with the Thornthwaite equation using mean temperatures over the entire Krishna river basin. The AET is estimated at 12 month scale using Budyko equation, which combines the precipitation, AET and PET estimated from Thornthwaite equation. The performance of SPAEI is evaluated using historical droughts and projected variability under climate change. The SPAEI at annual scale is compared with SPEI and performance of each of the indices was discussed with the historical drought events. The SPAEI was used to estimate the effect of climate change and land surface change on drought variability using the projected changes in precipitation and temperatures. Due to increasing effect of evapotranspiration and changes in precipitation patterns the possible drought regions are analyzed under climate change.