Development of hydro-meteorological drought index under climate change – Semi-arid river basin of Peninsular India

• Published in: Journal of hydrology (Amsterdam) Vol. 594; p. 125973
• Main Authors: Rehana, S., Sireesha Naidu, G.
• Format: Journal Article
• Language: English
• Published: Elsevier B.V 01.03.2021
• Subjects: Climate change; Evapotranspiration; Hydrological modelling; Hydrometeorological drought; SPEI; SRI; Hydrometeorological drought; Hydrological modelling; Climate change; SRI; Evapotranspiration; SPEI
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2021.125973

•Catchment scale hydrometeorological drought index to account for both meteorological and hydrological variability.•Inclusion of hydrological induced AET including the effect of P, PET and R.•Statistical downscaling model to relate climate and hydrological variables using machine learning algorithm.•Assessment of hydrometeorological drought impacts over a semi-arid river basin of Peninsular India. Univariate meteorological drought indices are inadequate to represent the complexity of hydrological conditions under the intensification of hydrological cycle due to climate change at catchment scale. In this study, Standardised Precipitation Actual Evapotranspiration Index (SPAEI) was proposed, which can combine both meteorological and hydrological drought characteristics at catchment scale. The proposed new drought index considers the hydrologically calibrated AET to account for the water use in addition to meteorological effect. The proposed hydrometeorological drought index was potential in identifying meteorological and hydrological drought events accounting for the time-lag effects and comparable with Global Land Evaporation Amsterdam Model (GLEAM) remote sensing AET data-based drought index. The PET based drought index of SPEI, which is based on energy demand, has shown intensified drought characteristics compared to SPAEI, which is based on both energy demand and available moisture supply and can be a promising variable in the drought estimation. The climate change projections of precipitation and temperatures downscaled using statistical downscaling model based on K-means clustering, Classification and Regression Trees and Support Vector Regression were used using three General Circulation Model outputs. Intensified drought characteristics under climate change has been predicted over Krishna River basin, India, in terms of increase of drought areal extent of about 25%-31%, with increase of drought frequency as 5 years per 20 years and durations as 4–5 months based on the proposed hydrometeorological drought index of SPAEI.