Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring

By B. Narasimhan, Raghavan Srinivasan. 2005

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Response of ecosystem intrinsic water use efficiency and gross primary productivity to rising vapor pressure deficit (2019, background): “…are relevant for drought monitoring and prediction indices that incorporate information about the difference between potential and actual evapotranspiration (Narasimhan and Srinivasan 2005, Otkin et al 2013), which is largely driven by stomatal conductance during dry periods (Novick et al 2016a).”
Drought effects on US maize and soybean production: spatiotemporal patterns and historical changes (2016, methodology): “While soil moisture-based methods of drought quantification exist (e.g. Sheffield et al 2004, Narasimhan and Srinivasan 2005, Hunt et al 2009, Carrao et al 2016), observational soil moisture datasets are sparse both spatially and temporally (Hunt et al 2009), and these methods typically rely on…”
Review and classification of indicators of green water availability and scarcity (2015, background): “Narasimhan and Srinivasan (2005) Crop Moisture Index CMI Abnormal evaporation deficit, defined as the difference between Eact and climatologically expected weekly evaporation.”
Hydrological Drought Class Transition Using SPI and SRI Time Series by Loglinear Regression (2015, background): “Besides, many other drought indices have been developed for different drought categories (Byun and Wilhite 1999; Narasimhan and Srinivasan 2005; Vasiliades et al. 2011).”