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Keyhan Gavahi, Peyman Abbaszadeh, Hamid Moradkhani, Xiwu Zhan, and Christopher Hain

) techniques with these models has been highly recommended because it improves the accuracy of water and energy balance computations and increases the model’s predictive skills ( Reichle et al. 2014 ; Sawada et al. 2015 ; Seo et al. 2003 ). Earth system DA seeks to exploit real-time observations for more accurate hydrologic forecasts ( Kumar et al. 2014 ; Reichle et al. 2014 ). DA aims at merging current and past observations with a dynamical model, using the model’s prognostic equations to estimate

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Christa D. Peters-Lidard, David M. Mocko, Lu Su, Dennis P. Lettenmaier, Pierre Gentine, and Michael Barlage

surface models that run routinely for monitoring or forecasting has opened up many more possibilities for calculating drought indicators. Because the availability of data and/or model outputs determines which indicators are possible, we broadly classify indicators into traditional and land surface model based, with a third category—remotely sensed—to be discussed in a later section. Traditional drought indicators As noted in the Introduction, dozens of drought indicators are in common use (e.g., Heim

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