Drought modeling – A review

SummaryIn recent years droughts have been occurring frequently, and their impacts are being aggravated by the rise in water demand and the variability in hydro-meteorological variables due to climate change. As a result, drought hydrology has been receiving much attention. A variety of concepts have been applied to modeling droughts, ranging from simplistic approaches to more complex models. It is important to understand different modeling approaches as well as their advantages and limitations. This paper, supplementing the previous paper (Mishra and Singh, 2010) where different concepts of droughts were highlighted, reviews different methodologies used for drought modeling, which include drought forecasting, probability based modeling, spatio-temporal analysis, use of Global Climate Models (GCMs) for drought scenarios, land data assimilation systems for drought modeling, and drought planning. It is found that there have been significant improvements in modeling droughts over the past three decades. Hybrid models, incorporating large scale climate indices, seem to be promising for long lead-time drought forecasting. Further research is needed to understand the spatio-temporal complexity of droughts under climate change due to changes in spatio-temporal variability of precipitation. Applications of copula based models for multivariate drought characterization seem to be promising for better drought characterization. Research on decision support systems should be advanced for issuing warnings, assessing risk, and taking precautionary measures, and the effective ways for the flow of information from decision makers to users need to be developed. Finally, some remarks are made regarding the future outlook for drought research.

► This paper supplements the previous paper (Mishra and Singh, 2010) where different concepts of droughts were highlighted.
► It is observed that there have been significant improvements in modeling droughts over the past three decades.
► Finally, suggestions are made for improving different drought modeling components.