Role of DRINET in Drought Research

One goal of our project is to develop objective standards for analyzing hydrologic records and specifying drought status based on multiple variables. We achieve this by constructing a joint deficit indicator (JDI) that can combine information from multiple sources, and would therefore enable better estimation of drought return periods, persistence of droughts at a given severity, future risk assessment, and improved identification of possible portents of droughts. We employ copulas are employed in this study to facilitate the identification and construction of dependence structure of droughts, and to improve our understanding of the statistical nature of droughts and our ability to characterize them. We propose a new drought indicator that enables us to compute a probability-based overall water deficit index from multiple drought-related quantities (or indices).

The Joint Drought Deficit Index (JDI) Current drought information is based on indices that do not capture the joint behaviors of hydrologic variables. We start from the standardized index (SI) introduced by McKee et al. (1993) for statistical analyses of hydrologic variables. The standardized index is an expression of cumulative probability measure of for any hydrologic variable and drought severity can be compared across variables and locations on the same scale.

The procedure for constructing the JDI requires fairly advanced understanding of probability theory, and interested readers are referred to Kao (2008) for details. There are two important innovations in the development of JDI when compared to existing indices:

  • The seasonality in hydrologic variables is explicitly accounted for by modifying the standardized index.
  • Based on past observations, the dependence between droughts of various durations (from one to twelve months) is extracted by state-of-the-art techniques

An important feature of JDI is that the overall deficit status is based on the dependence structure of deficit indices with various temporal windows. While a direct comparison is not possible, it is possible to interpret the JDI in a similar manner as the drought status from the US Drought Monitor. Examples of correspondence between the JDI and categorization by the US Drought Monitor are shown below for precipitation stations in Indiana.

A regional illustration of the required precipitation for July 1988 to achieve normality based on the observations made from August 1987 to June 1988 and the corresponding probability of exceedance is shown in the figure. As indicated in the figure, a majority of Indiana would have needed over 150-mm of rain in July 1988. Based on historical July precipitation, this information can be further transformed into exceedance probability, and it suggests that the probability for recovering to normal conditions is small (less than 0.1 for most of the state). Such drought maps can be an effective way of relaying drought information, as most of the current indices are not amenable to statistical interpretation and are artificially converted into drought severity levels.

Not only is the JDI able to reflect both emerging and prolonged droughts in a timely manner, it also allows a month-by-month drought assessment such that the required amount of precipitation for achieving normal conditions in future can be computed. The use of JDI is generalizable to other hydrologic variables and facilitates the construction of inter-variable drought indices that will preserve the dependence properties among different hydrologic variables. This is a topic of future research.