Drought Climatology Characterization
Characterizing and developing drought climatology continues to be a challenging problem. Also as decision makers seek guidance on water management strategies, there is a need for assessing the performance of drought indices. This requires the adaptation of appropriate drought indices that aid in monitoring droughts and hydrological vulnerability on a regional scale.
Our study aims to assist the process of developing a statewide water shortage and assessment plan (WSP) for the state of Indiana, USA by conducting a focused hydroclimatological assessment of drought variability. Drought climatology was assessed using in-situ observations and regional reanalysis data. A summary of precipitation and evaporation trends, estimated drought variability, worst-case drought scenarios, drought return period, as well as frequency and duration was undertaken, using multiple drought indices and streamflow analysis. Results indicated a regional and local variability in drought susceptibility. The worst-case (200 year return period) prediction showed that Indiana has a 0.5% probability of receiving 45% of normal precipitation over a 12 month drought in any years. Consistent with other studies, the Standard Precipitation Index (SPI) was found to be appropriate for detecting short-term drought conditions over Indiana. This recommendation has now been incorporated in the 2009 Indiana Water Shortage Plan. Our study also highlights the difficulties in identifying past droughts from available climatic data, and our results suggest a persistent, high degree of uncertainty in making drought predictions using future climatic projections.
An example of high resolution land data assimilation system with MODIS land use was able to capture severe drought conditions across the U.S. for August, 2007. The LDAS is configured with 4 km grid space and 1 year spin up from 2001-2002 to stabilize the model. The model has been improved using a photosynthesis scheme (GEM, Niyogi, 2009) for transpiration and water cycle. The results show the GEM/MODIS method is better at estimating drought conditions than the current default version used by the Drought Monitor.