2.4 Model based drought indices
The soil-moisture and runoff data derived from the VIC model were used to develop drought
indices hereafter referred as the model based indices. The soil moisture and runoff is the
indicator of the water availability for various purposes such as crop-production and the
municipal water supply. As mentioned previously VIC model captures the total soil-moisture
persistence and simulates the streamflow well, thus the VIC model simulated soil moisture and
runoff data can be used as a surrogate to develop a drought indices. Furthermore in lieu of the
actual values use of the soil moisture and runoff percentile, allows the comparison of drought
severity across different spatial domains (Andreadis et. al 2005).
2.4.1 Standardized soil moisture and runoff index:
Daily soil-moisture was averaged and the runoff was summed to produce monthly values for the
period 1950-2006. These historical monthly values of soil-moisture and runoff for each grid
were sorted for each month and empirical climatological distributions were developed using the
Weibull plotting positions. The monthly soil-moisture and runoff values were then assigned a
percentile depending on where they lie in the empirical distribution for soil-moisture and runoff
values – i.e., their climatological non-exceedence probabilities. This non-exceedance probability
is then transformed to the standard normal distribution in the same way as in Mackee et al. 1993,
Wood and Shukla 2007. The transformation rescales the percentile values between -4 to +4,
which are otherwise from 0 to 1. The probabilistic indices thus obtained is referred as the
Standardized Soil moisture Index (SSMI) and the Standardized Runoff Index (SRI). While
calculating the SSMI though soil moisture values were averaged over the different time period
unlike the summation done for SRI and SPI. The median and mean of the distribution lie at zero
thus negative values is indicator of the dry conditions and the positive values are the indicator of
the wet conditions. The method of calculating the SSMI and SRI is outlined in the Fig. 1.1.
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2.5 Ensemble Soil Moisture and Runoff Deficit Recovery Day Prediction:
Model was also implemented in the prediction mode to assess the soil moisture and runoff
deficiency in the future and estimate the days to recovery from the current water deficit.
Prediction of the severity and duration of the deficit is of particular importance for the Water
Management decisions to mitigate the impact of the ongoing drought and prepare for the future
conditions. For a given drought severity and the precipitation the recovery time may also vary for
the different seasons.
The VIC model was implemented at 1/16th deg spatial resolution over the domain of the
Washington State. Model was run in the real-time mode using the observed forcings data, with a
spin-up period of two months. The VIC model simulates the estimated of daily soil moisture and
runoff for each grid cell. The state files which is mainly comprised of the current day soil
moisture and Snow Water Equivalent over the entire domain was saved. This state file which is
the representation of the current hydrological conditions was now used to initialize the model run
in the forecasting mode for the next 5-6 months using the ensembles of the meteorological
variables based on the 30 year climate period (…..). The model predicted soil moisture was then
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spatially averaged over the each Water Resources Inventory Agency. This average soil moisture
value was used to estimate the recovery day, which is the day when soil moisture becomes equal
to the long term mean soil moisture. Model therefore estimates the ensemble of recovery days
given the current drought severity and the expected meteorological conditions. The ensembles of
the recovery days were then used to construct a cumulative probability distribution function
(CDF) curve. Depending on the current drought conditions the CDF of the recovery day can be
positively or negatively skewed.
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