Shraddhanand Shukla Andrew W. Wood Drought Monitoring with Hydrologic Models an alternative to standard indices? Shraddhanand Shukla Andrew W. Wood

Drought: The Creeping Disaster Drought in the United-States result in an estimated avg annual damage of $6-8 billion

Monitoring Drought Severity Lack of Precipitation Antecedent Moisture Averaged over different periods Hydrologic Condition Socio-economic Status Precipitation Temperature Snowpack Streamflow Reservoir Lack of observed data Weighting scheme Palmer Drought Indices (PDI) Precipitation Temperature Available Water Holding Capacity Simplified Water Balance model Precipitation Temperature Cold season process Complex water and energy balance scheme No info of socio-economic conditions Intensity Duration Standardized Precipitation Index (SPI) Surface Water Supply Index (SWSI) Hydrologic Model-Based Indices Severity

U.S. Drought Monitor

Short-Term Drought Indicator blend

Long-Term Drought Indicator Blend

CPC Soil Moisture Model (Huang et al. 1996) Where: W(t) = the soil Moisture at any time t P(t) = the mean areal precip over any area A E(t) = the mean areal evap over any R(t) = the net streamflow divergence from area A G(t) = the net groundwater loss from area A

Objectives To analyze historical drought events in Washington state using model derived Soil moisture and runoff To compare model-based indices with other independent drought indicators To reconstruct the historical drought events at monthly time-scale and evaluate the model performance in monitoring drought

Characteristics of a Drought Index Adaptable to the appropriate time scale Quantitative measure of the large spatial and temporal scale drought conditions Applicable to different types of drought Can be used for the retrospective analysis

Hydrologic Model-Based Indices Soil moisture and runoff percentiles (Scheffield 2004, 2007; Andreadis 2005, 2006) Beta Distribution Empirical Distribution (Weibull Plotting Position) (84 years of data) Standardized Runoff Index (Wood and Shukla, 2007) Fitted Distribution (ln2,3; gamma, GEV) Transformation of Cum. Prob. to a Standard Normal Deviate

Soil Moisture Percentile (Justin 2004)

Severity-Area-Duration Curve (Andreadis, 2005)

Standardized Runoff Index (Wood and Shukla, 2007)

Standardized Runoff Index (Wood and Shukla, 2007)

Historical Droughts in WA State Meteorological Drought: 1934,1941,1945,1952, 1973,1976, 1996,2001, 2005 Model based indices can identify all the historical drought events

1976-77 Drought Wet winter of 1975-76 and relatively abundant precipitation through the spring and summer of 1976. Drought began in Sep 1976. Persisted through the February 1977. Precipitation less than 75 nearly everywhere and for some areas even less than that. Slight relief to the western Washington in March 1977 but things remained ugly in the Eastern Washington state. Series of storms brought rainfall well above normal in the month of September and October 1977

1976-77 Drought : Simulated Water Balance

1976-77 Drought : SWE and SM Percentiles

1976-77 Drought: SM, SRI, SSI Onset of agricultural and hydrological drought around September 1976 Recovered by October 1977

Drought 1976-77: SM, SRI, SSI

2001 Drought: November and December 2000 were unusually dry Abnormally dry weather in winter. By mid-March all most every corner of the state was in water scarcity. Statewide drought was declared on March 14, 2001 In effect till Dec, 2001. (Source: http://www.ecy.wa.gov)

2001 Drought: Simulated Water Balance plots

2001 Drought SWE and SM Percentiles

Drought 2001: SM,SRI,SSI Onset of drought in winter 2001 Recovered by the end of the year

Drought 2001: SM,SRI,SSI

Summary The VIC model simulated soil moisture and runoff based indices identify the major historical drought events The model is reasonably accurate in monitoring drought onset, duration and spatial extent It is implemented at 1/8-1/16th deg and daily time step thus suitable for the real-time drought monitoring and prediction Hydrologic models should be used as one of the decision tools for monitoring drought and given more weight in the Drought Monitor

Expected Soil Moisture Deficit Recover Period Future Work Expected Soil Moisture Deficit Recover Period Soil Moisture Deficit Normal Soil Moisture Current Soil Moisture Ensembles of Expected Recovery Period

Questions http://www.hydro.washington.edu/forecast/sarp/