| Abstract: | Short-term drought forecasting is helpful for establishing drought mitigation plans and
for managing risks that often ensue in water resource systems. Additionally, hydrologic modeling
using high-resolution spatial and temporal data is used to simulate the land surface water and
energy fluxes, including runoff, baseflow, and soil moisture, which are useful for drought forecasting.
In this study, the Soil and Water Assessment Tool (SWAT) and Variable Infiltration Capacity (VIC)
models are used for short-term drought forecasting in the contiguous United States (CONUS),
as many areas in this region are frequently affected by varying drought intensities. Weekly-to-seasonal
meteorological inputs are provided by the Climate Prediction Center (CPC) for the retrospective
period (January 2012 to July 2017) and Climate Forecasting System version 2 (CFS v2) for the
forecasting period (August 2017 to April 2018), and these inputs are used to estimate agricultural
and groundwater drought conditions. For drought assessment, three drought indices, namely,
the Standardized Soil Moisture index (SSI), the Multivariate Standardized Drought Index (MSDI),
and the Standardized Baseflow index (SBI), were analyzed. The accuracy of the forecasting results
was verified using several a performance measure (Drought area agreement (%); DA). Generally,
eight weeks of lead time forecasting showed good drought predictability from both the SWAT and
VIC models for the MSDI simulations (62% for SWAT and 64% for VIC for all drought categories).
However, the DA values for eight weeks lead time forecasting for SSI were 23% (SWAT) and 10%
(VIC) and 7% (SWAT) and 7% (VIC) for the SBI, respectively. In addition, the accuracies of drought
predictions remarkably decreased after eight weeks, and the average DA values were 36% for SWAT
and 38% for VIC due to an increase in the uncertainties associated with meteorological variables in
CFS v2 products. For example, there are increases in the total number of grids where the absolute
values of monthly differences between CFSv2 and CPC observations exceed 20 mm and 1 C during
the forecasting period. Additionally, drought forecasting using only one variable (i.e., SSI and SBI)
showed low prediction performances even for the first eight weeks. The results of this study provide
insights into drought forecasting methods and provide a better understanding to plan for timely
water resource management decisions. |