Toward a Drought Seasonal Forecast in the Platte River Basin

The goal is to explore the predictability of drought using hydrologic seasonal forecast and implement the foundation of the Water for Food Integrated System-Hydrologic Forecast (WaFIS-HF). The state of Nebraska contributes ~5% of the world's annual corn supply. Nebraska is also the largest user of groundwater for irrigation in the country. Groundwater from the northern portion of the Ogallala aquifer is primarily used for irrigation in response to the effect of deficits in precipitation or drought conditions, as well as to fuel crop production along the state. However, the current rate of extraction from the Ogallala Aquifer is 12-40 times the recharge rate. Because of this, Nebraska faces great risks in regards to decreased agricultural production due to high dependence on a dwindling and finite groundwater resource. Subsequently, Nebraska's agriculture may increase reliance on surface water availability as groundwater resources decrease. These factors arise the question of how the interdependence water-climate varies as we increase the lead-time in seasonal forecasts? Our objective is to use climate data in an ensemble-based platform to identify possible sources of drought predictability in the Platte River Basin. Our hypothesis is that prevalent water states (snow water equivalent and soil water) will improve the predictability of hydrologic drought. We will test our hypothesis by conducting an ensemble streamflow prediction (ESP, consistent multiple 1-year simulations initialized with a single initial condition) and inverted ESP (I-ESP, consistent a single 1-year simulation initialized with multi-year initial conditions) based on the use of the Variable Infiltration Capacity model (VIC). VIC is forced with observational data gathered regarding temperature minimum and maximum, precipitation, and wind values from the Sub-continental Observation Dataset, a gridded 1/16th degree resolution data obtained from climatological stations in Canada, US, and Mexico. The model will be initialized with wet and dry conditions for an ESP-initial condition and 50, 1-year simulations (1950 to 1999); the inverted-ESP year will be a particularly dry water year. Preliminary results from the VIC model on the PRB in regards to streamflow sensitivity with respect to temperature and precipitation found that all sub basins are more sensitive to changes in precipitation than temperature, which can add skill to the model in specific locations and times of the year. Ultimately, WaFIS-HF will become the complementary module of an under-development multi-scale climate-based forecast module (WaFIS-CF) and an interoperability platform (WAFIS). in regards to streamflow sensitivity with respect to temperature and precipitation found that all sub basins are more sensitive to changes in precipitation than temperature, which can add skill to the model in specific locations and times of the year. Ultimately, WaFIS-HF will become the complementary module of an under-development multi-scale climate-based forecast module (WaFIS-CF) and an interoperability platform (WAFIS).