86 Role of Calibration on Ensemble Streamflow Prediction for Seasonal Agricultural Drought Forecasts

Monday, 11 January 2016
Daniel Anthony Rico, Univ. of Nebraska, Lincoln, NE; and K. Smith, J. Chacon, G. Corzo, and F. Munoz-Arriola

The goal of our research is to explore the improvements calibration can have on predictability of agricultural drought forecasts. Surface water (SW) and groundwater (GW) in Nebraska satisfy crop irrigation requirements, which enables the state to produce ~5% of global corn production. While GW from the northern portion of the Ogallala aquifer is primarily used for irrigation in response to deficits in precipitation in the western part of Nebraska, the eastern part of the state depends on available SW for crop production in the state. However, the current rate of extraction from the Ogallala Aquifer is 12-40 times the recharge rate, which may increase agriculture reliance on SW availability. Also, more frequent and intense droughts require accurate hydrologic seasonal forecasts. These factors arise the question of how calibrating hydrologic seasonal forecast systems will affect the forecast accuracy and range of predictability? Our objective is to use climate data in an ensemble-based platform to calibrate and determine improvements in drought predictability in the Platte River Basin (PRB). Our hypothesis is that the calibrated version of our hydrologic seasonal forecast system will be improved in its ability to more accurately predict seasonal drought when compared to the un-calibrated forecast system. We will test our hypothesis by conducting an ensemble streamflow prediction (ESP, consistent multiple 1-year simulations initialized with a single initial condition) 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 speed values from the North American sub-continental Observation Dataset, a gridded 1/16th degree resolution daily dataset. Automatic calibration will consist of a krigging homogenization of the parameter fields. The system will be (1) initialized with wet and dry conditions for an ESP-initial condition and 50, 1-year simulations (1950 to 1999); (2) will run for wet and dry years in the northern high plains; and (3) will run with and without VIC's calibration. This system is a module of the Water for Food Integrated System-Hydrologic Forecast (WaFIS-HF) aimed to enhance seasonal hydrologic, crop, and climate forecasts in the High plains and the Missouri River Basin.
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