Publication Date
1993
Description
Long-term weather forecasts (>14 days) have improved, but still lack accurate enough information to be valuable; thus, drought forecasts must be based on historical records and calculated probabilities of occurrence. The use of regression techniques to investigate linear dependence between current and preceding years' precipitation or forage yield is illustrated. A 3-state Markov process is used to determine relationships between below-average, average and aboveaverage consecutive annual herbage yields, and winter and spring precipitation amounts. Methods for using natl/ml resource simulation models to forecast ecosystem components such as herbage production, runoff, and erosion with their associated probabilities of occurrence are also discussed.
Citation
Hanson, C L. and Wight, J R., "Forecasting Annual Drought Conditions for Arid and Semi-Arid Rangelands" (2024). IGC Proceedings (1993-2023). 9.
https://uknowledge.uky.edu/igc/1993/session7/9
Included in
Agricultural Science Commons, Agronomy and Crop Sciences Commons, Plant Biology Commons, Plant Pathology Commons, Soil Science Commons, Weed Science Commons
Forecasting Annual Drought Conditions for Arid and Semi-Arid Rangelands
Long-term weather forecasts (>14 days) have improved, but still lack accurate enough information to be valuable; thus, drought forecasts must be based on historical records and calculated probabilities of occurrence. The use of regression techniques to investigate linear dependence between current and preceding years' precipitation or forage yield is illustrated. A 3-state Markov process is used to determine relationships between below-average, average and aboveaverage consecutive annual herbage yields, and winter and spring precipitation amounts. Methods for using natl/ml resource simulation models to forecast ecosystem components such as herbage production, runoff, and erosion with their associated probabilities of occurrence are also discussed.
