Evaluating changes and estimating seasonal precipitation for Colorado River Basins using nonparametric density estimation
Evaluating the hydrologic impacts of climate variability due to changes in precipitation has been an important and challenging task in the field of hydrology. This requires estimation of rainfall, preserving its spatial and temporal variability. The current research focuses on 1) analyzing changes (trend/step) in seasonal precipitation and 2) simulating seasonal precipitation using k-nearest neighbor (k-nn) non-parametric technique for 29 climate divisions covering the entire Colorado River Basin. The current research analyzes water year precipitation data ranging from 1900 to 2008 subdivided into four seasons i.e. autumn (October-December), winter (January-March), spring (April-June), and summer (July-September). Two statistical tests i.e., Mann Kendal and Spearman’s Rho are used to evaluate trend changes and Rank Sum test is used to identify the step change in seasonal precipitation for the selected climate divisions. The results show that changes are mostly during winter season. Eleven divisions show increase in precipitation, 6 divisions show decrease and the remaining 12 show no change in the precipitation for the period of record. A total of eight climate divisions observed changes during autumn season precipitation, with four climate divisions showing increasing and remaining four showing decreasing changes. Decreasing precipitation changes are observed for 6 divisions during spring season. In summer season, three climate divisions show increase and one division showed decrease in precipitation. The increasing precipitation changes during winter season are attributed to gradual step change, whereas the decreasing changes are due to trend changes. The decreasing precipitation changes in spring season occurred due to trend changes. The summer season changes occurred due to a gradual step change. During autumn season six divisions showed changes (3 increasing and 3 decreasing) due to a gradual step change and the remaining two divisions observed changes due to trend change. Satisfactory precipitation estimates are obtained using the k-nn resampling technique. A 50% probability exceedence estimation error is computed for the selected climate divisions during the four seasons. It is seen that best estimates are obtained for summer season precipitation and worst for autumn season. As many as 18 climate divisions show an estimation error of 20% or less during summer, 14 divisions during spring, 11 divisions during winter and, 9 divisions during autumn. The analysis of seasonal changes and estimates of precipitation can help water managers in better management of water resources in the Colorado River Basin.
Fresh Water Studies | Meteorology
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Evaluating changes and estimating seasonal precipitation for Colorado River Basins using nonparametric density estimation.
2009 AGU Fall Meeting
American Geophysical Union.