Optimal Extension of Rain Gauge Monitoring Network for Rainfall Intensity and Erosivity Index Interpolation

Abstract

Rain gauge monitoring networks are highly important for precipitation and erosion estimation. In general, measurement accuracy depends on the precipitation as well as on the network size and design. This paper proposes a method for assessing the optimal location of new monitoring stations within an existing rain gauge network. It takes account of precipitation as well as the prediction accuracy of rainfall erosivity. A well known geostatistical variance-reduction method is applied jointly with simulated annealing as an algorithm for objective function minimization. With respect to the first objective, the kriging variance of intensity estimation is minimized considering a reference duration of one hour. The erosion-related objective, meanwhile, is focused on the minimization of the kriging variance of estimation of the logarithm of the erosivity factor. The spatial variability of rainfall observed during the extreme rainfall event recorded in March 1973, which was the heaviest rainfall event in the period 1973–2003, is selected as the basis for developing the geostatistical approach. Scenarios in which the size of the initial network is increased by 25, 50, and 100% are tested. Another application is shown for increasing the network to meet the minimum requirement of the World Meteorological Organization relative to the network spatial density. Optimal single objective networks are compared for both the intensity and erosivity factor objectives. With regard to the new station locations, it is found that the optimal single objective networks differ by just one or two stations. Multiobjective optimization techniques are then applied to help in the network augmentation process. If both the spatial distribution of the rainfall intensity and the spatial distribution of the erosivity index are captured, this helps with the selection of the most relevant new stations. Results are identical to examples of single objectives when equal weighting factors are adopted for both objectives for the smallest augmentation scenario (only three new stations to be implemented). Different optimal rain gauge locations are obtained if one aspect is emphasized more than the other (rainfall versus erosion and vice versa) when a greater number of new stations is to be added (50 and 100% augmentation).