Estimation of Annual Runoff Statistics in Ungauged Basins with Parsimonious Evaluation of Climatic Indices

Relations between climatic parameters and hydrological variables at the basin and the regional scale are investigated using climatic classifications as synthetic indices representing the average annual water budget. Precipitation, temperature and net radiation are the climatic variables required for evaluating the climatic indices in the formulations proposed by Thornthwaite, Emberger and Budyko. The spatial distribution of these variables has been studied in the 10,000 km2 territory of the Basilicata region (Southern Italy), to evaluate the possibility of their indirect estimation. Precipitation and temperature data was available for several stations within the region, and measures of global radiation were available for few stations in a reasonable number of years. Simple, yet robust, literature methods for estimation of net radiation were adopted, to limit the ground data requirement to temperature and relative heliophany, which was replaced by average measures of cloudiness from remote sensing. Consequently, the climatic indices considered can have an approximate evaluation using only data of elevation, latitude and cloudiness. The above-mentioned climatic indices were evaluated over a grid of resolution of about 1 km. Lumped climatic indices computed on the gauged basins available in Basilicata were found to be clearly related to mean and variance of the measured annual runoff series. The Budyko index was the best in terms of symmetry of the frequency distribution, sensitivity to aridity and quality of the correlation with the moments of the annual runoff. To further substantiate the potential of synthetic climatic information to support a regional hydrologic studies, the NOAA-AVHRR normalized difference vegetation index (NDVI), obtained with the maximum value composite technique, has been compared to the above estimates of climatic indices. Dependency of the vegetation phenology from the energy and water budget support the connections found between NDVI and the estimated climatic indices. These initial results indicates that there are good premises in the task of reducing the dependence of climatic mapping in a region from ground data, with the possibility of reducing the importance of the measure of precipitation.