High-spatial-resolution precipitation data are of great significance in many applications, such as ecology, hydrology, and meteorology. Acquiring high-precision high-resolution a large area is still challenge. In this study, downscaling–merging scheme based on random forest cokriging presented to solve problem. First, the enhanced decision tree model, which from machine learning algorithms, use...

The geometric variability of soil layers is a large source uncertainty in the reliability assessment dikes. Because direct samples subsurface soils are often insufficient to capture complexity subsurface, geophysical methods provide powerful complementary information. A combined approach estimate geometry presented. combines local point data, i.e. data obtained from CPT or borehole log, and tom...

according to the importance of groundwater resources in providing of human needs, lack of control and inappropriate management of these resources can lead to the problems such as nitrate pollutions arising from the use of chemical fertilizers in agricultural lands. with generalized point data to the area using the geostatistics methods can be determine the pollution content in areas without sam...

rainfall spatial analysis methods are very helpful since there are not enough rainfall gauge stations and watersheds are scattered in large extent. there are many different methods for estimating average precipitation such as; arithmetic method and thiessen polygon. however, the arrangement and location of data and their correlations are not considered by classic methods. thus, geostatistical t...

for the purposed water resources management, irrigation scheduling, water usage optimization and gaining maximum yield two step fao method was applied to determine the water requirement (evapotranspiration) of sugar beet.  in this paper reference evapotranspiration were computed from recorded meteorological data at 38 weather stations using the hargreaves-samani method; and then through applyin...