Precipitation is considered a crucial component in the hydrological cycle and changes in its
spatial pattern directly influence the water resources. We compare different interpolation …

Handling missing values is a critical component of the data processing in hydrological
modeling. The key objective of this research is to assess statistical techniques (STs) and …

Combating climate change has emerged as a global concern recently, and meteorological
data remain an important measure for analyzing and predicting climate trends. However …

Accurate estimation of precipitation patterns is essential for the modeling of hydrological
systems and for the planning and management of water resources. However, rainfall time …

Remote sensing can provide important and updated information for agricultural water
accounting (AWA). In this study, data from the open-access portal (WaPOR) of the Food and …

Gridded climate datasets such as satellite and reanalysis products have biases related to
the methods used to develop them. This study aims to improve the hourly rainfall distribution …

Open-source climate products provide the possibility of complementing observed data,
which sometimes suffer from the scarcity and inconsistency issues. This study aims to …

Comprehensive precipitation data is essential for hydrological, agricultural, and
climatological studies. Yet, gaps and sparse rain gauge distribution pose challenges …

Missing data is one of the main difficulties in working with fluviometric records. Database
gaps may result from fluviometric stations components problems, monitoring interruptions …

Modelling hydrological process in the critical zone not only contributes to a better
understanding of interactions across different Earth surface spheres but also holds …