The high spatial and temporal variability of precipitation poses a substantial challenge to its global monitoring, particularly over the global oceans. The insufficient coverage of surface-based measurements adds to this problem. These data-sparse areas profit from passive microwave (PMW) satellite sensors, which essentially contribute to the estimation of global long-term precipitation estimat...

abstract obligatory modelling of precipitations in various periods, have a lot of problems and weakness because of their casual nature in time and space. moreover, their uncertainty in predictions, reduce credibility of estimations which have done via these models. wavelet is one of the novel and very effective methods in analyzing of time series and signals considered in the hydrology in recen...

Hydrologic and ecologic studies in mountainous terrain are sensitive to the temporal and spatial distribution of precipitation. In this study a geostatistical model, Auto-Searched Orographic and Atmospheric Effects Detrended Kriging (ASOADeK), is introduced to map mountain precipitation using only precipitation gauge data. The ASOADeK model considers both precipitation spatial covariance and or...

a watershed management program is usually based on the results of watershed modeling. accurate modeling results are decided by the appropriate parameters and input data. precipitation is the most important input for watershed modeling. precipitation characteristics usually exhibit significant spatial variation, even within small watersheds. therefore, properly describing the spatial variation o...

precipitation regime refers to distribution of seasonal- monthly precipitation. by studying this character, it could be find out about the most important parts of mechanism(s) dominant in temporal distribution of precipitation. precipitation regime can have positive or negative effects on other environmental components performance. in the present research, the monthly data in 73 stations during...

This study integrates a Box-Cox power transformation procedure into a common trend two-phase regression model based test (the PMFred algorithm) for detecting changepoints, to make the test applicable to non-Gaussian data series, such as non-zero daily precipitation amounts or wind speeds. The detection power aspects of the transformed method (transPMFred) are assessed by a simulation study, whi...