Estimation of missing precipitation records is one of the important tasks in hydrological study. The completeness of precipitation data leads to more accurate results from the hydrological models. This study proposes the use of modular artificial neural networks to estimate missing monthly rainfall data in the northeast region of Thailand. The simultaneous rainfall data from neighboring control...

Results of observations of groundwater table in Roztocze are presented. Four types of fluctuation are distinguished. Most common and typical is the first one, dependent on annual hydrological cycle. The second type with amplitudes to 6 m depends on many years' cycle and is accompanied with insignificant influence of annual hydrological cycle. Correspondence of water table to groundwater runoffw...

Long-term streamflow data are vital for analysis of hydrological droughts. Using an artificial neural network (ANN) model and nine tree-ring indices, this study reconstructed the annual streamflow of the Sacramento River for the period from 1560 to 1871. Using the reconstructed streamflow data, the copula method was used for bivariate drought analysis, deriving a hydrological drought return per...

rainfall-runoff is one of complex hydrological processes that is affected by a variety of physical and hydrological factors. in this study statistical method armax model, neural network, neuro-fuzzy (anfis subtractive clustering and grid partition) and two hybrid models of this methods were used to simulate rainfall-runoff and prediction of streamflow. in each method optimum structure was deter...

[1] An intensification of the hydrological cycle is a likely consequence of global warming. But changes in the hydrological cycle could affect sea-surface temperature by modifying diffusive ocean heat transports. We investigate this mechanism by studying a coupled general circulation model sensitivity experiment in which the hydrological cycle is artificially amplified. We find that the amplifi...

daily discharge data of 12 hydrometric recording stations in atrak river basin were manipulated to calculate low flows for 7-day duration for studying hydrological drought using regional analysis method. using regression models, the low flows for 7-days duration of 10-year return period were calculated and regional low flows were estimated for 20 stations. daily data in each station used to sim...

In urban areas, hydrological processes are characterized by high variability in space and time, making them sensitive to small-scale temporal and spatial rainfall variability. In the last decades new instruments, techniques, and methods have been developed to capture rainfall and hydrological processes at high resolution. Weather radars have been introduced to estimate high spatial and temporal...

Methods for determining the parameters necessary for modeling fluid flow and contaminant transport in the shallow subsurface are in great demand. Soil properties such as permeability, porosity, and water retention are typically estimated through the inversion of hydrological data (e.g., measurements of capillary pressure and water saturation). However, ill-posedness and non-uniqueness commonly ...

The important criteria for designing in the most of hydrologic and hydraulic construction projects are based on runoff or peak-flow of water. Mostly, this measure and criterion is calculated or estimated by stochastic data. Another feature of these data that are used in watershed hydrological studies is their impreciseness. Therefore, in this study, in order to deal with uncertainty and impreci...