Many satellite soil moisture products are today globally available in near real-time. These observations are of paramount importance for enhancing the understanding of the hydrological cycle and particularly useful for flood forecasting purposes. In recent decades, several studies assimilated satellite soil moisture observations into rainfall-runoff models to improve their flood forecasting ski...

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...

The accurate simulation of SWAT can assist the government in making correct decisions about water management practices, which are important for human health, agricultural management, industry development, environmental quality, flood risk assessment, and recreation. In this project, the PIs were trying to improve the simulation accuracy of the SWAT model through developing new algorithm to obta...

The prediction uncertainty of a hydrologic model is closely related to model formulation and the uncertainties in model parameters and inputs. Currently, the foremost challenges concern not only whether hydrologic model outputs match observations, but also whether or not model predictions are meaningful and useful in the contexts of land use and climate change. The latter is difficult to determ...

Rainfall prediction is very complex hydrologic process and is important as it holds the key to any countries’ economy. Proposed model presents a new approach for yearly rainfall prediction of 30 Indian subdivisions. Yearly rainfall data of the Indian subdivision is available from IITM, Pune. The combination of Fast Fourier Transform (FFT) and Feed Forward Neural Network (FFNN) is applied for ne...

The physically-based flood frequency models use readily available rainfall data and catchment characteristics to derive the flood frequency distribution. In the present study, a new physically-based flood frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) metho...

introduction: rainfall is affected by changes in the global sea level change, especially changes in sea surface temperature sst sea surface temperature and sea level pressure slp sea level pressure. climate anomalies being related to each other at large distance is called teleconnection. as physical relationships between rainfall and teleconnection patterns are not defined clearly, we used inte...

A dynamical model for orographic rainfall with particular reference to the Western Ghats is presented. The model assumes a saturated atmosphere with pseudo-adiabatic lapse rate and is based on linearized equations. The rainfall, as computed from the theoretical model, is in good agreement, both in intensity and in distribution, with the observed rainfall on the windward side of the mountain. Th...

We examine the hypothesis that basins characterized by (1) marked spatial variability in precipitation, and (2) less of a filtering effect of the input rainfall signal will show improved outlet simulations from distributed versus lumped models. Basin outflow response to observed spatial variability of rainfall is examined for several basins in the Distributed Model Intercomparison Project. The ...