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...

Macro Rainwater Harvesting (RWH) under recorded and forecasting rainfall scenarios helps to overcome the water shortage problem. Eastern Sinjar District-Iraq had been investigated for the potential of RWH with a catchment area of four basins. Three recorded rainfall scenarios (S1, S2, and S3) were diagnosed representing seasons of the maximum, minimum and average weekly rainfall events for the ...

Accurate and timely weather forecasting is a major challenge for the scientific community in hydrological research such as river training works and design of flood warning systems. Neural Network (NN) is a popular regression method in rainfall predictive modeling. This paper investigates the effectiveness of the hybrid Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) evolved neural ...

Accurate forecasting of rainfall has been one of the most important issues in hydrological research. In this paper, a novel neural network technique, support vector regression (SVR), to monthly rainfall forecasting. The aim of this study is to examine the feasibility of SVR in monthly rainfall forecasting by comparing it with back–propagation neural networks (BPNN) and the autoregressive integr...

Reservoir is one of the emergency environments that required fast an accurate decision to reduce flood risk during heavy rainfall and contain water during less rainfall. Typically, during heavy rainfall, the water level increase very fast, thus decision of the water release is timely and crucial task. In this paper, intelligent decision support model based on neural network (NN) is proposed. Th...

The use of radar in Quantitative Precipitation Estimation (QPE) for radar-rainfall measurement is significantly beneficial. Radar has advantages in terms of high spatial and temporal condition in rainfall measurement and also forecasting. In Malaysia, radar application in QPE is still new and needs to be explored. This paper focuses on the Z/R derivation works of radarrainfall estimation based ...

To recognize application of Artificial Neural Networks (ANNs) in weather forecasting, especially in rainfall forecasting a comprehensive literature review from 1923 to 2012 is done and presented in this paper. And it is found that architectures of ANN such as BPN, RBFN is best established to be forecast chaotic behavior and have efficient enough to forecast monsoon rainfall as well as other wea...

The application of a flash-flood prediction chain, developed by CIMA, to some testcases for the Tanaro river basin in the framework of the EU project HYDROPTIMET is presented here. The components of the CIMA chain are: forecast rainfall depths, a stochastic downscaling procedure and a hydrological model. Different meteorological Limited Area Models (LAMs) provide the rainfall input to the hydro...

[1] Using existing data sets of spaceborne soil moisture retrievals, streamflow and precipitation for 26 basins in the United States Southern Great Plains, a 5-year analysis is performed to quantify the value of soil moisture retrievals derived from the Tropical Rainfall Measuring Mission (TRMM) Microwave Imager (TMI) X-band (10.7 GHz) radiometer for forecasting storm event-scale runoff ratios....

This paper discusses the modelling of rainfall-flow (rainfall-run-off) and flow-routeing processes in river systems within the context of real-time flood forecasting. It is argued that deterministic, reductionist (or 'bottom-up') models are inappropriate for real-time forecasting because of the inherent uncertainty that characterizes river-catchment dynamics and the problems of model over-param...