Within the context of predicting and mitigating flood hazards, this paper motivates the development of innovative ideas in three engineering research areas: (a) spatially-distributed quantitative rainfall prediction, (b) spatially-distributed flow prediction, and (c) long-term flow prediction for water resources management. Design, operational implementation, real-time testing, and training of ...

This discussion paper is/has been under review for the journal Hydrology and Earth System Sciences (HESS). Please refer to the corresponding final paper in HESS if available. Abstract Monsoon rainfall is of great importance for the agricultural production in both China and India. Understanding its rule and possibility of long term prediction is a challenge for research. This paper gives a joint...

Time-series analysis techniques for improving the real-time flood forecasts issued by a deterministic lumped rainfall-runoff model are presented. Such techniques are applied for forecasting the short-term future rainfall to be used as real-time input in a rainfall-runoff model and for updating the discharge predictions provided by the model. Along with traditional linear stochastic models, both...

India is basically an agricultural country and the success or failure of the harvest and water scarcity in any year is always considered with the greatest concern. The average annual or seasonal rainfall at a place does not give sufficient information regarding its capacity to support crop production. Rainfall distribution pattern is the most important. The rainfall forecasting is scientificall...

Weather is certainly the most important factor over which man has no control, and hence it has created dominance on the success or the failure of agricultural enterprises. Most important efforts since long time have been on weather and rain forecasting. However, the unpredictable nature of rainfall has not changed. Meteorologists can neither solve nor evaluate the problem of effective rainfall ...

This paper presents rainfall-induced landslide thresholds and predicts landslide hazard in Kuala Lumpur metropolitan city and surrounding areas. Landslide events from 2000 to 2012 were collected. The long and short antecedent rainfall days were prepared for landslide and non-landslide days simultaneously. First, threshold analysis was conducted by using data obtained from rainfall stations loca...

Rainfall derivatives are in their infancy since starting trading on the Chicago Mercentile Exchange (CME) since 2011. Being a relatively new class of financial instruments there is no generally recognised pricing framework used within the literature. In this paper, we propose a novel framework for pricing contracts using Genetic Programming (GP). Our novel framework requires generating a risk-n...

Spatial relationship between vegetation and rainfall in Central Kazakhstan has been modelled using Normalized Difference Vegetation Index (NDVI) and rainfall data from weather stations. The modelling based on application of two statistical approaches: conventional ordinary least squares (OLS) regression, and geographically weighted regression (GWR). The results support the assumption that the a...