Rainfall-runoff forecasting techniques for avoiding global warming

Abstract

Now a days, golobal warming becomes most sensitive issue.. Since the early 20th century, Earth's mean surface temperature has increased by about 0.8 °C (1.4 °F), with about two-thirds of the increase occurring since 1980[12]. Warming of the climate system is unequivocal, and scientists are more than 90% certain that it is primarily caused by increasing concentrations of greenhouse gases produced by human activities such as the burning of fossil fuels and deforestation.[13][14][15][16] These findings are recognized by the national science academies of all major industrialized nations.[17][18]. We can decrease or controls the earth temperature by saving our trees and increasing earths water level. This needs Rainfall and Runoff forecasting techniques. It is not only useful in IT sector, but also very useful in predicting or forecasting the monsoon. It is certainly beneficial for human for better water consumption as well as increasing greenery in our environment. This information can be beneficial for controlling soil pollution and all types of environmental pollution. RUNFALL-RUNOFF modeling is very important and challenging area of research. The issue becomes more crucial and difficult as the monsoon prediction is becomes wrong. The semiarid area of western Maharashtra province is a important grain production base in India, in the area the nature characteristics is small quantity and concentrate distribution in rainfall, and agriculture development was restricted by drought and soil and water loss seriously. Surface runoff not only leads to rainfall use efficiency decrease, it is also the important factor which causes soil erosion. The objective of this paper is to review the different forecasting algorithms of rainfall- runoff modeling. Furthermore, comparative analysis about the incorporation of spatial distribution of rainfall in the upstream brought out the necessity of the combined incorporation of both direct and averaging area for better accuracy.