Climate and Weather

In this study, an attempt has been made to study the characteristics of short interval rainfall data of the Punpun river basin lying in Bihar-Jharkhand, which has been identified as the representative basin for the NIH- Centre for Flood Management Studies, Patna. The estimation of flood peaks for small catchments is required for water resources planning, flood forecasting, design of various drainage systems, flood control and design of hydraulic structures.

The report presents a methodology for planning of crop and water management practices using weekly rainfall data.

The report presents an estimation of soil erosion and sediment yield for the Karso catchment of Barakar basin in Jharkhand using ANSWERS model. Quantitative assessments of runoff and soil erosion are needed for proper management of land and water resources.

The report discusses the application of deterministic and stochastic approaches in daily rainfall-runoff modeling. The structure of a simple hydrologic water balance type conceptual model of daily time scale is discussed and tested on three catchments of India. Further, the deviations of historic and computed runoff series obtained by using the model, which indicate the error in the fitting of model, is analyzed and used to improve the predicted flows.

A peer paper in Science Magazine focuses on the core of a riverine system, the upstream basin, and its impact on the entire river basin.

The report presents a seasonal rainfall-runoff model developed for the Saurashtra region as well as parts of Narmada river basin. The successful planning and implementation of water resources projects require reliable data on volumetric runoff. It is not feasible to have discharge stations in all the river basins of interest given resource constraints. Therefore, regional rainfall-runoff models are preferred. The utility of such models can be improved if rainfall-runoff models for different regions are developed using data specific to the regions.

The research study attempts to develop a rainfall-runoff model using the Artificial Neural Network (ANN) technique for the Baitarni river in Orissa. A detailed review of the research work in the area of interest revealed that the approach of neural computations was very effective in developing the required model, due to its various advantages. Accordingly, three candidate models based on ANN architecture were developed for the study area, to represent rainfall-runoff transformation.

In the study, raingauge network design has been developed for the Pagladiya basin of Brahmaputra river in Nalbari, Assam and Bhutan. Precipitation is the most basic data required for any water resources study and the estimation of the number & location of raingauge stations that provide adequate information regarding rainfall falling over the catchment is referred to as network design. A raingauge network is intended to serve general as well as specific purposes such as water supply, hydropower generation, flood forecasting, irrigation and flood control.

This report by ACWADAM describes the results of a research study conducted under the DFID funded AGRAR project at the Kolwan site in Pune district of Maharashtra state in India. The research focused on studying the usefulness of artificial recharge to augment groundwater resources through watershed development.

An important criterion of the study was also to understand the impact of artificial recharge on already changing livelihoods in areas where watershed development was conducted on a large scale.