G-WADI—the first decade

The G-WADI network by UNESCO promotes the global capacity for management of water resources in arid and semi-arid areas. The primary aim has been to build a comprehensive global network to promote regional and international cooperation so as to increase knowledge and improve management practices through the sharing of information. The G-WADI objectives and achievements of the past 10 years are reviewed. A number of key initiatives have been implemented––the formation of five regional networks, the creation of a central G-WADI web site, promotion of near-real-time rainfall distribution software enhanced by the inclusion of satellite based precipitation estimations, as well as workshop and web-based activities on chemical and isotopic tracers and on rain water harvesting. Two workshops on surface and on groundwater modeling, supported by publications have been held in India and China. The Asian G-WADI network remains very active, but activities in the other three regions are developing (Africa, Arab Region, Latin America and the Caribbean).     

The role of hydrograph indices in parameter estimation of rainfall–runoff models

A reliable prediction of hydrologic models, among other things, requires a set of plausible parameters that correspond with physiographic properties of the basin. This study proposes a parameter estimation approach, which is based on extracting, through hydrograph diagnoses, information in the form of indices that carry intrinsic properties of a basin. This concept is demonstrated by introducing two indices that describe the shape of a streamflow hydrograph in an integrated manner. Nineteen mid‐size (223–4790 km²) perennial headwater basins with a long record of streamflow data were selected to evaluate the ability of these indices to capture basin response characteristics. An examination of the utility of the proposed indices in parameter estimation is conducted for a five‐parameter hydrologic model using data from the Leaf River, located in Fort Collins, Mississippi. It is shown that constraining the parameter estimation by selecting only those parameters that result in model output which maintains the indices as found in the historical data can improve the reliability of model predictions. These improvements were manifested in (a) improvement of the prediction of low and high flow, (b) improvement of the overall total biases, and (c) maintenance of the hydrograph's shape for both long‐term and short‐term predictions. Copyright © 2005 John Wiley & Sons, Ltd.