Influence of storage areas on tidal wave propagation

In river engineering practice it is often required to set up a mathematical model for (part of) a river. A standard computer programme for one-dimensional unsteady flow is of ten available. The input data for the model are obtained through measurements in the prototype. The aim of this study is to provide information on this subject which could be used to design a more systematic calibration methode. Such a method, in turn, should give an indication on the sort and number of measurements that are required ,to carry out a proper calibration.Fluid MechanicsHydraulic EngineeringCivil Engineering and Geoscience

Making Water Everyone's Business

Vision Statement and Key Messages Vision statement Actions needed Responsibility for implementation The Use of Water Today The world's water resources Main uses of water for human purposes Threats to nature-and to people Key water management issues Water Futures Turning points in water futures Scenarios and models Projected water use and water stress in 2025 Expanding irrigated agriculture Increasing water productivity Developing biotechnology for agriculture Increasing storage Reforming water resource management institutions Valuing ecosystem functions Increasing cooperation in international basins Supporting innovation World Water Vision Our Vision of Water and Life in 2025 People come first... but we cannot live without the rest of nature How we achieved our Vision Investing for the Water Future Closing the resource gap Mobilising new financial resources Launching a movementKWP-collectio

World Water Vision: Making Water Everybody's Business

Vision of the World Water Council on the use of water in the next centrury.KWP-collectio

Development of a regional soil productivity index using an artificial neural network approach

Soil productivity indices represent ratings of the potential plant biomass production of soils. Inductive approaches determine productivity based on inferred effects of soil properties on yield. Conversely, deductive approaches use yield information to estimate productivity. Our objective was to compare the performance of both types of productivity indices for assessing regional soil productivity for wheat (Triticum aestivum L.) yield in the Pampas. Soil data from soil surveys and interpolated climate information were utilized. Wheat yield data from a 40-yr period and representing ?45 Mha were used. Inductive productivity indices showed a low correlation with observed yield (R2 < 0.45, P = 0.05). The best performance of deductive empirical methods was attained using a blind guess option, but soils could only be rated when yield data were available. Yield models based on the neural network approach had good performance (R2 = 0.614, root mean square error [RMSE] = 548 kg ha–1) and was used for regional productivity index development. This index could be extrapolated to soils for which yield data are not available, and its validation with yield averages was optimal (R2 = 0.728, P = 0.05). Regional high productivity was achieved for combinations of medium to high levels of soil organic C and soil available water storage capacity variables, which showed a positive interaction. This methodology for assessing soil productivity based on an empirical yield-based model may be applied in other regions of the world and for different crops.Fil: de Paepe, Josefina. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Alvarez, Roberto. Universidad de Buenos Aires. Facultad de Agronomía; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin