Cost-benefit analysis and ideas for cost sharing of groundwater irrigation: evidence from north-eastern Ethiopia

The government of Ethiopia has invested in groundwater development for smallholder irrigation in the Raya Valley and Kobo Valley, north-eastern Ethiopia, where the hydrogeological potential is large but not fully developed. A cost-benefit analysis shows that investment in deep groundwater irrigation development is viable at a 9.5% discount rate in 75% of the wells. Assuming full cost recovery of capital investment, the annual payment rates (annuity) that irrigation users should pay over the wells’ service life (25 years) were estimated. It is recommended that future investment be based on cost sharing rather than full cost recovery to facilitate uptake and address financial realities.     

Joint Application of Artificial Neural Networks and Evolutionary Algorithms to Watershed Management

Artificial neural networks (ANNs) have become common data driven tools for modeling complex, nonlinear problems in science and engineering. Many previous applications have relied on gradient-based search techniques, such as the back propagation (BP) algorithm, for ANN training. Such techniques, however, are highly susceptible to premature convergence to local optima and require a trial-and-error process for effective design of ANN architecture and connection weights. This paper investigates the use of evolutionary programming (EP), a robust search technique, and a hybrid EP–BP training algorithm for improved ANN design. Application results indicate that the EP–BP algorithm may limit the drawbacks of using local search algorithms alone and that the hybrid performs better than EP from the perspective of both training accuracy and efficiency. In addition, the resulting ANN is used to replace the hydrologic simulation component of a previously developed multiobjective decision support model for watershed management. Due to the efficiency of the trained ANN with respect to the traditional simulation model, the replacement reduced the overall computational time required to generate preferred watershed management policies by 75%. The reduction is likely to improve the practical utility of the management model from a typical user perspective. Moreover, the results reveal the potential role of properly trained ANNs in addressing computational demands of various problems without sacrificing the accuracy of solutions.     

Erratum to: The Value of Rain: Benefit-Cost Analysis of Rainwater Harvesting Systems

Water Resources Management -     

The Value of Rain: Benefit-Cost Analysis of Rainwater Harvesting Systems

Water Resources Management - Rainwater harvesting is increasingly viewed as a practical means of reducing stormwater runoff and supplementing water supply in water-scarce regions, although its...     

Small‐Molecule‐Doped Organic Crystals with Long‐Persistent Luminescence

Traditional long‐persistent luminescence (LPL) materials, which are based on inorganic systems containing rare elements and with preparation temperatures of at least 1000 °C, exhibit afterglow times of more than 10 h and can be tuned for different applications. However, the development of this field is hindered due to the large thermal energy consumption and the need for nonrenewable resources. Thus, the development of a “green” design and preparation of LPL materials is of some importance. A doped‐crystalline material based on two metal‐free organic small molecules is easily prepared through ultrasonic crystallization at room temperature. It has a high‐quality, single‐crystalline structure, and visible LPL performance with a duration of more than 6 s upon low‐energy photoexcitation. A green, flexible, and convenient screen‐printing technology for controllable pattern anticounterfeiting is then developed from this purely organic material, which improves the prospects for commercial utilization in the future.     

Watershed Management Technique to Control Sediment Yield in Agriculturally Dominated Areas

Abstract

Non-point source pollution is recognized internationally as a critical environmental problem. In Illinois, soil erosion from agricultural lands is the major source of such pollution. The erosion process, which has been accelerated by human activity, tends to reduce crop productivity and leads to subsequent problems from deposition on farmlands and in water bodies. Comprehensive watershed management, however, can be used to protect these natural resources. In this study, a discrete time optimal control methodology and computational model are developed for determining land use and management alternatives that minimize sediment yield from agriculturally-dominated watersheds. The solution methodology is based on an interface between a genetic algorithm and the U.S. Department of Agriculture's Soil and Water Assessment Tool. Model analyses are performed on a farm field basis to allow capture of different, local stakeholder perspectives, and crop management alternatives are based on a three-year rotation pattern. The decision support tool is applied to the Big Creek watershed located in the Cache River basin of Southern Illinois. The application demonstrates that the methodology is a valuable tool in advancing comprehensive watershed management. The study represents part of an ongoing research effort to develop an even more comprehensive decision support tool that uses multi-criteria evaluation to address social, economic, and hydrologic issues for integrative watershed management.