Water Resources and the Urban Environment 

About: Water Resources and the Urban Environment is an academic journal. The journal publishes majorly in the area(s): Surface runoff & Water quality. Over the lifetime, 85 publications have been published receiving 699 citations.

Short Term Streamflow Forecasting Using Artificial Neural Networks

Abstract: The research described in this article investigates the utility of Artificial Neural Networks (ANNs) for short term forecasting of streamflow. The work explores the capabilities of ANNs and compares the performance of this tool to conventional approaches used to forecast streamflow. Several issues associated with the use of an ANN are examined including the type of input data and the number, and the size of hidden layer(s) to be included in the network. Perceived strengths of ANNs are the capability for representing complex, non-linear relationships as well as being able to model interaction effects. The application of the ANN approach is to a portion of the Winnipeg River system in Northwest Ontario, Canada. Forecasting was conducted on a catchment area of approximately 20 000 km2. using quarter monthly time intervals. The results were most promising. A very close fit was obtained during the calibration (training) phase and the ANNs developed consistently outperformed a conventional model during the verification (testing) phase for all of the four forecast lead-times. The average improvement in the root mean squared error (RMSE) for the 8 years of test data varied from 5 cms in the four time step ahead forecasts to 12.1 cms in the two time step ahead forecasts.

Allocation of Water Withdrawals in a River Basin

Abstract: An increasing number of states use permit programs to coordinate and to control water resource allocations. A general approach is suggested for allocating and permitting water withdrawals in a river basin. A mathematical programming methodology facilitates optimal streamflow allocation while maintaining desired levels of instream flow. The approach uses a graphical tool, the flow duration curve, to illustrate the quantity and frequency of joint streamflow withdrawals in a river basin. The methodology is unique because while it uses mathematical programming methods, it is implemented using a spreadsheet optimization tool, Microsoft Excel Solver, and the solution is illustrated in a graphical form so that nontechnical individuals can easily understand the methodology results. The ability to apply the methodology and clearly explain the results is extremely important since many nontechnical individuals are involved as policymakers in water allocation decisions.

Remediation of nitrate-contaminated surface water using sulfur and limestone autotrophic denitrification processes

Abstract: The feasibility of using the sulfur/limestone autotrophic denitrification (SLAD) process as an in situ method for remediation of nitrate-contaminated surface water was investigated. Four bench-scale pond systems with working volumes of 21.4 liters each and hydraulic retention time (HRT) of 30 days were operated under mixed conditions. Under mixed (aerobic) conditions, with the addition of alkalinity to raise pH, NO{sub 3}{sup {minus}}-N removal in the SLAD ponds was 85--100%, while the control reactor showed negative removal. Sulfate production under mixed conditions was between 1,000--2,500 mg/l SO{sub 4}{sup 2{minus}}, which shows that 40--60 mg/l of SO{sub 4}{sup 2{minus}} is produced for every 1 mg/l of NO{sub 3}{sup {minus}}-N reduced. Although the system is very efficient in removing nitrates under simulated surface water conditions, the sulfate production makes the process questionable for use under aerobic conditions. However, batch experiments under anaerobic conditions demonstrate that system maybe very efficient in removing nitrate while not producing insufferable amounts of sulfates.