Journal of Water Resources Planning and Management

The interdisciplinary nature of water resources problems requires the integration of technical, economic, environmental, social, and legal aspects into a coherent analytical framework. This paper presents the development of a new integrated hydrologic-agronomic-economic model in the context of a river basin in which irrigation is the dominant water use and irrigation-induced salinity presents a major environmental problem. The model’s main advantage is its ability to reflect the interrelationships between essential hydrologic, agronomic, and economic components and to explore both economic and environmental consequences of various policy choices. All model components are incorporated into a single consistent model, which is solved in its entirety by a simple but effective decomposition approach. The model is applied to a case study of water management in the Syr Darya River basin in Central Asia.

In March 2000, the National Oceanic and Atmospheric Administration issued forecasts of spring and summer droughts for five Midwestern states. Summer brought heavy rains across the Midwest, ending the drought and revealing the forecast’s failure. The uses of forecasts and the resulting impacts were assessed by interviewing 45 state agency water managers in the drought region plus managers of 31 community water systems facing serious shortages. All state water managers had received the forecasts and most believed the forecast was accurate. As a result of the forecast, 70% of them initiated various activities, primarily by warning managers of water short communities and initiating meetings of state drought response groups. Many managers of water-short local systems reported that the forecast led them to impose water use restrictions or to seek new sources of water. Most state water officials and local managers felt the forecast-based actions were beneficial and created few problems. State climatologists handled many complaints, primarily from agricultural interests who claimed large losses resulting from use of the forecast. The forecast failure led to a loss of credibility over future use of climate forecasts by water managers. Long-range weather forecasts issued without expressing levels of uncertainty are misleading.

This paper describes the development of a general operating policy for a water supply system using the methodology of data mining. To define an operating policy using this approach, both a single-reservoir and a multireservoir water system were modeled and optimized for a set of historical inflows. These optimization results defined the best possible performance for the systems with historical hindsight, and were used as input for the data mining process. The data mining algorithm then generated the set of control rules that gave the best historical operating policy. The data mining tool used in this work is based on the induction tree technique, C5.0, reported by Quinlan in 1993. However, the process of reservoir control rule extraction is not straightforward and requires several data preparation steps to enhance the performance of the data mining algorithm. To demonstrate the effectiveness of the rules developed through data mining, simulation runs of the system were performed. The results of these simulations were compared with simulation results using operating policies derived from linear regression. Another comparison between operating rules derived using different methodologies was performed for the multireservoir system where, in addition to data mining and regression-based rules, there were rules available from the U.K. Environment Agency (South West). The paper shows that “data-mined” rules come closest to the optimization results.

Conjunctive-management models that couple numerical simulation with linear optimization were developed to evaluate trade-offs between groundwater withdrawals and streamflow depletions for alluvial-valley stream-aquifer systems representative of those of the northeastern United States. A conjunctive-management model developed for a hypothetical stream-aquifer system was used to assess the effect of interannual hydrologic variability on minimum monthly streamflow requirements. The conjunctive-management model was applied to the Hunt-Annaquatucket-Pettaquamscutt stream-aquifer system of central Rhode Island. Results show that it is possible to increase the amount of current withdrawal from the aquifer by as much as 50% by modifying current withdrawal schedules, modifying the number and configuration of wells in the supply-well network, or allowing increased streamflow depletion in the Annaquatucket and Pettaquamscutt rivers. Alternatively, it is possible to reduce current rates of streamflow depletion in the Hunt River by as much as 35% during the summer, but such reductions would result in smaller increases in groundwater withdrawals.

The coefficient of variation of the optimal cost (CVOC) method is applied to the Acqua dei Corsari coastal aquifer in Sicily’s north coast to find the best point for a new water-level measurement location. The purpose of collecting data from the new measurement location is to reduce uncertainty associated with a stochastic management model for salt-water intrusion control. Assuming that uncertainty mainly stems from spatial variability of permeability, the structural parameters of the stochastic spatial permeability field are estimated using data from a nearby aquifer with similar geological properties. It is first shown through sensitivity analysis that the lack of previous information inhibits reliable estimation of the economic benefit of a new measurement location. A brief review of the CVOC method is presented, followed by identification of the best site for a permeability and a water-level measurement location. Finally, description of data collection at the proposed optimal site and calculation of the a posteriori optimal pumping strategy are provided.

New methods are used to evaluate stormwater controls and best management practices (BMPs) within a land development context. Costs are developed using published literature and standard cost estimation guides. A method is developed in which costs are determined for each parcel within a development for specific land uses. The effect of including the opportunity cost of land in the analysis is evaluated. Costs attributable to stormwater controls are allocated among purposes. A method is developed in which stormwater control costs are assigned at the parcel level. Data gaps and research needs are then explored to address this complex problem.

Urban water management is a demanding decision-making environment where optimal planning presupposes a synthesis of heterogeneous information of high spatial resolution to ensure site-specific implementation. To assist the decision maker in this task, the development of spatial decision support systems (SDSS) with a distinct spatial character is considered sine qua non. The paper describes the development of a prototype SDSS supporting strategic planning, providing examples from a particular application in water demand management (WDM). A three-stage approach is developed and utilized: After an initial user-defined choice of strategies to be explored, the system produces suitability maps for each individual attribute of the strategies in question using type-1 and type-2 fuzzy inference systems. The results are aggregated using ordered weighted averaging, allowing for the incorporation of the decision maker’s optimism in the final outcome. The last stage consists of an optimization procedure enabling the identification of an optimal composite strategy, from a water saving point of view, under user defined investment constraints. The results support the case of using SDSS based on approximate reasoning to complement engineering expertise for urban water management applications tailored to user characteristics and site-specific constraints.

Mathematical models of chlorine concentration in water distribution systems require the bulk decay coefficient to be quantified. The coefficient needs to be determined with respect to independent variables if models are to maintain their predictive capability as seasonal and water treatment operational changes occur. Reported herein are experiments undertaken to determine the functional dependence of the bulk-free, chlorine decay rate coefficient on total organic carbon concentration, initial chlorine concentration, temperature, and the number of rechlorinations. The resulting equation gives satisfactory results during annual cycles and the introduction of granular activated carbon treatment at a water treatment plant.