Journal of Water Resources Planning and Management

The negotiation support system (NSS) proposed in this paper is designed to aid two parties in their negotiations for allocation of water from a shared water resource. The NSS has several components which are activated in a series of negotiating iterations: (1) creation/modification by each party of its utility function, using the analytic hierarchy process to structure and weight a set of objectives; (2) the water allocation system model for optimal economic allocation of water among districts and users in a specified territory, subject to physical, hydrological, legal, administrative and other constraints, which can be run by each party alone or by both jointly; and (3) a procedure for moving jointly in utility space toward efficient (Pareto) solutions in the current negotiation iteration, identification of the Nash equilibrium point on this frontier, and then seeking to move from this point beyond this temporary efficient frontier and create new values for both parties. The negotiation proceeds by alternating between individual analysis (each party in private) and joint problem solving by examination of alternatives in utility space. The NSS has been tested and evaluated in a series of simulations, which are the topic of a companion paper.

Simulation experiments were conducted with the negotiation support system (NSS) presented by Kronaveter and Shamir to evaluate its efficacy in improving the negotiation process, and in getting to an agreed cooperative solution in which both sides gain relative to a simple bargaining process. Two sets of experiments were conducted: (1) with real actors—participants who played the negotiation game; and (2) with simulated actors, where the negotiation process was run through more iterations using objectives and preferences provided by participants. A hypothetical case study was used, in which two adjacent countries are competing for water from a finite common source. The paper describes the experiments and results, and draws conclusions regarding the value of using a negotiation framework in which multiobjective evaluation (using the analytic hierarchy process) and economic evaluation (using the water allocation system) are embedded.

This paper describes a model developed for optimizing water supply plans for water customers when a water network is partially operational due to the destruction of water networks by malicious attacks or any catastrophic events. The model uses the information regarding the priority of water customers in emergency situations, their functional sensitivities to water supply, and the dynamic nature of water demand patterns. The solutions generated from the model are water rationing plans which can guarantee at least a short-term water supply to water customers during any $24\text{-}\mathrm{h}$ period. A genetic algorithm based program linked with a hydraulic solver (EPANET 2.0) is developed to find optimal water rationing plans. A case study indicates that the proposed model can successfully generate water rationing plans to reduce the consequences while meeting hydraulic constraints in water networks. The model developed in this study is also applicable to extreme water supply shortage situations due to severe drought or nonintentional incidents such as major pump failures and main breaks.

Levee setback (location) and height are important issues in flood levee system design and modification. This paper derives an economic-engineering theory of the optimal trade-off of levee setback for height both for original and redesigned flood levees, demonstrating the interconnection of levee setback, height, costs and risks, and economically optimal design. These analyses assume stationary flood hydrology and static ratios among damageable property value, unit construction cost, and land price. The economic trade-off of levee setback for height depends on economic cost and benefit and hydraulic parameters, and only indirectly on flood frequency and economic damage parameters. The redesign rules derived in this paper indicate conditions where existing levees should be raised or moved in response to changes in conditions. Numerical examples illustrate the results. This paper demonstrates several ideas and theory for economic flood levee system planning and policy rather than providing guidelines for direct design practice.

Water quality and related management issues for a proposed lake source cooling (LSC) facility discharge of water from oligotrophic Lake Ontario to polluted eutrophic Onondaga Lake, NY, are considered in the context of ongoing rehabilitation programs for domestic waste and industrial contamination at Onondaga Lake. The analysis is supported by monitoring data for the lakes, a nearby LSC facility, a domestic wastewater treatment discharge (Metro), and local meteorological conditions. Model simulations are presented to address effects of a LSC discharge on thermal stratification, hypolimnetic dissolved oxygen, and epilimnetic total phosphorus, critical features for cold water fish and eutrophication. Eight LSC discharge scenarios, representing a range of flows, entry depths within the lake, and mixture with Metro effluent, are identified and evaluated. The high salinity of Onondaga Lake would prevent retention of the LSC discharge within the hypolimnion and associated benefits with respect to oxygen resources. Further, a hypolimnetic discharge would increase the upward transport of undesirable constituents mobilized from the sediments. In contrast, water quality and habitat benefits for two metalimnetic LSC discharge scenarios were predicted that would either ameliorate the lake’s cultural eutrophication problem or could serve to provide a modest refugium for certain cold water fish.

One of the primary reasons water-quality standards are not met is the effect of storm runoff and combined sewer overflows. A methodology is presented here to determine the duration of storm effects on stream water quality. The evaluation of the duration of storm effects on water quality involves two steps. First, calibration of an appropriate water quality model that is capable of simulation of unsteady-state conditions. Second, execution of the calibrated model with a number of storm loadings randomly sampled from a specific probability distribution that represents realistic ranges of pollutant concentrations. When the variations in the simulated water quality variables become negligible, it is assumed that the river system goes back to prestorm, dry-weather conditions. To illustrate this methodology, the DUFLOW unsteady-state water quality model and Latin hypercube sampling are applied to evaluate the duration of storm effects on water quality in the Chicago Waterway System (CWS). The duration of the storm impacts on dissolved oxygen lasts $2\text{days}–2\text{weeks}$ in the CWS depending on the location in the system and the magnitude of the storm. Moreover, a strong relation between the precipitation depth and the duration of the storm effects on in-stream water quality constituents was found in the CWS. Outcomes of this research suggest that the duration of the storm effect on water quality can be reasonably predicted with the help of robust unsteady-state water quality models.

The paper describes a procedure for the robust design of water distribution networks which incorporates the uncertainty of nodal water demands and pipe roughness in a multiobjective optimization scheme aimed at minimizing costs and maximizing hydraulic reliability. The methodology begins with a deterministic system design in order to generate a set of optimal networks that serves as the initial population for subsequent multiobjective stochastic design. This approach does not depend on the choice of multiobjective optimizer (for example, a multiobjective genetic algorithm is used here) and can drastically reduce the number of “stochastic” runs needed for searching robust solutions. A collection of probability density functions based on the $\beta$ function is introduced and applied to modeling variable uncertainty according to different physical requirements. The approach is tested in a case study involving a real network, illustrating its computational advantages.

A nested optimization problem that utilizes a multiscenario approach based upon a method known as robust optimization is employed to determine a groundwater remediation design that considers the uncertainty in the hydraulic conductivity in the flow and transport model. This optimization approach reduces a complicated multiscenario approach to a simple deterministic method for optimization. The parameter values associated with the final deterministic model represent not the true physical model, but rather a model that results in a conservatively designed remediation system that accounts for the uncertainty in the hydraulic conductivity. Both flow constraints and concentration constraints are considered in this approach, and as such the optimization problem is nonlinear in both its objective function and its constraints. A search method that combines simulated annealing and a downhill simplex algorithm is used to determine the solution to this optimization problem.