A new methodology for determining a sustainability index (SI) for the management of river basins is developed. Sustainability is defined in terms of minimizing the long-term risks to supply and maintaining the ecological, environmental and hydrological integrity of a river resource. The SI procedure developed uses two groups of performance criteria. The first group is based on demand-supply deficits and measures the risk to water supplies. The second group is only applied to river demands and compares a river’s allocation to a target flow regime using the Range of Variability Approach (RVA) and the Modified Hydrological Alteration factor. The RVA measures differences in flow regimes and is used to compare a projected flow regime to a targeted flow regime. This is the first attempt to use the RVA to develop a sustainability index for river basin management. A combined sustainability metric for the system (SS) is also determined. The methodology is applied to an area including the Prescott Active Management Area (AMA) in north-central Arizona. Sustainability for the entire system is determined using the weighted sum of the sustainability indices. The methodology has been used to measure and compare the sustainability of two allocation scenarios for the Prescott AMA.

This paper presents a new methodology for the sustainable and optimal allocation of water for a river basin management area. The model distinguishes between short and long-term planning horizons and goals using a short-term modeling component (STM) and a long term modeling component (LTM) respectively. An STM is a linear programming problem, and optimizes a monthly allocation schedule on an annual basis in terms of maximum net economic benefit. A cost of depletion is included in the STM net benefit calculation to address the non-use value of groundwater. An LTM consists of an STM for every year of the long-term planning horizon. Each LTM is quantified using a sustainability index, with sustainability defined in terms of risk to supply and ecological, environmental, and hydrological integrity. The LTMs are optimized to determine the most sustainable net economic benefit for the management area using a genetic algorithm. The model is applied to a test case representative of a management area in Arizona in order to highlight its potential utility.

A model for the design of detention basin systems is presented that interfaces a simulated annealing (SA) optimization procedure with the U.S. Army Corps of Engineer’s Hydrologic Engineering Center - Hydrologic Modeling System (HEC-HMS). The optimization model is based upon the simulated annealing method to optimize the size and location of detention basin system including the outlet structures subject to design constraints. The program is implemented in Visual Basic for Applications (VBA) interfacing the simulated annealing model with the HEC-HMS model using an MS Excel environment. The respective result files are created by using a VBA executed Python script to extract the appropriate data from the HEC-HMS project DSS file after each simulation performed for the SA procedure. Example applications include a single detention basin system and multiple detention basin systems considering two scenarios. Though the implementation requires considerable computational effort with respect to the number of hydrologic simulations, simulated annealing proves to be an effective tool in the optimal design of detention basin systems as compared to traditional standards of practice.