Journal of Water Resources Planning and Management

Using long-term (1948–1996) pan evaporation measurements, a 6% increase in warm-season (May–October) actual evapotranspiration (ET) is computed over the conterminous United States between 1949 and 1996 via the complementary hypothesis. This predicted increase in ET is in agreement with the measured precipitation increase for the same period if long-term wet-surface ET is assumed to be constant. Long-term relative humidity and air temperature measurements express an increase in mean air temperature and water vapor concentration but not a statistically significant change in vapor pressure deficit. The latter implies a smaller than 6% increase in actual warm-season ET. Water-balance estimates for six watersheds, covering about 50% of the land area of the contiguous states of the United States, indicate a 3% increase in annual ET over the same period.

Most large nonlinear optimization models are composed of “pieces”—subsets of decision variables—and constraints whose union is the entire model. Each piece represents an additional aspect of the situation being modeled. This opens the possibility of solving the simplest piece first, adding the constraints and variables of another piece, and solving this submodel from a starting point provided by the first solution. This process is repeated until the original model is solved. This “piece-by-piece” approach provides each submodel with a good starting point, which greatly increases the probability that a good nonlinear solver will find an optimal solution. We apply it to a large multiperiod nonlinear programming (NLP) model with 13,700 variables, 10,000 equations, and a high degree of nonlinearity (54.3% of the nonzero Jacobian elements are nonconstant), arising from water resources planning and operation in a river basin. Using the GAMS modeling language and the CONOPT2 NLP solver, the piece-by-piece method is able to solve this model, while all attempts to solve the complete model from various starting points fail to find a feasible solution.

We assess the economic impacts of some externalities from mine dewatering using the discrete choice version of the contingent valuation method. “Dewatering” refers to the pumping of ground water from areas surrounding mines. Our focus is on the dewatering being conducted by the large open-pit gold mines located in the Humboldt River basin of northern Nevada and its downstream impacts. Results indicate that in the short term the mines have created a positive externality for downstream parties. In the long term downstream impacts may be negative, but upstream “pit lakes” will be created that may have some value to users, depending on the lakes' quality.

Two main goals are achieved in this review of the empirical literature on factors affecting conflict resolution in watershed partnerships. The first is an assessment of two public policy theories relevant to partnership structure and function. The second is a set of practical suggestions for designing successful partnerships. The 37 available studies collectively identified 210 “lessons learned,” which were grouped into 28 thematic categories. The most frequently recurring themes are the necessity of adequate funding (62% of the studies), effective leadership and management (59%), interpersonal trust (43%), and committed participants (43%). Exploratory factor analysis was used to search for patterns in the lessons. Four factors were identified, which together explain 95% of the variance in the 28 themes. The first two factors emphasize the importance of (1) balancing the partnership's resources with its scope of activities; and (2) employing a flexible and informal partnership structure. The third and fourth factors offer modest support for two theoretical perspectives on collaborative resource management—the alternate dispute resolution framework and the institutional analysis and development framework.

Many aquatic species of management interest, such as endangered, sport, or commercially valuable fish, move extensively within a hydrosystem as they use different habitats for spawning, rearing, feeding, and refuge. Engineering tools are presently inadequate to simulate movement by such species as part of the water resources planning and management. We describe how fixed grid-cell methods can be coupled with mobile object-oriented modeling methods (called Eulerian-Lagrangian methods) to realistically simulate movement behavior of fish in the complex hydraulic and water quality fields of aquatic ecosystems. In the coupled system, the Lagrangian framework is used to simulate the movement of symbolic fish (that is, an individual fish, schools of fish, or some aggregate of the population), and the Eulerian framework is used to simulate the physicochemical regimes that influence fish movement behavior. The resulting coupled Eulerian-Lagrangian hybrid modeling method is based on a particle-tracking algorithm supplemented with stimuli-response rules, that is, the numerical fish surrogate.

Computer based floodplain delineation tools have become increasingly popular in flood hazard mapping and floodplain management. Water resources engineers are using these tools as a part of their professional practices. A number of available tools with varying levels of complexity and different approaches have been examined for their uniqueness, strength, and suitability. These methods are explained and discussed in detail to provide a better understanding of the automated floodplain delineation. This increased understanding when combined with the practitioner's experience in hydraulic modeling will lead to better application. Refinements are presented that combine the strength of current methods and overcome existing limitations.

Latin hypercube sampling (LHS) and the mean first-order reliability method are applied to determine the parameters significantly affecting uncertainty in the simulated dissolved oxygen (DO) concentrations at the point in the Zenne River in Brussels, most prone to low concentrations. The DO simulation involves the coupling of a nonpoint pollution load model, a constant treatment efficiency model, and a river water-quality model. LHS found that six of the 53 model parameters significantly contribute to the variance of the annual mean DO concentration, and five model parameters significantly contribute to the variance in the number of hours that DO concentrations are <2 mg/L. The mean first-order reliability method found that these parameters accounted for 73.6 and 84.7% of the variance in the respective output features. Reanalysis with LHS, letting only these six parameters be uncertain, confirmed the identification of these parameters as accounting for 78.1 and 83.0% of the respective variances. The identification of key sources of uncertainty provided insight with respect to treatment plant operation, model improvements, and data collection programs.