Journal of Water Resources Planning and Management

A dimensional analysis approach to a regional analysis of annual flood peaks in much of India is described and developed. Dimensional variables were formed using the mean annual flood, the average rainfall, the rainfall duration, the return period, the drainage area, the catchment slope, the fraction forested, and the gravitational acceleration. The utility of the approach is demonstrated by fitting it to a sample of 93 Indian catchments (river basins) ranging in size from 14.5 km ² to 935,000 km ² , and with record lengths of 10 to 84 years. Most (90%) of the model predictions fall within ±50% of the observed mean annual flood. During the calibration of the model, average rainfall of different durations varying from 0.75 h to 12 h and return period varying from 2 to 25 years were used. The validity of this model was further investigated using the average rainfall of 24 h duration and 2 yr recurrence interval. Although the model was validated with only a 2-yr-return-period 24-h-duration rainfall data, it was found that 85% of the model predictions fell within ±50% of the observed mean annual flood.

A new methodology is developed for determining optimal reservoir releases to minimize the downstream adverse effects in alluvial rivers. The methodology is based on describing the problem as a discrete-time optimal control problem. The solution methodology is based on a differential dynamic programming approach that uses the U.S. Army Corps of Engineers HEC-6 sediment simulation model for the transition equation. The objective of the model is to determine the release policy of an upstream reservoir that minimizes the bed aggradation and degradation along the downstream river. The constrained discrete-time optimal-control problem is transformed into an unconstrained problem using a hyperbolic penalty function that incorporates the bound constraints and the boundary condition into the loss function. Two application examples were used to demonstrate the capability of the model: These include (1) a hypothetical reservoir-river system; and (2) the New Waddell Dam and the Agua Fria River in Maricopa County, Arizona.

The Model State Water Code establishes procedures for definition of water rights and their maintenance over time. Provisions for maintenance become increasingly important with passage of time, as a higher portion of a state's water is subjected to initial allocation. The code presents two distinct options for water-allocation systems that handle water-rights maintenance differently. In the option based on prior appropriation, water rights are issued for an unspecified duration, are not subject to significant governmental restriction while in effect, and are transferred to new water uses by market transactions. In the option compatible with water-use permitting in the eastern United States, permits are subject to specified terms, administrators impose restrictions during permit terms, and transfers to new uses are accomplished primarily by governmental reallocation. Adoption of these fundamentally different approaches is a consequence of recognizing two distinct allocation theories within the Model Code, a decision based on the belief that a significant number of states will continue to rely on each of the two major doctrines for the water-allocation function.

Passage of the Safe Drinking Water Act in 1974 and its Amendments in 1986 (SDWAA) is changing the way water is treated and delivered in the United States. Under the SDWAA the U.S. Environmental Protection Agency (EPA) is required to regulate chemical contaminants and pathogenic microorganisms in drinking water. Emphasis has shifted from a primary concern with treated drinking water to attainment of standards at the point of consumption. Two regulations promulgated under the SDWAA, the Surface Water Treatment Rule (SWTR) and the Total Coliform Rule (TCR) specify treatment and monitoring requirements that must be met by all public water suppliers. This paper will examine the effect of various system variables on chlorine residual propagation. A recently proposed model (EPANET) will be utilized to examine the extent of fluid velocity and pipe radius on chlorine demand. The effect of these variables on the maintenance of chlorine residuals will be demonstrated. It will be shown that the same variables that affect the propagation of chlorine residual levels can potentially affect disinfection efficacy and the formation of disinfection by-products.

Water rationing is a common, but little studied, technique for managing urban water supplies during drought. This paper reviews a wide range of approaches for implementing water rationing for urban drought management. These rationing approaches are assessed in terms of practical and theoretical performance. The paper then examines the potential benefits of allowing drought water rations to be transferable or marketable. Transferable rights have become a common suggestion for allocating scarce resources for a wide range of water-quantity and water-quality problems. Although attractive in terms of economic theories of resource allocation, transferable drought water rations often will be uneconomical for small transactions, due to likely high costs of completing transactions. However, transferable drought water rations might be useful for allocating scarce water among large industrial, commercial, and institutional users and among residential users with very different water demands. The equity effects of transferable drought rations would vary with the initial allocation of water rations. Legal aspects of how transferable rations might be implemented for public water-supply systems remain to be explored.

The Lower Colorado River Authority (LCRA) of Texas is both a water and energy supplier to central Texas. LCRA's power production includes hydroelectric power plants at the six dams of the Highland Lakes reservoir system, on the Colorado River. To improve power generation, LCRA has investigated alternative operating procedures to increase the winter hydroelectric power generation in the upper reservoirs of the Highland Lakes. A methodology using both optimization and simulation techniques was developed to evaluate the ability of the hydroelectric power plants to meet weather-related winter peak power requirements. A linear-programming procedure determined the hourly generation schedule, over a 24-hr period, that maximized the total power generated over the 6 h of peak power demand. Based on statistical simulation of daily winter inflows and releases using a LOTUS 1-2-3 spreadsheet, it was found that the full generating capacity could be supplied to meet winter power demands with no significant impact on water availability or lake water-surface levels. The developed operating plan is being implemented in LCRA power system operations.

Allocation of water in Texas evolved historically over several centuries into an essentially unmanageable system. Water management has progressed significantly in recent years with the transition of riparian rights to a surface-water permit system. Although the “law of the biggest pump” still governs, pressure for ground-water regulation continues to intensify. Water rights have become a major consideration in water-resources development and management in the state. This paper describes the Texas experience in allocating water resources among many competing users. The evolution of the water-rights system is outlined, and key issues remaining to be resolved are noted. The strategies adopted and the complexities encountered in Texas are representative of other states as well.

A differential dynamic programming (DDP) procedure is applied to solve both linear and nonlinear estuarine-management problems to determine the optimal amount of freshwater inflows into bays and estuaries to maximize fishery harvests. Fishery harvests are expressed in regression equations as functions of freshwater inflows. The optimization problem is posed as a discrete-time optimal control problem in which salinity represents the state variable and freshwater inflow represents the control variable. Both linear and nonlinear regression equations that relate salinity to freshwater inflow are used as the transition equations. The bound constraints for the control and state variables are incorporated into the objective function using a penalty-function method to convert the problem into an unconstrained formulation. To guarantee the quadratic convergence of the DDP procedure, a constant-shift and an adaptive-shift method are used. The DDP procedure is applied to the Lavaca-Tres Palacios estuary in Texas and the results are compared with a nonlinear programming solver. This work demonstrates the potential of DDP for developing a more complex model that uses a two-dimensional hydrodynamic-salinity transport model for the transition.

Management of agricultural non-point-source pollution in watersheds requires an integrated approach involving implementation of on-field and off-field management practices. An off-field management practice that is widely used to control sediment and water-borne pollutants from entering surface waters is vegetated buffer (or filter) strips. When situated between a potential pollutant source and a surface water body that receives runoff, vegetated buffer strips have been shown to be very effective in removing substantial amounts of sediment and nutrients (primarily nitrogen and phosphorus) from the runoff. However, the effectiveness of vegetated buffer strips depends not only on their hydrologic and hydraulic characteristics but also on their physical characteristics (e.g., width and placement within the agricultural landscape). This paper examines the influence of width and placement of vegetated buffer strips on sediment yield in an agricultural watershed. The AGNPS hydrologic/water-quality model was linked with ARC/INFO geographic information system to predict sediment yield in the Bluegrass watershed in southern Iowa. The linked modeling system was also used to assess the impact of various buffer strip implementation strategies (width and placement along segments of the perennial stream) on sediment yield. When compared with the baseline condition, consisting of current land use/land management and no buffer strip, the vegetated buffer strip implementation strategies were effective in reducing sediment yield. For example, a buffer strip 30 m wide with a very dense alfalfa/smooth bromegrass stand reduced sediment yield by about 30% compared to the baseline condition. Furthermore, when the vegetated buffer strips were implemented along certain segments of the perennial stream within the watershed, disproportionate reductions in sediment yield were obtained.

Optimal sustained ground-water yield and conjunctive water-use strategies are presented for northeastern Arkansas, based on water demands projected for the five decades of 1990–2039. Each strategy consists of spatially and temporally distributed values of ground-water and surface-water use. The 33,700 km ² region has much irrigation and is very dependent upon ground water. Ground-water flow simulation/ optimization (S/O) models are used to attempt to satisfy temporally increasing water needs for alternative future management scenarios. The S/O models employ a sequential steady-state embedding approach, and contain over 1,600 embedded ground-water and river-volume balance constraints per decade (stage).

A condensed disaggregation procedure has been employed to generate synthetic recharge sequences for the Edwards aquifer in the San Antonio region. Two stochastic processes ae used in the procedure: a multivariate annual flow generator, and an annual-to-monthly disaggregation model. The processes are multivariate, first-order autoregressive, implemented in SPIGOT, and fit to a 58-yr historical record based on U.S. Geological Survey (USGS) recharge estimates for the nine river basins of the Edwards aquifer recharge zone. Transformations of basin recharge are employed in order for the autoregressive models to reproduce the marginal distributions of recharge. Validation of the synthetic recharge generation procedure shows some discrepancies between the marginal distributions, correlations, and drought characteristics of the historical and synthetic flows.

A presented methodology and model compute optimal ground-water use strategies that approximate optimality for water supply, while achieving desired ground-water quality goals. This MODCON approach utilizes a new goal programming-based modification of the advective transport equation. Applied to dispersed ground-water contamination, MODCON allows the accurate constraining of concentrations that will exist in selected locations as a result of optimal pumping. Constraint locations can be initially contaminated, and contaminated ground water can be extracted. MODCON is hierarchical in a sense because a volumetrically optimal strategy is first computed for a study area and then modified only as needed to achieve water-quality goals. In the process, a subsystem that includes the dispersed contamination is selected and discretized. Within this subsystem, transport is modeled with method of characteristics accuracy via modified advective transport equations. These equations are modified in a new approach using coefficients derived through goal programming and external simulation. Application to the Bayou Bartholomew Basin in Arkansas is shown.

Spatially distributed rainfall patterns can now be detected using a variety of remote-sensing techniques ranging from weather radar to various satellite-based sensors. Conversion of the remote-sensed signal into rainfall rates, and hence into runoff for a given river basin, is a complex and difficult process using traditional approaches. Neural-network models hold the possibility of circumventing these difficulties by training the network to map rainfall patterns into various measures of runoff that may be of interest. To investigate the potential of this approach, a very simple 5 × 5 grid cell synthetic watershed is used to generate runoff from stochastically generated rainfall patterns. A backpropagation neural network is trained to predict the peak discharge and the time of peak resulting from a single rainfall pattern. Additionally, the neural network is trained to map a time series of three rainfall patterns into a continuum of discharges over future time by using a discrete Fourier series fit to the runoff hydrograph.