Journal of Water Resources Planning and Management

A chance‐constrained optimization model for a stream‐aquifer system is developed using an approximate solution for the transient drawdown of the water table of an aquifer by a well operating near a river. The model explicitly considers the random nature of the hydraulic conductivity and specific yield of an unconfined aquifer. This enables the determination of the optimal groundwater pumping pattern and induced recharge from the stream to the aquifer (i.e., stream depletion rate) under specified system performance probability requirements. An application of the model is demonstrated using a hypothetical problem, and the sensitivity of the results is examined by varying probability requirements and the statistical properties of the aquifer parameters, which are: the coefficient of variation of the loghydraulic conductivity; the coefficient of variation of the log‐specific yield; and the correlation between the log‐hydraulic conductivity and log‐specific yield. The results obtained by the model indicate that the optimal pattern of pumping rates obtained by the management policy are highly sensitive to the probability levels and coefficient of variation of the log‐hydraulic conductivity. The induced rate of stream depletion is insensitive to the coefficient of variation of the log‐specific yield and is slightly sensitive to the probability levels. In contrast, the induced stream depletion rate is highly sensitive to the hydraulic conductivity statistics.

EPA'S Storm Water Management Model (SWMM) simulates all aspects of the hydrologic and quality cycles. Using expert system technology, an interactive user‐support framework has been developed to automate the calibration of the runoff block. It acts as a front end to assist the user in the initial estimation of the parameter values and in building the SWMM input files. It interprets the simulation results and suggests some useful adjustments in the value of significant parameters thus reducing the user's time and effort. For the interpretation of simulation results, production rules are employed to help the user decide what parameters need to be adjusted. Some heuristics have been developed to evaluate the new parameter values. The combination of simulation techniques and expert system methodologies facilitates the use of sophisticated models such as SWMM.

The safety of many existing dams could be improved by modifying hem structurally in accordance with recent advances in statistical hydrology and mproved availability of meteorological and hydrological data. Any increase insafety that might be gained by structural changes must be balanced against their costs. The risk analysis methodology known as the partitioned multiobjective risk method (PMRM) is explored in this paper through a dam‐safety problem. The PMRM is well suited to the task of solving the probabilistic optimization problem posed by such risk‐versus‐cost considerations. With the PMRM, a number of conditional expected‐damage functions are generated. Of these, one that represents events of a more extreme and catastrophic character is of particular interest here. The close relationship that exists between the expectation of damage and the statistics of extremes is shown to simplify the implementation of the PMRM, and the relationship also permits the derivation of closed‐form equations that determine (for any partitioning of the probability axis) the expected damage, given that a flood with a return period that equals or exceeds n years occurs. Finally, an analysis is made as to how the choice of the distribution function representing the annual flood peaks might affect the conditional expectations.

A reliable method of predicting long‐term future lake levels with associate exceedance frequencies is essential to establish planning elevations in the lakeshore environment. A methodology is proposed here to develop level‐frequency relationships for terminal lakes. The methodology is applied to Devils Lake, North Dakota. An autoregressive moving average (ARMA) model with a deterministic trend component for the annual storage changes is used as the basis. The storage changes are derived from the historical annual average level time series, and the level‐storage relationship. Using the validated ARMA model and simulation techniques, many sequences of annual incremental storage time series are generated. The concepts of mass curve and range analysis are applied to each synthetic sequence for deriving maximum and minimum lake volumes in each sequence. The resulting set of maximum and minimum lake volumes are then analyzed for their underlying frequency distributions. Utilizing the elevation‐storage function, the lake volume‐frequency relationship is converted to an annual average lake level‐frequency relationship. A separate treatment of within‐year maximum fluctuations about the average level is also developed. Both the average level and within‐year maximum fluctuation distributions represent the stochastic behavior of the lake and thus are found to be necessary to the development of the level‐frequency relationship.

Although a vast amount of literature exists on the selection of an appropriate probability distribution for annual maximum floodflows, few studies have examined which probability distributions are most suitable to fit to sequences of annual minimum streamflows. Probability plots have been used widely in hydrology as a graphical aid to assess the goodness of fit of alternative distributions. Recently, probability‐plot correlation‐coefficient (PPCC) tests were introduced to test the normal, two‐parameter lognormal and Gumbel hypotheses. Those procedures are extended here to include both regional and at‐site tests for the two‐parameter Weibull and lognormal distributional hypotheses. In theory, PPCC‐hypothesis tests can only be developed for two‐parameter distributions that exhibit a fixed shape. Nevertheless, the PPCC is a useful goodness‐of‐fit statistic for com‐paring three‐parameter distributions. The PPCC derived from fitting the two‐ and three‐parameter lognormal, two‐ and three‐parameter Weibull, and log‐Pearson type III distributions to sequences of annual minimum seven‐day low flows at 23 sites in Massachusetts are compared. How the PPCC can be used to discriminate among both competing distributional hypotheses for the distributions of fixed shape and competing parameter‐estimation procedures for the distributions with variable shape is described. An approximate regional PPCC test is developed and used to show that there is almost no evidence to contradict the hypothesis that annual minimum seven‐day low flows in Massachusetts are two‐parameter lognormal.

In the long term Syria has a high potential for development of irrigated agriculture. To define this potential, the available water and land resources are assessed. The total area of Syria is about 18.5×106 ha, of which only 618,000 ha are under irrigation and 3,117,000 ha are cropped under rainfed conditions. The available water resources in Syria are estimated at about $25\times {10}^9{m}^3/\mathrm{yr}$ taking into account the Syrian share of international rivers and excluding the Tigris River. Only 54% of the water volume is from the Euphrates, whereas the rest is divided between the Euphrates tributaries, other rivers, springs, and wells. At present only $8.9\times {10}^9{m}^3/\mathrm{yr}$ are being used, including $3.0\times {10}^9{m}^3/\mathrm{yr}\text{,}$ wasted to evaporation or to the sea. In order to fully utilize the available resources, around 1,500,000 ha may be irrigated. These will utilize about $20\times {10}^9{m}^3/\mathrm{yr}\text{.}$ This means increasing the area of irrigated land 150% in the future. This is a manageable target. If a rate of development of 80‐100,000 ha per 5‐yr plan is achieved, an expected development period of 40‐50 yr would be required to develop the country's resources. Present achievements in this regard are around 12,000 ha/yr only.

Regionalization is often recommended to help solve the water supply industry's problems but it has received little sustained policy attention. It offers three potential classes of benefits: economies of scale, extension of service to needy areas, and enhanced water quality. Recent reported trends include: consolidation of systems in growing areas, extension of the influence of strong central water suppliers, mergers of investor‐owned utilities, state government initiatives, and voluntary cooperation among utilities. Action at the local level is impeded by political considerations but cooperation or integration can be considered on a caseby‐ case basis. Action at the state level is needed because federal intervention will not be favorably received and decisive local action is unlikely except in a few major populations centers. The state level can serve as facilitator, broker, and regulator to resolve thorny institutional issues. To support such state actions, research is needed to determine the effectiveness of existing legislation and programs. The roles needed from the federal government are policy leadership and financing of research. Without the federal presence, a vacuum in policy analysis and research occurs. Little is known about industry‐wide trends in water rates, since they are not subjected to much regulatory scrutiny, and since the industry lacks centralized financial statistics. Improved data bases could aid in overcoming management problems that stem from the lack of both market incentives and economic regulation.

The sequencing problem for hydropower station development is a multidimensional problem involving space‐time decisions. In this paper, a mathematical model that uses a combination of dynamic programming and mixed‐integer programming is developed, and an efficient algorithm for its use in optimal sequencing problems is presented. The dynamic‐programming submodel (DPM) generates the alternative possible combinations of hydropower and thermal power stations (i.e., states) and analyzes the different sequences of hydropower station development. The mixed‐integer programming submodel (MIPM) simulates the operation of the power system and determines the minimum fuel‐cost operating policy. The MIPM requires an auxiliary flow regulation submodel (FRM). The combined use of the DPM, MIPM, and the FRM provides investment and operation decisions in one run. Therefore, the optimal development sequence of the hydropower stations and the timing of installation of power‐generating units in each station are obtained from the solution of the DPM‐MIPM‐FRM model. This model is applied to the preliminary planning of hydropower stations on the Wujiang River in the southwestern region of China, and the results are described.