STATE VARIABLE MODEL FOR URBAN RAINFALL-RUNOFF PROCESS1

ABSTRACT: A nonlinear hydrologic system model has been developed for analyzing the urban rainfall-runoff process. The model is formulated as a state variable model consisting of several parameters. A search technique is employed to find the set of parameters for which the model's response best fits observed data. The model could be used in either a simulation or forecasting mode. The model is applied to observed data for the Waller Creek Watershed in Austin, Texas, to develop the model parameters for various levels of urbanization of the watershed. The trend of each parameter with respect to levels of urbanization is examined.     

WATER FOR ENERGY: AN APPROACH TO COMPREHENSIVE IMPACT ASSESSMENT1

ABSTRACT: The effects of energy development on the water resources of the Colorado River and Great Basin regions is expected to be substantial. Complex physical, economic and institutional interactions may be expected. Most research on these impacts appears single purpose, fragmented, uncoordinated, and often inaccessible to potential users - particularly those with responsibility for energy/water policy and program decisions. A comprehensive, integrative framework for assessing alternative water allocation decisions is outlined, taking a heuristic decision making model for evaluating impacts on maximization of gross (or net) regional product, and regional social welfare, and for assessing the region's contribution to national objectives. The suggested model provides a structure for application and integration of data of various kinds to a range of situations arising from possible impacts from energy proposals. The focus is on water and energy relationships but the model may provide a framework for comprehensive analysis of a variety of environmental actions and resulting system perturbations and effects.     

Assessment of environmental impacts part two: Data collection

Intervention analysis is a relatively new branch of time series analysis. The power of this technique, which gives the probability that changes in mean level can be distinguished from natural data variability, is quite sensitive to the way the data are collected. The principal independent variables influenced by the data collection design are overall sample size, sampling frequency, and the relative length of record before the occurrence of the event (intervention) that is postulated to have caused a change in mean process level.For three of the four models investigated, data should be collected so that the post-intervention record is substantially longer than the pre-intervention record. This is in conflict with the intuitive approach, which would be to collect equal amounts of data before and after the intervention. The threshold (minimum) level of change that can be detected is quite high unless sample sizes of at least 50 and preferably 100 are available; this minimum level is dependent on the complexity of the model required to describe the response of the process mean to the intervention. More complex models tend to require larger sample sizes for the same threshold detectable change level.Uniformity of sampling frequency is a key consideration. Environmental data collection programs have not historically been oriented toward data analysis using time series techniques, thus eliminating a potentially powerful tool from use in many environmental assessment applications.     

OPTIMAL MANAGEMENT AND DESIGN OF HYDRAULIC SYSTEMS1

ABSTRACT: A possible methodology is developed to deal with the problem of designing complex pipeline systems, when they are subject to different rates of demand, and when a hypothesis of the flow distribution in different branches is not allowed. The mathematical algorithm used in linear programming. The problem, which is not linear, is dealt with by means of an iterative method; that is, by starting with a possible solution and inserting at each iteration the solution found in the preceding iteration. By taking as variables of the problem the piezometric heads of the ends for each branch of the network, the piezometric gradients and flows, and by thus considering the diameter as a derived variable, it is possible to isolate the nonlinearity in the cost function of the network. The latter is linearized each time close to the solution found in the preceding iteration.     

COST ANALYSIS OF WATER AND WASTE WATER TREATMENT PROCESSES IN DEVELOPING COUNTRIES1

ABSTRACT: Mathematical modeling techniques are used to develop predictive equations for cost of water and waste water treatment processes in developing countries utilizing socioeconomic, environmental, and technological indicators. Predictive equations are developed for each of the three regions (Africa, Asia, and Latin America) for construction, operation, and maintenance costs of slow sand filter, rapid sand filter, stabilization lagoon, aerated lagoon, activated sludge, and trickling filter. Data analysis indicated that cost of water treatment processes is a function of technological indicator (percentage of imported materials), population, and the design capacity. The variables which gave the best correlation for waste water treatment cost were population, design flow, and the percentage of imported waste water disposal materials.     

HYDROLOGIC IMPACT OF WEATHER MODIFICATION1

ABSTRACT: Weather modification is being proposed as a routine method of augmenting agricultural water supplies in the Southern Great Plains. This paper discusses some of the potential hydrologic impacts of weather modification. Previous work in assessing hydrologic impact is covered; the conclusion is drawn that the work is insufficient. An approach based on hydrologic models is suggested that can consider uncertainties about the effect of weather modification on rainfall and some uncertainties about the effect of model error on impact conclusions.     

A SELF-VERIFYING HYBRID COMPUTER MODEL OF RIVER-BASIN HYDROLOGY1

ABSTRACT. As demands upon available water supplies increase, there is an accompanying increase in the need to assess the downstream consequences resulting from changes at specific locations within a hydrologic system. The problem is approached in this study by hybrid computer simulation of the hydrologic system. Modeling concepts are based upon the development of basic relationships which describe the various hydrologic processes. Within a system these relationships are linked by the continuity-of-mass principle. Spatial resolution is achieved by considering the modeled areas as a series of subbasins. The time increment adopted for the model is one month, so that time varying quantities are expressed in terms of mean monthly values. The model is general in nature and is applied to a particular hydrologic system through a programmed verification procedure whereby model coefficients are evaluated for the particular system. In this study the model is applied to the Bear River basin of western Wyoming, southern Idaho, and northern Utah. Comparisons between observed and computed outflow hydrographs show good agreement. The utility of the model is demonstrated by predicting the effects of various possible water resource management alternatives. The verified hybrid computer program can be digitized for application to the digital computer.     

A HYBRID COMPUTER PROGRAM FOR PREDICTING THE CHEMICAL QUALITY OF IRRIGATION RETURN FLOWS1

ABSTRACT. A hybrid computer program was developed to predict the water and salt outflow from a river basin in which irrigation is the major user of water. The model combines a chemical model which predicts the quality of water percolated through a soil profile with a general hydrologic model. The chemical model considers the reactions that occur in the soil, including the exchange of calcium, magnesium, and sodium cations on the soil complex, and the dissolution and precipitation of gypsum and lime. The chemical composition of the outflow is a function of these chemical processes within the soil, plus the blending of undiverted inflows, evaporation, transpiration, and the mixing of sub surface return flows with groundwater. The six common ions of western waters, namely calcium (Ca⁺⁺), magnesium (Mg⁺⁺), sodium (Na⁺), sulfate (SO₄⁼), chloride (Cl^?), and bicarbonate (HCO₃^?) were considered in the study. Total dissolved solids (TDS) outflow was obtained by adding the individual ions. The overall model operates on a monthly time unit. The model was tested on a portion of the Little Bear River basin in northern Utah. The model successfully simulated measured outflows of water and each of the six ions for a 24-month period. The usefulness of the model was demonstrated by a management study of the prototype system. For example, preliminary results indicated that the available water supply could be used to irrigate additional land without unduly increasing the salt outflow from the basin. With minor adjustments the model can be applied to other hydrologic areas.     

FLOOD CONTROL STORAGE ALLOCATIONS BY LINEAR PROGRAMMING1

ABSTRACT. The setting of rule curves for reservoirs or lakes operation requires balancing the flood control storages reserved against the storage requirements for various conservation uses. In this study, a linear programming model is developed to perform single purpose analysis that minimizes flood damages of a multi-lake river system under various initial and input conditions. A flood control utility measure function is arrived from the resulting analysis, and the inclusion of the function in conservation analysis could provide the total functional analysis. The river-system transition function involving time-lags of short duration is described. The function constitutes the basis for the optimization model, and also provides the transformation to reduce significantly the size of the problem. The application to a critical subsystem in the Oswego River System is reported.     

Land Management in the American Southwest: A State-and-Transition Approach to Ecosystem Complexity

State-and-transition models are increasingly being used to guide rangeland management. These models provide a relatively simple, management-oriented way to classify land condition (state) and to describe the factors that might cause a shift to another state (a transition). There are many formulations of state-and-transition models in the literature. The version we endorse does not adhere to any particular generalities about ecosystem dynamics, but it includes consideration of several kinds of dynamics and management response to them. In contrast to previous uses of state-and-transition models, we propose that models can, at present, be most effectively used to specify and qualitatively compare the relative benefits and potential risks of different management actions (e.g., fire and grazing) and other factors (e.g., invasive species and climate change) on specified areas of land. High spatial and temporal variability and complex interactions preclude the meaningful use of general quantitative models. Forecasts can be made on a case-by-case basis by interpreting qualitative and quantitative indicators, historical data, and spatially structured monitoring data based on conceptual models. We illustrate how science- based conceptual models are created using several rangeland examples that vary in complexity. In doing so, we illustrate the implications of designating plant communities and states in models, accounting for varying scales of pattern in vegetation and soils, interpreting the presence of plant communities on different soils and dealing with our uncertainty about how those communities were assembled and how they will change in the future. We conclude with observations about how models have helped to improve management decision-making.