USE AND MISUSE OF COMPLEX MODELS: EXAMPLES FROM WATER DEMAND MANAGEMENT1

ABSTRACT: The power of computers has increased in recent decades, and one might expect improved management to result because decisions can be made with understanding available only via models. However, there is potential for quite the opposite: poor decisions due to unrealistic model output generated by users without access to appropriate training in the use of models. We discuss and, by reference to water demand models (IWR-MAIN, MWD-MAIN), illustrate three areas in which unintended errors of judgment by untrained personnel may cause difficulty:

• * Attributes of management models; if output from any type of model has no measure of confidence, then results may be over- or undervalued
• * Input data; with complex models, problems here typically will be difficult to detect.
• * Calibration and history-matching (verification); if these steps or data are combined, then users should be less trustful of model output than otherwise.

Because all models have weaknesses and because there always is uncertainty about output from any model, we end with suggestions for coping with complex models. Monitoring programs play a central role in such efforts because they can identify discrepancies between model predictions and actual events and because they can ensure time is available to develop solutions for problems unanticipated in the modeling effort.     

INTEGRATION OF A BASIN-SCALE WATER QUALITY MODEL WITH GIS1

ABSTRACT: Geographic Information Systems (GIS) have been successfully integrated with distributed parameter, single-event, water quality models such as AGNPS (AGricultural NonPoint Source) and ANSWERS (Areal Nonpoint Source Watershed Environmental Response Simulation). These linkages proved to be an effective way to collect, manipulate, visualize, and analyze the input and output date of water quality models. However, for continuous-time, basin large-scale water quality models, collecting and manipulating the input data are more time-consuming and cumbersome due to the method of disaggregation (subdivisions are based on topographic boundaries). SWAT (Soil and Water Assessment Tool), a basin-scale water quality model, was integrated with a GIS to extract input data for modeling a basin. This paper discusses the detailed development of the integration of the SWAT water quality model with GRASS (Geographic Resources Analysis Support System) GIS, along with an application and advantages. The integrated system was applied to simulated a 114 sq. km upper portion of the Seco Creek Basin by subdividing it into 37 subbasins. The average monthly predicted streamflw is in agreement with measured monthly streamflw values.     

INTEGRATION OF WATER QUALITY MODELING,REMOTE SENSING,AND GIS1

ABSTRACT: Water quality modeling has been developed for more than three quarters of a century, but is limited to the study of trends instead of making accurate short-term forecasts. A major barrier to water quality forecasting is the lack of an efficient system for water quality monitoring. Traditional water quality sampling is time-consuming, expensive, and can only be taken for small sizes. Remote sensing provides a new technique to monitor water quality repetitively for a large area. The objective of this research is to use remotely sensed data in a water quality model - QUAL2E - in a case study of the Te-Chi Reservoir in Taiwan. The water quality variables developed from the simulations are displayed in map form. The developed forecasting system is designed to predict water quality variables using remote sensing data as an input to initialize and update water quality conditions.     

WATER QUALITY MODEL OUTPUT UNCERTAINTY AS AFFECTED BY SPATIAL RESOLUTION OF INPUT DATA1

ABSTRACT: Resolution of the input GIS data used to parameterize distributed‐parameter hydrologic/water quality models may affect uncertainty in model outputs and impact the subsequent application of model results in watershed management. In this study we evaluated the impact of varying spatial resolutions of DEM, land use, and soil data (30 × 30 m, 100 × 100 m, 150 × 150 m, 200 × 200 m, 300 × 300 m, 500 × 500 m, and 1,000 × 1,000 m) on the uncertainty of SWAT predicted flow, sediment, NO₃‐N, and TP transport. Inputs included measured hydrologic, meteorological, and watershed characteristics as well as water quality data from the Moores Creek watershed in Washington County, Arkansas. The SWAT model output was most affected by input DEM data resolution. A coarser DEM data resolution resulted in decreased representation of watershed area and slope and increased slope length. Distribution of pasture, forest, and urban areas within the watershed was significantly affected at coarser resolution of land use and resulted in significant uncertainty in predicted sediment, NO₃‐N, and TP output. Soils data resolution had no significant effect on flow and NO₃‐N predictions; however, sediment was overpredicted by 26 percent, and TP was underpredicted by 26 percent at 1,000 m resolution. This may be due to change in relative distribution of various hydrologic soils groups (HSGs) in the watershed. Minimum resolution for input GIS data to achieve less than 10 percent model output error depended upon the output variable of interest. For flow, sediment, NO₃‐N, and TP predictions, minimum DEM data resolution should range from 30 to 300 m, whereas minimum land use and soils data resolution should range from 300 to 500 m.     

WATER QUALITY MODELING IN THE UPPER REACHES OF THE CHOWAN RIVER1

ABSTRACT: The Chowan River system consists of three rivers in southeast Virginia that form two confluences before flowing into Albermarle Sound in North Carolina. A computer program was written to simulate flows through the river system to determine flow rates, velocities, and depths. The output of the flow program was input into a second program that calculated the concentrations of BOD₅, COD, DO, and four nitrogen parameters (organic, ammonia, nitrite-nitrate and algal-N). Measured field data were used to calibrate the model. The effect of reducing the concentration of nutrients from overland runoff on algal concentrations at the mouth of the river was studied. The program was also run to simulate the water quality of the watershed in a primitive condition, in which the watershed was assumed to consist only of forests. The results of the computer program indicate that the major changes in the water quality of the river are simulated satisfactorily. The program can be used to assess the impact of any management scheme to improve water quality.     

NETWORK DESIGN FOR WATER SUPPLY FORECASTING IN THE WEST1

ABSTRACT: The objective is to develop techniques to evaluate how changes in basic data networks can improve accuracy of water supply forecasts for mountainous areas. The approach used was to first quantify how additional data would improve our knowledge of winter precipitation, and second to estimate how this knowledge translates, quantitatively, into improvement in forecast accuracy. A software system called DATANET was developed to analyze each specific gage network alternative. This system sets up a fine mesh of grid points over the basin. The long-term winter mean precipitation at each grid point is estimated using a simple atmospheric model of the orographic precipitation process. The mean runoff at each grid point is computed from the long-term mean precipitation estimate. The basic runoff model is calibrated to produce the observed long-term runoff. The error analysis is accomplished by comparing the error in forecasts based on the best possible estimate of precipitation using all available data with the error in the forecasts based on the best possible estimate of winter precipitation using only the gaged data. Different data network configurations of gage sites can be compared in terms of forecast errors.     

BASIN SCALE WATER MANAGEMENT AND FORECASTING USING ARTIFICIAL NEURAL NETWORKS1

ABSTRACT: Water scarcity in the Sevier River Basin in south‐central Utah has led water managers to seek advanced techniques for identifying optimal forecasting and management measures. To more efficiently use the limited quantity of water in the basin, better methods for control and forecasting are imperative. Basin scale management requires advanced forecasts of the availability of water. Information about long term water availability is important for decision making in terms of how much land to plant and what crops to grow; advanced daily predictions of streamflows and hydraulic characteristics of irrigation canals are of importance for managing water delivery and reservoir releases; and hourly forecasts of flows in tributary streams to account for diurnal fluctuations are vital to more precisely meet the day‐to‐day expectations of downstream farmers. A priori streamflow information and exogenous climate data have been used to predict future streamflows and required reservoir releases at different timescales. Data on snow water equivalent, sea surface temperatures, temperature, total solar radiation, and precipitation are fused by applying artificial neural networks to enhance long term and real time basin scale water management information. This approach has not previously been used in water resources management at the basin‐scale and could be valuable to water users in semi‐arid areas to more efficiently utilize and manage scarce water resources.     

COMPUTER ASSISTED NEGOTIATION OF MULTIOBJECTIVE WATER RESOURCES CONFLICTS1

ABSTRACT: Since the early 1970s, a large volume of literature has accumulated related to multiobjective water resources management problems. A relatively small portion of this specifically addresses the negotiation process required when there are multiple decision makers with conflicting objectives. This paper focuses on that process and describes a computer program designed to assist such negotiation processes. This interactive computer assisted negotiation support system is called ICANS. ICANS is designed for dynamic, multi-issue, multi-party negotiation problems. Based on information provided in confidence by each party via an interactive graphical interface, the program can help determine if there exist any possible alternatives that are equivalent or even preferred to each party's decision in the absence of a negotiated agreement. If such alternatives exist, through a series of iterations in which each party's input data, assumptions, and preferences may change, ICANS can assist the parties in their search for a mutually acceptable and preferred agreement. A simple example illustrates the data requirements and the use of ICANS in negotiation experiments.     

DOWNSCALED CLIMATE AND STREAMFLOW STUDY OF THE SOUTHWESTERN UNITED STATES1

ABSTRACT: Downscaling coarse resolution climate data to scales that are useful for impact assessment studies is receiving increased attention. Basin-scale hydrologic processes and other local climate impacts related to water resources such as reservoir management, crop and forest productivity, and ecosystem response require climate information at scales that are much finer than current and future GCM resolutions. The Regional Climate System Model (RCSM) is a dynamic downscaling system that has been used since 1994 for short-term precipitation and streamflow predictions and seasonal hindcast analysis with good skill. During the 1997–1998 winter, experimental seasonal forecasts were made in collaboration with the NOAA Climate Prediction Center and UCLA with promising results. Preliminary studies of a control and 2°CO₂ perturbation for the southwestern U.S. have been performed.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part I: A Review of Metrics and Adjoint Methods

Irrigation management consists of many components. In this work we review and recommend rainfall forecast performance metrics and adjoint methodologies for the use of predictive weather data within the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE estimates crop water uses to optimize irrigation scheduling. WISE and its components, input requirements, and related software design issues are discussed. The use of predictive weather allows WISE to consider economic opportunity‐costs of decisions to defer water application if rainfall is forecast. These capabilities require an assessment of the system uncertainties and use of weather prediction performance probabilities. Rainfall forecasts and verification performance metrics are reviewed. In addition, model data assimilation methods and adjoint sensitivity concepts are introduced. These assimilation methods make use of observational uncertainties and can link performance metrics to space and time considerations. We conclude with implementation guidance, summaries of available data sources, and recommend a novel adjoint method to address the complex physical linkages and model sensitivities between space and time within the irrigation scheduling physics as a function of soil depth. Such tool improvements can then be used to improve water management decision performance to better conserve and utilize limited water resources for productive use. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

EVALUATION OF PRACTICES IN WATER SUPPLY FORECASTING1

ABSTRACT: Snowmelt runoff is a primary source of water supply in much of the Western United States. Multipurpose planning requires long-range forecasts and the accuracy of the forecasts has a significant effect on economic benefits. In an effort to increase the accuracy of snowrnelt runoff forecasts, selected practices in water supply forecasting were evaluated. These practices include 1) using multiple regression in developing forecasting models;2) using a model that was calibrated to make forecasts an April 1 for making forecasts at other times;3) using maximum snow water equivalent measurements in forecast equations; and 4) using weighted snow water equivalent measurements for making forecasts. The results of a case study indicate that forecasting accuracy is significantly affected by these practices. Goodness-of-fit statistics may not be indicative of the accuracy of forecasts when the prediction equations are used to make forecasts for dates other than that used in calibration. The use of maximum snow water equivalentmeasurements and weighted averages did not improve forecast accuracy.     

AN ECONOMIC OVERVIEW OF HAWAII'S WATER INSTITUTIONS1

ABSTRACT: The problem of allocating scarce water resources among competing uses and users over time in Hawaii is addressed within the context of analytical institutional economics. The nature of this problem has been, in recent years, highly complicated by important institutional changes that control operating decisions for water supply and water pollution. Whereas the imbalance in governmental initiatives regarding changes in the system of water rights (predominantly state) and environmental laws (predominantly federal) are based on U.S. constitutional provisions, the more fundamental roots of the crucial legal doctrines involved have been traced back to the common property concept. This suggests that the more promising opportunities for meeting the water policy challenges of the state are to be found in the historical common property system (ahupua'a) of Hawaii.     

WATER RESOURCE MANAGEMENT AND DROUGHT FORECASTS IN SOUTH CAROLINA1

ABSTRACT: Despite potential benefits for resource planning, community water systems managers have not used seasonal climate forecasts extensively. Obstacles to forecast use include a lack of awareness of their existence, distrust of their accuracy, perceived irrelevance to management decisions, and competition from other technological innovations. In this paper, ways in which seasonal forecasts might be extended to address more directly some concerns of South Carolina community water systems managers are explored. From May 1998 through August 2002, this group experienced drought conditions that threatened water quality and supply and required restrictions on water consumption. Methods for incorporating long lead forecasts with joint probabilities of monthly temperature and precipitation to produce drought forecasts are demonstrated. When tailored to specific places, such forecasts show the likelihood of exceeding drought thresholds that would trigger water use restrictions. The methods illustrate how long lead forecasts can be extended and customized into secondary products that address issues of greater relevance to water resource managers.     

QUANTIFICATION OF INSTREAM FLOW NEEDS OF A WILD AND SCENIC RIVER FOR WATER RIGHTS LITIGATION1

ABSTRACT: The lower 4 miles of the Red River, a tributary of the Rio Grande in northern New Mexico, was designated as one of the “instant” components of the National Wild and Scenic River System in 1968. The Bureau of Land Management (BLM), as the managing agency of the wild and scenic river, was a participant in a general water rights adjudication of the Red River stream system. The BLM sought a federal reserved water right and asserted a claim to the instream flows necessary to protect and maintain the values of the river. Instream flows are not recognized under New Mexico water law. Instream flow requirements were determined by several methods to quantify the claims made by the United States for a federal reserved water right under the Wild and Scenic Rivers Act. The scenic (aesthetic), recreational, and fish and wildlife values are the purposes for which instream flow requirements were claimed. Since water quality is related to these values, instream flows for waste transport and protection of water quality were also included in the claim. The U.S. Fish and Wildlife Service's Instream Flow Incremental Methodology was used to quantify the relationship between various flow regimes and fish habitat. Experience in this litigation indicates the importance of using state-of-the-art methodologies in quantifying instream flow claims. The incremental methodology held up well under technical and legal scrutiny and is an example of the latest methodology that was applied successfully in an adjudication. On February 23, 1984, the parties involved in the adjudication entered a precedential stipulation recognizing a federal reserved right to instream flows for the Red River component of the National Wild and Scenic River System.     

THE ACCURACY OF WATER USE FORECASTS: EVALUATION AND IMPLICATIONS1

ABSTRACT: Forecasts of 1980 river basin water use presented in the reports of the 1960 Senate Select Committee on National Water Resources and in the Water Resources Council's First National Water Assessment of 1968 were compared to estimates of actual use in 1980 to assess the accuracy of efforts to forecast future water use. Results show that the majority of the forecasts were substantially in error. In general, the First National Assessment forecasts erred by a smaller margin, but tended to repeat the regional patterns of overestimation (underestimation) exhibited in the Senate Select Committee forecasts. Moreover, forecasts of the two groups that came within 20 percent of the 1980 withdrawals, in general were accurate, not because of superior prediction, but because of offsetting errors in forecast components. This performance leads us to conclude that water use forecasts, regardless of the time-frame or the forecast method employed, are likely to always be highly inaccurate. Accordingly, if such forecasting efforts are to be of value in contemporary water resources planning, forecasters should direct their attention toward methods which will illuminate the determinants of the demand for water.     

SPATIAL CLUSTERS OF SUBSURFACE DRAINAGE WATER NO3‐N LEACHING LOSSES1

ABSTRACT: Grouping of nitrate‐nitrogen (NO₃‐N) leaching losses from agricultural fields into spatial clusters can help determine the cause/effect relationships for their occurrence. This study was designed to investigate the spatial relationships of low, medium, and high NO₃‐N leaching losses clusters with soil and landscape attributes using cluster and discriminant analysis and the map overlay capability of a geographical information system (GIS). Field measured data of a six‐year (1993 through 1998) study on NO₃‐N leaching losses from 36 experimental fields at the Iowa State University's northeastern research center near Nashua, Iowa, were normalized on an annual basis to compare over the years. The cluster analysis resulted in the formation of three clusters based on the satisfactory evaluation criteria of pseudo‐F statistic, cubic clustering criterion, and R² values. The discriminant analysis, carried out on the basis of clusters, identified elevation and subsurface drainage as the factors that contributed significantly (p > 0.01) in discriminating among these clusters. The verification of discriminant functions developed on these factors predicted the cluster membership for all the groups with an overall accuracy of 86 percent. The map overlay analyses of GIS showed that spatial occurrence of the clusters transporting high NO₃‐N leaching losses was affected by the interaction of soil type and elevation levels.     

ACCOMMODATING CHANGE OF BACTERIAL INDICATORS IN LONG TERM WATER QUALITY DATASETS1

ABSTRACT: In 1996, the State of Oregon adopted a water quality standard based on Escherichia coli (E. coli), recognizing E. coli as an indicator of pathogenic potential. The Oregon Department of Environmental Quality (DEQ) began analysis for E. coli that same year. The Oregon DEQ continued collection and analysis of fecal coliform (a prior indicator organism) for data input to bacterial loading models and the Oregon Water Quality Index (OWQI). The OWQI is a primary indicator of general water quality for the Oregon DEQ and the Oregon Progress Board. The objective of this study was to develop a regression relationship between fecal coliform and E. coli. This relationship would fill data gaps and extend water quality models and indicators. Water quality policy is better informed by the ability of these extended water quality models to determine whether water quality meets present or would have met past bacterial standards. Monitoring resources spent on dual bacterial analyses could be conserved. This study also showed that changes to OWQI values (as a result of changing bacterial indicators) were minimal, and corresponded to improved characterization of water quality with respect to pathogenic potential.     

WATER QUALITY MODEL CALIBRATION: A COMPARISON OF INPUT AND OUTPUT ERROR CRITERIA1

ABSTRACT: A common framework for the analysis of water resources systems is the input-parameter-output representation. The system, described by its parameters, is driven by inputs and responds with outputs. To calibrate (estimate the parameters) models of these systems requires data on both inputs and outputs, both of which are subject to random errors. When one is uncertain as to whether the predominant source of error is associated with inputs or outputs, uncertainty also exists as to the correct specification of a calibration criterion. This paper develops and analyzes two alternative least squares criteria for calibrating a numerical water quality model. The first criterion assumes that errors are associated with inputs while the second assumes output errors. Statistical properties of the resulting estimators are examined under conditions of pure input or output error and mixed error conditions from a theoretical perspective and then using simulated results from a series of Monte Carlo experiments.     

MODELING AND CONTROL OF THE POLLUTION OF WATER RESOURCES SYSTEMS VIA MULTILEVEL APPROACH1

ABSTRACT. The problem of modeling and control of water pollution is considered. A general mathematical model, where the pollution effluent is discharged directly into the river, into the lake, or into a bypass pipe leading to an advanced Waste Water Treatment (AWT) plant, is developed. The Water Resource System (WRS) under consideration is decomposed into N subsystems. The pollution effluent input vector to each subsystem includes the water quantity and different water characteristics such as BOD, DO, pH, conductivity, temperature, algae, phosphates, nitrates, etc. Treatment cost functions and quality transition functions as well as system model constraints are introduced, where all functions can be nonlinear. A system Lagrangian is formed to incorporate the system constraints and coupling. The Lagrangian is decomposed into N independent subsystems, and a two level optimization methodology is introduced. Each subsystem is independently and separately minimized at the first level assuming known Lagrange multipliers. At the second level, the total Lagrangian is maximized with respect to the Lagrange multipliers using optimal values for effluent inputs from all subsystems obtained from the first level. Economic interpretation on the Lagrange multipliers reveals that they are merely prices imposed by the central authority (second level) for the pollution caused by the subsystems. Advantages of the multilevel approach are discussed.     

A PROCEDURE FOR ASSESSING WATER RESOURCES FOR URBAN PLANNING1

A matrix has been developed to guide the assessment of urban water resources. The matrix provides a means for determining the relative importance of water-related problems, and for identifying the data needed to evaluate these problems for the purpose of urban planning. The matrix columns list nine categories of potential water-related urban problems. The rows list 51 categories of data inputs which may be needed to evaluate the potential problems. The inputs include standard types of basic hydrologic data, information based on analysis and interpretation of these data, and information on the interfacing factors of climate, land, and culture. A system is described for ranking the relative importance of the problem categories and data inputs on a numerical scale of 0 to 3. From this, an index is derived that evaluates the relative importance of each input item to an overall program for water resource assessment. From the completed matrix the hydrologist can determine the availability of data to meet the identified requirements. Judgement can then be made as to priorities on work elements to provide the planner with maximum information in minimum time. The matrix also provides a basis for the development of programs and their funding in order to overcome critical data deficiencies.