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.     

COOPERATIVE MODELING: BUILDING BRIDGES BETWEEN SCIENCE AND THE PUBLIC1

As freshwater resources become more scarce and water management becomes more contentious, new planning approaches are essential to maintain ecologic, economic, and social stability. One technique involves cooperative modeling in which scientists and stakeholders work together to develop a computer simulation model to assist in planning efforts. In the Middle Rio Grande region of New Mexico, where water management is hotly debated, a stakeholder team used a system dynamics approach to create a computer simulation model to facilitate producing a regional plan. While the model itself continues to be valuable, the process for creating the model was also valuable in helping stakeholders jointly develop understanding of and approaches to addressing complex issues. In this paper, the authors document results from post‐project interviews designed to identify strengths and weaknesses of cooperative modeling; to determine if and how the model facilitated the planning process; and to solicit advice for others considering model aided planning. Modeling team members revealed that cooperative modeling did facilitate water planning. Interviewees suggested that other groups try to reach consensus on a guiding vision or philosophy for their project and recognize that cooperative modeling is time intensive. The authors also note that using cooperative modeling as a tool to build bridges between science and the public requires consistent communication about both the process and the product.     

Coming to the table: collaborative governance and groundwater decision-making in coastal California

Collaborative governance is on the rise in the United States. This management approach brings together state and non-state actors for environmental decision-making, and it is frequently used in California for decisions regarding local groundwater management. This study examines groundwater decision-making groups and practices in a central California coastal community to understand whether groups meet specific collaborative governance criteria and whether and why certain subsets of the population are excluded from groundwater decision-making practices. It also identifies actions for better group inclusion. We find that small farmers, the Hispanic/Latino community, and the general public are often excluded from groundwater decision-making groups and practices due to unawareness, mistrust, and insufficient resources. Education and awareness as well as incentives could help increase inclusion. This study provides insights into more equitable groundwater decision-making groups and practices, and also calls for more critical examination of the current stakeholder approach to decision-making.     

COMBINED SURFACE WATER-GROUNDWATER ANALYSIS OF HYDROLOGICAL SYSTEMS WITH THE AID OF THE HYBRID COMPUTER1

The solution with the aid of the hybrid computer of the partial and total differential equations for an integrated surface water groundwater system is described. A versatile computing technique has been developed to make a rapid and accurate study of the groundwater response due to varying inputs (deep percolation) or outputs (evapotranspiration) from the groundwater system. Spatial variations in basic vegetation phenomena, such as pattern, and hydrological parameters, are represented by means of a grid network which also allows the input of variable boundary conditions. The model is applied to an area in Columbia, South America which is subject to high water-table conditions. Various reclamation schemes and management practices under conditions of irrigated agriculture are assessed.     

Towards metrics of sustainable food systems: a review of the resilience and vulnerability literature

Food and nutrition security is a persisting global issue and, in addition, food systems are now facing a new set of intersecting economic, social and environmental challenges. Recurrent socio-economic and biophysical changes put the sustainability of food systems at risk. There is an urgent need to develop knowledge-based tools to assess and monitor food sustainability and to identify pathways for food security and resource conservation. The systemic nature of these interactions calls for multidimensional approaches and integrated assessments for decision-making to guide change. This paper reviews social–ecological system frameworks with the view to conceptualize the sustainability issues that affect the food systems. It is argued that the understanding of the food systems as social–ecological systems, and inputs from the theories of vulnerability and resilience in particular, can provide the concepts necessary to understand and model the complex system dynamics involved in the multiple interactions between human and natural components.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Landcare Networks in Australia: State-sponsored Participation Through Local Organizations

Landcare is an Australian success story and an important example of the potential of state-sponsored community participation. An important trend encouraged by the lead agencies is for Landcare groups to be linked through so-called networks. Linking together may appeal to groups as a way of increasing their capacity to compete for scarce resources and enhance their impact on agencies, regional catchment committees and government. Network formation is also driven by government and agency demands for efficiency, accountability and effective regional planning. In this paper the authors draw on their 1997 study of the Ovens Valley Landcare Network in Victoria. This research suggested networks are important local organisations and enhance the impact of groups by improving inter-group communication and 'pulling down' resources. Network processes also contributed to robust, productive, agency-community partnerships and suggested participation can increase community influence on decision making and be compatible with adaptive management.     

A General Equilibrium Model of Ecosystem Services in a River Basin

This study builds a general equilibrium model of ecosystem services, with sectors of the economy competing for use of the environment. The model recognizes that production processes in the real world require a combination of natural and human inputs, and understanding the value of these inputs and their competing uses is necessary when considering policies of resource conservation. We demonstrate the model with a numerical example of the Mississippi‐Atchafalaya river basin, in which grain production in the upper basin causes hypoxia that causes damages to the downstream fishing industry. We show that the size of damages is dependent on both environmental and economic shocks. While the potential damages to fishing are large, most of the damage occurs from economic forces rather than a more intensive use of nitrogen fertilizers. We show that these damages are exacerbated by increases in rainfall, which will likely get worse with climate change. We discuss welfare effects from a tax on nitrogen fertilizers and investments in riparian buffers. A 3% nitrogen tax would reduce the size of the hypoxic zone by 11% at a cost of 2% of Iowa's corn output. In comparison, riparian buffers are likely to be less costly and more popular politically.     

Communication in Ecosystem Management: A Case Study of Cross-Disciplinary Integration in the Assessment Phase of the Interior Columbia Basin Ecosystem Management Project

Effective communication is essential to the success of collaborative ecosystem management projects. In this paper, we investigated the dynamics of the Interior Columbia Basin Ecosystem Management Projects (ICBEMP) cross-disciplinary integration process in the assessment phase. Using a case study research design, we captured the rich trail of experience through conducting in-depth interviews and collecting information from internal and public documents, videos, and meetings related to the ICBEMP. Coding and analysis was facilitated by a qualitative analysis software, NVivo. Results include the range of internal perspectives on barriers and facilitators of cross-disciplinary integration in the Science Integration Team (SIT). These are arrayed in terms of discipline-based differences, organizational structures and activities, individual traits of scientists, and previous working relationships. The ICBEMP organization included a team of communication staffs (CT), and the data described the CT as a mixed group in terms of qualifications and educational backgrounds that played a major role in communication with actors external to the ICBEMP organization but a minor one in terms of internal communication. The data indicated that the CT-SIT communication was influenced by characteristics of actors and structures related to organizations and their cultures. We conclude that the ICBEMP members may not have had a sufficient level of shared understanding of central domains, such as the task at hand and ways and timing of information sharing. The paper concludes by suggesting that future ecosystem management assessment teams use qualified communications specialists to design and monitor the development of shared cognition among organization members in order to improve the effectiveness of communication and cross-disciplinary integration.     

Cross-achievements between policies for drinking water protection

Environmental dynamics have important spatial dimensions, which calls for a spatial approach in policy analyses. Further to this, assessing agri-environmental policies involves analyses of individual measures as well as their combined effects on farmer behaviour and the environment. The integration of an economic behavioural model in a spatial framework has enabled analyses of a geographically targeted subsidy scheme for drinking water protection in combination with a uniform tax on commercial nitrogen fertilizer. Results show that policy measures for reducing nitrogen use can have combined effects (cross-achievements), thereby affecting each other's cost-effectiveness. Cross-achievements between a nitrogen fertilizer tax and a subsidy scheme based on elicitation are shown not to be additive, making partial analyses of policy measures more uncertain.     

Assessing ICT risk through a Monte Carlo method

To assess and manage the risk due to an information and communication system before its deployment, data of interest can be produced by a Monte Carlo method. This paper presents Haruspex, a software tool that applies a Monte Carlo method to simulate intelligent and adaptive threat agents that reach predefined goals through plan with several attacks. The samples that Haruspex collects are used to compute statistics on the agent’s impacts and their plans as well as to select cost-effective countermeasures. We describe the rationale and the implementation of Haruspex, the inputs it requires and the simulation of how the agents select and implement their plans. After discussing the validation and the performance of the first version of Haruspex, we present a case study and the first set of experimental results.     

Spatial assessment of the economic feasibility of short rotation coppice on radioactively contaminated land in Belarus, Ukraine, and Russia. II. Monte Carlo analysis

A Monte Carlo analysis of two sequential GIS-embedded submodels, which evaluate the economic feasibility of short rotation coppice (SRC) production and energy conversion in areas contaminated by Chernobyl-derived (137)Cs, was performed to allow for variability of environmental conditions that was not contained in the spatial model inputs. The results from this analysis were compared to the results from the deterministic model presented in part I of this paper. It was concluded that, although the variability in the model results due to within-gridcell variability of the model inputs was considerable, the prediction of the areas where SRC and energy conversion is potentially profitable was robust. If the additional variability in the model input that is not contained in the input maps is also taken into account, the SRC production and energy conversion appears to be potentially profitable at more locations for both the small scale and large scale production scenarios than the model predicted using the deterministic model.     

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.     

Ensemble Streamflow Forecast: A GLUE‐Based Neural Network Approach1

Abstract: While training a Neural Network to model a rainfall‐runoff process, generally two aspects are considered: its capability to be able to describe the complex nature of the processes being modeled and the ability to generalize so that novel samples could be mapped correctly. The general conclusion is that, the smallest size network capable of representing the sample distribution is the best choice, as far as generalization is concerned. Oftentimes input variables are selected a priori in what is called an explanatory data analysis stage and are not part of the actual network training and testing procedures. When they are, the final model will have only a “fixed” type of inputs, lag‐space, and/or network structure. If one of these constituents was to change, one would obtain another equally “optimal” Neural Network. Following Beven and others' generalized likelihood uncertainty estimate approach, a methodology is introduced here that accounts for uncertainties in network structures, types of inputs, and their lag‐space relationships by looking at a population of Neural Networks rather than target in getting a single “optimal” network. It is shown that there is a wide array of networks that provide “similar” results, as seen by a likelihood measure, for different types of inputs, lag‐space, and network size combinations. These equally optimal networks expose the range of uncertainty in streamflow predictions and their expected value results in a better performance than any of the single network predictions.     

Silvicultural management in maintaining biodiversity and resistance of forests in Europe-the Mediterranean region

Outstanding features of Mediterranean forest area are highlighted with a special reference to biodiversity and connections with forest management. The naturally originated and anthropogenic progress of the mosaic-like evolution, as well as the man-induced factors and natural constraints are described. The past and present close linkages between management and biodiversity are then analysed by means of a few, outstanding cases typical of the geographical region. The management shift on increasing economically marginal forest area (abandonment) appears to be the major force currently driving connections with inherent and associated biodiversity. The goals following the new-established environmental roles of forests have shifted towards adaptive management, namely the implementation of locally tailored rules in accordance with prominent forest functions. Key priorities to face up to the new scenarios are then discussed.Economic and policy implications are addressed with reference to multipurpose forestry and the related annual flow of outputs. It is shown the role of water-related services, as well the provision of various non-wood forest products and public goods in addition to wood and other traditional forest outputs. Reference is also made to the dualism between the Northern and the South-Eastern Mediterranean countries due to different level of economic development (and pressure of forest resources) together with very different institutional structures, i.e. public ownership in Southern and South-Eastern Mediterranean countries. Nevertheless, the situation is going to become more harmonious in the medium run by growing economic development, the affirmation of local rights on forest resources, globalisation and, above all, rural out migration and exchanges of peoples confirming the traditional role of the Mediterranean Region at cross road of South-North and Eastern-Western cultures.     

A GIS/Simulation Framework for Assessing Change in Water Yield over Large Spatial Scales

Recent legislation to initiate vegetation management in the Central Sierra hydrologic region of California includes a focus on corresponding changes in water yield. This served as the impetus for developing a combined geographic information system (GIS) and simulation assessment framework. Using the existing vegetation density condition, together with proposed rules for thinning to reduce fire risk, a set of simulation model inputs were generated for examining the impact of the thinning scenario on water yield. The approach allows results to be expressed as the mean and standard deviation of change in water yield for each 1-km² map cell that is thinned. Values for groups of cells are aggregated for typical watershed units using area-weighted averaging. Wet, dry, and average precipitation years were simulated over a large region. Where snow plays an important role in hydrologic processes, the simulated change in water yield was less than 0.5% of expected annual runoff for a typical watershed. Such small changes would be undetectable in the field using conventional stream flow analysis. These results suggest that use of water yield increases to help justify forest-thinning activities or offset their cost will be difficult.     

NONLINEAR MODELING AND PREDICTION OF A RIVER FLOW SYSTEM1

ABSTRACT: Model estimation and prediction of a river flow system are investigated using nonlinear system identification techniques. We demonstrate how the dynamics of the system, rainfall, and river flow can be modeled using NARMAX (Nonlinear Autoregressive Moving Average with eXogenuous input) models. The parameters of the model are estimated using an orthogonal least squares algorithm with intelligent structure detection. The identification of the nonlinear model is described to represent the relationship between local rainfall and river flow at Enoree station (inputs) and river flow at Whitmire (output) for a river flow system in South Carolina.     

Pesticides: a wider perspective

Summary The importance of pesticides and other inputs into intensive agriculture is assessed not only in terms of the types of hazards that may arise but also the consequences of such inputs to overall economic structure in the countries concerned. The contrasting level of control of pesticides in countries with more or less advanced economies is examined and some of the dangers associated with pesticide use are discussed.Dr. Kenneth Hassall is Senior Lecturer in the Chemistry of Pesticides at the University of Reading. He is author ofChemistry of Pesticides: their metabolism, mode of action and uses in crop protection. Macmillans, England, 1982.     

PREDICTING IMPACTS FROM WATER CONSERVATION AND ENERGY DEVELOPMENT ON THE SALTON SEA,CALIFORNIA1

ABSTRACT: An input-output model was developed to predict changes in Salton Sea salinity and water level until the year 2000 due to proposed water conservation efforts and geothermal and solar pond energy developments. The model SALINP provided good agreement with the observed salinities for 1960–80. While SALINP was not overly sensitive to one-year changes in any of the major inputs, a change in the historical means of the Imperial Valley runoff and evaporative loss inputs produced a significant effect on future predictions. The proposed water conservation measures caused the predicted Salton Sea salinity for 2000 to greatly exceed 40,000 ppm, the level at which adverse effects to wildlife are believed to occur. The possible geothermal development also produced predicted salinities considerably above 40,000 ppm. The salinity predictions for solar ponds by themselves and in conjunction with geothermal development were below 45,000 ppm for 2000. The solar pond and geothermal combination also resulted in a predicted lowering of the “natural” water level by 5 to 7 feet by 2000.