TRANSIENT RESPONSE FUNCTIONS FOR CONJUNCTIVE WATER MANAGEMENT IN THE SNAKE RIVER PLAIN,IDAHO1

ABSTRACT: Increasing demands on western water are causing a mounting need for the conjunctive management of surface water and ground water resources. Under western water law, the senior water rights holder has priority over the junior water rights holder in times of water shortage. Water managers have been reluctant to conjunctively manage surface water and ground water resources because of the difficulty of quantification of the impacts to surface water resources from ground water stresses. Impacts from ground water use can take years to propagate through an aquifer system. Prediction of the degree of impact to surface water resources over time and the spatial distribution of impacts is very difficult. Response functions mathematically describe the relationship between a unit ground water stress applied at a specific location and stream depletion or aquifer water level change elsewhere in the system. Response functions can be used to help quantify the spatial and temporal impacts to surface water resources caused by ground water pumping. This paper describes the theory of response functions and presents an application of transient response functions in the Snake River Plain, Idaho. Transient response functions can be used to facilitate the conjunctive management of surface and ground water not only in the eastern Snake River Plain basin, but also in similar basins throughout the western United States.     

AN EVALUATION OF THE AVAILABLE TECHNIQUES FOR ESTIMATING MISSING FECAL COLIFORM DATA1

ABSTRACT: This paper presents the findings of a study aimed at evaluating the available techniques for estimating missing fecal coliform (FC) data on a temporal basis. The techniques investigated include: linear and nonlinear regression analysis and interpolation functions, and the use of artificial neural networks (ANNs). In all, seven interpolation, two regression, and one ANN model structures were investigated. This paper also investigates the validity of a hypothesis that estimating missing FC data by developing different models using different data corresponding to different dynamics associated with different trends in the FC data may result in a better model performance. The FC data (counts/100 ml) derived from the North Fork of the Kentucky River in Kentucky were employed to calibrate and validate various models. The performance of various models was evaluated using a wide variety of standard statistical measures. The results obtained in this study are able to demonstrate that the ANNs can be preferred over the conventional techniques in estimating missing FC data in a watershed. The regression technique was not found suitable in estimating missing FC data on a temporal basis. Further, it has been found that it is possible to achieve a better model performance by first decomposing the whole data set into different categories corresponding to different dynamics and then developing separate models for separate categories rather than developing a single model for the composite data set.     

环境政策作用机制的分析框架

了解环境政策作用机制是环境政策有效调控的前提和核心,准确理解环境政策作用的背景、成因、过程、作用机制、效应动态、演变规律等;全面而深刻地环境政策副作用和变形的生成-演变规律,了解政策副作用形成机制、传导机制、积累发展机制、作用机制、研究政策变形对环境政策适应性和效率的影响才可能准确预测环境政策所引发的变化,这些变化对社会经济的影响,进而对环境政策的反馈影响和反馈作用,才可能准确有效地设计开发政策工具和调控机制,有铲地进行环境政策调控,提高环境政策的预见性、准确性、操作性和适应性。     

Information Network Topologies for Enhanced Local Adaptive Management

We examined the principal effects of different information network topologies for local adaptive management of natural resources. We used computerized agents with adaptive decision algorithms with the following three fundamental constraints: (1) Complete understanding of the processes maintaining the natural resource can never be achieved, (2) agents can only learn by experimentation and information sharing, and (3) memory is limited. The agents were given the task to manage a system that had two states: one that provided high utility returns (desired) and one that provided low returns (undesired). In addition, the threshold between the states was close to the optimal return of the desired state. We found that networks of low to moderate link densities significantly increased the resilience of the utility returns. Networks of high link densities contributed to highly synchronized behavior among the agents, which caused occasional large-scale ecological crises between periods of stable and high utility returns. A constructed network involving a small set of experimenting agents was capable of combining high utility returns with high resilience, conforming to theories underlying the concept of adaptive comanagement. We conclude that (1) the ability to manage for resilience (i.e., to stay clear of the threshold leading to the undesired state as well as the ability to re-enter the desired state following a collapse) resides in the network structure and (2) in a coupled social–ecological system, the systemwide state transition occurs not because the ecological system flips into the undesired state, but because managers lose their capacity to reorganize back to the desired state. An erratum to this article can be found at .     

Indicators for sustainable energy development in Lithuania

This article summarizes some of the results from the application of the indicators for sustainable energy development (ISED) tool for analyzing Lithuania's energy sector, in terms of trends, setting energy policy goals and monitoring progress towards these goals. This experience illustrates the potential applicability of the ISED methodology for energy policy development in economies in transition, using Lithuania as an example. The article presents a summary of the results achieved and conclusions arrived at from the analysis of six priority areas in the context of the research project coordinated by the International Atomic Energy Agency, and provides recommendations for the development of sustainable energy policy using the ISED approach.     

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.     

ARE RURAL RESIDENTS WILLING TO PAY ENOUGH TO IMPROVE DRINKING WATER QUALITY?1

ABSTRACT: The concentrations of iron and sulfate in community water supplies are a concern for a number of areas in southwestern Minnesota. This study used the contingent valuation method to determine how much consumers would be willing to pay to improve their drinking water quality. On average, individuals were willing to pay US$5.25 per month (in 1995 U.S. dollars) to reduce the level of iron and US$4.33 per month to reduce the level of sulfate in their water to the USEPA's secondary standards for drinking water quality. Respondents with negative perceptions of their drinking water quality were willing to pay more to improve water quality. The aggregate annual willingness to pay (WTP) for all consumers in community water systems in southwestern Minnesota that were out of compliance with water quality standards were estimated to be US$2.4 million and US$2.0 million (in 1995 dollars) for reducing the levels of iron and sulfate, respectively. Yet the total WTP of consumers who use small community water systems may not be enough to pay the full cost of providing improved water in those systems. Economies of scale in water treatment and difficulties in financing improvements mean that technical innovation, government assistance, or institutional changes may be needed to improve water quality in these areas.     

The role of scientists in statutory interpretation of the U.S. Endangered Species Act

Like many federal statutes, the U.S. Endangered Species Act (ESA) contains vague or ambiguous language. The meaning imparted to the ESA's unclear language can profoundly impact the fates of endangered and threatened species. Hence, conservation scientists should contribute to the interpretation of the ESA when vague or ambiguous language contains scientific words or refers to scientific concepts. Scientists need to know at least these 2 facts about statutory interpretation: statutory interpretation is subjective and the potential influence of normative values results in different expectations for the parties involved. With the possible exception of judges, all conventional participants in statutory interpretation are serving their own interests, advocating for their preferred policies, or biased. Hence, scientists can play a unique role by informing the interpretative process with objective, policy‐neutral information. Conversely, scientists may act as advocates for their preferred interpretation of unclear statutory language. The different roles scientists might play in statutory interpretation raise the issues of advocacy and competency. Advocating for a preferred statutory interpretation is legitimate political behavior by scientists, but statutory interpretation can be strongly influenced by normative values. Therefore, scientists must be careful not to commit stealth policy advocacy. Most conservation scientists lack demonstrable competence in statutory interpretation and therefore should consult or collaborate with lawyers when interpreting statutes. Professional scientific societies are widely perceived by the public as unbiased sources of objective information. Therefore, professional scientific societies should remain policy neutral and present all interpretations of unclear statutory language; explain the semantics and science both supporting and contradicting each interpretation; and describe the potential consequences of implementing each interpretation. A review of scientists’ interpretations of the phrase “significant portion of its range” in the ESA is used to critique the role of scientists and professional societies in statutory interpretation.     

Robust technology policy against emission leakage: The case of upstream subsidies

Asymmetric regulation of a global pollutant between countries can alter the competitiveness of industries and lead to emissions leakage, which hampers countries’ welfare. In order to limit leakage, governments consider supporting domestic trade-exposed firms by subsidizing their investments in abatement technology. The suppliers of such technologies tend to be less than perfectly competitive, particularly when both emissions regulations and advanced technologies are new. In this context of twin market failures, we consider the relative effects and desirability of subsidies for abatement technology. We find a more robust recommendation for upstream subsidies than for downstream subsidies. Downstream subsidies tend to increase global abatement technology prices, reduce pollution abatement abroad and increase emission leakage. On the contrary, upstream subsidies reduce abatement technology prices, and hence also emissions leakage.     

Dynamic Bayesian networks for reliability evaluation of subsea wellhead connector during service life based on Monte Carlo method

The subsea wellhead connector is a critical connection component between subsea Christmas tree and subsea wellhead for preventing the leakage of oil and gas in the subsea production system. Excited by cyclical loadings due to environmental forces and the other support forces, the subsea wellhead connector is prone to the failure, which could lead to the loss of subsea tree or wellhead integrity and even catastrophic accidents. With the Monte Carlo simulation method, this paper presents a reliability analysis approach based on dynamic Bayesian Networks, aiming to assess the failure probability of the subsea wellhead connector during service life. Take the driving ring component of the subsea wellhead connector as an example to demonstrate the reasonability of the proposed model. The generation data is processed by the transform between the numerical value and the state variable. Based on the stress-strength interference theory, the structure reliability of the driving ring with 96.26% is achieved by the proposed model with the consideration the aging of the material strength and the most influential factors are figured out. Meanwhile, the corresponding control measures are proposed effectively reduce the failure risk of the subsea wellhead connector during service life.