Environmental indices in irrigation management

Irrigation management calls for objective criteria capable of representing the economy, reliability, and productivity of irrigation systems. These criteria must be compatible with long-term sustainability and conservation goals. The criteria representing the above goals are the economic effect of management on yield reduction, economic effect, and reliability referring to plant growth and operation of the network. In this study environmental indices are introduced to express the above criteria in quantitative terms. The inclusion of these indices at the farm and network level create a multicriteria framework for decision-making based on composite programming. An experimental study was conducted during the irrigation periods of 1989 and 1990 in Chania, Greece, concerning water delivered to 40 experimental plots, soil moisture content at the rootzone, and irrigation system operational failures. The data collected in real time were used for the calculation of the corresponding environmental indices. The variation in time and space is high and resulted in up to 62% of yield loss and low system performance (up to 7% of system temporal reliability). The study indicated that environmental indices could be incorporated to select alternatives and also to develop policies on water delivery. The final decision involves a trade-off analysis between cost of application and desired system performance. Measures of both primary objectives can be obtained using environmental indices that represent system operation aggregation at its basic levels (on farm and network).     

Extension of EU Emissions Trading Scheme to Other Sectors and Gases: Consequences for Uncertainty of Total Tradable Amount

Emissions trading in the European Union (EU), covering the least uncertain emission sources of greenhouse gas emission inventories (CO₂ from combustion and selected industrial processes in large installations), began in 2005. During the first commitment period of the Kyoto Protocol (2008–2012), the emissions trading between Parties to the Protocol will cover all greenhouse gases (CO₂, CH₄, N₂O, HFCs, PFCs, and SF₆) and sectors (energy, industry, agriculture, waste, and selected land-use activities) included in the Protocol. In this paper, we estimate the uncertainties in different emissions trading schemes based on uncertainties in corresponding inventories. According to the results, uncertainty in emissions from the EU15 and the EU25 included in the first phase of the EU emissions trading scheme (2005–2007) is ±3% (at 95% confidence interval relative to the mean value). If the trading were extended to CH₄ and N₂O, in addition to CO₂, but no new emissions sectors were included, the tradable amount of emissions would increase by only 2% and the uncertainty in the emissions would range from −4 to +8%. Finally, uncertainty in emissions included in emissions trading under the Kyoto Protocol was estimated to vary from −6 to +21%. Inclusion of removals from forest-related activities under the Kyoto Protocol did not notably affect uncertainty, as the volume of these removals is estimated to be small.     

The Impact of Uncertainty on Banking Behavior: Evidence from the US Sulfur Dioxide Emissions Allowance Trading Program

In this paper, we study empirically whether uncertainty has an influence on trade in the US sulfur dioxide allowances market. In particular, we investigate the role of uncertainty on banking behavior. To do this, we introduce a tractable, structural model of trading permits under uncertainty. The model establishes a relation between banking behavior and risk preferences, especially prudence in the Kimball (1990) sense. We then test this model using data on allowances, for utilities submitted to the US Environmental Protection Agency’s Acid Rain Program, carried over from one year to the next. Evidence is found of imprudence, namely, utilities bank permits in order to favor higher profits. Another finding is that larger utilities do not adopt behavior significantly different from that of smaller ones. This paper was presented at the “International Workshop on Uncertainty in Greenhouse Gas Inventories: Verification, Compliance & Trading” in Warsaw, Poland, September 2004, under the title “Portfolio Management of Emissions Permits and Prudence Behavior.”     

Compliance and Emissions Trading under the Kyoto Protocol: Rules for Uncertain Inventories

A solution is proposed for proving compliance with emission targets and for emissions trading in the event of uncertainties in reported emission inventories. The solution is based on the undershooting concept, from which the mathematical conditions for both proving compliance with a risk α and calculating effective emissions for trading are derived. Based on the reported emission units, the number of permits granted is reduced in proportion to the uncertainty in the inventory. A country whose inventory has higher uncertainty is thereby allotted fewer permits than a country with the same inventory but smaller uncertainty.     

基于模糊综合方法的工业污水环境安全影响评价研究

在综合分析水环境影响因素的基础上,应用模糊综合评价方法对工业污水环境安全影响进行了研究。首先构建工业污水污染程度模糊综合评价的数学模型,然后利用综合评价方法对污水中重金属污染程度进行有效评价。研究结果表明:模糊综合评价方法可以全面考虑企业排放废水中影响环境安全的各种因素,充分体现评价因素和评价过程所固有的模糊性,适用于复杂参数水环境的不确定分析与评价,可以有效地评价水的质量;将模糊评价方法引入工业污水对环境安全影响的评价体系,是污水处理评价发展的一个新方向和新领域,它是污水处理评价方法的补充和完善,在该领域具有广阔的应用前景。     

DETERMINATION OF SEDIMENT YIELD BY TRANSFERRING RAINFALL DATA1

ABSTRACT: A methodology for obtaining the optimal design value to allow for sediment storage in a reservoir is presented for the situation where no data on sediment loads in the incoming streams are available. Information concerning the amount of sediment delivered to the reservoir over its life-time is obtained by a sediment yield model which uses data on rainfall amount and duration obtained from a nearby experimental watershed. Bayesian Decision Theory is used to obtain the optimal storage requirements in order to consider the natural variation of rainfall and the sampling error due to the short rainfall record available. The normally difficult calculations involved were made tractable by the use of simplifications and approximations valid in the context of the problem. Results show that sediment storage requirements can be calculated in this manner and that consideration of the uncertainties involved leads to a storage requirement substantially larger than that calculated without such consideration.     

Science–policy interface for addressing environmental problems in arid Spain

Science–policy interfaces are avenues for finding solutions for environmental challenges through strengthening collaborations between research disciplines and public administrations. Here we present a methodology for the conduct of science–policy interfaces between scientists and policymakers for addressing day-to-day environmental problems in the southeastern Spanish drylands. A knowledge brokering approach based on six consecutive workshops was used to facilitate mutual understanding and trust between scientists and policymakers. Water policy and biodiversity loss were identified as major environmental concerns in the region, and 12 final environmental problems were agreed as priorities. A graphical tool was used for diagnosing each environmental problem according to the available scientific knowledge, the current regulatory capacity of administrations, and the level of public engagement necessary for addressing the problem. The use of the graphical tool also allowed for (a) the clarification of roles involved in problem solving, and (b) the promotion of a culture of shared responsibility for the implementation of management actions based on collaborative work. We discuss lessons learned and propose recommendations for future experiences.     

Rethinking receiver operating characteristic analysis applications in ecological niche modeling

The area under the curve (AUC) of the receiver operating characteristic (ROC) has become a dominant tool in evaluating the accuracy of models predicting distributions of species. ROC has the advantage of being threshold-independent, and as such does not require decisions regarding thresholds of what constitutes a prediction of presence versus a prediction of absence. However, we show that, comparing two ROCs, using the AUC systematically undervalues models that do not provide predictions across the entire spectrum of proportional areas in the study area. Current ROC approaches in ecological niche modeling applications are also inappropriate because the two error components are weighted equally. We recommend a modification of ROC that remedies these problems, using partial-area ROC approaches to provide a firmer foundation for evaluation of predictions from ecological niche models. A worked example demonstrates that models that are evaluated favorably by traditional ROC AUCs are not necessarily the best when niche modeling considerations are incorporated into the design of the test.     

Development and Operational Testing of a Super‐Ensemble Artificial Intelligence Flood‐Forecast Model for a Pacific Northwest River

Coastal catchments in British Columbia, Canada, experience a complex mixture of rainfall‐ and snowmelt‐driven contributions to flood events. Few operational flood‐forecast models are available in the region. Here, we integrated a number of proven technologies in a novel way to produce a super‐ensemble forecast system for the Englishman River, a flood‐prone stream on Vancouver Island. This three‐day‐ahead modeling system utilizes up to 42 numerical weather prediction model outputs from the North American Ensemble Forecast System, combined with six artificial neural network‐based streamflow models representing various slightly different system conceptualizations, all of which were trained exclusively on historical high‐flow data. As such, the system combines relatively low model development times and costs with the generation of fully probabilistic forecasts reflecting uncertainty in the simulation of both atmospheric and terrestrial hydrologic dynamics. Results from operational testing by British Columbia's flood forecasting agency during the 2013‐2014 storm season suggest that the prediction system is operationally useful and robust.