937 resultados para Illinois Staewide Water Quality Management Plan.


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"Prepared for the Illinois Institute of Natural Resources and the Illinois Environmental Protection Agency"--Cover

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"IPEA/WPC/92-220"--Cover.

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Mode of access: Internet.

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"July 1975"

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Cover and spine title: Water quality management plan.

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Cover title: Water quality management planning.

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Prepared by Division of Water Pollution Control, Planning and Standards Section.

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This is the Water Level Management Plan for the Rostherne Mere by the Environment Agency. The purpose of the Plan is to provide a formal basis for managing the land drainage system and water supply system of the area in order to provide a sustainable balance between the conservation and agricultural interest in the area. No changes are proposed to present water level management or maintenance practices unless and until such changes are agreed by all parties. The report contains sections on description of Site, water level management, maintenance, nature conservation, agriculture, fisheries, archaeology, water quality and water resources, development adjacent to watercourses, contingencies and objectives of the Water Level Management.

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A fuzzy waste-load allocation model, FWLAM, is developed for water quality management of a river system using fuzzy multiple-objective optimization. An important feature of this model is its capability to incorporate the aspirations and conflicting objectives of the pollution control agency and dischargers. The vagueness associated with specifying the water quality criteria and fraction removal levels is modeled in a fuzzy framework. The goals related to the pollution control agency and dischargers are expressed as fuzzy sets. The membership functions of these fuzzy sets are considered to represent the variation of satisfaction levels of the pollution control agency and dischargers in attaining their respective goals. Two formulations—namely, the MAX-MIN and MAX-BIAS formulations—are proposed for FWLAM. The MAX-MIN formulation maximizes the minimum satisfaction level in the system. The MAX-BIAS formulation maximizes a bias measure, giving a solution that favors the dischargers. Maximization of the bias measure attempts to keep the satisfaction levels of the dischargers away from the minimum satisfaction level and that of the pollution control agency close to the minimum satisfaction level. Most of the conventional water quality management models use waste treatment cost curves that are uncertain and nonlinear. Unlike such models, FWLAM avoids the use of cost curves. Further, the model provides the flexibility for the pollution control agency and dischargers to specify their aspirations independently.

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This report summarises work conducted by the QDPI, in partnership with the South Burdekin Water Board (SBWB) and the Burdekin Shire Council (BSC) between 2001 and 2003. The broad aim of the research was to assess the potential of native fish as biocontrol agents for noxious weeds, as part of an integrated program for managing water quality in the Burdekin Irrigation Area. A series of trials were conducted at, or using water derived from, the Sandy Creek Diversion near Groper Creek (lower Burdekin delta). Trials demonstrated that aquatic weeds play a positive role in trapping transient nutrients, until such time that weed growth becomes self-shading and weed dieback occurs, which releases stored nutrients and adversely affects water quality. Transient nutrient levels (av. TN<0.5mg/L; av. TP<0.1mg/L) found in the irrigation channel during the course of this research were substantially lower than expected, especially considering the intensive agriculture and sewage effluent discharge upstream from the study site. This confirms the need to consider the control of weeds rather than complete weed extermination when formulating management plans. However, even when low nutrient levels are available, there is competitive exploitation of habitat variables in the irrigation area leading to succession and eventual domination by certain weed species. During these trials, we have seen filamentous algae, phytoplankton, hyacinth and curled pondweed each hold competitive advantage at certain points. However without intervention, floating weeds, especially hyacinth, ultimately predominate in the Burdekin delta due to their fast propagation rate and their ability to out-shade submerged plants. We have highlighted the complexity of interactions in these highly disturbed ecosystems in that even if the more prevalent noxious weeds are contained, other weed species will exploit the vacant niche. This complexity places stringent requirements on the type of native fish that can be used as biocontrol agents. Of the seven fish species identified with herbivorous trophic niches, most target plankton or algae and do not have the physical capacity to directly eat the larger macrophytes of the delta. We do find however that following mechanical weed harvesting, inoculative releases of fish can slow the rate of hyacinth recolonisation. This occurs by mechanisms in addition to direct weed consumption, such as disturbing growth surfaces by grazing on attached biofilms. Predation by birds and water rats presents another impediment to the efficacy of large-scale releases of fish. However, alternative uses of fish in water quality management in the Burdekin irrigation area are discussed.

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Uncertainty plays an important role in water quality management problems. The major sources of uncertainty in a water quality management problem are the random nature of hydrologic variables and imprecision (fuzziness) associated with goals of the dischargers and pollution control agencies (PCA). Many Waste Load Allocation (WLA)problems are solved by considering these two sources of uncertainty. Apart from randomness and fuzziness, missing data in the time series of a hydrologic variable may result in additional uncertainty due to partial ignorance. These uncertainties render the input parameters as imprecise parameters in water quality decision making. In this paper an Imprecise Fuzzy Waste Load Allocation Model (IFWLAM) is developed for water quality management of a river system subject to uncertainty arising from partial ignorance. In a WLA problem, both randomness and imprecision can be addressed simultaneously by fuzzy risk of low water quality. A methodology is developed for the computation of imprecise fuzzy risk of low water quality, when the parameters are characterized by uncertainty due to partial ignorance. A Monte-Carlo simulation is performed to evaluate the imprecise fuzzy risk of low water quality by considering the input variables as imprecise. Fuzzy multiobjective optimization is used to formulate the multiobjective model. The model developed is based on a fuzzy multiobjective optimization problem with max-min as the operator. This usually does not result in a unique solution but gives multiple solutions. Two optimization models are developed to capture all the decision alternatives or multiple solutions. The objective of the two optimization models is to obtain a range of fractional removal levels for the dischargers, such that the resultant fuzzy risk will be within acceptable limits. Specification of a range for fractional removal levels enhances flexibility in decision making. The methodology is demonstrated with a case study of the Tunga-Bhadra river system in India.

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On-farm research on enhancement of P. monodon production through water quality management was carried out in five ghers of Paikgacha, Khulna. Based on the prevailing condition of the ghers, lime in the form of CaCO(sub 3), urea and TSP were used as the major inputs to minimize the soil-water acidity and to ensure the availability of natural food particles in the water bodies. Exchange of water at required level also practiced for the qualitative improvement of culture water. Ghers of varying sizes showed that water quality management and fertilization have a positive impact on production performance of P. monodon (61.59% increment) that yielded an average production of 385.43 kg/ha/crop against the present traditional rate of 238.50 kg/ha/year.