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221.
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. 相似文献
222.
Sara Larsen Stuart Hamilton Jessica Lucido Bradley Garner Dwane Young 《Journal of the American Water Resources Association》2016,52(4):859-872
Shared, trusted, timely data are essential elements for the cooperation needed to optimize economic, ecologic, and public safety concerns related to water. The Open Water Data Initiative (OWDI) will provide a fully scalable platform that can support a wide variety of data from many diverse providers. Many of these will be larger, well‐established, and trusted agencies with a history of providing well‐documented, standardized, and archive‐ready products. However, some potential partners may be smaller, distributed, and relatively unknown or untested as data providers. The data these partners will provide are valuable and can be used to fill in many data gaps, but can also be variable in quality or supplied in nonstandardized formats. They may also reflect the smaller partners' variable budgets and missions, be intermittent, or of unknown provenance. A challenge for the OWDI will be to convey the quality and the contextual “fitness” of data from providers other than the most trusted brands. This article reviews past and current methods for documenting data quality. Three case studies are provided that describe processes and pathways for effective data‐sharing and publication initiatives. They also illustrate how partners may work together to find a metadata reporting threshold that encourages participation while maintaining high data integrity. And lastly, potential governance is proposed that may assist smaller partners with short‐ and long‐term participation in the OWDI. 相似文献
223.
Andrew S. Jones Allan A. Andales Jos L. Chvez Cullen McGovern Garvey E.B. Smith Olaf David Steven J. Fletcher 《Journal of the American Water Resources Association》2020,56(2):201-211
We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. 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. 相似文献
224.
225.
针对四川石油天然气工业环境统计中存在的非稳定污染源监测数据的统计价值不高,统计调查方法单一,个别统计指标计算未使用国家统一标准等现状,从环境监测站改组入手,改革统计调查方法,建立以必要的周期性普查为基础,以经常性的抽样调查为主体,同时辅之以全面统计报表,重点调查和科学推算综合运用的统计调查方法体系。 相似文献
226.
227.
Sun F Shih Jonathan D. Jordan 《Journal of the American Water Resources Association》1992,28(4):713-719
ABSTRACT: Landsat satellite Thematic Mapper (TM) data were used to assess regional soil moisture conditions. The mid-infrared (MIR) data of TM band 7 were overlain onto four principal land-use categories (Agricultural/Irrigated, Urban/Clearings, Forest/ Wetlands, Water) using a geographic information system (GIS). M data were used to assess four qualitative surface soil-moisture conditions (water/very wet, wet, moist, and dry) within each land-use category of a 208,354 ha southwestern Florida study area. The MIR response was inversely related to the qualitative surface soil-moisture content. Integration of Landsat TM MIR data with land use through GIS appears to be a useful technique for high-resolution regional soil moisture assessment, and further research to reline this technique is recommended. 相似文献
228.
Yun Ouyang Elizabeth A. Wentz Benjamin L. Ruddell Sharon L. Harlan 《Journal of the American Water Resources Association》2014,50(2):448-467
Studies that evaluate determinants of residential water demand typically use data from a single spatial scale. Although household‐scale data are preferred, especially when econometric models are used, researchers may be limited to aggregate data. There is little, if any, empirical analysis to assess whether spatial scale may lead to ecological fallacy problems in residential water use research. Using linear mixed‐effects models, we compare the results for the relationship of single‐family water use with its determinants using data from the household and census tract scales in the city of Phoenix. Model results between the household and census tract scale are similar suggesting the ecological fallacy may not be significant. Common significant determinants on these two spatial scales include household size, household income, house age, pool size, irrigable lot size, precipitation, and temperature. We also use city/town scale data from the Phoenix metropolitan area to parameterize the linear mixed‐effects model. The difference in the parameter estimates of those common variables compared to the first two scales indicates there is spatial heterogeneity in the relationship between single‐family water use and its determinants among cities and towns. The negative relationship between single‐family house density and residential water use suggests that residential water consumption could be reduced through coordination of land use planning and water demand management. 相似文献
229.
Measurement and Management of Human-Induced Patterns of Forest Fragmentation: A Case Study 总被引：1，自引：0，他引：1
Tole L 《Environmental management》2006,37(6):788-801
In many tropical developing countries, the twin pressures of population and poverty are resulting in substantial fragmentation
of forests, increasing the probability of extinction for many species, Forest fragmentation occurs when large contiguous forests
are perforated by small holes or broken up into edges and smaller patches to form a nonforested matrix of open spaces. Thus,
forest fragmentation refers not only to the area of forest cleared, but also to the pattern of this clearance, the resulting
forest’s spatial properties. Both characteristics are important for species survivability. Apart from opening up forests to
many abiotic and biotic influences, fragmentation can affect species dispersal and migration through its effects on forest
connectivity. Landscape ecology conceptualizes connectivity as a gradient of critical thresholds, ranging from the large intact
forest to the small unconnected forest patch. This article reports results from a multiple-scale analysis of forest fragmentation
in Jamaica’s Cockpit Country, an area of once contiguous forest now under threat from human encroachment. Spatial forest data
derived from classification of ETM+ satellite imagery are used to measure fragmentation patterns representing various degrees
of forest connectivity and density. The results suggest that, overall, 81% of the region is in forest. However, fragmentation
patterns also suggest that this forest is riven with extensive perforations indicative of an early stage in the decline of
contiguity. The results provided by the spatial fragmentation model are a first step in the design of effective conservation
and rehabilitation plans for the area. The article concludes with a discussion of possible multiscale management options for
the region. 相似文献
230.