Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method

Wang, Wenchuan; Xu, Dianxiang; Chau, Kwok Wing; Lei, Guan

doi:10.1007/s11269-014-0738-4

Cited by 156 publications

(77 citation statements)

References 29 publications

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“…Therefore, further investigation is required to analyze topographic dependence on denitrification and assimilation in urban areas. In addition, the loading and nitrogen reducing process is ambiguous in urban area and therefore modeling evaluation using fuzzy pattern-recognition may be useful [43][44][45][46].…”

Section: Use Of the Topographic Index To Explain The Lower Percentagementioning

confidence: 99%

Differences in Stream Water Nitrate Concentrations between a Nitrogen-Saturated Upland Forest and a Downstream Mixed Land Use River Basin

et al. 2017

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Nitrogen (N) saturation of upland forests has been assumed to be a substantial N source downstream. However, removal processes of N, including assimilation and denitrification in the downstream area, have not been clarified. To evaluate the N removal processes, nitrate and organic N concentrations, as well as nitrogen isotope ratio (δ 15 N) and oxygen isotope ratio (δ 18 O) of NO 3 − were measured along three rivers of Tatara River Basin, Japan where upland forests have already been N-saturated. Geographic information system (GIS) based topographical analysis was also conducted to evaluate the land use as urban area in relation to topography. In two of the three rivers, NO 3 − concentrations did not increase from upstream to downstream, despite the potential non-point N sources of urban areas. In another river, NO 3 − concentrations rather decreased.The values of δ 15 N and δ 18 O of NO 3 − and organic N concentrations suggested the presence of denitrification and assimilation over N pollutants in the river whose watersheds have a lower percentage of urban area. The lower percentage of urban area could be explained by the lower topographic index. This study concluded that the NO 3 − leaching from upland N-saturated forests was substantially assimilated or denitrified in the downstream area.

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Section: Use Of the Topographic Index To Explain The Lower Percentagementioning

confidence: 99%

Differences in Stream Water Nitrate Concentrations between a Nitrogen-Saturated Upland Forest and a Downstream Mixed Land Use River Basin

et al. 2017

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“…One option would be the use of neural networks that predict solar energy from photovoltaic installations with similar orientation to the ENM roofs [26][27][28] . This would require prior work on searching and obtaining multi-year data history for training the neural networks.…”

Section: A Estimation Of Photovoltaic Productionmentioning

confidence: 99%

Estimation of photovoltaic potential for electricity self-sufficiency: A study case of military facilities in northwest Spain

Suárez‐García¹,

Arce²,

Álvarez-Feijoo³

et al. 2017

Journal of Renewable and Sustainable Energy

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Renewable energies, including photovoltaic energy, are attracting widespread international attention, in reaction to worsening environmental problems and the diminishing long-term sustainability of fossil fuel energies. In this work, the potential benefits of installing photovoltaic panels on several buildings at the Spanish Naval Military School (Escuela Naval Militar, ENM) of Marín are considered. The two salient advantages are: significant economic savings from the production and the sale of electricity to the Spanish Electricity Network, and by achieving self-sufficiency in electricity requirements. Consequently, the main objective of this work is to estimate the energy potential of photovoltaic installations on the roofs of the ENM buildings. This is the first time that a project of this nature and size is presented to the Spanish Navy. To that end, a three-dimensional geographic analysis of the buildings is performed using three freeware software: Trimble SketchUp, Skelion and Photovoltaic Geographical Information System (PVGIS). An economic study is also conducted to determine the feasibility of the installations, by estimating the Net Present Value (NPV) of the photovoltaic installation and the Internal Rate of Return (IRR) associated with the project. Subsequently, a sensitivity analysis that considers the most important parameters for the calculation of the amortization period is reported. The results show that the installation could fulfill the ENM electrical demands and could, in addition, generate significant economic benefits. The conclusions end with a recommendation to consider the merits of the proposed solution.

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“…Hydrological modelling has been widely used in numerous fields such as flood forecasting, water resource estimation, water project planning, groundwater level fluctuations, hydrological station planning, water quality monitoring and sediment load estimation [1][2][3][4][5][6][7][8][9][10]. At present, a significant goal of existing research efforts in hydrological modelling is to improve the accuracy of runoff simulation and prediction.…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method

Zhang

Shi

et al. 2018

Atmosphere

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Abstract:Rainfall stations of a certain number and spatial distribution supply sampling records of rainfall processes in a river basin. Uncertainty may be introduced when the station records are spatially interpolated for the purpose of hydrological simulations. This study adopts a bootstrap method to quantitatively estimate the uncertainty of areal rainfall estimates and its effects on hydrological simulations. The observed rainfall records are first analyzed using clustering and correlation methods and possible average basin rainfall amounts are calculated with a bootstrap method using various combinations of rainfall station subsets. Then, the uncertainty of simulated runoff, which is propagated through a hydrological model from the spatial uncertainty of rainfall estimates, is analyzed with the bootstrapped rainfall inputs. By comparing the uncertainties of rainfall and runoff, the responses of the hydrological simulation to the rainfall spatial uncertainty are discussed. Analyses are primarily performed for three rainfall events in the upstream of the Qingjian River basin, a sub-basin of the middle Yellow River; moreover, one rainfall event in the Longxi River basin is selected for the analysis of the areal representation of rainfall stations. Using the Digital Yellow River Integrated Model, the results show that the uncertainty of rainfall estimates derived from rainfall station network has a direct influence on model simulation, which can be conducive to better understand of rainfall spatial characteristic. The proposed method can be a guide to quantify an approximate range of simulated error caused by the spatial uncertainty of rainfall input and the quantified relationship between rainfall input and simulation performance can provide useful information about rainfall station network management in river basins.

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Assessment of River Water Quality Based on Theory of Variable Fuzzy Sets and Fuzzy Binary Comparison Method

Cited by 156 publications

References 29 publications

Differences in Stream Water Nitrate Concentrations between a Nitrogen-Saturated Upland Forest and a Downstream Mixed Land Use River Basin

Differences in Stream Water Nitrate Concentrations between a Nitrogen-Saturated Upland Forest and a Downstream Mixed Land Use River Basin

Estimation of photovoltaic potential for electricity self-sufficiency: A study case of military facilities in northwest Spain

Analysis of the Influence of Rainfall Spatial Uncertainty on Hydrological Simulations Using the Bootstrap Method

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