A New Water Environmental Load and Allocation Modeling Framework at Medium-Large Basin Scale

Published: 24 Sep 2019 | Version 1 | DOI: 10.17632/25pxyfbpff.1
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Description of this data

In this paper, a new, alternative, multi-scale, multi-pollution source waste load allocation (WLA) system was developed, with a goal to produce optimal, fair quota allocations at multiple scales. The new WLA system integrates multi-constrained environmental Gini coefficients (EGCs) and Delphi-analytic hierarchy process (Delphi-AHP) optimization models to achieve the stated goal.
This dataset consists of the raw data and the source code of models (The multi-constrained environmental Gini coefficients and Delphi-analytic hierarchy process optimization models).
The source code of the multi-constrained EGCs and Delphi-AHP models was used to run the program in MATLAB environment to allocate waste load reduction quotas at both the regional scale and the site-specific scale with multiple pollution sources. The raw data mainly consists of the following two parts: (1) The shp files of various geographic information data, which was used to depicture the administrative divisions, pollution source distribution, geographical characteristics and patterns of Xian-jiang watershed; (2) The basic data includes the statistical yearbook data of villages and towns in Ningbo city, the various indicator data using to calculate the weights at criteria level and decision-making level, the contribution coefficients, and the EGC values of the three pollutants.
On the basis of these data, a new, alternative, multi-scale, multi-sector optimal WLA framework was developed. The new scheme provides decision-makers critical information (i.e., the best compromise solutions of WLA) and practical guidance as they address the related water pollution control. The results, in comparison with existing practices by the local governments, suggested that the pollution discharge quota at regional scale is much fairer than the existing WLA and, even have some environmental economic benefits at pollutant source scale after optimal WLA.
Some important conclusions had been found: 1) Reductions and proportions of pollutants at regional scale are significantly associated with the region’s actual socioeconomic development modes. 2)There are certain characteristics that high-reduced pollution sources tend to share (which are listed in the article). The sources with the above features should be the top priorities in the reduction of removals. 3)Most previous studies reported primarily on the WLA of removals among point sources pollution. Conversely, we found that the industrial pollution source should be the last option for reduction from an environmental-economic benefit perspective. Instead, the often overlooked types, such as agricultural non-point source and domestic sources, deserve more attention, especially in extensive rural areas.

Experiment data files

  • Raw data
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    • The 2015 statistical yearbook data of villages and towns in Ningbo city
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      The 2015 statistical yearbook data of villages and towns in Ningbo city, which was used to model calculation.

    • The data of DEM in Xianjiang watershed
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      The data of (Digital Elevation Model) DEM in Xianjiang watershed.

    • The data using to calculate the contribution coefficients of the three pollutants
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      The basic data using to calculate the contribution coefficients of the three pollutants

    • The data using to calculate the EGC values of the three pollutants
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      The basic data using to calculate the EGC values of the three pollutants in multi-constrained EGCs.

    • The data using to calculate the weights at criteria level and decision-making level
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      The data using to calculate the weights at criteria level and decision-making level in Delphi-AHP models.

    • The district boundary in Xianjiang watershed
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      The shp file of the district boundary of the five towns in Xianjiang watershed.

    • The shp file of large-scale breeding farms locations
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      The shp file of the distribution of the large-scale breeding farms in Xianjiang watershed.

    • The shp file of monitoring section
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      The shp file of the monitoring section location for water quality monitoring.

    • The shp file of the industrial enterprises locations
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      The shp file of the distribution of the industrial enterprises locations in Xianjiang watershed.

    • The shp file of the Land use and Land cover (LULC) data
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      The shp file of the Land use and Land cover (LULC) data in Xianjiang watershed.

    • The shp file of the sewage treatment plant location
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      The shp file of the sewage treatment plant location in Xianjiang watershed.

    • The shp file of the watershed boundary
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      The shp file of the basin boundary of Xianjiang.

    • The shp file of water systems in Xianjiang watershed
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      The shp file of the spatial distribution of the water systems (15 rivers in total) and attribute information in Xianjiang watershed.

  • The source code of EGCs and Delphi-AHP models in MATLAB environment
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    • The .m file of Delphi-AHP models
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      The model computing program of the Delphi-AHP models run as the .m file in MATLAB environment.

    • The .m file of EGCs models
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      The model computing program of the multi-constrained EGCs models run as the .m file in MATLAB environment.

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Previous versions

  • Version 2

    2019-09-24

  • Version 1

    2019-09-24

    Published: 2019-09-24

    DOI: 10.17632/25pxyfbpff.1

    Cite this dataset

    Liu, Qiankun; Jiang, Jingang ; Jing, Changwei; Liu, Zhong; Qi, Jiaguo (2019), “A New Water Environmental Load and Allocation Modeling Framework at Medium-Large Basin Scale”, Mendeley Data, v1 http://dx.doi.org/10.17632/25pxyfbpff.1

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Categories

Environmental Science, Water, Water Quality Management, Integrated Water Resources Management, Water Quality Improvement

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