Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin

Minh Thu Nguyen

doi:10.61927/igmin258

145 of 152

Support for the use of Binomial Nomenclature in the Taxonomy of Viruses

Zdenek Hubalek

147 of 152

How Increased CO2 Warms the Earth-Two Contexts for the Greenhouse Gas Effect

Donald Rapp

Biology Group Research Article 記事ID: igmin258

Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin

Water Quality Soil Science Earth Science

Minh Thu Nguyen ^*

Affiliation

Vietnam Institute of Meteorology, Hydrology and Climate Change, Ministry of Natural Resources and Environment, Vietnam

DOI10.61927/igmin258 全文HTML 全文PDF この記事を引用する

要約

This research used the improved export coefficient model to estimate non-point source load in sub-watersheds and a self-organizing map model to identify the correlation relationship of factors, that can be affected by non-point source load in Yangtze River Basin. Research results indicate that total nitrogen load is 4.87 - 15.53 kg/ha; total phosphorus load is 0.18 - 0.51 kg/ha; Dong Ting Lake sub-basin has the lowest contribution value of total nitrogen and phosphorus; Tai Lake sub-basin has the highest contribution load of total nitrogen and total phosphorus; Jinsha River sub-basin reveals the highest value of total nitrogen and phosphorus contribution on grassy land and desert land; Tai Lake sub-basin has the highest total nitrogen and total phosphorus load on forest, agricultural land, and urban construction land. The correlation relationship of factors reveals a very close correlation with each other as precipitation, total nitrogen load, and total phosphorus load factors have correlation in the highest value, in which total nitrogen load and total phosphorus load factors have a close correlation with each other from the lowest value to highest value; wetland and barren land factors correlate with the lowest value and the highest value; agricultural land, forestland, and grassy land factors correlate with one another in the high value and the highest value. The forest cover rate factor, as well as the population factor, does not correlate with other factors.

数字

参考文献

Peng K, Li JK, Hao GR, Liu YW, Zhou X, Xie WF. Characteristics of non-point source pollution based on monitoring experiment in the Yinwugou small watershed, China. J Ecohydrol Hydrobiol. 2022;23(1):1-14. doi:10.1016/j.ecohyd.2022.09.001.
Ahmadi H. An overview of non-point source pollution modeling: current status and future prospect. J Civil Eng Res Technol. 2023;5(1):1-8.
Shen ZY, Liao Q, Hong Q, Gong YW. An overview of research on agricultural non-point source pollution modeling in China. J Sep Purif Technol. 2012;84:104-111.
Kast JB, Apostel AM, Kalcic MM, Muenich RL, Dagnew A, Long CM, Evenson G, Martin JF. Source contribution to phosphorus loads from the Maumee River watershed to Lake Erie. J Environ Manage. 2021 Feb 1;279:111803. doi: 10.1016/j.jenvman.2020.111803. Epub 2020 Dec 18. PMID: 33341725.
Chen M, Chen J, Sun F. Estimating nutrient releases from agriculture in China: an extended substance flow analysis framework and a modeling tool. Sci Total Environ. 2010 Oct 1;408(21):5123-36. doi: 10.1016/j.scitotenv.2010.07.030. Epub 2010 Aug 5. PMID: 20691463.
Abdulkareem JH, Solomon RI. Non-point source pollution modeling: an overview. J Appl Sci Environ Manage. 2022;26(5):865-870. doi:10.4314/jasem.v26i5.13.
Ding XW, Shen ZY, Hong Q, Yang ZF, Wu X, Liu RM. Development and test of the export coefficient model in the upper reach of the Yangtze River. J Hydrol. 2010;383:233-244.
Chang M, McBroom MW, Scott Beasley R. Roofing as a source of nonpoint water pollution. J Environ Manage. 2004 Dec;73(4):307-15. doi: 10.1016/j.jenvman.2004.06.014. PMID: 15531389.
Fang H. Effect of soil conservation measures and slope on runoff, soil TN, and TP losses from cultivated lands in northern China. J Ecol Indic. 2021;126:107677. doi:10.1016/j.ecolind.2021.107677.
Fu X, Liu J, Mei C, Luan Q, Wang H, Shao W, Sun P, Huo Y. Effect of typhoon rainstorm patterns on the spatio-temporal distribution of non-point source pollution in a coastal urbanized watershed. J Clean Prod. 2021;292:126098. doi:10.1016/j.jclepro.2021.126098.
Liu RM, Yang ZF, Shen ZY, Yu SL, Ding XW, Wu X, Liu F. Estimating nonpoint source pollution in the upper Yangtze River using the export coefficient model, remote sensing, and geographical information system. J Hydraul Eng. 2009;135:698-704.
Han LX, Huo F, Sun J. Method for calculating non-point source pollution distribution in plain rivers. J Water Sci Eng. 2011;4(1):83-91.
Shrestha S, Kazama F, Newham LTH, Babel MS, Clemente RS, Ishidaira H, Nishida K, Sakamoto Y. Catchment scale modeling of point source and non-point source pollution loads using pollutant export coefficients determined from long-term in-stream monitoring data. J Hydro Environ Res. 2008;2:134-147.
Sivertun A, Prange L. Non-point source critical area analysis in the Gisselö watershed using GIS. Environ Model Softw. 2003;18(10):887-898. doi:10.1016/S1364-8152(03)00107-5.
Kohonen T. The self-organizing map. J Neurocomputing. 1998;21(1):1-6.
Kiang MY. Extending the Kohonen self-organizing map networks for clustering analysis. J Comput Stat Data Anal. 2001;38(2):161-180.
Kohonen T. Essentials of the self-organizing map. Neural Netw. 2013 Jan;37:52-65. doi: 10.1016/j.neunet.2012.09.018. Epub 2012 Oct 4. PMID: 23067803.
Sang YF, Wang ZG, Liu CM. Spatial and temporal variability of daily temperature during 1961-2010 in the Yangtze River basin, China. J Quaternary Int. 2012;1-10. doi:10.1016/j.quaint.2012.05.026.
Zeng XF, Kundzewicz WZ, Zhou JZ, Su BD. Discharge projection in the Yangtze River basin under different emission scenarios based on the artificial neural networks. J Quaternary Int. 2011;1-9. doi:10.1016/j.quaint.2011.06.009.
Zhang Q, Jiang T, Gemmer M, Becker S. Precipitation, temperature and discharge analysis from 1951-2002 in the Yangtze Catchment, China. Hydrol Sci J. 2005;50(1):65-80.
Zhang Q, Xu YC, Zhang XZ, Chen DQ, Liu CL, Lin H. Spatial and temporal variability of precipitation maxima during 1960-2005 in the Yangtze River basin and possible association with large-scale circulation. J Hydrol. 2008;353:215-227.
Xu JJ, Yang WD, Yi HY, Lei DZ, Chen J, Yang JW. Spatial and temporal variation of runoff in the Yangtze River basin during the past 40 years. J Quaternary Int. 2008;186:32-42.
Johnes PJ. Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modeling approach. J Hydrol. 1996;183:323-349.
Ding XW, Shen ZY, Hong Q, Yang ZF, Wu X, Liu RM. Development and test of the export coefficient model in the upper reach of the Yangtze River. J Hydrol. 2010;383:233-244.
Liu RM, Yang ZF, Shen ZY, Yu SL, Ding XW, Wu X, Liu F. Estimating nonpoint source pollution in the upper Yangtze River using the export coefficient model, remote sensing, and geographical information system. J Hydraul Eng. 2009;135:698-704.

類似の記事

DNA Genetics and UHPLC-Q-TOF-MS Analysis of Phytochemicals for Asparagus racemosus Roots
Nguyen Thi Huong, Do Ngoc Thuy, Phung Van Trung, Le Ngoc Hung and Mai Van Nam
DOI10.61927/igmin217

Issues of Manufacturability of Roller Machines
Ayder Nabiev and Khushnudbek Rakhmonov
DOI10.61927/igmin252

Isolation and Characterization of Active Alkaloid Compounds from Cinnamomum Verum Cortexes and Proof of their Medicinal Efficacy against Pathogenic Fungus Alternaria Alternate Causing Upper Respiratory Tract Inflammatory Disease
Sanaa Qasem Badr
DOI10.61927/igmin177

On how Doping with Atoms of Gadolinium and Scandium affects the Surface Structure of Silicon
Egamberdiev BE, Daliev Kh S, Khamidjonov I Kh, Norkulov Sh B and Erugliev UK
DOI10.61927/igmin206

The Influence of Dynamical Downscaling and Boundary Layer Selection on Egypt’s Potential Evapotranspiration using a Calibrated Version of the Hargreaves-samani Equation: RegCM4 Approach
Samy A Anwar and Ankur Srivastava
DOI10.61927/igmin229

Efficient Room Temperature Ethanol Vapor Sensing by Unique Fractal Features of Tin Oxide
Rupali Nagar and Vishal Kamathe
DOI10.61927/igmin150

Exit Schreiner Collection
Per Erling Holck
DOI10.61927/igmin245

New Scientific Field for Modelling Complex Dynamical Systems: The Cybernetics Artificial Intelligence (CAI)
Peter P Groumpos
DOI10.61927/igmin183

Enforcement and Enlargement of the Saccharomyces cerevisiae Endoplasmic Reticulum through Artificial Evocation of the Unfolded Protein Response
Masaki Monguchi and Yukio Kimata
DOI10.61927/igmin142

Country Risk to Face Global Emergencies: Negative Effects of High Public Debt on Health Expenditures and Fatality Rate in COVID-19 Pandemic Crisis
Mario Coccia
DOI10.61927/igmin214

ソーシャルアイコン

研究を公開する

私たちは、科学、技術、工学、医学に関する幅広い種類の記事を編集上の偏見なく公開しています。

提出する

見る原稿のガイドライン追加論文処理料

IgMin 科目を探索する

トップ10の記事をクリック

クイックリンク

原稿を提出する

研究論文

グーグルスカラー

Google Scholarは2004年11月にベータ版が発表され、幅広い学術領域を航海する学術ナビゲーターとして機能します。それは査読付きジャーナル、書籍、会議論文、論文、博士論文、プレプリント、要約、技術報告書、裁判所の意見、特許をカバーしています。 IgMin の記事を検索

[1] Peng K, Li JK, Hao GR, Liu YW, Zhou X, Xie WF. Characteristics of non-point source pollution based on monitoring experiment in the Yinwugou small watershed, China. J Ecohydrol Hydrobiol. 2022;23(1):1-14. doi:10.1016/j.ecohyd.2022.09.001.

[2] Ahmadi H. An overview of non-point source pollution modeling: current status and future prospect. J Civil Eng Res Technol. 2023;5(1):1-8.

[3] Shen ZY, Liao Q, Hong Q, Gong YW. An overview of research on agricultural non-point source pollution modeling in China. J Sep Purif Technol. 2012;84:104-111.

[4] Kast JB, Apostel AM, Kalcic MM, Muenich RL, Dagnew A, Long CM, Evenson G, Martin JF. Source contribution to phosphorus loads from the Maumee River watershed to Lake Erie. J Environ Manage. 2021 Feb 1;279:111803. doi: 10.1016/j.jenvman.2020.111803. Epub 2020 Dec 18. PMID: 33341725.

[5] Chen M, Chen J, Sun F. Estimating nutrient releases from agriculture in China: an extended substance flow analysis framework and a modeling tool. Sci Total Environ. 2010 Oct 1;408(21):5123-36. doi: 10.1016/j.scitotenv.2010.07.030. Epub 2010 Aug 5. PMID: 20691463.

[6] Abdulkareem JH, Solomon RI. Non-point source pollution modeling: an overview. J Appl Sci Environ Manage. 2022;26(5):865-870. doi:10.4314/jasem.v26i5.13.

[7] Ding XW, Shen ZY, Hong Q, Yang ZF, Wu X, Liu RM. Development and test of the export coefficient model in the upper reach of the Yangtze River. J Hydrol. 2010;383:233-244.

[8] Chang M, McBroom MW, Scott Beasley R. Roofing as a source of nonpoint water pollution. J Environ Manage. 2004 Dec;73(4):307-15. doi: 10.1016/j.jenvman.2004.06.014. PMID: 15531389.

[9] Fang H. Effect of soil conservation measures and slope on runoff, soil TN, and TP losses from cultivated lands in northern China. J Ecol Indic. 2021;126:107677. doi:10.1016/j.ecolind.2021.107677.

[10] Fu X, Liu J, Mei C, Luan Q, Wang H, Shao W, Sun P, Huo Y. Effect of typhoon rainstorm patterns on the spatio-temporal distribution of non-point source pollution in a coastal urbanized watershed. J Clean Prod. 2021;292:126098. doi:10.1016/j.jclepro.2021.126098.

[11] Liu RM, Yang ZF, Shen ZY, Yu SL, Ding XW, Wu X, Liu F. Estimating nonpoint source pollution in the upper Yangtze River using the export coefficient model, remote sensing, and geographical information system. J Hydraul Eng. 2009;135:698-704.

[12] Han LX, Huo F, Sun J. Method for calculating non-point source pollution distribution in plain rivers. J Water Sci Eng. 2011;4(1):83-91.

[13] Shrestha S, Kazama F, Newham LTH, Babel MS, Clemente RS, Ishidaira H, Nishida K, Sakamoto Y. Catchment scale modeling of point source and non-point source pollution loads using pollutant export coefficients determined from long-term in-stream monitoring data. J Hydro Environ Res. 2008;2:134-147.

[14] Sivertun A, Prange L. Non-point source critical area analysis in the Gisselö watershed using GIS. Environ Model Softw. 2003;18(10):887-898. doi:10.1016/S1364-8152(03)00107-5.

[15] Kohonen T. The self-organizing map. J Neurocomputing. 1998;21(1):1-6.

[16] Kiang MY. Extending the Kohonen self-organizing map networks for clustering analysis. J Comput Stat Data Anal. 2001;38(2):161-180.

[17] Kohonen T. Essentials of the self-organizing map. Neural Netw. 2013 Jan;37:52-65. doi: 10.1016/j.neunet.2012.09.018. Epub 2012 Oct 4. PMID: 23067803.

[18] Sang YF, Wang ZG, Liu CM. Spatial and temporal variability of daily temperature during 1961-2010 in the Yangtze River basin, China. J Quaternary Int. 2012;1-10. doi:10.1016/j.quaint.2012.05.026.

[19] Zeng XF, Kundzewicz WZ, Zhou JZ, Su BD. Discharge projection in the Yangtze River basin under different emission scenarios based on the artificial neural networks. J Quaternary Int. 2011;1-9. doi:10.1016/j.quaint.2011.06.009.

[20] Zhang Q, Jiang T, Gemmer M, Becker S. Precipitation, temperature and discharge analysis from 1951-2002 in the Yangtze Catchment, China. Hydrol Sci J. 2005;50(1):65-80.

[21] Zhang Q, Xu YC, Zhang XZ, Chen DQ, Liu CL, Lin H. Spatial and temporal variability of precipitation maxima during 1960-2005 in the Yangtze River basin and possible association with large-scale circulation. J Hydrol. 2008;353:215-227.

[22] Xu JJ, Yang WD, Yi HY, Lei DZ, Chen J, Yang JW. Spatial and temporal variation of runoff in the Yangtze River basin during the past 40 years. J Quaternary Int. 2008;186:32-42.

[23] Johnes PJ. Evaluation and management of the impact of land use change on the nitrogen and phosphorus load delivered to surface waters: the export coefficient modeling approach. J Hydrol. 1996;183:323-349.

[24] Ding XW, Shen ZY, Hong Q, Yang ZF, Wu X, Liu RM. Development and test of the export coefficient model in the upper reach of the Yangtze River. J Hydrol. 2010;383:233-244.

[25] Liu RM, Yang ZF, Shen ZY, Yu SL, Ding XW, Wu X, Liu F. Estimating nonpoint source pollution in the upper Yangtze River using the export coefficient model, remote sensing, and geographical information system. J Hydraul Eng. 2009;135:698-704.

Correlation between Different Factors of Non-point Source Pollution in Yangtze River Basin

Affiliation

要約

数字