IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i7p675-d74210.html
   My bibliography  Save this article

A Quantitative Method for Long-Term Water Erosion Impacts on Productivity with a Lack of Field Experiments: A Case Study in Huaihe Watershed, China

Author

Listed:
  • Degen Lin

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China)

  • Hao Guo

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China)

  • Fang Lian

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China)

  • Yuan Gao

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China)

  • Yaojie Yue

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China)

  • Jing’ai Wang

    (School of Geography, Beijing Normal University, Beijing 100875, China
    Key Laboratory of Regional Geography, Beijing Normal University, Beijing 100875, China
    State Key Laboratory of Earth Surface Processes and Resource Ecology, Beijing Normal University, Beijing 100875, China)

Abstract

Water erosion causes reduced farmland productivity, and with a longer period of cultivation, agricultural productivity becomes increasingly vulnerable. The vulnerability of farmland productivity needs assessment due to long-term water erosion. The key to quantitative assessment is to propose a quantitative method with water loss scenarios to calculate productivity losses due to long-term water erosion. This study uses the agricultural policy environmental extender (APEX) model and the global hydrological watershed unit and selects the Huaihe River watershed as a case study to describe the methodology. An erosion-variable control method considering soil and water conservation measure scenarios was used to study the relationship between long-term erosion and productivity losses and to fit with 3D surface (to come up with three elements, which are time, the cumulative amount of water erosion and productivity losses) to measure long-term water erosion. Results showed that: (1) the 3D surfaces fit significantly well; fitting by the 3D surface can more accurately reflect the impact of long-term water erosion on productivity than fitting by the 2D curve (to come up with two elements, which are water erosion and productivity losses); (2) the cumulative loss surface can reflect differences in productivity loss caused by long-term water erosion.

Suggested Citation

  • Degen Lin & Hao Guo & Fang Lian & Yuan Gao & Yaojie Yue & Jing’ai Wang, 2016. "A Quantitative Method for Long-Term Water Erosion Impacts on Productivity with a Lack of Field Experiments: A Case Study in Huaihe Watershed, China," Sustainability, MDPI, vol. 8(7), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:8:y:2016:i:7:p:675-:d:74210
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/7/675/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/8/7/675/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. United Nations, 2016. "The Sustainable Development Goals 2016," Working Papers id:11456, eSocialSciences.
    2. Philip W. Gassman & Jimmy R. Williams & Xiuying Wang & Ali Saleh & Edward Osei & Larry M. Hauck & R. César Izaurralde & Joan D. Flowers, 2009. "Agricultural Policy Environmental EXtender (APEX) Model: An Emerging Tool for Landscape and Watershed Environmental Analyses, The," Center for Agricultural and Rural Development (CARD) Publications 09-tr49, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    3. Nathaniel D. Mueller & James S. Gerber & Matt Johnston & Deepak K. Ray & Navin Ramankutty & Jonathan A. Foley, 2012. "Closing yield gaps through nutrient and water management," Nature, Nature, vol. 490(7419), pages 254-257, October.
    4. Philip W. Gassman & Jimmy R. Williams & Xiuying Wang & Ali Saleh & Edward Osei & Larry M. Hauck & R. César Izaurralde & Joan D. Flowers, 2009. "Agricultural Policy Environmental EXtender (APEX) Model: An Emerging Tool for Landscape and Watershed Environmental Analyses, The," Center for Agricultural and Rural Development (CARD) Publications 09-tr49, Center for Agricultural and Rural Development (CARD) at Iowa State University.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Leroux, L. & Falconnier, G.N. & Diouf, A.A. & Ndao, B. & Gbodjo, J.E. & Tall, L. & Balde, A.A. & Clermont-Dauphin, C. & Bégué, A. & Affholder, F. & Roupsard, O., 2020. "Using remote sensing to assess the effect of trees on millet yield in complex parklands of Central Senegal," Agricultural Systems, Elsevier, vol. 184(C).
    2. Ribaudo, Marc & Savage, Jeffrey, 2014. "Controlling non-additional credits from nutrient management in water quality trading programs through eligibility baseline stringency," Ecological Economics, Elsevier, vol. 105(C), pages 233-239.
    3. Wainger, L. & Loomis, J. & Johnston, R. & Hansen, L. & Carlisle, D. & Lawrence, D. & Gollehon, N. & Duriancik, L. & Schwartz, G. & Ribaudo, M. & Gala, C., 2017. "Ecosystem Service Benefits Generated by Improved Water Quality from Conservation Practices," C-FARE Reports 260679, Council on Food, Agricultural, and Resource Economics (C-FARE).
    4. Cisneros, J.M. & Grau, J.B. & Antón, J.M. & de Prada, J.D. & Cantero, A. & Degioanni, A.J., 2011. "Assessing multi-criteria approaches with environmental, economic and social attributes, weights and procedures: A case study in the Pampas, Argentina," Agricultural Water Management, Elsevier, vol. 98(10), pages 1545-1556, August.
    5. Tsakmakis, I.D. & Kokkos, N.P. & Gikas, G.D. & Pisinaras, V. & Hatzigiannakis, E. & Arampatzis, G. & Sylaios, G.K., 2019. "Evaluation of AquaCrop model simulations of cotton growth under deficit irrigation with an emphasis on root growth and water extraction patterns," Agricultural Water Management, Elsevier, vol. 213(C), pages 419-432.
    6. Marshall, Elizabeth & Aillery, Marcel & Ribaudo, Marc & Key, Nigel & Sneeringer, Stacy & Hansen, LeRoy & Malcolm, Scott & Riddle, Anne, 2018. "Reducing Nutrient Losses From Cropland in the Mississippi/Atchafalaya River Basin: Cost Efficiency and Regional Distribution," Economic Research Report 277567, United States Department of Agriculture, Economic Research Service.
    7. Tewodros Assefa & Manoj Jha & Manuel Reyes & Abeyou W. Worqlul, 2018. "Modeling the Impacts of Conservation Agriculture with a Drip Irrigation System on the Hydrology and Water Management in Sub-Saharan Africa," Sustainability, MDPI, vol. 10(12), pages 1-19, December.
    8. Omidreza Mikaeili & Mojtaba Shourian, 2024. "Improving Evapotranspiration Estimation in SWAT-Based Hydrologic Simulation through Data Assimilation in the SEBAL Algorithm," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 38(11), pages 4101-4122, September.
    9. Osei, Edward & Jafri, Syed H., 2017. "Climate Change impacts on Corn and Soybean Production in Iowa," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258348, Agricultural and Applied Economics Association.
    10. Rossetto, Rudy & De Filippis, Giovanna & Triana, Federico & Ghetta, Matteo & Borsi, Iacopo & Schmid, Wolfgang, 2019. "Software tools for management of conjunctive use of surface- and ground-water in the rural environment: integration of the Farm Process and the Crop Growth Module in the FREEWAT platform," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    11. Ribaudo, Marc & Savage, Jeffrey & Aillery, Marcel P., 2014. "An Economic Assessment of Policy Options To Reduce Agricultural Pollutants in the Chesapeake Bay," Economic Research Report 171880, United States Department of Agriculture, Economic Research Service.
    12. Zilverberg, Cody J. & Angerer, Jay & Williams, Jimmy & Metz, Loretta J. & Harmoney, Keith, 2018. "Sensitivity of diet choices and environmental outcomes to a selective grazing algorithm," Ecological Modelling, Elsevier, vol. 390(C), pages 10-22.
    13. Ecker, Olivier & Hatzenbuehler, Patrick L. & Mahrt, Kristi, 2018. "Transforming agriculture for improving food and nutrition security among Nigerian farm households," NSSP working papers 56, International Food Policy Research Institute (IFPRI).
    14. Cao, Juan & Zhang, Zhao & Tao, Fulu & Chen, Yi & Luo, Xiangzhong & Xie, Jun, 2023. "Forecasting global crop yields based on El Nino Southern Oscillation early signals," Agricultural Systems, Elsevier, vol. 205(C).
    15. Westhoek, Henk & Ingram, John & van Berkum, Siemen & Hajer, Maarten, 2015. "The European food system and natural resources: Impacts and Options," 148th Seminar, November 30-December 1, 2015, The Hague, The Netherlands 229279, European Association of Agricultural Economists.
    16. Giacomo Falchetta & Nicolò Stevanato & Magda Moner-Girona & Davide Mazzoni & Emanuela Colombo & Manfred Hafner, 2020. "M-LED: Multi-sectoral Latent Electricity Demand Assessment for Energy Access Planning," Working Papers 2020.09, Fondazione Eni Enrico Mattei.
    17. Claudia Hanson & Sanni Kujala & Peter Waiswa & Tanya Marchant & Joanna Schellenberg, 2017. "Community-based approaches for neonatal survival: Meta-analyses of randomized trial data," WIDER Working Paper Series wp-2017-137, World Institute for Development Economic Research (UNU-WIDER).
    18. Eugenia Ganea & Valentina Bodrug-Lungu, 2018. "Addressing Inequality in Vocational/ Technical Education by Eliminating Gender Bias," Revista romaneasca pentru educatie multidimensionala - Journal for Multidimensional Education, Editura Lumen, Department of Economics, vol. 10(4), pages 136-155, December.
    19. Fu, Yuanhong & Ding, Guijie & Quan, Wenxuan & Zhao, Xizhou & Tao, Qinghong, 2024. "Coupling optimization of water-fertilizer for coordinated development of the environment and growth of Pinus massoniana seedlings," Agricultural Water Management, Elsevier, vol. 300(C).
    20. Gallopín, Gilberto, 2018. "Back to the future," Energy Policy, Elsevier, vol. 123(C), pages 318-324.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:8:y:2016:i:7:p:675-:d:74210. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.