International Journal of Environmental Monitoring and Analysis

| Peer-Reviewed |

A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services

Received:     Accepted:     Published: Oct. 30, 2013
Views:       Downloads:

Share This Article

Abstract

It is well known that land-use changes influence the hydrological cycle and that those changes in the hydrological cycle influence land use. The sophisticated spatial dynamic planning tools that have been developed in the last decades to support policy makers in the decision making process do not take into account the mutual feedbacks between land use and hydrology. In this study a framework for an integrated spatial decision support system is presented where the feedbacks between land use and hydrology are taken into account by coupling the SITE (Simulation of Terrestrial Environments) land-use model to the SWIM hydrological model. This framework enables policy makers to assess the impact of their planning scenarios on ecosystem services using a web-based tool that interactively presents trends in space and time of spatial indicators derived from both models. This approach is tested for the uThukela area, which is located along the northern areas of the Drakensberg Mountains which form the border between Lesotho and South Africa. The region is extremely important for its catchment-services as water derived from it is pumped into the Vaal River supplying water to the city of Johannesburg. Because of poor management of ecosystem services, less water is produced by the catchment more erratically, siltation levels are increasing and less carbon is retained in the soil. Biodiversity is threatened by grazing livestock, alien plants and other poor land management practices. In addition, overstocking, frequent burning and lack of soil protection measures have caused rill and gully erosion in areas of communal ownership where an overall management policy is lacking. The presented framework for a spatial integrated decision support system is currently being implemented and will be used by policy makers to assess policies developed for an Environmental Management Framework (EMF). Scenarios will be defined during stakeholder workshops. A prototype of the decision support system has been developed, but not all data necessary for modelling and calibration is yet available. From the analysis of land-use maps of 2005 and 2008 it was observed that forest and bush decreased, while settlements, subsistence farming, commercial farming and grassland increased.

DOI 10.11648/j.ijema.20130105.18
Published in International Journal of Environmental Monitoring and Analysis ( Volume 1, Issue 5, October 2013 )
Page(s) 230-236
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Integrated Water Resources Management, Spatial Planning, Land-Use Modelling, Ecosystem Services

References
[1] G. Arciniegas, R. Janssen, Spatial decision support for collaborative land use planning workshops, Landscape Urban Plan. 107 (2012) 332–342.
[2] J. E. Vermaat, S. Broekx, B. Van Eck, G. Engelen, F. Hellmann, J. L. De Kok, H. Van der Kwast, J. Maes, W. Salomons, W. Van Deursen, Nitrogen Source Apportionment for the Catchment, Estuary, and Adjacent Coastal Waters of the River Scheldt,Ecol. Soc. 17 (2012) art30.
[3] R. White, B. Straatman, G. Engelen, Planning scenario visualization and assessment: a cellular automata based integrated spatial decision support system, in:M. F. Goodchild, D. G. Janelle (Eds.), Spatially Integrated Social Science (Spatial Information Systems), Oxford University Press, Oxford, 2004, pp. 420–443.
[4] H. Van Delden, P. Luja, G. Engelen, Integration of multi-scale dynamic spatial models of socio-economic and physical processes for river basin management,Environ. Modell. Softw. 22 (2007) 223–238.
[5] G. Engelen, C. Lavalle, J. L. Barredo, M. van der Meulen, R. White, The MOLAND modelling framework for urban and regional land-use dynamics, in: E. Koomen, J. Stillwell, A. Balkema, H. J. Scholten (Eds.), Modelling land-use change progress and applications, Springer, Dordrecht, 2007, pp. 297–320.
[6] C. Schweitzer, J. A. Priess, S. Das, A generic framework for land-use modelling, Environ. Modell. Softw. 26 (2011) 1052–1055.
[7] R. M. Argent, An overview of model integration for environmental applications—components, frameworks and semantics, Environ Modell Softw. 19 (2004) 219–234.
[8] J. Hinkel, The PIAM approach to modular integrated assessment modelling, Environ Modell. Softw. 24 (2009) 739–748.
[9] V. Krysanova, D.-I. Müller-Wohlfeil, A. Becker, Development and test of a spatially distributed hydrological/water quality model for mesoscale watersheds, Ecol.Model. 106 (1998) 261–289.
[10] DSPED, UThukela District Municipality Integrated Development Plan (I.D.P.) Draft 2010/2011, Ladysmith, 2010.
[11] DEAT, Environmental Management Plans, Integrated Environmental Management, Pretoria, 1998.
[12] DAEA&RD, KwaZulu-Natal State of the Environment: Terrestrial Specialist Report, Pietermaritzburg, 2010.
[13] DWAF, Internal Strategic Perspective: Thukela Water Management Area, 2004.
[14] M. Mimler, J. Priess, Design and complementation of a generic modeling framework-a platform for integrated land use modeling. Kassel university press GmbH, Kassel, 2008.
[15] O. Schmitz, D. Karssenberg, K. de Jong, J. de Kok, Constructing integrated models: a scheduler to execute coupled components, Proceedings of the 14th AGILE conference, Utrecht, 2011.
[16] J. B. Gregersen, P. J. A. Gijsbers, S. J. P. Westen, OpenMI: Open modelling interface,J. Hydroinf. 9 (2007) 175–191.
[17] J. A. Priess, M. Mimler, A. Klein, S. Schwarze, T. Tscharntke, I. Steffan-Dewenter, Linking deforestation scenarios to pollination services and economic returns in coffee agroforestry systems, Ecol. Appl. 17 (2007) 407–417.
[18] J. A. Priess, C. Schweitzer, F. Wimmer, O. Batkhishig, M. Mimler, The consequences of land-use change and water demands in Central Mongolia, Land Use Policy28 (2011) 4–10.
[19] J. Schiff, Cellular automata: a discrete view of the world. John Wiley & Sons, Hoboken, 2008.
[20] R. Aspinall, D. Pearson, Integrated geographical assessment of environmental condition in water catchments: Linking landscape ecology, environmental modelling and GIS, J. Environ. Manage. 59 (2000) 299–319.
[21] D. Niemeijer, Developing indicators for environmental policy: data-driven and theory-driven approaches examined by example Environ Sci. Policy 5 (2002) 91–103.
Cite This Article
  • APA Style

    J. van der Kwast, S. Yalew, C. Dickens, L. Quayle, J. Reinhardt, et al. (2013). A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services. International Journal of Environmental Monitoring and Analysis, 1(5), 230-236. https://doi.org/10.11648/j.ijema.20130105.18

    Copy | Download

    ACS Style

    J. van der Kwast; S. Yalew; C. Dickens; L. Quayle; J. Reinhardt, et al. A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services. Int. J. Environ. Monit. Anal. 2013, 1(5), 230-236. doi: 10.11648/j.ijema.20130105.18

    Copy | Download

    AMA Style

    J. van der Kwast, S. Yalew, C. Dickens, L. Quayle, J. Reinhardt, et al. A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services. Int J Environ Monit Anal. 2013;1(5):230-236. doi: 10.11648/j.ijema.20130105.18

    Copy | Download

  • @article{10.11648/j.ijema.20130105.18,
      author = {J. van der Kwast and S. Yalew and C. Dickens and L. Quayle and J. Reinhardt and S. Liersch and M. Mul and M. Hamdard and W. Douven},
      title = {A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services},
      journal = {International Journal of Environmental Monitoring and Analysis},
      volume = {1},
      number = {5},
      pages = {230-236},
      doi = {10.11648/j.ijema.20130105.18},
      url = {https://doi.org/10.11648/j.ijema.20130105.18},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijema.20130105.18},
      abstract = {It is well known that land-use changes influence the hydrological cycle and that those changes in the hydrological cycle influence land use. The sophisticated spatial dynamic planning tools that have been developed in the last decades to support policy makers in the decision making process do not take into account the mutual feedbacks between land use and hydrology. In this study a framework for an integrated spatial decision support system is presented where the feedbacks between land use and hydrology are taken into account by coupling the SITE (Simulation of Terrestrial Environments) land-use model to the SWIM hydrological model. This framework enables policy makers to assess the impact of their planning scenarios on ecosystem services using a web-based tool that interactively presents trends in space and time of spatial indicators derived from both models. This approach is tested for the uThukela area, which is located along the northern areas of the Drakensberg Mountains which form the border between Lesotho and South Africa. The region is extremely important for its catchment-services as water derived from it is pumped into the Vaal River supplying water to the city of Johannesburg. Because of poor management of ecosystem services, less water is produced by the catchment more erratically, siltation levels are increasing and less carbon is retained in the soil. Biodiversity is threatened by grazing livestock, alien plants and other poor land management practices. In addition, overstocking, frequent burning and lack of soil protection measures have caused rill and gully erosion in areas of communal ownership where an overall management policy is lacking. The presented framework for a spatial integrated decision support system is currently being implemented and will be used by policy makers to assess policies developed for an Environmental Management Framework (EMF). Scenarios will be defined during stakeholder workshops. A prototype of the decision support system has been developed, but not all data necessary for modelling and calibration is yet available. From the analysis of land-use maps of 2005 and 2008 it was observed that forest and bush decreased, while settlements, subsistence farming, commercial farming and grassland increased.},
     year = {2013}
    }
    

    Copy | Download

  • TY  - JOUR
    T1  - A Framework for Coupling Land Use and Hydrological Modelling for Management of Ecosystem Services
    AU  - J. van der Kwast
    AU  - S. Yalew
    AU  - C. Dickens
    AU  - L. Quayle
    AU  - J. Reinhardt
    AU  - S. Liersch
    AU  - M. Mul
    AU  - M. Hamdard
    AU  - W. Douven
    Y1  - 2013/10/30
    PY  - 2013
    N1  - https://doi.org/10.11648/j.ijema.20130105.18
    DO  - 10.11648/j.ijema.20130105.18
    T2  - International Journal of Environmental Monitoring and Analysis
    JF  - International Journal of Environmental Monitoring and Analysis
    JO  - International Journal of Environmental Monitoring and Analysis
    SP  - 230
    EP  - 236
    PB  - Science Publishing Group
    SN  - 2328-7667
    UR  - https://doi.org/10.11648/j.ijema.20130105.18
    AB  - It is well known that land-use changes influence the hydrological cycle and that those changes in the hydrological cycle influence land use. The sophisticated spatial dynamic planning tools that have been developed in the last decades to support policy makers in the decision making process do not take into account the mutual feedbacks between land use and hydrology. In this study a framework for an integrated spatial decision support system is presented where the feedbacks between land use and hydrology are taken into account by coupling the SITE (Simulation of Terrestrial Environments) land-use model to the SWIM hydrological model. This framework enables policy makers to assess the impact of their planning scenarios on ecosystem services using a web-based tool that interactively presents trends in space and time of spatial indicators derived from both models. This approach is tested for the uThukela area, which is located along the northern areas of the Drakensberg Mountains which form the border between Lesotho and South Africa. The region is extremely important for its catchment-services as water derived from it is pumped into the Vaal River supplying water to the city of Johannesburg. Because of poor management of ecosystem services, less water is produced by the catchment more erratically, siltation levels are increasing and less carbon is retained in the soil. Biodiversity is threatened by grazing livestock, alien plants and other poor land management practices. In addition, overstocking, frequent burning and lack of soil protection measures have caused rill and gully erosion in areas of communal ownership where an overall management policy is lacking. The presented framework for a spatial integrated decision support system is currently being implemented and will be used by policy makers to assess policies developed for an Environmental Management Framework (EMF). Scenarios will be defined during stakeholder workshops. A prototype of the decision support system has been developed, but not all data necessary for modelling and calibration is yet available. From the analysis of land-use maps of 2005 and 2008 it was observed that forest and bush decreased, while settlements, subsistence farming, commercial farming and grassland increased.
    VL  - 1
    IS  - 5
    ER  - 

    Copy | Download

Author Information
  • UNESCO-IHE Institute for Water Education, Delft, the Netherlands

  • UNESCO-IHE Institute for Water Education, Delft, the Netherlands

  • Institute of Natural Resources, Scottsville, South Africa

  • Institute of Natural Resources, Scottsville, South Africa

  • Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany

  • Potsdam Institute for Climate Impact Research (PIK), Potsdam, Germany

  • International Water Management Institute (IWMI), Ghana

  • UNESCO-IHE Institute for Water Education, Delft, the Netherlands

  • UNESCO-IHE Institute for Water Education, Delft, the Netherlands

  • Section