Application of the coupled MIKE SHE/MIKE 11 modelling system to a lowland wet grassland in southeast England
Introduction
The last decades of the 20th century witnessed the growing appreciation of wetlands as important ecosystems that are not only valuable wildlife habitats but which also provide a range of benefits to human communities (e.g. Williams, 1990, Thompson and Hollis, 1997, Mitsch and Gosselink, 2000). However, over the same period the magnitude of wetland loss and degradation which had taken place, especially in the second half of the century, was identified by many as a major cause for concern (e.g. Finlayson and Moser, 1992, Mitsch et al., 1994, CEC, 1995). In response to these concerns, a host of initiatives at local, national and international levels have been developed which aim to improve the management of existing wetlands, restore or recreate those which have been lost or degraded and even to create wetlands on previously dry sites. Hydrological information and understanding is central to the success of such wetland management, restoration and creation initiatives (Gilvear and Bradley, 2000, Hollis and Thompson, 1998, Thompson and Finlayson, 2000). This is not only because hydrological processes influence the formation and subsequent physical, chemical and biological characteristics of wetlands (Mitsch and Gosselink, 2000) but also because many of the human-induced impacts on wetlands result from hydrological modifications within the wetlands themselves or within their catchments. Conservation-oriented wetland management practices may include further hydrological modifications, such as raising water levels and infilling or diverting drainage channels, in order to establish and maintain conditions required by desirable wetland plant and animal species. Improvements in the ability to predict the impacts of such manipulations before they are undertaken are required in order to develop management schemes that will achieve their goals, avoid undesirable outcomes and effectively target the often limited resources available to wetland management and conservation practitioners. There is therefore significant potential for models that can accurately represent the often complex hydrological situations found in wetlands.
This paper presents results from one part of a three-year project, System for HYdrology using Land Observation for model Calibration (SHYLOC), which was partly funded by the European Commission's Space Technology Programme under the fourth Framework Programme (Al-Khudhairy et al., 2001b). The first main aim of this project was to develop a remote sensing technique that provides estimates of water levels within wetland channels from satellite imagery (Shepherd et al., 2000). This was designed to address the often inadequate monitoring undertaken within many wetlands (e.g. Hollis and Thompson, 1998) which limits the establishment of historical and contemporary base-line data against which the results of hydrological management schemes can be assessed. The results of this part of the project are discussed elsewhere (Al-Khudhairy et al., 2001a, Al-Khudhairy et al., 2002). The project's second main aim was to couple the MIKE SHE hydrological model with the MIKE 11 hydraulic model, thereby creating a modelling system suitable for wetland hydrological applications. The application of this coupled modelling system to one of the wetland test sites used within the SHYLOC project forms the basis of this paper.
Section snippets
MIKE SHE
The MIKE SHE modelling system (Refsgaard and Storm, 1995) is based on the SHE (Système Hydrologique Européen; Abbott et al., 1986a, Abbott et al., 1986b) model. It is a deterministic, fully distributed and physically based modelling system. The MIKE SHE Water Movement module has a modular structure comprising six process-oriented components which describe the major physical processes of the land phase of the hydrological cycle: interception/evapotranspiration, overland/channel flow, unsaturated
Wet grasslands in the UK and the Elmley Marshes
The Elmley Marshes are an archetypal example of a UK lowland wet grassland. They are located on the southern side of the Isle of Sheppey, to the west of the Bells Creek catchment modelled by Al-Khudhairy and Thompson, 1997, Al-Khudhairy et al., 1999, and constitute part of the North Kent Marshes (Fig. 3). Wet grasslands are important wetland types in the UK and include semi-natural floodplain grasslands, grazing marshes, flood meadows, man-made washlands and water meadows (e.g. RSPB, 1997,
Data availability
A coupled MIKE SHE/MIKE 11 model was developed for the Elmley Marshes with the aim of representing observed hydrological conditions during a 36 month period (25/6/1997-29/6/2000) for which sufficient data were available for model calibration and validation. The large data requirements of distributed hydrological models such as MIKE SHE has been acknowledged (e.g. Refsgaard, 1997, Christiaens and Feyen, 2000, Christiaens and Feyen, 2001, Biftu and Gan, 2001). The coupling of a MIKE 11 river
Model calibration and validation
Refsgaard and Storm (1995) suggested that the number of parameters subject to adjustment during calibration of a distributed hydrological model such as MIKE SHE should be as small as possible. For example, the parameters employed by Al-Khudhairy et al. (1999) to calibrate their MIKE SHE model of the Bells Creek catchment were limited to the hydraulic conductivity in the saturated zone, the Manning's roughness coefficient for overland flow and the drainage time constant. As discussed above, the
MIKE SHE groundwater results
Fig. 6 shows observed and simulated groundwater depth at four locations within the Elmley Marshes. The piezometers installed at these locations provided the most complete records as they were only infrequently subject to inundation. The model calibration and validation periods are indicated in Fig. 6 and for both periods the Nash-Sutcliffe efficiency coefficient, R2, for each location are provided. In addition, the R2 value for the whole simulation period is shown for each of the comparisons of
Summary and conclusions
Hydrology is central to the management, restoration and creation of wetland environments. Much of the wetland loss and degradation which has taken place is associated with hydrological changes while efforts to stem and reverse the trends of loss and degradation frequently rely on further hydrological manipulations to achieve conditions conducive to certain wetland plant and animal species. Improved ability to predict the impacts of hydrological modifications upon wetlands is therefore an
Acknowledgments
The SHYLOC project was partly funded by the European Commission's Space Technology Programme under the fourth Framework Programme. The authors would like to express their gratitude to all members of the SHYLOC team. The Elmley Conservation Trust granted access to the field site and provided logistical support during fieldwork. Assistance in the field was provided by Alison Berry, Emma Durham and Alistair Graham. Krissie Auld assisted in the processing of some field data. The Centre for Ecology
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2022, Journal of HydrologyCitation Excerpt :This simplification and dimensionality reduction could reduce computational time compared to variably saturated flow simulations in 2D or 3D (Panday and Huyakorn, 2004, Niswonger et al., 2006, Seo et al., 2007). Several conjunctive surface/subsurface models have been developed to simulate the overland flow on a plane with 1D or 2D overland flow and 1D, 2D, or 3D flow in the vadose zone (Smith and Woolhiser, 1971, Abbott et al., 1986, Singh and Bhallamudi, 1998, Morita and Yen 2002, Panday and Huyakorn, 2004, Thompson et al., 2004, He et al., 2008). Large-scale coupled hydrologic models, such as MIKE SHE (Thompson et al., 2004) and MODFLOW2000-H1D (Seo et al., 2007, Beegum et al., 2018) are examples of this dimensionality reduction approach.
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