Hydrological modelling of a drained grazing marsh under agricultural land use and the simulation of restoration management scenarios

The capability of the spatially-distributed, physically-based, rainfall-runoff modelling system, MIKE SHE, to simulate the hydrological behaviour of the natural and drained parts of the North Kent Grazing Marshes, UK, is investigated. The MIKE SHE code is applied to Bells Creek, a small, underdraine...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Hydrological sciences journal 1999-12, Vol.44 (6), p.943-971
Hauptverfasser: AL-KHUDHAIRY, D. H. A., THOMPSON, J. R., GAVIN, H., HAMM, N. A. S.
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:The capability of the spatially-distributed, physically-based, rainfall-runoff modelling system, MIKE SHE, to simulate the hydrological behaviour of the natural and drained parts of the North Kent Grazing Marshes, UK, is investigated. The MIKE SHE code is applied to Bells Creek, a small, underdrained, agricultural catchment located within the marshes. The model is used to both provide insights into the essential parameters that control the hydrological processes in the catchment, and predict the influence of various, hypothetical, water management strategies (land use and drainage) on pumped discharge and soil moisture storage in the catchment. The water table model predictions arising from these hypothetical scenarios are also compared against field data obtained from on-going hydrological research on the neighbouring, natural, Elmley Marshes. The comparison is found to be favourable. The results of this study indicate the potential of the MIKE SHE system to simulate the hydrological regime of these wetlands, and hence to play an important role as a tool that can assist environmental and conservation agencies in the sound management of wetland resources.
ISSN:0262-6667
2150-3435
DOI:10.1080/02626669909492291