Application of a GIS-Based Hydrological Model to Predict Surface Wetness of Blanket Bogs.

Wetlands (Wilmington)

National Parks and Wildlife Service, 90 King Street North, Smithfield, Dublin 7, Ireland.

Published: January 2024

Unlabelled: Understanding hydrological processes operating on relatively intact blanket bogs provides a scientific basis for establishing achievable restoration targets for damaged sites. A GIS-based hydrological model, developed to assess restoration potential of Irish raised bogs, was adapted and applied to four relatively intact blanket bogs in Ireland. The Modified Flow Accumulation Capacity (MFAC) model utilised high-resolution topographic data to predict surface wetness, based on climatic conditions, contributing catchment and local surface slope. Modifications to MFAC parameters aimed to account for differences in hydrological processes between raised bogs and blanket bogs. Application of a climatic correction factor accounted for variations in effective rainfall between the four study sites, while monitoring of water table levels indicated a log-linear relationship between MFAC values and summer water table levels and range of water table fluctuations. Deviations from the observed relationship between MFAC and water table levels were associated with hydrological pressures, such as artificial drainage or the occurrence of subsurface macropores (peat pipes), which further lowered summer water tables. Despite being effective as a predictor of relative surface wetness, the relationship between MFAC and ecological variables such as cover proved poor, pointing to the impact of past activities and damage caused by anthropogenic pressures. Findings demonstrated MFAC as an effective tool in predicting surface wetness within blanket bog-covered landscapes, thus proving useful to peatland practitioners in planning and prioritising areas for restoration.

Supplementary Information: The online version contains supplementary material available at 10.1007/s13157-023-01765-5.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10764537PMC
http://dx.doi.org/10.1007/s13157-023-01765-5DOI Listing

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