Chrome Extension
WeChat Mini Program
Use on ChatGLM

Predicting Wetland Occurrence in the Arid to Semi—Arid 1 Interior of the Western Cape, South Africa, for Improved 2 Mapping and Management

Research Square (Research Square)(2021)

Cited 0|Views7
No score
Abstract
Abstract As for drylands globally, there has been limited effort to map and characterize such wetlands in the Western Cape interior of South Africa. Thus, the study assessed how wetland occurrence and type in the arid to semi-arid interior of the Western Cape relate to key biophysical drivers, and, through predictive modelling, to contribute towards improved accuracy of the wetland map layer. Field-verified test areas were selected to represent the aridity gradient, rainfall seasonality, hydrogeomorphic (HGM) types and physiographic zones encompassed in the study area. The arid areas of the Karoo physiographic zones had: (1) a low (<1%) proportional area of wetland; (2) an almost complete absence of seepage slope wetlands; (3) ephemeral depressions, all non-vegetated; and (4) much of the wetland associated with valley bottoms confined within a channel. The less arid mountain zones had: (1) a much higher (>3%) proportional area of wetland; and (2) wetlands being predominantly hillslope seepages, but also including valley bottom wetlands. A spatial probability surface of wetland occurrence was generated based on the statistical relationship of verified wetland presence and absence data points with a range of catchment-scale predictor variables, including topographic metrics and hydrological/climatic variables. This layer was combined with raster images of most likely HGM type within the landscape to provide a final product of wetland occurrence, attributed by HGM type. Vulnerabilities of the wetlands were identified based on key attributes of the different wetland types, and recommendations were provided for refining the wetland map for the Western Cape.
More
Translated text
Key words
wetland occurrence,arid,western cape,south africa
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined