Abstract:
Gullies often occur in semi-arid regions characterized by rainfall variability,
seasonality and increased overland flow, affecting ecological fragility of an area.
In most gully prone areas, extent of land affected by gullies is increasing. Thus,
predicting susceptibility to gully erosion in semi-arid environment is an
important step towards effective rehabilitating and prevention of gully erosion.
Proneness to gully occurrence was assessed against; Land cover/land use, slope,
soil characteristics, rainfall variability and elevation, and modelled using GISbased bivariate statistical approach. The study assessed influence of
geomorphological factors on gully erosion, analyzed and developed gully
erosion susceptibility map and verified gully susceptibility images using error
matrix of class labels in classified map against ground truth reference data. A
total of 66 gullied areas (width and depth ≥ ranging 0.5m), were mapped using
15m resolution Landsat images for 2018 and field surveys to estimate
susceptibility to gully erosion by Global Mapper software in GIS. The images
were verified using 120 pixels of known 15 gully presence or absence to produce
an error matrix based on comparison of actual outcomes to predicted outcomes.
Influence of conditioning factors to gully erosion showed a significant positive
relationship between gully susceptibility and gully conditioning factors with
consistency value; CR =0.097; value< 0.1, indicating, individual
conditioning factors influenced gully erosion. Slope (43%) and soil
lithotype (25%), had most influence on gully susceptibility, while land
cover/land use (12%) and rainfall (12) had least impact. Verification results
showed satisfactory agreement between susceptibility map and field data on
gullied areas at approximately 76.2%, an error of positive value of 4% and a
negative value of 7%. Thus, production of susceptibility map by bivariate
statistical method represents a useful tool for ending long and short-term gully
emergencies by planning conservation of semi-arid regions.
