Impacts of Land Use/Land Cover change on boundary layer climate over eastern South Africa

Abstract

Land Use and Land Cover Change (LULCC) is a global phenomenon that has significant impacts on climate by regulating surface air temperatures and rainfall in a variety of ways. Examining the impacts of LULCC on surface moisture and heat fluxes, as well as hydro-meteorological variables has become critical to ensure that long-term climate variability and change are managed. The period (1990-2020) of rapid population growth and urbanisation necessitates the need for this study to determine the impacts of LULCC on climate variability and change over eastern South Africa in order to fully understand land-atmosphere interactions. Multi-temporal Landsat imagery, ground-based observations and reanalysis datasets were analysed in the investigation of the impact of LULCC on boundary layer climate over eastern South Africa from 1990 to 2020. Landsat imagery classification into six classes Land Use Land Cover (LULC) was done using the Random Forest (RF) classifier in Google Earth Engine cloud platform. The Detecting Breakpoints and Estimation Segments in Trends (DBEST) algorithm was used to detect and analyse LULCC. The time series of LULC classes, Climate Hazards Group's Infrared Precipitation with Station (CHIRPS) rainfall, CRU minimum and maximum air temperature, Global Land Data Assimilation System (GLDAS) evapotranspiration (ET) and potential evapotranspiration (PET), and Famine Early Warning System Network (FEWS NET) Land Data Assimilation System (FLDAS) surface heat fluxes - latent heat flux (LHF) and sensible heat flux (SHF) were computed, whilst Mann-Kendall (MK) trend test was analysed in RStudio. The Pearson Correlation Coefficient was used to test the statistical significance of LULCC's impact on surface energy and moisture fluxes, as well as hydrometeorological variables. The most sensitive variable to change influencing boundary layer climate was identified using variables of importance. Furthermore, Multiple-Linear Regression and Pearson correlation analyses were used to determine land cover types that affect boundary layer climate. LULCC is occurring more frequently and significantly primarily due to anthropogenic influence, with natural phenomena occasionally contributing to land surface modification. DBEST detected that LULCC is occurring annually and during periods of weather and climate extremes as significant abrupt change of natural land cover occurs. The MK trend test indicates that the Normalised Difference Vegetation Index (NDVI), and land surface temperature (LST) increased significantly, while Normalised Difference Infrared Index (NDII) indicates an insignificant decreasing trend. Furthermore, MK trends revealed that rainfall and LHF decreased insignificantly, while maximum temperature, evapotranspiration (ET), SHF and PET increased significantly from 1979 to 2020. The great escarpment over eastern South Africa influences climate conditions on the west side of the study, resulting in lower temperatures but higher rainfall due to orographic effects. Results indicated that LULCC have significant influence on rainfall and

temperature, and their impacts and significance vary across land cover and regions. The study revealed that PET is the most sensitive parameter affecting temperature variability over eastern South Africa, while LHF affects rainfall variability, influences rainfall over eastern region. The expansion of urban land and bare land in the study area have significantly altered rainfall and temperature patterns whilst water, cropland, grassland and forest influenced different study regions. ENSO and IOD were found to have a significant positive correlation with rainfall and temperature in this study. In eastern South Africa, the vulnerability of rainfall to IOD varied, with some regions exhibiting no correlation and others displaying significant positive and negative correlations.