Spatial modeling of soil erosion hazards and crop diversity change with rainfall variation in the Central Highlands of Sri Lanka

Sumudu Senanayake; Biswajeet Pradhan; Alfredo Huete; Jane Brennan

doi:10.1016/j.scitotenv.2021.150405

Spatial modeling of soil erosion hazards and crop diversity change with rainfall variation in the Central Highlands of Sri Lanka

Sci Total Environ. 2022 Feb 1;806(Pt 2):150405. doi: 10.1016/j.scitotenv.2021.150405. Epub 2021 Sep 25.

Authors

Sumudu Senanayake¹, Biswajeet Pradhan², Alfredo Huete³, Jane Brennan⁴

Affiliations

¹ The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, NSW, Australia; Natural Resources Management Centre, Department of Agriculture, Peradeniya 20400, Sri Lanka.
² The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, NSW, Australia; Department of Energy and Mineral Resources Engineering, Sejong University, Choongmu-gwan, 209 Neungdong-ro, Gwangjin-gu, Seoul 05006, Republic of Korea; Earth Observation Center, Institute of Climate Change, University Kebangsaan Malaysia, 43600 UKM Bangi, Selangor, Malaysia. Electronic address: Biswajeet.Pradhan@uts.edu.au.
³ The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, NSW, Australia; Faculty of Science, University of Technology Sydney, Sydney, NSW 2007, Australia.
⁴ The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), Faculty of Engineering and IT, University of Technology Sydney, Sydney 2007, NSW, Australia.

PMID: 34582866
DOI: 10.1016/j.scitotenv.2021.150405

Abstract

The spatial variation of soil erosion is essential for farming system management and resilience development, specifically in the high climate hazard vulnerable tropical countries like Sri Lanka. This study aimed to investigate climate and human-induced soil erosion through spatial modeling. Remote sensing was used for spatial modeling to detect soil erosion, crop diversity, and rainfall variation. The study employed a time-series analysis of several variables such as rainfall, land-use land-cover (LULC) and crop diversity to detect the spatial variability of soil erosion in farming systems. Rain-use efficiency (RUE) and residual trend analysis (RESTREND) combined with a regression approach were applied to partition the soil erosion due to human and climate-induced land degradation. Results showed that soil erosion has increased from 9.08 Mg/ha/yr to 11.08 Mg/ha/yr from 2000 to 2019 in the Central Highlands of Sri Lanka. The average annual rainfall has increased in the western part of the Central Highlands, and soil erosion hazards such as landslides incidence also increased during this period. However, crop diversity has been decreasing in farming systems, namely wet zone low country (WL1a) and wet zone mid-country (WM1a), in the western part of the Central Highlands. The RUE and RESTREND analyses reveal climate-induced soil erosion is responsible for land degradation in these farming systems and is a threat to sustainable food production in the farming systems of the Central Highlands.

Keywords: Crop diversity change; GIS; Rainfall variation; Remote sensing; Soil erosion; Sri Lanka.

MeSH terms

Environmental Monitoring
Humans
Rain
Soil Erosion*
Soil*
Sri Lanka

Substances

Soil