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

2021 ◽  
pp. 150405
Author(s):  
Sumudu Senanayake ◽  
Biswajeet Pradhan ◽  
Alfredo Huete ◽  
Jane Brennan
Keyword(s):  
Sri Lanka ◽  
Soil Erosion ◽  
Spatial Modeling ◽  
Crop Diversity ◽  
Rainfall Variation ◽  
Erosion Hazards ◽  
Central Highlands

scholarly journals A Review on Assessing and Mapping Soil Erosion Hazard Using Geo-Informatics Technology for Farming System Management

2020 ◽  
Vol 12 (24) ◽  
pp. 4063
Author(s):  
Sumudu Senanayake ◽  
Biswajeet Pradhan ◽  
Alfredo Huete ◽  
Jane Brennan
Keyword(s):  
Soil Erosion ◽  
Food Production ◽  
Land Use Changes ◽  
Farming Systems ◽  
Farming System ◽  
Water Erosion ◽  
Time Data ◽  
Erosion Hazard ◽  
Rainfall Variation ◽  
Erosion Hazards

Soil erosion is a severe threat to food production systems globally. Food production in farming systems decreases with increasing soil erosion hazards. This review article focuses on geo-informatics applications for identifying, assessing and predicting erosion hazards for sustainable farming system development. Several researchers have used a variety of quantitative and qualitative methods with erosion models, integrating geo-informatics techniques for spatial interpretations to address soil erosion and land degradation issues. The review identified different geo-informatics methods of erosion hazard assessment and highlighted some research gaps that can provide a basis to develop appropriate novel methodologies for future studies. It was found that rainfall variation and land-use changes significantly contribute to soil erosion hazards. There is a need for more research on the spatial and temporal pattern of water erosion with rainfall variation, innovative techniques and strategies for landscape evaluation to improve the environmental conditions in a sustainable manner. Examining water erosion and predicting erosion hazards for future climate scenarios could also be approached with emerging algorithms in geo-informatics and spatiotemporal analysis at higher spatial resolutions. Further, geo-informatics can be applied with real-time data for continuous monitoring and evaluation of erosion hazards to risk reduction and prevent the damages in farming systems.

scholarly journals Assessing soil quality and soil erosion hazards in the Moneragala District, Sri Lanka

2020 ◽  
Vol 2 (12) ◽  
Author(s):  
K. H. K. Perera ◽  
W. A. C. Udeshani ◽  
I. D. U. H. Piyathilake ◽  
G. E. M. Wimalasiri ◽  
H. K. Kadupitiya ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Soil Erosion ◽  
Soil Quality ◽  
Erosion Hazards

scholarly journals Application of Revised Universal Soil Loss Equation (Rusle) Model to Assess Soil Erosion in “Kalu Ganga” River Basin in Sri Lanka

2019 ◽  
Vol 2019 ◽  
pp. 1-15 ◽  
Author(s):  
D. L. D. Panditharathne ◽  
N. S. Abeysingha ◽  
K. G. S. Nirmanee ◽  
Ananda Mallawatantri
Keyword(s):  
Land Use ◽  
Sri Lanka ◽  
Soil Erosion ◽  
River Basin ◽  
Soil Loss ◽  
Management Practices ◽  
Agricultural Land ◽  
Universal Soil Loss Equation ◽  
Rusle Model ◽  
Soil Loss Equation

Soil erosion is one of the main forms of land degradation. Erosion contributes to loss of agricultural land productivity and ecological and esthetic values of natural environment, and it impairs the production of safe drinking water and hydroenergy production. Thus, assessment of soil erosion and identifying the lands more prone to erosion are vital for erosion management process. Revised Universal Soil Loss Equation (Rusle) model supported by a GIS system was used to assess the spatial variability of erosion occurring at Kalu Ganga river basin in Sri Lanka. Digital Elevation Model (30 × 30 m), twenty years’ rainfall data measured at 11 rain gauge stations across the basin, land use and soil maps, and published literature were used as inputs to the model. The average annual soil loss in Kalu Ganga river basin varied from 0 to 134 t ha−1 year−1 and mean annual soil loss was estimated at 0.63 t ha−1 year−1. Based on erosion estimates, the basin landscape was divided into four different erosion severity classes: very low, low, moderate, and high. About 1.68% of the areas (4714 ha) in the river basin were identified with moderate to high erosion severity (>5 t ha−1 year−1) class which urgently need measures to control soil erosion. Lands with moderate to high soil erosion classes were mostly found in Bulathsinghala, Kuruwita, and Rathnapura divisional secretarial divisions. Use of the erosion severity information coupled with basin wide individual RUSLE parameters can help to design the appropriate land use management practices and improved management based on the observations to minimize soil erosion in the basin.

Geoenvironmental factors related to high incidence of human urinary calculi (kidney stones) in Central Highlands of Sri Lanka

2015 ◽  
Vol 38 (5) ◽  
pp. 1203-1214 ◽  
Author(s):  
Buddhika Abeywickarama ◽  
Udaya Ralapanawa ◽  
Rohana Chandrajith
Keyword(s):  
Sri Lanka ◽  
Kidney Stones ◽  
Urinary Calculi ◽  
High Incidence ◽  
Central Highlands

scholarly journals Notes on the diet and habitat selection of the Sri Lankan Leopard Panthera pardus kotiya (Mammalia: Felidae) in the central highlands of Sri Lanka

2014 ◽  
Vol 6 (9) ◽  
pp. 6214-6221 ◽  
Author(s):  
Andrew M. Kittle ◽  
Anjali C. Watson ◽  
P.H.S. Chanaka Kumara ◽  
S.D. Kashmi C. Sandanayake ◽  
H.K. Nimalka Sanjeewani ◽  
...  
Keyword(s):  
Sri Lanka ◽  
Habitat Selection ◽  
Sri Lankan ◽  
Panthera Pardus ◽  
Central Highlands ◽  
Selection Of

scholarly journals GIS and RS Based Soil Erosion Modelling in Sri Lanka: A Review

2021 ◽  
Vol 16 (1) ◽  
pp. 143
Author(s):  
I. D. U. H. Piyathilake ◽  
E. P. N. Udayakumara ◽  
Sunethra Kanthi Gunatilake
Keyword(s):  
Sri Lanka ◽  
Soil Erosion ◽  
Erosion Modelling ◽  
Gis And Rs

scholarly journals Modeling and Assessing Potential Soil Erosion Hazards Using USLE and Wind Erosion Models in Integration with GIS Techniques: Dakhla Oasis, Egypt

Agriculture ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 1124
Author(s):  
Salman A. H. Selmy ◽  
Salah H. Abd Al-Aziz ◽  
Raimundo Jiménez-Ballesta ◽  
Francisco Jesús García-Navarro ◽  
Mohamed E. Fadl
Keyword(s):  
Soil Erosion ◽  
Soil Loss ◽  
Wind Erosion ◽  
Water Erosion ◽  
Soil Erodibility ◽  
Gis Techniques ◽  
Five Factors ◽  
Dakhla Oasis ◽  
Erosion Hazards ◽  
Loss Rates

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.

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