Spatio-temporal changes in rate of soil loss and erosion vulnerability of selected region in the tropical forests of Borneo during last three decades

An attempt has been made to analyze the spatial-temporal characteristics of soil erosion vulnerability and soil loss from the forested region in the north-eastern Borneo, Sarawak, Malaysia during the last three decades (1991–2015) using the revised universal soil loss equation (RUSLE) and geographical information systems (GIS). The components of RUSLE such as rainfall erosivity (R), soil erodibility (K), slope-length and steepness (LS), cover management (C) and conservation practice (P) factors were grouped into two categories by keeping one set as temporally changing and others as static. Among them the R and C factors are calculated for the years 1991, 2001 and 2015 whereas the K and LS factors are considered for the single time frame. Because of the forested nature of the study area, the P factor is kept constant for the whole analysis. The R factor and C factor is shown changes in values and its distribution over the years, which reflected in the final soil loss and erosion vulnerability map as a change in the rate of erosion and spatial domain. The analysis of three time slices has shown that the maximum value of the soil loss per unit area i.e. at erosion hotspots, is relatively similar throughout at around 1636 to 1744 t/ha/y. This is the result of maximum values of R factor and C factor i.e. high rainfall erosivity combined with lack of vegetation cover in those hotspots, which are generally steeply sloping terrain. The reclassification of annual soil loss map into erosion vulnerability zones indicated a major increase in the spatial spread of erosion vulnerability from the year 1991 to 2015 with a significant increase in the high and critical erosion areas from 2.3% (1991) to 31.5% (2015). In 1991, over 84% of the study area was under low erosion vulnerability class but by the year 2015 only 12% was under low erosion vulnerability class. Moreover, a dynamic nature in the erosion pattern was found from the year 1991 to 2015 with more linear areas of land associated with higher rate of soil loss and enhanced erosion vulnerability. The linearity in the spatial pattern is correlated with the development of logging roads and logging activities which has been confirmed by the extraction of exposed areas from satellite images of different years of analysis. The findings of the present study has quantified the changes in vegetation cover from dense, thick tropical forest to open mixed type landscapes which provide less protection against erosion and soil loss during the severe rainfall events which are characteristic of this tropical region.

[1]  G. R. Foster,et al.  Predicting soil erosion by water : a guide to conservation planning with the Revised Universal Soil Loss Equation (RUSLE) , 1997 .

[2]  Kenneth G. Renard,et al.  Using monthly precipitation data to estimate the R-factor in the revised USLE , 1994 .

[3]  S. D. Angima,et al.  Soil erosion prediction using RUSLE for central Kenyan highland conditions , 2003 .

[4]  Neil Sipe,et al.  Planning implications of telecommunication: Why telecommunication infrastructure? Why now? , 2015 .

[5]  E. J. Roose.  Application of the universal soil loss equation of Wischmeier and Smith in West Africa , 1977 .

[6]  Soo Huey Teh.  Soil erosion modeling using RUSLE and GIS on Cameron highlands, Malaysia for hydropower development , 2011 .

[7]  I. Moore,et al.  Physical basis of the length-slope factor in the universal soil loss equation , 1986 .

[8]  Bofu Yu,et al.  An Assessment of a Daily Rainfall Erosivity Model for NSW , 1996 .

[9]  I. D. Moore,et al.  Modelling Erosion and Deposition: Topographic Effects , 1986 .

[10]  W. H. Wischmeier,et al.  Predicting rainfall erosion losses : a guide to conservation planning , 1978 .

[11]  A..  Hydrological effects and nutrient losses of forest plantation establishment on tropical rainforest land in Sabah , Malaysia , 2003 .

[12]  T. Stadtmueller.  Soil erosion in East Kalimantan, Indonesia. , 1990 .

[13]  G. R. Foster,et al.  storm Erosivity Using Idealized Intensity Distributions , 1987 .

[14]  W. H. Wischmeier,et al.  SOIL ERODIBILITY NOMOGRAPH FOR FARMLAND AND CONSTRUCTION SITES , 1971 .

[15]  Shoji Noguchi,et al.  Sediment pathways in a tropical forest: effects of logging roads and skid trails , 2004 .

[16]  Ravi Prabhu,et al.  Factors affecting runoff and soil erosion: plot-level soil loss monitoring for assessing sustainability of forest management , 2003 .

[17]  G. R. Foster,et al.  Conversion of the universal soil loss equation to SI metric units , 1981 .

[18]  A. Ziegler,et al.  Erosion processes in steep terrain—Truths, myths, and uncertainties related to forest management in Southeast Asia , 2006 .

[19]  B. Evans.  Soil erosion and Conservation. Third edition , 2006 .

[20]  G. R. Foster,et al.  RUSLE: Revised universal soil loss equation , 1991 .

[21]  Georgios N. Silleos,et al.  Quantification and site-specification of the support practice factor when mapping soil erosion risk associated with olive plantations in the Mediterranean island of Crete , 2009, Environmental monitoring and assessment.

[22]  T. Lihan,et al.  Integration of remote sensing, RUSLE and GIS to model potential soil loss and sediment yield (SY) , 2013 .

[23]  I. Douglas.  The impact of land-use changes, especially logging, shifting cultivation, mining and urbanization on sediment yields in humid tropical Southeast Asia: a review with special reference to Borneo , 1996 .

[24]  Aaron Russo,et al.  Applying the Revised Universal Soil Loss Equation model to land use planning for erosion risk in Brunei Darussalam , 2015 .

[25]  J. Poesen,et al.  The European Soil Erosion Model (EUROSEM): A dynamic approach for predicting sediment transport from fields and small catchments. , 1998 .

[26]  Biswajeet Pradhan,et al.  Soil erosion prediction based on land cover dynamics at the Semenyih watershed in Malaysia using LTM and USLE models , 2016 .

[27]  Luca Montanarella,et al.  Soil erosion risk assessment in Europe , 2000 .

[28]  Dengsheng Lu,et al.  Mapping soil erosion risk in Rondônia, Brazilian Amazonia: using RUSLE, remote sensing and GIS , 2004 .

[29]  Panos Panagos,et al.  Estimating the soil erosion cover-management factor at the European scale , 2015 .

[30]  Luca Montanarella,et al.  Soil erosion risk assessment in Italy , 1999 .

[31]  I. Moore,et al.  Digital terrain modelling: A review of hydrological, geomorphological, and biological applications , 1991 .