assessment of soil erosion using usle model and gis for integrated ...

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Fig.7: Thematic land cover mapFig.8: Spatial distribution of C FactorIII.5/ Support practice P-factorThe P-factor is the ratio of soil loss with specific support practice to the corresponding losswith up and downslope tillage. These practices proportionally affect erosion by modifying theflow pattern, gradient, or direction of surface runoff and by reducing the amount and rate ofrunoff. The P values are between 0 and 1. Because of a lack of information on practicesconservation tillage, we adopt P = 1 over the study area for not modify the final result.IV RESULTSAll factors layers R, LS, K, and C, computed and spatialized previously by the use of GISfunctions, are combined together to obtain a soil loss rate layer (Fig. 9). We obtain an averageof 137 t/ha/yr of potential erosion in the study area. Three-quarters of the study area (64%)have an erosion rate under 200 t/ha/yr. These areas correspond primarily to the basinfloodplains and flat areas of the “Central Chain” covered by forests. These regions are theleast sensitive to erosion. The very high estimations of soil loss (more than 1000 t/ha/yr) arelocated in 6% of the study area and correspond primarily at the top hills of the “CentralChain”. The high values of soil loss are the result of the combination of steep slopes, highprecipitation, altered soils and bare soils due to human activities, such as agriculture, landclearingby fire and mining activities located on the most sensitive areas to erosion. A firstvisual interpretation of the different factors shows that topography seems to be the dominantdriver for explaining the variation in erosion rate. The results and particularly the high valuesseem to be overestimated. The LS values will be overweighted in this analysis. In fact, theextreme slopes throughout the mountain areas do not correlate well with the USLE model,which was originally developed for mild slopes in agricultural areas. The others reasons areprobably the quality of the input data implemented in the model. The spatial scale is notadapted as the soil map for example or the typology of the land use map is not precise: it'snecessary to have more detailed land use data in which agricultural land use could beensubdivided into specific crops. The estimation of soil loss is in the same order of magnitudeas other studies: 200 to 400 t/ha/yr in Tahiti (Servant, 1974) or 200 to 500 t/ha/yr in theBurundi (Rishirumuhirwa, 1997). It’s also important to note that USLE model gives the longtermaverage soil loss resulting from sheet erosion processes. However, soil loss from othertypes of erosion, gully erosion from lavakas for example, need to be estimated.8
Fig. 9: Potential soil loss erosion in the study area. The high estimations of soil loss correspond primarily at thetop hills of the “Central Chain”. They are the result of the combination of steep slopes, high precipitation, alteredsoils and bare soils due to human activities, such as mining activities.V/ CONCLUSION AND DISCUTIONSoil erosion is a serious problem in New-Caledonia mainly due to the cyclonic tropicalweather, bush fires and human activities such as openpit mining. Runoff on stripped soilscauses degradations for anthropic laying out on high ultramafic terranes and pollution(mobilized soil particles) which modifies the coastal region and degrades the coral reefs byhypersedimentation processes. All the human activities chain that depend on natural resourcesregularly suffer the effects or the consequences of these phenomena. The situation, not for thesame reasons and not in the same proportions, is similar in others high islands of the SouthPacific such as Efate island in Vanuatu (Dumas and Fossey, 2009). These countries need toidentify and rank erosion risk and define sensitivity maps, particularly for decisionmakers. Inthis case, the USLE model can be useful for processing the potential soil erosion mapping at aregional scale, implemented with some data not too complex and compatible with theirintegration into a Geographical Information System (GIS), generally available in the Pacificcountries as a digital elevation model, a soil map, precipitation data or satellite images. Theuse of GIS becomes an important and powerful tool for the implementation of this model. TheUSLE equation used lead a better understanding of spatial distribution of the erosion hazard.Moreover, a comparison with a multi-criteria method (expert approach) demonstrates thatresults obtained in term of spatial variation are similar (Dumas et al., 2009). But the values ofsoil loss from USLE should be considered as an order of magnitude and not as absolutevalues. In fact, USLE model is useful to identify risks areas and catchments that are moresensitive to erosion. This type of mapping should be relevant to classify the reef zone mostaffected by hypersedimentation hazard. Within the framework of Integrated Coastal ZoneManagement, the areas most affected by erosion will be classified as priority managementareas so as to limit their impacts on the marine environment.ACKNOWLEDGMENTSThe authors would like to acknowledge the support of CRISP program (Coral ReefsInitiatives for the Pacific) for funding this research project.9
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Page 5 and 6: Fig.2: Localisation of the weather
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