Vegetation canopy changes and use of SoilGrids data for assessing the effect of extreme rains on annual soil losses

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Extreme rains can trigger natural hazard processes such as soil erosion, land sliding and flash floods. Climate change studies show that the frequency of extreme rains is in an increasing trend, resulting in the amplification of hazard processes. For assessing the magnitude of soil losses various models are available. While annual empirical models (e.g. USLE, RUSLE, MMF) are easy to use, they do not take into account the effect of extreme rains. The event based models (e.g. LISEM, WEPP) can simulate erosion processes in detail, but rainfall event data is simply not available everywhere. To solve this problem, Shrestha and Jetten, (2018)have developed a daily erosion model and demonstratedthat the effect of extreme rains can be incorporated easily in annual estimates. For running the model, daily rainfall, vegetation canopy changes, topography and soil dataare required. Daily vegetation canopy changes mapping is a challenge and soil data may not be available easily everywhere due to higher cost involved in soil survey. Recently, time series NDVI and SoilGrids data are available freely, solving data scarcity problem. But, we do not know how good is the data for hazard assessment. The objectives of the study are in assessing the effect of daily canopy coverchanges on rain interception, and in the use of SoilGrids data for erosion estimation.The study area is located in Sehoul, Morocco. Time series NDVI data at 1 Km resolution was obtainedfrom Vito, Belgium (, and resampled to 15mand at daily time step. Similarly, SoilGrids data at 250 m resolution was downloaded from ISRIC, The Netherlands ( Pedotransfer functions were used to generate soil parameters and the daily erosion model was applied to assess soil losses. The results show that vegetation canopy cover plays an important role in the magnitude of soil losses. Canopy cover intercepts rain and protects the soil from raindrop impact. When canopy cover is lower, erosion rates are higher. During extreme rains, erosion can be very severe. The study shows that SoilGrids is a useful data source, and can be applied in daily erosion assessment in the semi-arid environment. The results also showthat daily erosion modelling gives better picture of annual soil losses since the effects of extreme rains are also incorporated.
Original languageEnglish
Number of pages8
Publication statusPublished - 2018
Event39th Asian Conference on Remote Sensing, ACRS 2018: Remote Sensing Enabling Prosperity - Kuala Lumpur, Malaysia
Duration: 15 Oct 201819 Oct 2018
Conference number: 39


Conference39th Asian Conference on Remote Sensing, ACRS 2018
Abbreviated titleACRS
CityKuala Lumpur
Internet address

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