Abstract
The Mediterranean part of Syria is affected by soil water erosion due to poor land management. Within this context, the main aim of this research was to track soil erosion and runoff after each rainy storm between September 2013 and April 2014 (rainy season), on two slopes with different gradients (4.7%; 10.3%), under three soil cover types (SCTs): bare soil (BS), metal sieve cover (MC), and strip cropping (SC), in Central Syria. Two statistical multivariate models, the general linear model (GLM), and the random forest regression (RFR) were applied to reveal the importance of SCTs. Our results reveal that higher erosion rate, as well as runoff, were recorded in BS followed by MC, and SC. Accordingly, soil cover had a significant effect (p < 0.001) on soil erosion, and no significant difference was detected between MC and SC. Different combinations of slopes and soil cover had no effect on erosion, at least in this experiment. RFR performed better than GLM in predictions. GLM’s median of mean absolute error was 21% worse than RFR. Nonetheless, 25 repetitions of 2-fold cross-validation ensured the highest available prediction accuracy for RFR. In conclusion, we revealed that runoff, rain intensity and soil cover were the most important factors in erosion.
Highlights
In the last few decades, land degradation has posed major concerns all over the world [1,2].Over 60% of the world’s land is subjected to different types of land degradation, and more than3.2 billion people suffer from it [3,4,5]
Important to note that the two R2 is not the same: in Tables 3 and 4 it is an adjusted R2 which was corrected with number of predictors, and in repeated cross validation (RCV) we report the square of the correlation of the modelled and observed values; i.e., the latest is more reliable measure as the models are applied on independent data
We revealed that R2 alone is not meaningful enough because random forest regression (RFR)’s R2 -values were worse than general linear model (GLM)’s but both mean absolute error (MAE) and root mean square error (RMSE) indicated lower errors: minimum was better with 38% for RFR
Summary
In the last few decades, land degradation has posed major concerns all over the world [1,2].Over 60% of the world’s land is subjected to different types of land degradation, and more than3.2 billion people suffer from it [3,4,5]. The main issues are desertification and salinization [6,7], fertility reduction [8,9] and soil erosion [10], soil acidification [11,12], and pollution [13]. Soil erosion is a serious degradation hazard that threaten agricultural production and sustainability of natural ecosystems all over the world [20]. More than 12 million ha/year of fertile soil were excluded from agricultural production due to this degradation form [21]. Soil erosion is a great challenge for sustainability in agroecosystems worldwide, such as Europe [22,23,24,25], Africa [26,27], Asia [28], and Australia [29]
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