Most climate change scenarios predict a significant increase in the frequency of high intensity rainfall events especially in the dry areas, which will increase runoff and soil erosion. Understanding the factors that control soil erosion is crucial to recommending appropriate measures to protect soils and reduce their vulnerability. The objective of this research was to investigate the effect of rainfall intensity, slope, land use and antecedent soil moisture on soil erosion and runoff. Twelve sites from Al-Muwaqqar watershed, Jordan, were selected to represent six slope angles: 1, 2, 3, 5, 7 and 9%. Two sites, one cultivated with barley and one as rangeland, were selected within each slope. Erosion was measured under three rainfall intensities: 3, 5 and 10 mm h À1; and three different antecedent soil moisture contents: dry, wet and very wet; using a rotating disk rainfall simulator. Regression equations indicated that rainfall intensity was the most important factor affecting soil erosion and that erosion could occur at a relatively small intensity on wet soils as a result of subsequent rainfall events. Soil erosion on cultivated land was primarily affected by moisture content, while on uncultivated land, it was mostly affected by slope steepness. Rainfall intensity, slope and antecedent moisture explained 84-89 and 59-66% of the variation in runoff and soil loss, respectively. The results indicated the significant influence of cultivating the land on soil erosion.

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Accurate information about soil attributes, presented in a spatially continuous form, is prerequisite for many land resources management applications. The availability of detailed soil maps and its ability to supply such information for modern tools and applications are questionable. Some alternatives, based on using terrain attributes derived from digital elevation model (DEM) to predict soil attributes are investigated in this study. A study area of 148 km2 in the northern part of Jordan was used. The area is covered by detailed soil map and 2193 field observations, from which the soil attributes were extracted. Terrain attributes derived from 20‐m resolution DEM were utilized to predict soil attributes by implementing different statistical and clustering techniques. The use of multiple linear regression models within small watershed subdivisions enabled the prediction of soil depth for 89.3% of the field observations within ±50 cm, the water‐holding capacity (WHC) for 75.8% within ±50 mm cm−1 and the surface cover percentage for 78.7% within ±10%. The models also predicted surface cover type for 94.5% of the field observations, erosion type for 48.4%, erosion class for 98.0%, and soil texture for 90.3%, within one class difference between predicted and field estimated classes. Comparing these results with estimates of soil attributes using the soil map indicated that the modeling of the soil‐landscape relationships within small watershed subdivisions is a promising approach to predict soil attributes for large areas. An important feature is the spatial distribution of the predicted soil attributes, which is provided in more detailed form than what the soil map provides.

Soil salinity has become one of the major problems 4 affecting crop production and food security in Mesopotamia, Iraq. 5 There is a pressing need to quantify and map the spatial extent and 6 distribution of salinity in the country in order to provide relevant 7 references for the central and local governments to plan sustain-8 able land use and agricultural development. The aim of this study 9 was to conduct such quantification and mapping in Mesopotamia 10 using an integrated, multiscale modeling approach that relies 11 on remote sensing. A multiyear, multiresolution, and multisen-12 sor dataset composed of mainly Landsat ETM+ and MODIS data 13 of the period 2009-2012 was used. Results show that the local-14 scale salinity models developed from pilot sites with vegetated and 15 nonvegetated areas can reliably predict salinity. Salinity maps pro-16 duced by these models have a high accuracy of about 82.5-83.3% 17 against the ground measurements. Regional salinity models devel-18 oped using integrated samples from all pilot sites could predict 19 soil salinity with an accuracy of 80% based on comparison to 20 regional measurements along two transects. It is hence concluded 21 that the multiscale models are reasonably reliable for assessment 22 of soil salinity at local and regional scales. The methodology 23 proposed in this paper can minimize problems induced by crop 24 rotation, fallowing, and soil moisture content, and has clear advan-25 tages over other mapping approaches. Further testing is needed 26 while extending the mapping approaches and models to other 27 salinity-affected environments.

Abstract. Land degradation resulting from improper land use and management is a major cause of declined productivity in the arid environment. The objectives of this study were to examine the effects of a sequence of land use changes, soil conservation measures, and the time since their implementation on the degradation of selected soil properties. The climate for the selected 105 km 2 watershed varies from semi-arid sub-tropical to Mediterranean sub-humid. Land use changes were detected using aerial photographs acquired in 1953, 1978, and 2008. A total of 218 samples were collected from 40 sites in three different rainfall zones to represent different land use changes and variable lengths of time since the construction of stone walls. Analyses of variance were used to test the differences between the sequences of land use changes (interchangeable sequences of forest, orchards, field crops, and range), the time since the implementation of soil conservation measures, rainfall on the thickness of the A-horizon, soil organic carbon content, and texture. Soil organic carbon reacts actively with different combinations and sequences of land use changes. The time since stone walls were constructed showed significant impacts on soil organic carbon and the thickness of the surface horizon. The effects of changing the land use and whether the changes were associated with the construction of stone walls varied according to the annual rainfall. The changes in soil properties could be used as indicators of land degradation and to assess the impact of soil conservation programs. The results help in understanding the effects of land use changes on land degradation processes and carbon sequestration potential and in formulating sound soil conservation plans.