Remote sensing and GIS techniques were employed for prioritization of the Zerqa River watershed. Forty-three 4 th order sub-watersheds were prioritized based on morphometric and Principal Component Analysis (PCA), in order to examine the effectiveness of morphometric parameters in watershed prioritization. A comparison has been carried out between the results achieved through applying the two methods of analysis (morphometric and PCA). Afterwards, suitable measures are proposed for soil and water conservation. Topo sheets and ASTER DEM have been employed to demarcate the 43 subwatersheds, to extract the drainage networks, and to compile the required thematic maps such as slope categories and elevation. LANDSAT 8 image (April-2015) is employed to generate land use/cover maps using ENVI (v 5.1) software. The soil map of the watershed has been digitized using Arc GIS software. Prioritization of the 43 sub-watersheds was performed using ten linear and shape parameters, and three parameters which are highly correlated with components 1 and 2. Subsequently, different sub-watersheds were prioritized by ascribing ranks based on the calculated compound parameters (Cp) using the two approaches. Comparison of the results revealed that prioritization of watersheds based on morphometric analysis is more consistent and serves for better decision making in conservation planning as compared with the PCA approach. The recommended soil conservation measures are prescribed in accordance with the specified priority, in order to avoid undesirable effects on land and environment. Sub-watersheds classified under high priority class are subjected to high erosion risk, thus, creating an urgent need for applying soil and water conservation measures. It is expected that decision 114makers will pay sufficient attention to the present results/information, activate programs encouraging soil conservation, integrated watershed management, and will continue working on the afforestation of the government-owned sloping lands. Such a viable approach can be applied at different parts of the rainfed highland areas to minimize soil erosion loss, and to increase infiltration and soil moisture in the soil profile, thus, reducing the impact of recurrent droughts and the possibility of flooding hazards.

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Socioeconomic factors and farmer's perception of soil erosion and conservation were examined with special reference to Wadi Kufranja catchment, northern Jordan. Field data were collected through a household field survey, and soil erosion loss was calculated and mapped using the Revised Universal Soil Loss Equation (RUSLE), within a GIS/RS environment. In-situ field measurements of soil erosion were also conducted to assess splash, sheet and runoff soil erosion. The estimated potential average annual soil loss is 10 ton•ha −1 year for the watershed. 42.1% (5317. 23 ha) of the watershed area was estimated to have moderate soil loss (5-25 ton•ha −1 •years −1). Soil erosion risk is severe to extreme over 31.2% (3940.56 ha) of the catchment, whereas the calculated soil loss is 25-50 and >50 ton•ha −1 •year −1. The measured sheet and splash soil erosion in W. Kufranja was 10 ton•ha −1 •year −1 from tillage land, and 3 ton•ha −1 •year −1 from the fallow land, with an average ranges from 8 to 10 ton•ha −1 •year −1. Similarly, the maximum measured soil erosion on the eastern margin of W. Kufranja was 12.7 ton•ha −1 •year −1 , while the minimum soil erosion was 2.9 ton•ha −1 •year −1. The collected household socioeconomic/conservation data have been subjected to multivariate statistical analysis. Through factor analysis, the twenty one variables were reduced into four significant factors which account for 69.7% of the variation in the original variable. Stepwise multiple regression analysis revealed that the total variance explained by three independent variables was 0.585 (R = 0.765, R 2 = 0.585). Out of the total variance, forest clearance explained 34.7%, fallow land 7.7%, and land use/land cover 16.1% respectively. The F-value for forest clearance, fallow land, and land use/land cover are significant at 0.1% level. Most of the farmers aware that poor land management, deforestation, overgrazing, traditional cultivation (cultivation up-and-down the slope, and mono-cropping), and population pressure, are the major direct and indirect causes of soil erosion. By contrast, vegetative measures (i.e., afforestation and tree planting), adoption of structural soil and water conservation measures (terraced farming, check dams and gully control), and crop system management were recommended to control soil erosion. Y. Farhan et al.

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GIS-based morphometric analysis was employed to prioritize the W. Mujib-Wala watershed southern Jordan. Seventy six fourth-order sub-watersheds were prioritized using morphometric analysis of ten linear and shape parameters. Each sub-watershed is prioritized by designated ranks based on the calculated compound parameter (Cp). The total score for each sub-basin is assigned as per erosion threat. The 76 sub-basins were grouped into four categories of priority: very high (12 sub-basins, 15.8% of the total), high (32 sub-watersheds, 42.1% of the total), moderate (25 sub-watersheds, 32.9% of the total), and low (7 sub-watersheds, 9.2% of the total). Sub-watersheds categorized as very high and high are subjected to high erosion risk, thus creating an urgent need for applying soil and water conservation measures. The relative diversity in land use practices and land cover, including variation in slope and soil types, are considered in proposing suitable conservation structures for sub-watersheds connected to each priority class. The adaptation of soil conservation measures priority-wise will reduce the erosivity effect on soil loss; while increasing infiltration rates; and water availability in soil profile. Principal component analysis (PCA) reduces the basic parameters and erosion risk parameters to three components, explaining 88% of the variance. The relationships of these components to the basic and erosion risk parameters were evaluated, and then the degree of inter-correlation among the morphometric parameters was explored. The verification of priority classes obtained through morphometric analysis was tested using Discriminant Analysis (DA)