Journal Resume of Watershed Prolems

JOURNAL OF WATERSHED PROBLEM REVIEW

JOURNAL INFORMATION1. Journal Title: Spatial Estimation of Soil Erosion Risk Using RUSLE Approach, RS, and GIS Techniques : A Case Study of Kufranja Watershed, Nothern Jordan.2. Authors Information: Yahya Farhan Dalal Zregat Ibrahim FarhanDepartement of Geography, Faculty of Arts, The University of Jordan, Amman, JordanEmail : [email protected]. Publication Information:Published on Journal of Water Resource and Protection, 2013, 5, 1247-1261http://www.scirp.org/journal/jwarp 4. Keywords:Jordan, soil Erosion, Risk Mapping, Severity, RUSLE, Wadi Kufranja

JOURNAL RESUME :1. IntroductionIntense human growth affect in pressure of land. This condition lead an area be suffering from serious soil erosion. Erosion had bad impact in environmental such as declining soil productivity, land degradation and sediment problems. In Jordan, high amount of erosion occured and eroded materials are deposit over wadi floors and agricultural lands, irrigation canals, and intensly in reservoir. Clearing sedimentation take long time and high cost. Conservation, management and agricultural reorganization needed for reduce potential of erosion. For doing that, needed an estimation of soil risk including the potential soil loss, severity maps and critical soil erosions area identification. Previous study using USLE formula in central Jordan shows that average soil erosion losses in Jordan estimated about 78 ton/ha/year and 5-25 ton/ha/year in north side. This study try estimate soil erosion risk in Northern Jordan used Revized Universal Soil Loss Equation (RUSLE) formula combined with GIS and Remote Sensing Technologies.2. Study AreaWadi Kufranja is a 126.3 km2 watershed area located at northern highland of Jordan. Astronomically, Wadi Kufranja state at 3214N to 3222N and 3521E to 3547E. Characteristic of Wadi Kufranja at upper part consists of maturely dissected terrain, with broad valley forms and smooth interfluves with dry mediteranian climate. In the middle and lower parts, rejuvenation resulted in a narrow, in- cised, steepsided gorge with semi arid to arid climate. Forest and cropland stress occured due to overgrazing activity and charchoal-wood needs. Land are bare so when there are rainfall, soil displaced easily (splash erosion). This condition led into serious widespread soil erosion in Wadi Kufranja.3. Material and MethodsSoil Loss Estimation MethodSo far, USLE model widely used to estimate soil erosion risk. The requirements of the model, in terms of intensive data and computation, reinforce the elaboration of more accurate and less demanding ones. Method use in this study was USLE improved version of USLE, or RUSLE. Revized Universal Soil Loss Equation (RUSLE) has same fundamental and principal as USLE but adding new term values, corrections, factor algorithms, slope morphology, and elaborated approaches for calculating the parameters of the model to acomodate each parameter in erosion estimation. RUSLE model is normally executed in conjunc tion with a raster-based GIS, to predict erosion potential on a cell by cell basis. The RUSLE model was developed as an equation rep- resenting the main factors controlling soil erosion, name- ly climate, soil characteristics, topography, and land co- ver management. The equation is expressed as: A = R . K . L . S . C . PWhere :A= Computed annual soil loss per unit area [ton/ha/year]. R= Runoff erosivity factor (rainfall and snowmelt) in [MJ.mm/ha/hr/year]. K = Soil erodibility factor (soil loss per erosion index unit for a specified soil measured on a standard plot, 22.1 m long, with uniform 9% (5.16) slope, in continuous tilled fallow) [ton.ha.hr/ha/MJ/mm]. L= Slope length factor (ratio of soil loss from the field slope length to soil loss from standard 22.1 m slope under identical conditions) (dimensionless). S= Slope steepness factor (ratio of soil loss from the field slope to that from the standard slope under identical conditions) (dimensionless). C = Cover management factor (ratio of soil loss from a specified area with specified cover and management to that from the same area in tilled continuous fallow) (dimensionless). P = Support practice factor (ratio of soil loss with a support practice contour tillage, strip-cropping, terracing to soil loss with row tillage parallel to the slope (dimensionless).Data and ToolsGIS 10.1 and ERDAS Imagine 8.5 used to compute annual loss rates and severity based on RUSLE. Landsat ETM+ image and Google Earth Pro used to obtain land cover data and NDVI to determine the C factor. 4. Calculation of RUSLE Factorsa. Rainfall Erosivity (R)Rainfall erosivityis energy of raindrop's impact and the rate of associated runoff. The R-factor is a multi-annual average index that measures rainfall's energy and intensity to describe the effect ofrainfallon sheet and rill erosion. 30 year data period used for computing R-factor, with equation expressed as :R = 23.61 xe(0,0048p), with p is the mean actual precipitation.IDW (Inverse Distance Weighted) used as interpolation tool of R factor between each points of weather stations.b. Soil Erodibility Factor (K)Thesoil erodibility factor(K-factor) is a quantitative description of the inherenterodibilityof a particularsoil; it is a measure of the susceptibility ofsoilparticles to detachment and transport by rainfall and runoff. The factor was computed using the following equation: K = 27.66m1.14 x 108 x (12-a) + 0.0043 x (b-2) + 0.00333 x (c-3)where: K= Soil erodibility factor (ton/hr/haMJmm). m= (Sil t% + Sand %) (100 clay %). a= % organic matter. b= structure code: 1) very structured or particulate, 2) fairly structured, 3) slightly structured, and 4) solid. c= profile permeability code: 1) rapid, 2) moderated to rapid, 3) moderate, 4) moderate to slow, 5) slow, 6) very slow.Soil types in study area identified from National Soil Map and Land Use Project. IDW was used for generate map of sample analyzed. c. Slope Length and Steepness Factor (LS)The (LS) factor expresses the effect of local topography on soil erosion rate, combining effects of slope length (L) and slope steepness (S). The Digital Elevation Model (DEM) with a resolu- tion of 30 m was used to calculate L and S parameters. The following equation was adopted to compute the LS factor :LS(r)= (m+1+[A(r)/a0]m x [sin b(r)/c0]nWith A(r) = upslope contributing area per unit contour width; b(r) is = slope; m = 0.6; n = 1.3 are parameters, ao = 22.1 m = 72.6 ft is the length; b = 0.09 = 9% = 5.16 degree is the slope of the standard USLE plot.d. Crop Management Factor (C)C is a relation between erosion on bare soil and erosion observed under a cropping system. Cropping and management practice effect expressed in C. C mapping taken by computing NDVI values from LANDSAT image. The relationship between C and NDVI was determined as C = (0.7388 NDVI + 0.4948), where the C value in each land cell can be specified.

e. Conservation Practice FactorConservation practice factor (P) in the RUSLE model expresses the effect of conservation practices that reduce the amount and rate of water runoff, which reduce ero- sion. It is the ratio of soil loss with a specific support practice on croplands to the corresponding loss with slope-parallel tillage. P factor mapping derived from land cover map by reclassify the land cover and slope length according to P value.5. Result and DiscussionArcGIS spatial analyst used for integrating raster calculation of K, LS, R, C and P extracted data in purpose of quantity, evaluate and generate soil erosion and severity map of Wadi Kufranja.

Rainfall erositivity factor (R) for five weather stations was found to be in the range of 85.5 and 487 MJmm/ha/hr/year. The distribution of R values assumed to be varied and consistent with annual precipitation across the watershed. K values for the entire catchment shows a maximum value of 0.063 tonha/hr/MJ/mm in the middle and upper catchment, especially where vertisols and typic xerochrepts soils are dominant, and were landslide compexes characterized the lay marly and the marly limestone units exist and minimum K values is of 0.048 tonha/hr/MJ/mm in the lower catchment and associated with soils materials constituting the infill wadis/tributaries. The LS factor values in the watershed vary from low (0.0) to high (405.0). C factor show values between 0.01and 0.2 . The highest (poor land cover management) almost coincide with the lowest NDVI values, (0.22 - .05). P factor ranges from 0.19 to 1.0, the higher values in areas east of Krayma with no conservation practices (forest, natural vegetation), and other major settlements in the catchment. P values decrease towards the upper catchment, where in flat land units slope length decreases. Average annual soil loss of 10 ton/ha/year was estimated for the whole catchment, and the final soil loss map compiled using the RUSLE model indicates a minimum of 0.0 to a maximum of 1865 ton/ha/year.Higher A value indicates higher rate of sediment yield. Wadi Kufranja was classified into five soil erosion risk categories. Erosion risk and severity increase from upper to lower area.

Highest soil loss values are clearly correlated with slope steepness. The upper and lower reaches of the wadi is dominated by moderate and steep slope categories: 10 - 15, 15 - 20 and 20 - 30. second slope category comprises more than 75% of the area of the upper reaches. Slopes greater than 20 - 30 and more create a distinctive pattern and are restricted to steep wadi side slopes.

Present investigation result are comparable with other similiar research in Jordan. This result also consistent with those obtained from other Mediterranean watersheds of similar envionmental characteristics investigated elsewhere using the RUSLE model. Soil erosion rates across Wadi Kufranja changes due to land cover/land use changes and climatic change. RUSLE parameters like C, P, and LS can be modified for soil erosion reduction. Control structures like check dam also useful for gully erosion reduction. Crop management and suitable foresting system may give more benefit in erosion management. The results of soil erosion risk, severity, and land use/cover-type can assist decision makers in identification of priority areas in urgent need of conservation and land management plans. 6. ConclusionRUSLE calculation result of Wadi Kufranja basin shows the severity of soil ero- sion. The mean soil loss estimated for the watershed was 10 ton/ha/year, with the five erosion risk classes, ranging from 0.0 to 1865 tonha1year1. Areas of 53.1723 km2 (5317.23 hectares) and 39.4056 km2 (3940.56 hectares) were classed as suffering moderate or very severe soil erosion. From this research and comparing with other similiar research, Wadi Kufranja catchment, and other similar areas in northern and central Jordan should therefore be prioritized for conservation. High soil erosion rates in the middle and lower reaches of the catchment. Continuous human disturbance and deforestation, with the combined effect of K, LS, and C factors, result in high soil erosion loss across the study area. GIS and RS techniques are simple and low cost tools for modeling soil erosion, with the pur pose of assessing erosion potential and risk for the watersheds of northern Jordan.

JOURNAL REVIEW :This study trying to analyze and mapping soil erosion risk and severity using RUSLE method integrated with GIS application and Remote Sensing data. Due to its disadvantages, soil erosion risk and severity must be analyzed to obtain information on amount of potential soil erosion loss and its severity and area which needed appropriate conservation. Result of this study can be used as decision making of conservation plan or can be a representative example for other similiar watershed problem. The use of RUSLE method has several advantages, such as easy implementation and understandable, compatible with GIS system, and simple data parameter required. Use of satellite observations (Remote Sensing Data) and GIS have an advantage of acquiring and processing data for large and hard-to-reach territories. RS data make us easier for obtain information for further calculation. For example in C factor analysis, NDVI data derived from RS data use to determine C values then GIS have role in classify landcover based on thus C value. This way more easier and accurate than calculate it manually by C table for varies landuse. In-situ measurements are often used for calibration and validation of modelling and remote sensing data, and usually assimilated into models.It shows in this study that soil loss estimated for the watershed was 10 ton/ha/year, with the five erosion risk classes, ranging from 0.0 to 1865 tonha1year1. Areas of 53.1723 km2 (5317.23 hectares) and 39.4056 km2 (3940.56 hectares) were classed as suffering moderate or very severe soil erosion. Similiar result between this analysis compared with other erosion analysis in other similiar characteristic area in Jordan indicates accuracy of this research. More data series, continuity of fields survey and other predicting method can support accuracy of this study. Generally, erosion problems ocured either because of topographics problems, and also due to high expansion for crop land and residential without proper conservation. RUSLE parameters (R, L, K, S, C, P) can be modified by human activity to decrease soil risk potential in watershed area. Watershed Health Assessment / Performance Evaluation.Information obtained from this paper can be used as guide for watershed performance evaluation. This evaluation important to decided what conservation and management needed for that watershed. Watershed performance can be evaluated by measuring land cover index, land management index, sedimentation, water management index, erosion risk index, water quality, etc.Eventhough watershed health assessed by many factor, in this case, due to data and information limitation, erosion risk index and land management used as only parameter for evaluate watershed health and performance based on land condition criteria. Watershed health in this review assessed based on Ministrial Decree of Forestry of Indonesia, stated as follows :Erosion Risk Index (IE)= Erosion Risk Index (IE)= = 1,42(note : 7 is tolerated erosion value for dominant forest and crop landuse based on Ministrial Decree of Forestry of Indonesia. This condition similiar with Wadi Kufranja condition)Erosion risk classification criteria divided into : IE< 0,5= Very Low0,5 < IE 1,0= Low1,0 < IE 1,5= Moderate1,5 < IE 2,0= High IE> 2,0= Very HighFrom calculation above, shows that based on erosion rate Wadi Kufranja belongs to Moderate Level erosion conditions. Land management indicator also can indicate healthiness of watershed. Land management factor assesed by calculating C factor and P factor. Showed as result of this study, highest C factor values was 0,2 with P factor values 1,0. Land Management Factor= C x P = 0,2 x 1,0 = 0,2Land management classification criteria divided into : CP 0,10 = Very Low0,10 < CP 0,30 = Low0,30 < CP 0,50 = Moderate0,50 < CP 0,7 = High CP > 0,7 = Very High The result shows that Wadi Kufranja Watershed belongs to Low Risk level of watershed. It can be conclude that based on criteria of land condition, Wadi Kufranja watershed are in moderate level of performance. For better result of watershed health assessment of Wadi Kufranja, other indicator must be analyzed. Watershed Recovery Attempt.Recovery activity project arranged based on scoring of watershed health performance. Based on soil erosion risk map, we can determine conservation activity necessary for certain area such as which area need forest proteection, and which need land conservation, water treatment, structural control like dam or sabo, river normalization, etc. Those recovery and conservation activity implemented based on risk level of each area.Land use management plan also can be determine by soil erosion risk and severity map from this study. Land use management purpose is to decrease erosion rate of watershed. RUSLE parameters especially C and P factor used to erosion control modelling. CP value can be modified vegetative and mechanically. Identification of soil erosion map provide information indicator that produce high level of erosion such as land steepness, soil solum, slope, etc. From that information, conservation activity can be planned. As example, for area with 15% slope and moderate erosion needs forestation, terarcing, etc. Other condition will need different conservation. Unfortunately in this paper, each result of RLKSCP calculation not shown so we cant arrange any recovery and conservation project for Wadi Kufranja watershed. Good quality of conservation and recovery activity implemented in a watershed, healthiness of the watershed increase so watershed can be in well-performing condition. In this condition, problems such as sedimentation, landslide, water scarcity and many other problems can be solved.

Intan Madya Ratna Master DD Program of Civil EngineeringWATER RESOURCES ENGINEERING6