151 may/june 2010—vol. 65, no. 3 journal of soil and water conservation RESEARCH SECTION Erik Bühlmann is project leader at Grolimund & Partner AG, Bern, Switzerland. Bettina Wolf- gramm is a PostDoc Researcher, Centre of De- velopment and Environment (CDE), University of Bern, Switzerland, based in Dushanbe, Tajiki- stan. Daniel Maselli is program manager for the Swiss Agency for Development and Cooperation, Berne, Switzerland. Hans Hurni is a professor and director of the CDE at the Institute of Ge- ography, University of Bern, Bern, Switzerland. Sanginboy R. Sanginov is emergency coordina- tor for the Food and Agriculture Organization, Bishkek, Kyrgyzstan. Hanspeter Liniger is a senior researcher at CDE Institute of Geography, University of Bern, Bern, Switzerland. Geographic information system–based decision support for soil conservation planning in Tajikistan E. Bühlmann, B. Wolfgramm, D. Maselli, H. Hurni, S.R. Sanginov, and H.P. Liniger Abstract: Soil erosion on sloping agricultural land poses a serious problem for the environ- ment, as well as for production. In areas with highly erodible soils, such as those in loess zones, application of soil and water conservation measures is crucial to sustain agricultural yields and to prevent or reduce land degradation. The present study, carried out in Faizabad, Tajikistan, was designed to evaluate the potential of local conservation measures on crop- land using a spatial modeling approach to provide decision-making support for the planning of spatially explicit sustainable land use. A sampling design to support comparative analysis between well-conserved units and other field units was established in order to estimate fac- tors that determine water erosion, according to the Revised Universal Soil Loss Equation (RUSLE). Such factor-based approaches allow ready application using a geographic infor- mation system and facilitate straightforward scenario modeling in areas with limited data resources. The study showed first that assessment of erosion and conservation in an area with inhomogeneous vegetation cover requires the integration of plot-based cover. Plot-based vegetation cover can be effectively derived from high-resolution satellite imagery, providing a useful basis for plot-wise conservation planning. Furthermore, thorough field assessments showed that 25.7% of current total cropland is covered by conservation measures (terracing, agroforestry, and perennial herbaceous fodder). Assessment of the effectiveness of these local measures, combined with the RUSLE calculations, revealed that current average soil loss could be reduced through low-cost measures such as contouring (by 11%), fodder plants (by 16%), and drainage ditches (by 53%). More expensive measures, such as terracing and agroforestry, can reduce erosion by as much as 63% (for agroforestry) and 93% (for agrofor- estry combined with terracing). Indeed, scenario runs for different levels of tolerable erosion rates showed that more cost-intensive and technologically advanced measures would lead to greater reduction of soil loss. However, given economic conditions in Tajikistan, it seems advisable to support the spread of low-cost and labour-extensive measures. Key words: decision support—implementation and maintenance costs—remote sensing— soil erosion modeling—soil conservation—Tajikistan Soil erosion by water poses a major threat to long-term sustainable use of natural resources on cultivated sloping lands. Controlling erosion on such lands is crucial to sustaining agricultural yields and reduc- ing environmental damage (Pimentel et al. 1993). This is especially true for loess soils, which are known to be highly susceptible to erosion (Zhang et al. 2005). Accurate mapping, assessment, and monitoring of soil erosion on a local scale are important for conservation planning, erosion control, and management of natural resources (Lal 2001). Valuable experience with conservation mea- sures often exists locally. Documentation and analysis of this knowledge provides a reliable basis for evaluation of future conservation activities (WOCAT 2005a, 2005b). The Universal Soil Loss Equation (USLE) by Wischmeier and Smith (1978) is the most widely used modeling tool for spatial risk assessment in large areas (e.g., Gaffer et al. 2008; Cohen et al. 2005; Shi et al. 2004; Fernandez et al. 2003; Yang et al. 2003; Lin et al. 2002). Renard et al. (1997) have modi- fied the USLE to create a revised Universal Soil Loss Equation (RUSLE) for wider application by introducing improved means of computing the soil erosion factors. The RUSLE is written as A = LS R K C P, (1) where A represents average annual soil loss (t ha –1 y –1 ), R is the rainfall and runoff fac- tor (MJ mm ha –1 h –1 y –1 ), and K expresses soil erodibility (t ha h –1 ha –1 MJ –1 mm –1 ).The quantities L, S, C, and P are dimensionless factors representing slope length, slope angle, vegetation cover, and management practices. The main advantage of the RUSLE is that the C factor can be estimated from infor- mation on vegetation form, decay, and tillage practices rather than from experimental plot data as proposed in the original USLE (Merrit et al. 2003). According to Benkobi et al. (1994), the C factor, together with the LS factors (slope length and steepness), is most sensitive to soil loss. Remote sensing data have provided a useful basis for deter- mining the C factor in many erosion studies (Vrieling 2006). However, automated clas- sification approaches that assign average C factor values to each vegetation type result in smoothed estimates and the disappearance of spatial heterogeneity and variability. Such values are therefore not suitable for areas with highly inhomogeneous vegetation cover. In these areas, it is important to fill this gap by drawing a reliable map of vegetation cover as a basis for more accurate C factor derivation (Wang et al. 2002). If validated with ground truth data, this can be done efficiently on the basis of high-resolution satellite imagery. Opportunities for improved land manage- ment and conservation measures are usually integrated into erosion modeling without taking into account the present condition of doi:10.2489/jswc.65.3.151