Aims: The present study has used results of the application of Revised Universal Soil Loss Equation (RUSLE) in integrated with the economic cost of soil loss to prioritize sub-watersheds of Selj-Anbar Watershed in Mazandaran Province, northern of Iran.
Materials and Methods: Overlay of five input layers of RUSLE model, viz., rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), cover and management (C) and support and conservations practices (P) factors has been done in Geographical Information system (GIS) platform for the study watershed. Then, the soil loss and sedimentation cost have assessed using soil nutrient depletion analysis. In this method, monetary value to the depleted nutrients based on the cost of purchasing an equivalent amount of used chemical fertilizer in the watershed was assigned.
Findings: The average soil loss and sediment rates of 4.92 and 1.98 t ha^-1, respectively was obtained for the study watershed. In addition, the direct and indirect costs caused by soil loss during the five-year period in the Selj-Anbar Watershed were obtained 4.32×10⁵ and 6.40×10⁵ US$ which was totally equal to 10.98×10⁵ US$. The highest (5.59×10⁴ US$) and lowest (1.16×10⁴ US$) annual cost of soil loss was estimated in the sub-watersheds S1-1-1 and S1-1-2, respectively.
Conclusion: Spatial distribution of soil loss and erosion cost could provide a basis for comprehensive and sustainable watershed management. The sub-watersheds with high soil erosion and cost rates deserve superior priority for implementation of conservation activities.

Aims: Land subsidence is one of the phenomena that has been abundantly observed in Iran's fertile plains in recent decades. If it is not properly managed, it will cause irreparable damages. So, regarding the frequency of subsidence phenomenon, the evaluation of the potential of the country's fertile plains is necessary. Towards this, the present study is formulated to assess the vulnerability of the Tehran-Karaj-Shahriyar Aquifer to land subsidence.
Materials & Methods: The vulnerability of Tehran-Karaj-Shahriyar Aquifer was determined using the GARDLIF method in a Geographic Information System (GIS) environment. Seven parameters affecting ground subsidence including groundwater loss, aquifer media, recharge, discharge, land use, aquifer layer thickness, and the fault distance were used to identify areas susceptible to land subsidence. Then, they were ranked and weighted in seven separate layers. In the next step, the subsidence location and rates were obtained using the differential interferometric synthetic aperture radar (DInSAR) method. The weights of the input parameters of the GARDLIF model using the subsidence map obtained from the DInSAR method and the particle optimization algorithm (PSO) were then optimized. Accordingly, the subsidence susceptibility map was generated based on the new weights.
Findings & Conclusion: The results showed that by increasing correlation coefficient (r) from 0.55 to 0.67 and the amounts of Coefficient of Determination (R²) from 0.39 to 0.53 between the subsidence index and the obtained subsidence in the aquifer, the optimization of weights applied by the PSO algorithm is more capable for evaluating the land subsidence than the map created by GARDLIF. It was also found that the central parts of the study aquifer had the largest potential for land subsidence.