Iranian Journal of Soil and Water Research
Year:2020 | Volume:51 | Issue:9|Papers Count:20

Considering the limitation of water resources and their value in agriculture, determining the optimal crop cultivation pattern and irrigation planning in low water conditions in the country's catchments is of great importance. Therefore, it is necessary to develop an optimal cultivation model to be flexible in wet and dry conditions. The purpose of this study is to develop a model for offering the best program for irrigation and cultivation area for network operation under different conditions of water resources. After receiving basic information (plant, soil and meteorology) and various irrigation and deficit irrigation scenarios by connecting to the plant growth model (Aqucrop), the model calculates crop yield under defined scenarios. The scenario with the highest economic efficiency is determined as irrigation planning and by connecting to Ant Colony Optimization (ACO), the optimal cultivation pattern for different volumes of available surface water is determined with the aim of maximizing net profit. The optimal cultivation pattern for all crops grown in Qazvin irrigation network in four different modes of water delivery (100%, 80%, 75% and 70%) was performed for 93-94 crop year to evaluate the efficiency of model. The results showed when the year is normal and the amount of water delivered to the network is equal to the long-term average (100% scenario), the largest area is allocated to wheat cultivation (10740) and the dryland will be the least. In the case of 70% of average annual long-term amount to be provided, the area under wheat cultivation will be 3, 000 hectares, and about 15, 000 hectares of the network must be managed dryland or without irrigated cultivation. The results showed that the developed program with high capability and high flexibility for a variety of existing conditions is able to determine the optimal pattern and maximize network profits.

For wheat crop irrigated with drip tapes, water productivity, optimum tape spacing and soil salinity are issues which are important in terms of agricultural economic and soil sources sustainability. For this purpose, an experiment was conducted on a loamy soil texture to study the effect of drip tape spacing on wheat yield and its components, water productivity and variations in the soil salinity. A randomized complete block design consisting of four treatments; three drip tape spacings (45, 60, and 75 cm; denoted by A, B, and C, respectively), and a basin-irrigated treatment (as the Control; represented by D) was carried out on a loamy soil for two years from 2017 to 2019 in Mahyar area of Isfahan Province. The treatments were replicated three times. The volume of applied water for treatments A, B, and C was identical in each irrigation event, whereas the amount of applied water for treatment D was similar to the farmer method. The result of composite variance analysis revealed that the treatments had a significant effect on grain and biological yield at 99% level of confidence, but they did not have any significant effect on water productivity and harvest index. The average water productivity for treatments A, B, C, and D were 0. 72, 0. 71, 0. 66, and 0. 64 kgm-3 respectively. The maximum yield was found for treatment D. During the two years of testing, the soil salinity in the tape treatments was significantly increased, but it did not change in the basin irrigation. Considering that the all three tape irrigation treatments were placed statisticaly in a common group, therefore the 75 cm-tape distance is recommended for loamy soil texture.

Despite studies on the performance of superabsorbents in improving soil physical conditions, as well as increasing the yield and productivity of water consumption, economic issues have received less attention from researchers. Therefore in this study to investigate the effects of water stress and superabsorbent polymers on yield and yield components of wheat in 2015-2016 growing years, a factorial experiment was carried out in a randomized complete block design with three replications. Treatments consisted of combination of three levels of irrigation to supply 100, 70 and 50% crop water requirement (FC, 0. 7FC, 0. 5FC respectively) and three levels of superabsorbent (Stockosorb) with the amount of 0, 50 and 100 kg. ha-1 (S0, S1, S2 respectively). The results of economic indicators showed that the highest net income was allocated to S0, FC and S1, 0. 7FC treatments. The highest gross income to production cost ratio was allocated to the S0, 0. 7FC treatment, which had a significant difference with the control treatment (S0, FC) at the 5% level. The maximum (+44. 2%) and minimum (-11. 7%) of net income to irrigation water amount ratios were belong to S1, 0. 7FC and S2, 0. 5FC treatments, as compared to control treatment (S0, FC), respectively. Therefore, in the best (S1, 0. 7FC treatment) condition, compared with control treatment, superabsorbent and water stress interaction effects increased gross income and net income equal to 12. 2 and 1. 1%, respectively. The investigating interaction effects of treatments showed that the superabsorbent application is recommended only in S1, 0. 7FC treatment condition due to increasing yield and cultivation area (leading of reducing water consumption) and economic justification.

Pressurized flushing is one of the techniques for evacuating sediments from reservoirs. In this study, the impact of submerged vanes on performance of pressurized flushing were investigated. For this purpose, submerged vanes with convergent, divergent and combined arrangements in three distances from the bottom outlet (𝐿 𝑣 ), three middle distances (𝐿 ℎ 𝑟 ) and three heights above the sediment bed (𝐻 𝑠 𝑣 ) were used and the results were compared with the non structural test (reference test). The results showed that the submerged vanes by creating rotational flow and turbulence, enhanced the performance of flushing and also by evacuating much sediment below the bottom outlet, the amount of evacuated sediments increased in all experiments. As, in the convergent and divergent arrangements, the volume of evacuated sediments increased respectively 6. 5 and 48 times compared to the non structural test. Also, in the combined arrangement with two-row divergent of submerged vanes, in 𝐿 ℎ 𝑟 Do=0. 5, 𝐿 𝑣 Do=0. 3 and 𝐻 𝑠 𝑣 𝐷 𝑜 =1, the volume of flushing cone increased 51 times compared to reference test. Finally, by using a polynomial correlation with vane spacing, a non-dimensional equation for estimating the scour cone volume was proposed.

Different regions of Iran are affected by internal or external dust sources. Satellite data can be used to investigate the temporal and spatial distribution and the detected source of dust. The aim of this study was to analyze the concentration of surface dust, dust in air column and aerosol optical depth (AOD) using MERRA-2 model and Aqua satellite data in Iran. Data were prepared between 2007 and 2017 and the figures were plotted by Grads and OriginPro software. The research findings showed three cross-border dust sources including western, eastern and northeastern Iran and two internal area in the Dasht Kavir and southeastern of Iran. The dust source located in southeastern Iraq and Kuwait have the highest concentration of surface dust. In Abadan, the highest concentration of surface dust with 552 (μ gm3⁄ ) in summer, dust in air column with 709 (mgm2⁄ ) and the AOD of MERRA-2 with 0. 58 in spring took placed. The correlation coefficient between surface dust and air column dust was obtained in internal area including Tabas, Kahnooj, Khor Biabank and Nikshahr with 0. 94, 0. 93, 0. 89 and 0. 89, which can indicate the effect of local conditions on dust development. Time series of air column dust in three stations of Bushehr, Abadan and Ahvaz shows the highest decreasing trend with-0. 05 and-0. 035, indicating reduction effect of dust external sources. In temporal distribution, the years of 2008 and 2012 were determined by the most severe and widespread dust in Iran. In monthly distribution, the maximum dust concentration were obtained in April and July 2008, May 2012 and July 2016 in Ahvaz.

Reduction of reservoir storage capacity due to high rate of sedimentation affects all the purposes of dam operation, such as hydropower energy production and seasonal flood control. Using some sediment management techniques are not economically and technically affordable and one of the main solutions, especially in arid and semi-arid regions, is pressurized flushing that faced with low efficiency as a main challenge. In this research a new structure named DBE was used for enhancing sediment removal efficiency. Therefore DBE structure with four different lengths and four diameters in three discharges mode was investigated. For carrying out the experiments, non-cohesive silica sediment with a median diameter of 𝐷 50=0. 73 𝑚 𝑚 was used and temporal development of sediment flushing cone was investigated. Finally the best dimensions of the structure that leads to creation of the maximum sediment flushing cone dimensions and the minimum scouring equilibrium time were presented. Also, time dependent dimensionless equations for calculating the sediment flushing cone dimensions were presented.

Various factors affect stability and seepage rate in the embankment dams. These factors are geometrical characteristics of dam embankment and core, permeability coefficient of soil and height of water level in upstream. The above-mentioned factors are discussed using numerical, analytical and experimental methods, and their impacts are evaluated. In the present paper, using the numerical and analytical methods, the saturation condition of downstream curst of non-homogeneous earth dam is investigated. For this purpose, the earth dam embankment was modeled in Geo-Studio software and the effects of different factors including: width, dam core, permeability and water level in the reservoir on saturation rate of dam downstream crust were evaluated. The results of this study indicate that the width and the permeability coefficient ratio of core to curst, have a greatest impact on saturation of dam downstream. In total, 250 models were analyzed in different condition and finally a function was presented in order to investigate the effects of various parameters on saturation of downstream curst of earth dam.

Calcite, the most stable calcium carbonate in soil, is a major part of soil solid phase in arid and semiarid regions. This mineral significantly affects the chemical behavior of ions including oxyanions and transition metal ions in the soil. Arsenate and phosphate are two important oxyanions in natural systems like soil and because of similar ionic properties strongly compete for the colloids surface charge via adsorption and desorption reactions. Because of the importance of this reaction in controlling the equilibrium concentrations of arsenate and phosphate in soil, in this research, arsenate adsorption on calcite was measured and modeled as a function of arsenate concentration and ionic strength and also in competition with phosphate. In addition, charging behavior of calcite was measured by acid-base titration at various ionic strength. Based on the titration data, calcite point of zero charge (PZC) was obtained at pH=8. 2. Adsorption isotherms showed that arsenate adsorption is affected by the ionic strength and the initial concentration of arsenate. Adsorption of arsenate was high at low ionic strength and was decreased with increasing the ionic strength. Arsenate adsorption was also decreased with increasing phosphate concentration, but arsenate had no effect on phosphate adsorption indicating phosphate is adsorbed stronger than arsenate on calcite. The experimental data were successfully (R2=0. 998) described with a single set of parameters by CD-MUSIC model, considering two inner sphere surface complexes ≡ Ca2O2AsO2 and ≡ Ca2O2PO2. Overall, the experimental data and model parameters implied that the stronger interaction of phosphate with calcite increases bioavailability and mobility of arsenate in calcareous soils.

In the current years, increase of greenhouse gas emissions such as methane (CH4), nitrous oxide (N2O) and nitric oxide (NO) from soils to atmosphere is a global concern. Tillage and agricultural lands deveopment have been the main sources of greenhouse gases production. The aim of this study is to determine the rate of greenhouse gas emissions in agricultural lands of Khuzestan province using DAYCENT model. For this purpose, the rate of gas emmission from the soil surface was measured in each agricultural unit. Also, the emmission of methane, nitrous oxide and nitric oxide gases were estimated in agricultural ecosystems of Khuzestan province, using DAYCENT software. The global warming potential was determined for all the study areas. The highest methane emission (1. 369 tons/ha) was estimated by DAYCENT model which corresponded to the paddy fields of Baghmalek. Also, the highest emission of nitrous oxide and nitric oxide were corresponded to Shush wheat fields with 0. 101 and 0. 111 tons per hectare per year, respectively. The maximum global warming potential (66. 664 tones equivalent to carbon dioxide) was determined based on DAYCENT data which was corresponded to Shush wheat fields. The results showed a lower gas emissions and heating potential in sugarcane fields as compared to the other cultivars. Also, according to the statistical indicators of determination coefficient (0. 98, 0. 99 and 0. 77), root means square Error (0. 05, 0. 31and 0. 03) and model efficiency (0. 61, 0. 85 and 0. 76), respectively for three gases of nitrous oxide, methane and nitric oxide, DAYCENT model showed an acceptable accuracy.

Precipitation is one of the main components of flood, drought and water resources warning studies, hence, its quantitative prediction is of the great importance. The increasing development of computing and satellite technologies and remote sensing in recent years has led to the development of several meteorological forecasting models, of which the TIGGE database with a large number of powerful forecasting models, is the most important. The aim of this study was to evaluate the performance of all available numerical models in the database to predict daily precipitation in 38 synoptic stations located in different climates of Iran. In addition, removing biases from raw datasets using Quantile Mapping (QM) method is another objective of this study. Results showed that in humid, semi-humid, Mediterranean and Arid climate zones (mostly includes the southwest, northwest and northeast parts of Iran), most of the prediction models are highly correlated with ground observations, while in semi-arid and extra-arid regions the correlation coefficient (CC) between the forecasted and observed datasets is very low. For example, the CC and RMSE values obtained from ECMWF and METEO centers in most parts of the country are higher than 0. 6 and lower than 4 mm/day, respectively, while the performance of CMA and CPTEC models is not remarkable and leads to the weak results. Also, evaluation of the corrected precipitation values by QM method indicates that there is a significant improvement in the performance of most prediction systems. Findings in extra-arid, arid, and Mediterranean zones demonstrate an increase in CC value, averagely about 20%. Moreover, the results depicted that by removing biases from the raw datasets, the performance of numerical weather prediction (NWP) models in estimating the low and high precipitation events is improved and this issue further increases the applicability of precipitation forecasting systems in flood warning systems and water resources management.

The aim of this study was to evaluate the removal of phosphate, nitrate and ammonium from Saravan landfill leachate by chlorella vulgaris. The effect of leachate on growth characteristics of chlorella vulgaris, including dry cell weight, chlorophyll and carotenoids content was also investigated. The experiment was performed as repeated measures in a completely randomized design with three replications. Leachate levels were considered as main plot (zero leachate (L0), diluted leachates of 1: 1 (L11) and 2: 1 (L21)) and sampling time (0, 2, 4, 6, and 8 days) as sub-plot. Total chlorophyll in L0 treatment was the maximum and in L11 treatment was significantly more than the one in L21 treatment (p<0. 05). Microalgae dry cell weight and nutrient removal increased over time, so that the highest amount of dry cell weight and the lowest amount of nutrients in leachate (L11) was observed at 8th day after incubation. The percentage removal of phosphate, nitrate and ammonium at the end of 8th day of incubation was 92. 76, 56. 94 and 98. 70, respectively. The kinetic equation of biomass production was also determined in relation to phosphate, nitrate and ammonium removal. The results showed that the nutrient removal followed the first-order model, and Monod's equation was able to well describe the growth of microalgae under restricted substrate conditions. The R2 values of Lineweaver– Burk for phosphate and ammonia were 0. 97 and 0. 99, respectively. Therefore, this equation can be used to remove phosphate and ammonium. Finally, it seems that chlorella vulgaris can be used for bioremediation of Saravan leachate.

Today, application of nanoparticles in various sciences including agriculture has expanded greatly. One of the important roles of nanoparticles in agricultural and horticultural production is to increase plant resistance to environmental stresses, such as salinity and water stress. Therefore, the present study investigated the effect of spraying with silica nanoparticles on increasing drought resistance of grain millet. For this purpose, a field research was conducted in the form of split plots in a completely randomized design with three replications. The main plots consisted of four irrigation treatments i. e. 100, 80, 60, and 40 percent of the crop water requirement, and the sub-plots included six spraying treatments with concentrations of 0, 100, 200, 300, 400 and 500 mg/l of silica nanoparticles. The results indicated that the deficit irrigation significantly reduced plant height, grain weight, grain yield, harvest index and water productivity at 1% level. On the other hand, in all irrigation treatments, spraying with silica nanoparticles could significantly increase grain yield, harvest index and water productivity. The highest grain yield, harvest index and water productivity were observed in full irrigation treatment (100% water requirement) and 500 mg/l spraying of nanoparticles and the lowest amount was observed in 40% water treatment without spraying. Due to the severe scarcity of water resources in the arid region of Kashmar, providing 80% of the water requirement of millet along with spraying with a concentration of 500 mg/l silica nanoparticles is recommended in the tillering stage and flowering to deal with water crisis in the study area.

Soil quality, as a factor, is changing due to variation of soil inherent characteristics and the type of management practices on the soil. Integrated Quality Index and Nemero Quality Index were applied to evaluate the influence of land use types, different irrigation managements, and types of cultivated products on the soil quality in Semnan region. After describing 13 soil profiles in five selected crop fields and orchards, soil samples were taken from different horizons and 14 properties efective on the soil quality were determined and the proposed indecs were calculated. The results showed that the quality of top layers of agricultural lands are classified as II and III degree, while the top layer and sublayer of garden lands are classified as IV degree due to lack of profile evolution, low organic carbon and high salinity. The highest average soil quality indices were assigned to alfalfa (flood irrigation) with 0. 67; followed by barley (sprinkler irrigation) with 0. 59, olive orchard (drip irrigation) with 0. 39 and olive orchard (flood irrigation) with 0. 32. This finding indicates the positive effect of cover crops on land reclamation of Semnan region. The effect of irrigation system on soil quality indices did not show any significant difference among them, as the flood irrigation in alfalfa and olive farms showed the highest and the lowest soil quality indecs, respectively. Also, there was no significant difference in soil quality of olive orchards under drip irrigation vs. flood irrigation. Soil quality indecs make opportunity to agricultural managers to choose appropriate management strategies and monitoring the changes in the soil quality.

Evaporation from the pan has an effective role in water resources management. But due to the interaction of meteorological variables in the calculation of evaporation, several nonlinear relationships have been presented that their efficiency is arguable according to the climatic conditions of each region. Therefore, in the present study, the capabilities of temperature-radiation-based empirical equations and data mining methods of support vector regression (SVR), Gaussian process regression (GPR) and nearest neighborhood (IBK) were investigated under 10 different scenarios resulting from the combination of meteorological factors in estimating and predicting the evaporation amounts in 5 selected stations in the east of Urmia Lake basin. NRMSE and MAPE statistical indicators were used to evaluate the results. In order to model the effective parameters on pan evaporation, the effect of each parameter was calculated using the principal component analysis through the correlation values of parameters with the pan evaporation rate. The results showed that among the implemented meteorological parameters, temperature have the maximum impact and wind speed and precipitation have the minimum impacts on modeling process. Also, among the empirical methods, the Jensen-Haise method had the highest accuracy. Moreover, among the data mining methods, the SVR in Tabriz, Sarab, and Harris stations and GPR in Bostanabad and Maragheh stations had higher accuracies as compared to the others. In general, in all the studied stations, the accuracy of the best data mining scenario was higher than the best empirical method. Also, in terms of data limitation, the Jensen-Haise method had suitable accuracy. Also, despite the low accuracy of the IBK method compared to other data mining methods, this method reachs to its highest accuracy rates with the lowest input variable.

To study the effect of different amounts of municipal compost and sewage sludge on soil properties and wheat, a field experiment was conducted in Ruddasht research station in Isfahan, for five years. Five treatments including 25 and 50 t/ha/year of municipal solid waste compost and 15 and 30 t/ha/year of sewage sludge and control treatment (non-application of organic fertilizer) were used in a randomized complete block design with three replications for five years. The organic fertilizer application increased organic matter in the soil. Also, the application of organic fertilizers, especially at higher levels, increased phosphorus, potassium, iron, copper, manganese, zinc, cadmium and lead in the soil. Also, the application of organic fertilizers increased signifivantly phosphorus, potassium, nitrogen, iron, copper and zinc in the grain and straw of wheat. The concentration of these elements increased significantly with application of organic fertilizers after five years. For manganese, this trend was reversed due to the antagonistic relationship with the iron element. The concentration of lead and cadmium in the plant was so low that it could not be measured by atomic absorption. In general, municipal waste compost and sewage sludge increased the soil organic matter and the concentration of nutrients in the plant, especially in terms of micronutrients such as zinc and iron.

Climate and drought conditions in recent years have faced the Zayandehrud catchment area with the challenge of water resources sustainability. The sustainability of water resources will be achieved by institutions appropriate to the basin conditions and stakeholders. The purpose of this study was to identify the water boady and its components in Zayandehrood catchment. Statistical population of this study were Water experts of Zayandehrud catchment (N=312). Data collection tools were questionnaire in the quantitative part and structured interview in the qualitative part. The sampling size in quantitative part was determined to be 173 individuals using Cochran formula. The sampling approach in the qualitative part was purposeful and 15 individuals were selected by snowball method. Data analysis was performed using structural equation modeling (lisrel8. 8 software) and the rainbow diagram. The findings indicate that the Ministry of Energy, the Agricultural Jihad and their subordinate organizations are the key players at the basin level. The results also showed that the water institution has three components of water management, water policy and water laws, whose standardized coefficients were 0. 64, 0. 53 and 0. 80, respectively. All three components were significant at 99% confidence level.

Phosphorus (P), is the second important nutrient for rice that its deficiency and low application efficiency causes severe nutrient disorder in the world paddy fields. Therefore, the effect of phosphorus fertilizer splitting on morphological characters, yield, and yield components of two rice cultivars (Hashemi and Guilaneh) in two soil type was investigated by a factorial experiment in a randomized complete block design with three replications. The experimental factors included time division of phosphorus fertilizer at five levels, two soil types, and two rice varieties (local Hashemi and modified Guilaneh). Results showed that the grain yield of Hashemi cultivar in two-division treatment (50% at the base and 50% at 60th day after transplantion) incresed 14. 9% and the grain yield of Guilaneh cultivar in two-division treatment (50% at the base and 50% at 20th day after transplantion) incresed 8. 42% as compared to the base application treatment. The maximum increase in filled grain percentages were found to be 9. 1% for Hashemi cultivar and two-division treatment (50% at the base and 50% at 20th day after transplanting) and 18. 3% for Guilaneh cultivar and two-division treatment (50% at the base and 50% at 60th day after transplanting) in silty clay soil. Hence, the two-split application of P might be a solution to enhance the rice grain yield at paddy field conditions.

One of the methods to decrease the oxidative damage caused by salinity is using the nutrition methods and increasing resistance of plants against salinity stress. The aim of this study was to investigate the effect of soil application of humic acid and zinc sulfat on some properties of corn seedlings under salinity stress. For this purpose, an experiment was conducted as split-plot using a randomized complete block design with three replications in the greenhouse. Experimental treatments were included soil salinity (at two levels included non-saline and saline soils with EC of 2. 2 and 8 dSm-1, respectively) as the main factor and application of 5 kgha-1 humic acid [HA], 40 kgha-1 zinc sulfat [Zn], 5 kgha-1 humic acid+40 kgha-1 zinc sulfate [HA+Zn] and control [Co] as sub-factor. Results showed that the stem height and diameter, wet and dry weight of root and shoot and chlorophyll index decreased significantly with increasing salinity in soil, while proline content, catalase and superoxide-dismutase activities increased. Among the studied treatments, HA+Zn treatment had the greatest effect on improvement of seedling growth parameters, so that the application of treatment increased the amount of stem height, stem diameter, wet and dry weight of shoot and root and chlorophyll index, 18. 31, 16. 76, 58. 27, 59. 89, 62. 62, 65. 25 and 4. 85%, respectively compared to control treatment in saline soils. The highest level of catalase and superoxide dismutase activities and proline content were observed under salinity stress along with HA+Zn treatment, and the effect of humic acid was greater than the effect of zinc sulfate. Therefore, the combined use of humic acid and zinc was recommended to improve the growth of corn seedlings in stress salinity conditions.

Agricultural wastes are appropriate precursors for producing modified biochar due to their availability and cheapness. To investigate the effect of activating material type, activation temperature and biochar type on the properties of modified biochar, a factorial experiment was conducted in a completely randomized design with three replications. Experimental factors included four types of activating agents (CaCl2, ZnCl2, H3PO4 20%, and H3PO4 50%), three types of biochar produced from organic wastes (wheat straw, almond, and walnut hull) and two activation temperatures (300 and 500° C). Also, the control treatment included non-treated biochar with activating material and heated at 300° C and 500° C. The results showed that the highest CEC content was related to modified biochar by H3PO4 20% and 50% as an activating material at both 300 and 500° C activation temperatures. The maximum pH and EC values were related to the modified biochar by CaCl2 at both activation temperatures of 300 and 500° C. The highest yield was obtained for modified biochar produced at an activation temperature of 300° C. The highest amount of organic carbon (OC) and nitrogen were obtained from the modified biochar produced at activation temperature of 300° C from H3PO4 (20% and 50%) and ZnCl2 as an activating material, respectively. The maximum C/N content was related to the modified biochar activated with H3PO4 20% and 50% at activation temperature of 300° C. According to the results, the best treatment for producing modified biochar in order to store carbon in the soil and to adsorb pollutants from the soil is the H3PO4 (20% and 50%) as an activating material and 300° C as an activation temperature.

Modeling and providing accurate information on the spatial distribution of soil properties is a key factor in many environmental and agricultural applications. Therefore, the purpose of the present study was to model and prepare a digital map of soil organic carbon using remote sensing indices in the Balikhli Chay watershed. At first, topographic and spectral characteristics affecting soil organic carbon content were extracted from digital elevation model and Landsat 8 satellite image. Then the performance of soil organic carbon modeling for different states was evaluated and compared based on random forest models. The states including 1) terrain covariates, 2) spectral indices, and 3) combination of terrain and spectral covariates, were evaluated and compared together. To this end, the correlation coefficient (R2) between the estimated and measured soil organic carbon and root mean square error (RMSE) were calculated for the different states. The results showed that the amount of organic carbon in the study area varied from 0. 32 to 6. 98 and the mean value was 3. 04%. Carbon changes in the study area mostly dependent on changes in spectral indices. Elevation and Emissivity were respectively the most important terrain and spectral covariates in soil organic carbon modeling. The R2 values in the three models were 0. 61, 0. 62 and 0. 75 and the RMSE values were 0. 88, 0. 67 and 0. 57, respectively, which indicates the better performance of the third model. The use of a combination of terrestrial and spectral variables significantly increases the accuracy of soil organic carbon modeling.