JOURNAL OF WATERSHED MANAGEMENT RESEARCH
Year:2019 | Volume:10 | Issue:19|Papers Count:20

This research uses the multilayer perceptron (MLP) model to predict daily evaporation at two synoptic stations located in Rasht and Manjil, Guilan province, in north-west of Iran. Initially the most important combinations of climatic parameters for both of the stations were identified using the gamma test; and daily evaporation were modeled based on the obtained optimal combination. The results of the artificial neural network-Gamma Test (ANN-GT) model are evaluated using the root mean square errors (RMSE), correlation coefficient and Nash-Sutcliffe (NS) criteria. The results showed that the ANN-GT model for Rasht station with a correlation coefficient 0. 86, root mean square error 0. 95 and Nash-Sutcliffe criteria 0. 74 and for Manjil station with correlation coefficient 0. 94, root mean square error1. 58 and Nash-Sutcliffe criteria 0. 89 has an acceptable performance in predicting daily evaporation. To evaluate the uncertainty, we considered a percentage of data which were included in 95 percent of uncertainty (p-factor) and the average width of the 95ppu band (d-factor). Regarding the uncertainty results, the average with of 95PPU bound were obtained as 0. 33 and 0. 3 for the Manjil and Rasht stations, respectively. This shows the low uncertainty level of the ANN-GT model for predicting daily evaporation at both of the stations. Furthermore, the percentage of the observed data at 95PPU band was low and equal to %25 and %45 for the Rasht and Manjil stations, respectively. The reason for these low values can be due to low uncertainty in the parameters.

Water resources management in the country has been confronted with conflicts over the last years due to increasing demand on one hand and decreasing renewable water per capita on the other hand. The game theory is one of the scientific methods for resolving conflicts in management. The purpose of this study is to investigate and provide a solution to the conflict resolution of downstream part of Sefidrud dam using game theory. For modeling and analysis of the conflict, Graph Model for Conflict Resolution (GMCR) was used. After determining players (Agricultural Jihad Organization, Regional Water Company, Farmers, Governorate and Environmental Organization) and options and inserting them into the model, 128 states were created in this conflict. It uses non-cooperative solution concepts. With regard to prioritize strategies by decision-makers, 4 situations were identified as equilibrium points. After the final analysis of the software، the most favorable state in the conflict between the points of equilibrium was the state of 96 that the farmers and the regional water company, respectively, have observed alternative irrigation and proper distribution of water required According to the results, solving these conflicts without effective governance in the large Sefidrud watershed is not possible due to the cooperation between the exploiters and the punishment of the offenders.

Evaluating potential evapotranspiration plays an important role in planning, designing, and managing water resources, especially in arid and semi arid zones. The aim of the present research is considering spatio-temporal changes of different potential evapotranspiration methods such as Thornthwaite, Hargreaves, and Blaney-Criddle in the Maharlou Watershed, Fars province. So, yearly statistics of temperature in a course of 12 years (2002-2013) with 12 meteorology stations in Maharlou Watershed have been used. In order to zonation map of evapotranspiration and studing spatial changes, Inverse Distance Weighting (IDW) method has been used in GIS software. To choose the most suitable method for evaluating potential evapotranspiration using Blany-Criddle, Hargreaves-Samani, and Thornthwaite in this present research, statistics indicators including Mean Absolute Error (MAE) (8. 64, 12. 06, 9. 93), Mean Bias Error (MBE) (-0. 42,-0. 56,-1. 36), and Root-Mean-Square error (RMSE) (2. 49, 2. 86, 3. 48) is used. Results showed that spatio-temporal changes of potential evapotranspiration in Blaney-Criddle method indicates the most amount of evapotranspiration in Dobene Station in 2009 with the amount of 127. 5 mm. Whereas the least that amount of attached is in Kaftar Station in 2006 with the amount of 85. 1 mm. Also based on Hargreaves results, the most and least amount of evapotranspiration is in Jahan abad bakhtegan Stations in 2009 with the amount of 152. 1 mm and Komhar station in 2003 with the amount of 96. 5 mm, respectively. In contrast, based on Thornthwaite method, the most amount of evapotranspiration is included in Dobene Sstation in 2009 with the amount of 103. 6 mm and the least that amount of attached is in Komhar Station in 2011 with the amount of 52. 7 mm. Subsequently, the results of evaluating of different evapotranspiration methods according to RMSE and MAE showed that Blaney-Criddle method the least error amount (2. 49, 8. 64) and also according to the MAE and RMSE criteria, the most amount of error attached of Hargreaves-Samani method with the amount measured MAE 12. 06 and RMSE 3. 48. In general, the Blaney-Criddle method is the best potential evapotranspiration method. On the other hand, the low error rate is due to Hargreaves-Samani and Thornthwaite based methods.

Digital Elevation Model is one of the most important data for watershed modeling whit hydrological models that it has a significant impact on hydrological processes simulation. Several studies by the Soil and Water Assessment Tool (SWAT) as useful Tool have indicated that the simulation results of this model is very sensitive to the quality of topographic data. The aim of this study is evaluating the spatial resolution effect of three type's digital elevation model such as ASTER (30 m), SRTM (90 m) and GTOPO30 (1000 m) on the uncertainty of results for flow and total nitrogen simulation. With increasing spatial resolution of 30 to 1, 000 m physiographic characteristics such as the number HRU reduced but the average slope and the average minimum and maximum elevation increased. Furthermore, the channel drawing is heavily affected by the spatial resolution of DEM. The Best results of monthly calibration and validation are obtained in Shirgah station for ASTER digital elevation model. R2 and NS coefficient obtained 0. 71 and 0. 68 for during calibration period and 0. 70 and 0. 54 during validation period, respectively. Finally, calculated relative error of SRTM and GTOPO30 simulation results compared with ASTER. The results shows that the model overestimated flow and nitrate by increasing spatial resolution 30 to 90m and underestimated these two parameters by increasing spatial resolution 90 to 1000m. The results of this study showed that the accuracy simulation of discharge and total nitrate with the ASTER with the highest spatial resolution presented the best simulation compared to SRTM and GTOPO30 which this is due to the improvement of important physiographic properties, such as slope length and gradient and thus better simulation of hydrological processes.

Nowadays using field depth measurement to estimate capacity of water reservoirs is a costly and time consuming method. In this regard, different multiple techniques of remote sensing method has been adopted. In this study, a radiation and reflection based model was introduced to estimating the bathymetry and water capacity of reservoir by images of OLI sensor. For this, at May 17, 2015 water depth was measured each 50 meters in Mahdasht, Sorbon and Dasht-e-naz water reservoirs using Sonar system. All water reservoirs located in Miandoroud plain between latitude of and longitude of in north east of Sari city, Mazandaran province, Iran. Then, the measurement continued for five more times; on May 26, Aug 5 of 2015 and again on May 28, June 29 and August 23 of 2016 to record depth and precise determination of water capacity. In order to estimate the reservoir capacity image values for blue, green and red band two times more than maximum depth, were classified equally (any given class represents 0. 5 meter depth). Subsequently, total volume of reservoir was extracted by a sum of product of number of cells, cell depth index and cell area. Finally, the average relative error and estimated correlation coefficients of volume estimation for 3 mentioned reservoirs in 6 times in blue, green and red bands were 11. 19, 4. 95, 5. 5 and 96, 97 and 98 percent, respectively. Consequently, the use of this method is proposed to measure the volume of reservoirs.

Given the importance of climate change issue, consideration of the climate and hydrological data trend has become very important. This study aimed to evaluate the effectiveness of different methods to remove the effect of autocorrelation in assessing the trend of parameters such as temperature, precipitation and discharge of the Eastern Gorganrood Basin, Golestan Province. For this purpose, in addition to conventional Mann-Kendall test, nonparametric tests like MK-PW, MK-TFPW, MK-VCA, MK-SA and MK-HSA were used for trend analysis. As well as determining the slope of the trend line and identifying the jump points, San slope estimator and Mann-Kendall sequence (SQMK) were used. The results showed that the values of temperature and precipitation at all stations uptrend and this was significant for temperature in Lazoreh stations and Ramian. Also, discharge flow in Arazkuseh station had significant descending trend. Using nonparametric tests decreased Z statistic. In most stations, MK-PW method had the minimum significance and MK-TFPW and MK-VCA methods showed better performance and reduced the risk of Type I error. In the station where there was no significance in the first and higher order autocorrelation, MK-VCA and MK-PW methods provided similar results. MK-TFPW showed a different behavior due to calculating the autocorrelation after the removal process. Considering of turning points in Mann-Kendall sequence test indicated that at Arazkuseh, Ramiyan, Nodeh, Tamar and Ghazaghli stations, the begining point of trend was related to the years 2000, 1987, 1988, 2001 and 2001 and only in 2 stations including Tamar and Ghazaghli, it was significant in the years 2006 and 2005 (at 5%). In all of the stations, temperature had an abrupt change point of different trend and the time of increasing temperature was equal to the point jump of discharge decreasing trend in 1993 in Arazkuseh station.

Every phenomena in the nature, despite the complexity of the subject, has certain rules and regulations. River pattern and behavior as one of the most complex natural phenomena to this is not an exception. Depending on geomorphologic, climatic, topographic and erosive conditions, the waterways exhibit different patterns and behaviors. One of the parameters which can be achieved using the complexity of the pattern of the form of phenomena is fractal geometry. The purpose of this study is to calculate and compare the fractal dimension of hydrographic networks in Ilam watersheds, which were extracted from 50 m DEM and SRTM satellite data. Hydrographic networks that were derived from SRTM data with a precision of more than 5 meters are mapped by using Google Earth images. For this purpose, 12 watersheds were first selected in Ilam province (Ema, Tang-e-Sazbon, Doiraj, Holylan, Nazarabad, Chamgahs, Kolm, Siagav, Jafarabad, Chaviz, Jezman and Vargach) and after determining the units of 25 square kilometers in each of the areas and drawing and completing the drainage network patterns in the studied areas, their fractal dimension were calculated using Fractalys software. The results showed that the calculation and comparison of fractal dimension with visual methods is correct if the compared fields have the same area, and the accuracy and scale of the drawing of hydrographic networks is also the same. On the other hand, the drainage network drafted on Google Earth with a precision of more than five meters compared to the corresponding waterway network with a precision of 50m DEM in 5 × 5 square kilometers (25 square kilometers), has a very high accuracy. Also, the minimum fractal dimension before the modification of hydrographic networks is for Ema watershed (1/042) and the maximum amount is for Tang-e-Sazbon watershed (1, 424). However, after the modification of hydrographic networks and calculating fractal dimension, the lowest fractal dimension is for Chaviz watershed (1. 1) and the highest amount is for Nazarabad (1. 49).

Sustaining environmental flows to preserve biodiversity of aquatic plant and animal species, as well as constancy of water for human communities, is essential in many river ecosystems. On the other hand, hydrological changes caused by the dam and its related environmental problems have provoked many concerns for hydrologists, ecologists and policymakers. Therefore, the main aim of this research was to study the rate of change in the Environmental Flow Components (EFCs) caused by the construction of Sabalan Dam in the Qarehsou River of Ardebil at stations of Arbabkandi and Dostbeiglou (before and after Dam) using IHA Software7. 1 during the time period of 2005-2014. For this purpose, the values of 34 environmental flow parameters were estimated at each hydrometric station. Consequently, changes in the parameters of the environmental flow discharge were investigated in four groups of Extreme Low Flows, Low Flows (Base flow), High Flow pulses, and Floods events. The diagram below shows the parameters of minimum flow, peak flow and small flood. Based on the results, the frequency of Extreme Low Flows at the Dostbeiglou station had a 59% increase with respect to Arbabkandi station. On the other hand, the peak flow component showed more balanced nature in Dostbeiglou station after the dam, which can be related to the regulating effect of dam on high flow and balancing outflow in downstream reaches. The Peak flow, Duration, Timing and Frequency of small flood events had decreased in Dostbeiglu Station compared to the Arbabkandi with amount of 27, 78, 68 and 17 percent, respectively. Also, the peak and frequency of large floods had decreased at Dostbeiglu station with amount of 26 and 50%, compared with the observed flood events at the Arbabkandi station which located before the Sabalan dam.

The lack of complete coverage of hydrological data forces hydrologists to use the homogenization methods in regional analysis. In this research, in order to choose the best Hierarchical clustering method for regional analysis, base flow and related index were extracted from daily stream flow data using two parameter recursive digital filters in 43 hydrometric stations of the Kerman province. Physiographic, climatic and hydrological parameters were calculated. Using factor analysis of 14 parameters, six factors including: hydrograph recession constant, mean annual precipitation, actual evapotranspiration, permeability, topography (slope and height) and curve number were chosen as the most important independent factors. Hierarchical clustering of catchments using independent factors in different methods including: Nearest neighbor, Furthest neighbor, Centroid clustering and Ward were down. Then the regional equations using linear regression at 1% significant level for each homogeny region were determined. To compare and evaluate the accuracy and efficiency of the models, Independence errors, Colinerity and normal distribution of errors were tested. The results showed that “ Centroid clustering method " because of low relative error with the amount of 27. 137% for zone A and 36. 89% for zone B of homogeneous region, minimum standard error of the estimate and the high correlation coefficient, diagnosed as the best homogeneity method to estimate regional base flow index in the study area.

Evaluation of watershed projects is one of the most fundamental problems in countries for future implementation planning and management of natural resources. In regard to lack of required equipment for monitoring and evaluation of watershed projects and investigation of management measures in watersheds, application of hydrologic models is an efficient tool for simulation of watershed behavior before and after implementation of watershed projects. So, this study was carried out in order to evaluate of hydraulic structures using HEC-HMS in the Haftan watershed, Markazi province, Iran. For this purpose, with use of rainfall-runoff data from two storm events the initial rainfall losses and curve number parameters were calibrated. Then, the model was validated using one event. Finally, six hours rainfall was used as design storm for flood simulation before and after construction of check dams along the water ways. Variation of runoff lag time due to changes in channel slope because of construction of check dams was evaluated. Finally, after definition of peak discharge error percentage as objective function, effect of construction of protective hydraulic structures on flood hydrograph properties were evaluated. Results showed that watershed management constraction operations have the most effect on small flood events. Waterways could decrease both flood peak and flood volume. . So with increasing in rainfall intensity, the effect of structure have been decreased. Also the results of this study showed that implementation of protective hydraulic structures cause 21 to 83 percent decrease in flood peak and 11 to 79 percent decrease in flood volume. It can be concluded that protective hydraulic structures are more effective on decrease in flood peak compare to decrease in flood volume.

One of the natural disasters that occurs in abundance in Iran, due to the geological structure, morphological and seismic conditions, and damages the lives and property of people is a landslide. Roodbar Alamoot watershed in the east of Qazvin province is a mountainous region with a high potential for occurrence of landslides. Because of their active status, there is also a growing trend of landslide occurrence and damage to rangeland, agricultural lands and residential areas. In this research, landslide survey was conducted using Artificial Neural Network model (ANN). Soil, geology, slope, aspect, elevation classes, linear parameters including distance from the river, distance from the fault, distance from the road, sensitivity of the rocks to erosion, rainfall and land use as factors affecting landslide. Using artificial neural network model with the multiple-layer perceptron structure and back propagation learning algorithm, landslide hazard zonation was performed. The results showed that the arrangement of 11-7-1 with active sigmoid function is the best structure for studying the phenomenon of landslide in this study area. The training, test and validation of the model were performed with 15, 15 and 75 Percentage of data that randomly selected. After optimizing the network structure, standardized information was provided to the network. Based on the results of landslide hazard zonatin with Artificial Neural Network model, respectively, 6. 2, 10. 7, 17. 1, 64. 3 and 5. 3 percent of the area placed in the very low, low, moderate, high and very high risk classes. The network has 0. 5 learning ratio, 7 neurons in the hidden layer and the least amount of error in the experiment (RMSe = 0. 0321).

Study of sedimentation trend in artificial recharge projects and flood spreading on the aquifer (Aquifer management) can be effective in designing structures and network management. Literature review shows that most studies in the flood spreading area shave been conducted in networks that have a low life span or low flood numbers. Since 1997, the flood spreading station on the Jajarm aquifer in North Khorasan province has recorded 37 floods. Events In this study, in order to investigate the surface sedimentation and soil texture changes in the flood spreading area, sampling of sediments were done in the main canal and 9 secondary canals. In the next step, three soil profiles inside the grid and a profile outside the field were drilled (as a control sample) and samples were taken at three depths of 0-30, 60-30 and 60-90cm. Sediment and soil samples were prepared by using standard sieves. The fine particles were gained by hydrometric testing. The results show that the sediments in the flood spreading network have silt and texture clay. The sediment aggregates become smaller toward downstream flood spreading region. Although the changes in tapes 4 to 9 are much less. The results of soil profiles show that fine-grained sediments are deposited on the surface of the soil at a depth of 0 to 30cm and a small portion of the sediments penetrates into the underlying layers. Based on the results, it is suggested in the implementation plans, the initial strips should be considered as sediment traps and the dimensions and distances of the structures should be designed in accordance with these conditions.

Sediment rating curve is an essential factor for many river engineering subjects and computations such as dredging, design of storage dams, river intakes design and sand mining management. Although, this curve is established using simultaneous measurement of flow and sediment transport discharges, however, due to lack of reliable data during flood events, it has limited reliability in flood conditions. This limitation may be coped with using a simple and practical tool like a semi two dimensional mathematical model. As an efficient and practical solution, these kinds of models currently have widespread applications in hydraulics of flow and sediment transport subjects. In this study, using the semi 2-D mathematical model of Shiono and Knight, the transverse distribution of flow velocities were computed and then with combining these results with some empirical sediment transport formulas, the lateral profiles of sediment transport and total sediment discharges were predicted across Gharesoo river at the SiahAb station. The results indicated the suitable capability of Shiono and Knight model in computation of lateral distribution of flow velocity with about mean error of 8. 7 percent. Also, among the selected sediment transport formulas, the Engelund-Hansen (1967) equation with mean error of 34 percent had a highest accuracy in prediction of river sediment transport discharges and sediment rating curve. The Yang (1996) and Ackers-White (1973) equations with mean errors of 48 and 64 percent, respectively attained the second and third places. Laursen equation with mean error of 258% corresponds to very low accuracy.

Landslideeventin Iran, as a natural hazard, causes a lot of mortal and financial losses annually. Thus, the comprehensive researches are necessary to provide useful solution for preventing and reducing the damages caused by landslide events. Accordingly, the present study uses a logistic regression approach whit the aim of prioritizing the factors affecting the occurrence of landslides in a part of KopetDagh-HezarMasjed zone, in North-East of Iran. In this work, after applying the GIS functions on each initial information layer, the logistic regression analysis was performed to identify the effective factors, and then the frequency of landslides in each class was determined. Based on the results of Type II analysis, among all selected factors, soil factor with the lowest value of Pr>LR ratio (0. 001) was identified as the most important driving force in landslide happening. After that, altitude, lithology, Topographic Position Index (TPI), Stream Power Index (SPI), Normalized Difference Vegetation Index (NDVI), roughness index and landuse, with the Pr>LR values of0. 002, 0. 003, 0. 004, 0. 032, 0. 037, 0. 100, and 0. 109, had the most impact on the occurrence of landslides in the study area, respectively. Four initial factors at the 99% confidence level and other factors at 95% confidence level were effective in landslide occurrence in the study area.

Due to the important role of non-point source pollution in water resources management, in this study time series modeling was applied to forecast water quality parameters and L-THIA model (one type of non-point source pollution models) was applied to estimate water pollutants. The purpose of this study was to compare results of L-THIA model and ARIMA models in Namrood sub-basin located in the Hablehrood watershed. At first, land use changes were studied from the years 1974 till 2017 that showed increase in agricultural lands and expansion of cities and roads. Then, using L-THIA model for both land use categories, the amount of pollutant and the volume of runoff were calculated that showed high growth. In the end, using ARIMA models were estimated water quality parameters for 30 years. Among the different ARIMA models, a model with a lowest error and akaike (AIC) criterion was selected as an optimal model for TDS, total of cations and anions. Desirable models for TDS, total of cations and anions were (0, 1, 1), (1, 1, 2) and (1, 1, 1), respectively. The end, diagrams of Trend Analysis and Time Series were performed for three parameters that indicated high growth in amount of pollutant. The results showed efficiency of time series modeling in water resources studies in order to forecast water quality parameters.

The estimation of the correct amount of suspended sediment has an important role in the optimal design of water structures, erosion studies and water quality studies. The sediment rating curve (SRC) is a conventional and well-known regression model. However, due to logarithmic transformations in calibrating this model, its estimated values are often less than actual values. In the present study, using the instantaneous flow discharge and suspended sediment load of Beytas hydrometric station in the Mahabad-Chai River, the SRC model was calibrated, and then using Non-dominated Sorting Genetic Algorithm II (NSGA-II), the coefficients of this model optimized again. This algorithm is an automatic procedure and can use different objective functions in the calibration process simultaneously. In this regard, in the calibration process of the model, four objective functions RMSE, MAE, NSE, and LOGE were used as pairwise combinations. According to the results of the model evaluation, the NSE and LOGE objective functions were selected as the best objective functions for optimization of the model. In order to increase the power of the model's generalization, the self-organizing map (SOM) neural network was used to cluster data and form two homogeneous data sets (calibration and evaluation sets) of 70% and 30% respectively. The results showed that the use of the NSGA II algorithm resulted in improved model efficiency so that the results are much more favorable than the other results of conventional SRC models (such as the rating curve of mean load within discharge classes, SRC models corrected by correction factors). In this regard, the error value (RMSE) of the test data set in the best model of the conventional SRC models was 383. 65 tons/day, which was reduced by using the NSGA II algorithm to 102. 94 tons/day. In sum, using the NSGA-II algorithm, we can optimize the coefficients of the SRC model, which is more efficient than the other conventional models.

Spur dikes are one of the common methods to protect rivers against erosion. Scouring around the spur dike is an important factor that can disorder the structural performance. Using protective spur dike is proper technique reduce the scour amount. In this research, the GMDH and GEP model used in order to evaluate and estimate the effect of various parameters of protective spur dike on scour depth around the main spur dike. Important parameters consist of protective spur dike angle (Ө ), protective spur dike length ( ), main spur dike length ( ), distance from main spur dike (X), flow intensity ( ) and Froude number ( ) are considered as the model inputs. Results of training set and testing set indicate that GMDH model is better than GEP model as the MAE and RMSE error in the testing set data are reduced from 0. 063 and 0. 086 (in GEP model) to 0. 045 and 0. 061 (in GMDH model) respectively. Also, the Nash-Sutcliffe criteria increased from 0. 51 (in GEP model) to 0. 75 (in GMDH model). In the following, using the GMDH and GEP models and according to the nature of the problems, the equations are suggested to predict the scour depth reduction in the first main spur dike. The results of sensitivity analysis indicate that the most effective parameter in decreasing the scour depth around the first main spur dike is ( ).

In the present study, the impact of watershed management practices on flood hydrograph characteristics was investigated using HEC-HMS model. In order to design, calibrate, and validate the model, data from a representative paired watershed (Kakhk Watershed, Khorasan Razavi Province, Iran) was collected and field surveys were performed to have the dataset further completed. Results of paired sample t-test, relative error statistics, Nash– Sutcliffe relative error and coefficient of determination for both real data and simulated results utilizing the HEC-HMS simulation software confirmed efficiency of the model in simulating flood hydrographs of the control and sample watersheds. Based on the results, watershed management practices could attenuate hydrologic response of the watershed and flood hydrograph characteristics such as flood coefficient (p-value: 0. 001), peak discharge (p-value: 0. 027), and flood volume (p-value: 0. 026). Moreover, a comparison between structural practices and biological practices showed that, the biological practices could further attenuate the peak discharge and flood volume by 8. 8 and 12. 64%, respectively.

One of the most important issues in watersheds management is rainfall-runoff hydrological process forecasting. Using new models in this field can contribute to proper management and planning. In addition, river flow forecasting, especially in flood conditions, will allow authorities to reduce the risk of flood damage. Considering the importance of river flow forecasting in water resources management, various methods are used to model rivers flow in order to minimize their potential damage by using the model in drought and flood management. In this study, the neuro-fazzy and hybrid neural-wavelet models were used to forecast the daily flow time series of the Sarmo water meter station located on the Mohammad Abad River. For this purpose, the original time series has been translated to three sub-series for 28 years using wavelet transformation and type IV Daubechies mother wavelet. The correlation coefficient value was obtained 0. 88 for neuro-fuzzy model and 0. 95 for hybrid wavelet-neural model, and the RMSE, MSE, and NS evaluation parameters in neural-wavelet model were 0. 004, 0. 043, and 0. 91, respectively; these parameters in neuro-fuzzy model were 0. 32, 0. 10, and 0. 77, respectively. Finally, the results of wavelet-neural transformation were compared with the results of neuro-fuzzy model, and it was observed that the wavelet-neural method has a higher predictive accuracy than the neuro-fuzzy method.

Land use change is an important issue in Iran, especially in the north of the country. In the present research, effect of changing land use from rangeland to cropland and garden on some physical and chemical characteristics of soil, was studied in Babolrood Watershed in southern part of Babol, Eastern Bandpey in Mazandaran province. For each land use, soil samples were collected from 2 depths at 4 replicates and the data were statistically analyzed by factorial test using a randomized complete block design. Results indicated that the highest percentage of sand, silt and clay in garden, Rangeland and Cropland, respectively. Change from rangeland to cropland, significantly increased bulk density and the bulk density in the lower layer was higher than that in the surface layer. The most amount of porositywas observed in the garden lands at a rate of 54. 87 percent. The highest Aggregate stability was obtained for rangeland, garden and highest water holding capacity was observed at the depth of 20-40 cm, (64. 62 percent). The highest saturated hydraulic conductivity (Ks) of the soil was in garden. Furthermore land use change resulted in change in soil reaction content, so that the highest amount of it was 7. 54 in cropland. The highest soil electrical conductivity (EC) was in garden. The highest percentage of organic carbon (OC) was in the surface layer, at a rate of 2. 47 percent in garden and the lowest percentage of it was in the subsurface layer at a rate of 0. 26 percent in cropland. The result of this study regarding the above comparing some soil quality properties showed that the change of land use to cropland usage and as result of severity of agriculture operation, have an negative impact on soil properties.