Watershed Management Research
Year:2016 | Volume:28 | Issue:109|Papers Count:10

The saturated hydraulic conductivity is one of the most important and widely used geotechnical parameters. This parameter depends on properties of the fluid, pore size distribution, and characteristics of the solid surfaces. Because the latter two are not necessarily constant, the hydraulic conductivity may vary significantly. So far several empirical relationships for estimation of the hydraulic permeability with respect to the type of materials have been presented.In this research seven applicable method including Terzaghi, Kozeny-Carman, Chapuis and Aubertin, modified Navfac, Shahabi et al., Mbonimpa et al. and Chapuis were evaluated. Four samples of sandy soils (R1 to R4) with a rather wide range of particle sizes were prepared and were compacted within the Plexiglas box. After providing the head of 0.5, 1 and 1.5 meters; flow discharge and static pressure were measured which result phreatic and isopotential lines extraction. By applying the results of the model, the accuracy of some common methods used in the estimation of saturated hydraulic conductivity of sandy soils was evaluated. For the samples (R1 to R4), the coefficient of permeability was 0.0051, 0.048, 0.076, and 0.19 cm/s respectively. Due to the limited range of input parameters, the method of Shahabi et al. can be used only for the R4 sample; so this method was discarded from statistical analysis. Comparing the results of laboratory test with common methods shows the methods of Kozeny-Carman and Chapuis and Aubertin were more accurate according to the highest R2 and lowest RE and RMSE.These methods were based on effective parameters and the results of accurate laboratory studies. The method of Mbonimpa et al. (2002) indicates the maximum deviation from observed values which may be due to the sensitivity of this model to void ratio (e). Also the results shows by increasing of void ratio the error of Mbonimpa et al. method increases.

The occurrence of landslides in Sanandaj cause significant financial losses and lot of stress on people living in the sliding regions. The purpose of this research is to separate and identify the sensitivity of landslide area and performance compared with two logistic regression model and fuzzy membership function with Gaussian and triangular. According to the review of internal and external studies and Field survey of Sanandaj, eight factors on the occurrence of landslides of the study area were considered effective. SPSS 19 software for data processing by logistic regression model and MATLAB software for using in fuzzy logic model and Arc GIS 9.2 software for landslide susceptibility map of the study area were used. Based on the coefficients obtained from the logistic regression model, equation Probabilistic and landslide susceptibility zonation map of the city of Sanandaj in Arc GIS 9.2 software and the sensitivity of the 4 classes low, medium, high sensitivity, and were very susceptible to preparation. Logistic regression model was evaluated using ROC curves and the area under the curve of 0.958 showed a high accuracy of the statistical models. Lithology and elevation of sea because of the statistical confidence level of 95% correlation with the landslide were introduced as the most influential factors in the logistic regression model. In the fuzzy logic model, normalized tables classes for each factor provide and using the final formula as two Triangular and Gaussian function were entered into the software. Results show that in the fuzzy model, the most landslides has occurred in areas with activities and road building, north aspect, slope between 30-40 percent, elevation of sea 1700 to 1500 m, 400 meters away from the fault, a distance of 100 -0 m from the road, constructive KSh2 (yellow with black shale’s and limestone Mykraity (shale Sanandaj), the soil was too shallow to shallow, rocky and gravel on schist with some sandy loam. Final results of comparing the validity of landslide susceptibility maps showed that in the case study the fuzzy logic with tow membership functions; triangular by 13.21 percentage of accuracy and Gaussian by 13.14 percentage of accuracy is more precise of the mapping than the logistic regression model by 1.9 percentage of accuracy.

This study was carried out in order to evaluate the ability of artificial neural network in the preparation of predictive distribution map of plant species habitat and recognizing the strengths and weaknesses of this method. For this purpose, vegetation and soil sampling was conducted after determination of the homogenous unit using digital elevation model and geological map with a scale of 1: 25, 000. Then environmental variable maps were obtained using GIS and Geostatistic. Input variables were selected based on the results of logistic regression. In order to develop of the artificial neural network model the best structure of the neural network was determined using Mean Square Error (MSE) after data normalizing and randomly data portioning into train, test and validation sets. Then simulation of presence / absences probability species was done with optimal network and continuous probability maps of presence or absence species in each habitats were prepared using Arc GIS software and presence optimal threshold was determined. Then compliance of the predictive and actual maps was assessed through the calculation of the kappa coefficient. The results showed which prediction maps of Pteropyrum olivieri-Stipa barbata habitat has excellent correspondence with actual vegetation map (kappa=90%) and Amygdalus scoparia, Artemisia aucheri-Astragalus glaucacanthus, Scariola orientalis- Stipa barbata habitats have very good correspondence with the ground truth maps. These results indicate that the use of logistic regression preprocessing simplify the network architecture and has increased learning speed and accuracy of the simulation results. Therefore in case of performing appropriate preprocessing of the data and selection of the appropriate input variables, neural networks can be an appropriate approach to estimation of the distribution of plant species habitats and selection of suitable species for rehabilitation activities in the rangelands.

In this study, the relationship between the spatial distribution patterns with environmental factors have been studied types of rangeland Ariz. After the vegetation types Astragalus. gossypinus - Centaurea.aucheri, Centaurea.aucheri-Bromus. tectorum and Festuca.ovina- Bromus. tomentellus as appearance, appropriate level of plot according to the type and distribution of vegetation types as The minimum level and the number of plots was determined by drawing.In each vegetation type, sampling was performed during 4 transects 300 m along each transect, 15 plots of 1 square meter to 20 meter intervals were established. In each plot type and number of plant species and their percentage was determined. In each vegetation type in the 12 soil profiles were taken from a depth of 40-0 cm. Physiographic features tilt, direction and height were measured, but to a height greater impact on distribution patterns of plants this parameter data was entered into the final analysis Percentage of soil texture, organic matter, phosphorus, pH, electrical conductivity, potassium and nitrogen were measured, as well as the management of rangeland condition and trends in balance method were calculated by four factors. After collecting the data, to determine the factors influencing vegetation distribution patterns of canonical correspondence analysis (CCA) using PC-ORD software was used. The results showed that among the factors studied and Spatial Pattern plants there and the most influence on the spatial distribution of vegetation types height, texture, phosphorus, potassium, nitrogen and organic matter are.

Functional diversity is an emerging concept which summarizes key properties of ecosystems of special interest in global climate change studies and in the evaluation of the effects of land management in the preservation of ecosystem services. Functional diversity may be linked directly to the ecosystem services; The Plant biomass encompasses many ecosystem services such as food supply, conservation, tourism pollination. In this study, we tested several hypothesis (1) existence of a close relationship between species richness and plant biomass (2) existence of a close relationship between CWM Functional Diversity index and plant biomass (3) Explain the high percentage of plant biomass variations. The results showed that the species richness in order to predict the plant biomass with a correlation coefficient equal to 3 not count as a proper indicator. But, the correlation coefficient CWM Functional Diversity with plant biomass was about 0.53, which is relatively good indicator to estimate the plant biomass because explained a significant percentage of the biomass variations. Finally, can be seen that the incorporation of Abiotic factors, plant traits and functional diversity (CWM) that contains the parameters of rainfall, leaf length, temperature, CWM- Height, CWM- Long Leaf and CWM-ME are more up 76 percent of plant biomass variations and considered as the most appropriate model predicts plant biomass.

The Doab Samsami watershed is located in Chaharmahal Va Bakhtiari province and is one of the main tributaries of the Karoon River basin. Landslide distribution map of the study area was prepared using air photos interoperation and field studies.37 cases of happened landslides were observed. Nine parameters including elevation, slope, aspect, lithology, distances from fault, stream and road, land use, and annual precipitation were chosen as landslide effective factors. Potential landslide hazard maps were also provided using weighted density area bivariate statistical model (semi-quantitative model), multivariate stepwise regression model and logistic multivariate regression model and were compared by field data. Chi-square test was used to analyze difference between hazard classes of models. Kappa index was used to compare the conformity rate of the hazard maps. Qs and ROC Indexes was also used for evaluation of models accuracy. Hazard map, elements at risk map and vulnerability map were used in the preparation of risk map. Results show that measured Chi-square statistics is statistically significant at 95% of confidence interval, and there is an appropriate differentiation among landslide hazard classes. Kappa index between hazard maps of models vary between -1 to 0.2, indicating that there is a slight conformity between them. Weighted bivariate statistical model has been identified as the superior model for Doab Samsami watershed with Qs and ROC equal to 0.87 and 0.914.

Recognizing the function of a natural ecosystem and awareness aware of its potential require to knowledge of the characteristics and the soil and plant represents. Evaluation of important characteristic of soil and vegetation identify potential ability of rangeland and it is possible to determine the rangeland condition. The purpose of this study is Comparison and determine the function of soil surface indicators the ecological patches in both the eastern and western slopes, in Lishter rangelands of Kohgiluye and Buyerahmad province. In order to, in eastern and western slopes, 3 transects of 50 meter in the along slope, patches and inter patches in the area (5 repetitions) were established.Patches in western slopes including (Cousinia sp., Centaurea intricanta Boiss and Astragalus sieberi), inter patches including (bare soil, gravel) and also patches in eastern slopes including (Stachys byzantina C. Koch and Astragalus fasciculifolius Boiss) and inter patches (bare and litter). Landscape Function Analysis model were used to measure stability, infiltration and nutrient cycles using the 11 soil parameters. To compare, the western and eastern slopes the t-test was used. The results showed significance difference among stability, infiltration and nutrient cycling in both eastern and western slopes (p<0.05). Three indices in Cousinia sp. patches in eastern slope and Astragalus fasciculifolius patches in western slope compared to other patches in this study there were more.

Without knowing the characteristics and amount of forage plants in a rangeland during the grazing period, planning and management, and livestock grazing is not possible. So changes the production and consumption of important grasses was measured in the semi-steppe rangelands of Badamstan area. Every year the same number in the enclosure stand 30 and stand 30 outside the enclosure of the same species Agropyrun trichophorum -Festuca ovina-Bromus tomentellus Was chosen to investigate changes in production and consumption. In each month of the season forage production and consumption, 5 Base of each species harvested and transported to the laboratory separation in separate envelopes after air drying, dry weight difference inside and outside the enclosure, the calculation of forage produced and consumed at the site was. Data from 1386 to 1389 (for four years), the combined analysis of variance was used in a completely randomized design. Analysis of Variance results showed that the studied species the significant differences between years and months inventory is considered in terms of forage production and consumption of the species there. The Consumption compared to the same species and time to peak strain It was also different between the months of operation.

Kashkan Formation comprises marl and clay minerals and characterized by hilly lands with forest and rain-fed area as well as high soil degradation potential. This research was conducted at the Merek watershed located in the Zagros Mountains, Kermanshah, Iran. The objectives of this study were to determine the dominant erosion and soil and rock mineralogy at the Kashkan Formation and Older terraces. Soil and rock sampling and analysis carried out within study area where subjected to gully erosion and landslide occurrence. Land-use at these areas includes forest and rainfed agriculture. Soil and rock minerals explored through XRD technique and erosion intensity was estimated using MPSIAC model. The results showed that landslide and gully were dominant erosion in the forest and agriculture area, respectively. Both gully and landslide are triggered via crust as the primary step in degradation process. Mineralogical results also explored that smectite is dominant mineral in the landslide area, whereas quartz, calcite and dolomite are the other respective common minerals. Mineralogical properties in the gully areas at the older terraces (originated from Kashkan Formation), dominated by mica/smectite and vermiculite and other minerals approximately were as same as landslide area. The respective soil erosion intensity in the forest and rain-fed were 16.66 and 12.50 t ha-1yr-1.However, high interlayer space of smectite contributes to soil erodibility and consequently dissolve phenomenon for piping process.

Application of Neuro-fuzzy and tree regression models is not too old in hydrology of river sediments and also in watersheds and in this regard, sediment rating curves have been identified as the most common method for estimating sediment. In this study for comparison and correction of estimation methods of river sediment load, estimated rates of several uni-variate types of sediment rating curves and a multivariate type of sediment rating curves were investigated with Neuro-fuzzy and tree regression models in five selective hydro-metric station of different climatic zones of Iran and with various indexes of the accuracy and the precision. The results show that the mean of the accuracy index of Neuro-fuzzy and tree regression models in selective stations are 151 and 536 percent respectively which shows low efficiency compared with sediment rating curves. The results of the application of multivariate sediment rating curve in various station shows that the rate of the accuracy index of multivariate sediment rating curve in the best case is belong to Glinak station with the rate of 1.12. Also the average value of the accuracy index of multivariate sediment rating curve is 1.15 which is an acceptable amount to the other considered various methods.