نشریه آب و خاک
سال بیست و هفتم شماره 3 (پیاپی 29، امرداد و شهریور 1392)

The man’s craving for water has inspired many civilizations to be formed near rivers. The social and economic destructive consequences of flood in human societies are considered undeniable facts. Today human trespasses on riversides and also vegetation destruction have caused increase in flood damages. These factors lead to be not only vital and financial damages, but also damages such as soil erosion in upstream and soil deposition in downstream. This research aims to decrease flood damages using structural methods as well as investigating and finding proper locations to construct protective levees in high risk areas via studying torrent area of riversides. In this research, the Genetic Algorithm (GA) are applied to maximize the benefit of flood control and also to minimize the cost of protective levees construction. Therefore, the fitness function of the research is defined to maximize net benefit of the project. The objective of the present paper is to evaluate this method for decreasing flood damages in the “Sarm” and “Khoor Abad” rivers, located in Qom province in Iran. The proper location and height of levees are defined whether the factor of “the level of saved losses to the region by constructing protective levees minus the cost of constructing protective levees” is maximized. The results indicate that by constructing protective levees the rate of damages reduces up to 99% in comparison with a non-constructed protective levees scenario.

With respect to the problem of direct measurement of soil parameters in recent year using indirect method such as artificial neural networks has been considered. In the present study, 200 soil samples were collected from Ghoshe location in Semnan province. Half of samples were collected from disturbed agricultural lands and the other half were collected from undisturbed nearby lands. Some soil chemical as well as physical properties such as electrical conductivity (EC), soil texture, lime percentage, sodium adsorption ration (SAR) and bulk density were considered as easy and fast obtainable features and soil cation exchange capacity as difficult and time consuming feature. The collected data randomly divided in two categories of training (70%) and testing (30%) and they used for train and test of two artificial neural networks, multi-layer perception using back-propagation algorithm (MLP/BP) and Radial basis functions (RBF) and nonlinear regression model. Results of this research show high efficiency of artificial neural network compared with nonlinear regression and also MLP network was better than RBF network. Sensitivity analysis was also performed for all parameters to find out the relationship between soil mentioned parameters and soil cation exchange capacity for both disturbed and undisturbed soils. At last, the correlation between soil parameters and soil cation exchange capacity was determined and most important parameters which could influence the soil cation exchange capacity were described.

Rootstocks are of primary importance to the citrus industry. Rough lemon (Citrus jambhiri L.) is one of major and widely used rootstocks in Citrus production. The experiment was a completely randomized design in a factorial arrangement with three replications. The factors were mycorrhizal treatments at two levels (inoculation with Glomus mosseae and control) and irrigation treatments in 4 irrigation intervals (2, 4, 6 and 8 days). Water deficit decreased shoot and root dry weights and decreasing effect was more on the shoot. As water deficit levels increased, root colonization, leaf water potential and chlorophyll content decreased, but leaf temperature increased. Arbuscular mycorrhizal fungus increased root colonization, shoot and root dry weights, chlorophyll content and leaf water potential, while decreased leaf temperature in comparison with non mycorrhizal treatments.

The requiring of reducing agricultural water demand as the world’s largest consumer of water, for having sustainable water resources is not concealed to anyone. With measurements such as increasing irrigation efficiency, changing in cropping pattern, reducing the cultivation area, etc, this goal can be achieved. In this study, the status of water resources and irrigation demands within the Neyshabour Plane was evaluated by using Water Evaluation and Planning model (WEAP). To assess the effect of these strategies in WEAP model, scenarios with different topics for cropping pattern, reducing cultivation area, and combined scenarios were developed and then the simulations were performed for 20 years in future. The results suggested that above measurements reduced the mean annual water demand of agriculture by 9, 10 and 18 percents respectively and subsequently reduced the average of annual groundwater deficit by 13, 8 and 18 percents. On the other hand these measurements had a significant role in reducing the agricultural water demand, and therefore, in reducing the extraction from different water resources.

Empirical models specially event-based versions for estimating erosion are site specific, so calibration is essential for designing soil conservation practices measures. In this study, the efficiency of Universal soil Loss Equation and other event-based versions include USLEM, MUSLE-S and AUSLE evaluated in semi-arid region of khorasan Razavi. Because of small plot size (20 m2 area with annual shrubs cover), The amount of estimated soil loss equaled with measured sediment. Result showed that in addition to overestimation of USLEM and MUSLE-S, models showed temporal variation of sediment significantly. With respect to high and negative values of RMSE and ME of Nash-Shatklyf, models have no significant efficiency. Also, because of the same model structure of AUSLE and USLE models, thay have not significantly efficiency.

Soil salinity and sodicity are considered as the important factors limiting the plants growth. This study was conducted to assess the influence of the sample size on the accuracy of estimation of soil salinity and sodicity status, made by ordinary kriging, inverse distance weighting and spline estimators in Eslamieh area, Rafsanjan city. First, electrical conductivity (EC) and sodium adsorption ratio (SAR) were measured for 100 observation points, collected from three depths using a regular grid sampling pattern with an interval of 500 meter. These properties were mapped using aforesaid estimators. Then, random omission of 20, 40 and 60 samples from the total primary dataset (100 samples), was done and in each new situation, EC and SAR were mapped again. At the end of all 10 stages used to omit the samples, the index of standardized root mean square error (RMSE%) was measured for each estimator. Finally, the obtained contents of RMSE% were statistically compared using Friedman and Wilcoxon tests. The results showed using relatively high number of samples (all 100 observation points), three analyzed estimators have no significant difference (95% confidence level). In the cases of lower sample sizes, Friedman test revealed a significant difference among the estimators; whereas using Wilcoxon test, as a supplementary procedure, no significant difference was observed between the results obtained from ordinary kriging and inverse distance weighting. Hence, thanks to the relatively good precision, ease of processing and lower required sampling points, the inverse distance weighting estimator is recommended for future studies in the studied area.

After introducing similar media theory, many scaling methods were developed and have been widely used to cope with soil variability problem as well as to achieve invariant solutions of Richards’ equation. Recently, a method was developed for scaling Richards’ equation (RE) for dissimilar soils such that the scaled RE is independent of soil hydraulic properties for a wide range of soils. This method uses exponential – power hydraulic functions which are restricted to a limited range of soil-water content and matric potential. Hence, this method does not apply to the phenomena in which soil-water content and matric potential exceeds this range. Therefore, this research was performed to extend the method for a wider range of soil-water content and matric potential. This objective was achieved by modifying the exponential – power hydraulic functions and the scaling method was extended to the entire range of soil wetness (from saturated to dry). This study was followed to solve RE for soil-water infiltration using scaling. To do so, numerical solutions of the scaled RE was approximated by a scaled form of Philip three-term equation with soil-independent coefficients. The obtained approximate solution was tested using literature data of infiltration experiments on a sandy and two clayey soils. Results indicated that the solution can reasonably estimate (with the average relative error at most 9% for the cases studied here) measured infiltrated water. Also, it was shown that this solution can accurately approximate (with the average relative error at most 4% for the cases studied here) the numerical solutions of RE (for the same conditions and hydraulic functions). Hence, because of its simplicity, the solution is proposed as an alternative for numerical solutions of RE or other empirical equations for soil-water infiltration. Additionally, this solution can be easily applied to determine soil hydraulic functions by inverse solutions.

Climate change is one of the most significant challenges that all living matters on the Earth needs to face. A warmer climate will accelerate the hydrologic cycle, altering rainfall, magnitude and timing of runoff.Iran might become one of the most vulnerable areas in the world regarding climate change. To study the effects of climatic variations, the Soil and Water Assessment Tool (SWAT) model was implemented to simulate the hydrologic regime on Gorganroud basin. The SUFI-2 algorithm in the SWAT-CUP program was used for parameter optimization using the monthly river discharge. The climatechange scenarios were constructed using outcomes of three General Circulation Models (CGCM2, HadCM3 and SCIRO)for low and high levels of greenhouse gas emission scenarios (A1F1 and B1). The calibration andvalidation results of the SWAT model agreedwell with the observed data. The study result showed that Compared with the present climate, the climate models predicted a −3.2% to -6.5% changes in annual precipitation, 3 to 5.7°C rises in maximum temperature, and 2.8 to 5.2°C rises in minimum temperature. SWAT predicted a −0.4% to -7.7% changefor runoff, −5.2% to -13% change for soil water content, 5.3% to 10.2% change for water yield, and -1.6% to -3.6% decrease for evapotranspiration during 2010–2039 under all climate scenarios.These results highlight the strong impact of climate change in regional water resources and reflect the importance of incorporating these analysis into adaptive management in the future watershed management strategies.

One of the main problems in soil pollution evaluation is the lack of regional standards. The objectives of this study were (i) to estimate the background concentration of some heavy metals for environmental assessment and, (ii) to locate heavy metal polluted soils in part of central Mazandaran Province. The study region with 5500 km¬2¬ area is important in terms of agricultural activities and population density. Using nested-systematic method, 256 composite soil samples were taken from the depth of 0-10 cm, including 148, 60, and 48 soil samples in agricultural land, urban area, and natural lands (forest and rangeland), respectively. After preparation and extraction of soil samples with 5 N nitric acid, the total concentration of Cu, Zn, Ni, Pb, and Cd was measured by an atomic absorption spectrometer. Natural background concentration (NBC) of Cu, Zn, Ni, Pb, and Cd was estimated to be 28.3, 40.2, 45.7, 34.2, and 0.23 mg kg-1, respectively. Interpolated distribution map of contamination factors (CF) and pollution load index (PLI) of heavy metals were prepared using NBC. The overlap of CF and PLI maps with geology and land use maps was indicated that the concentration of Pb, Zn, and Cu has been affected by human activities such as traffic, whereas Cd and Ni contents are controlled by natural factors such as parent material, and agricultural activities, mostly. Based on the classes of CF, most samples are moderately contaminated with heavy metals.

Soil pollution by heavy metals is an important environment issue throughout the world. Heavy metals’ origin, accumulation, and distribution in soil have been the focus of much attention by many researchers. The objective of this study was to recognize the sources of some heavy metals in surface soils in Zob-Ahan industrial district, Isfahan province, using multivariate geostatistical techniques. A total of 202 surface (0–30 cm) soil samples were collected. Total lead (Pb), zinc (Zn), manganese (Mn), iron (Fe), copper (Cu), nickel (Ni), cobalt (Co) and chromium (Cr) contents of the samples were determined. A multivariate geostatistical analysis was performed to identify the common source of heavy metals. The results of principal component analysis led to the identification of three components. So, these components were explained 31, 27, and 16 % of total variance of heavy metal concentration, respectively. The distribution of scores of each components were shown that the quantities of Fe, Mn, Pb and Zn were found to be associated with anthropogenic activities, corresponding to the first factor was termed the “anthropogenic component”. The quantities of Co were found to be associated with parent rocks, corresponding to the second factor was termed the “lithologic component”. Also, the third factor was mainly attributed to Cu, Ni and Cr which also comprised the first and third factors, indicating a mixed source both from lithologic and anthropogenic inputs.

Hydraulic jump plays a significant role in dissipation of kinetic energy downstream of hydraulic structures in a stilling basin. In the present research, hydraulic jump characteristics on roughened bed with half cylindrical shape bars and rectangular bed sill on two adverse slopes of 1 and 1.5 % and horizontal bed were investigated. In total 338 experiments were performed for Froude numbers ranging from 4.6 to 7.4. The results indicated that the length of the hydraulic jump on the adverse slope of 1.5% decreased 46% with sill and 49% on rough bed. Also maximum reduction of sequent depth on the adverse slope of 1.5 % with sill and on rough bed was 24.4% and 44%, respectively, compared with the classic jump. Furthermore, application of a continuous sill on adverse slope to stabilize hydraulic jump with decreasing its length will be economical.

The main objective of this research was to find the stable side slope of irrigation canals, considering type of subgrade materials as well as canal depth. For this purpose two methods of limit equilibrium and finite element methods were used for stability analysis. In respect to the geotechnical properties of subgrade materials, the Unified Soil Classification System as well as the technical properties of each soil group such as cohesion, angle of internal friction and unit weight was used based on the recommendations given in the literature. To consider operation conditions, three cases namely: steady seepage, rapid drawdown and end of construction of canal were taken in to consideration. The results of investigation showed that stability of side slopes in canals is a function of type of subgrade material in respect to its cohesiveness, operation conditions and depth. In non-cohesive materials, the safety factor is not related to the canal depth and is normally less. Based on the mentioned functions safety factor of side slopes of canals with depth up to 8 meters were calculated. For non-cohesive soils stable slopes were about 1:0.6 and for cohesive soils it was determinate around 1:3.

In geo-statistics, prediction of an unknown value of random field has been performed in specified time and position, using spatio-temporal Kriging. In some circumstances, a suitable covariate increase the estimation prediction. Geo-statistical methods of Universal Kriging (UK) and Kriging with External Trend (KwET) were applied to Mashhad plain water quality data sets. The optimal network to monitor groundwater quality was presented, using Entropy. All wells ranked based on the criterion of Entropy and mutual information. Then, the optimal network was determined based on the percentages of acquired information and relying on the spatio-temporal Kriging. Based on UK and KwET, electrical conductivity (EC) was the best covariate. KwET with EC as a covariate was the superior Kriging method. A network covering 111 wells showed to be as informative as the existing monitoring network with a total of 237 wells.

Estimation of soil moisture content at different soil suctions is preferred to its determination due to required cost and time. The aim of the present work was to explore the relationship between soil texture fractal dimension and soil volumetric water content. A dataset of 195 soil samples from UNSODA database was selected. A pedotransfer developed by Sepaskhah & Tafteh (2013) was used to estimate soil fractal dimension. Exponential functions better describe the fractal-water content relationship than linear functions. A set of exponential pedotransfer functions using texture fractal dimension or additionally soil bulk density is proposed for predicting water content at several suctions across soil water retention curve. These pedotransfer functions, generally, function well or better than the most recent pedotransfer functions proposed by Ghanbarian-Millan (2010).

The drawdown trend of the water level in Urmia Lake poses a serious problem for northwestern Iran that will have a negative impact on the agriculture and industry. This research investigated the possible causes of this adversity by estimating trends in the time series of hydro-climatic variables of the basin as well as tracking changes in the land use of the study area, using satellite images. Four non-parametric statistical tests, the Mann-Kendall, Theil-Sen, Spearman Rho and Sen's T test, were applied to estimate the trends in the annual time series of streamflow, precipitation and temperature at 18 stations throughout the case study. Furthermore, by using the LANDSAT satellite images of 1976, 1989, 2002 and 2011, land use classification was determined using maximum likelihood, minimum distance and mahalanobis distance methods. The results showed significant increasing temperature trend throughout the region and an area-specific precipitation trend. The trend tests also confirmed a general decreasing trend in region streamflows that was more pronounced in the downstream stations. The results showed that the classification by the maximum likelihood method wass associated with minimum error. The results of processing the images showed that the irrigated crops, horticultural and dry lands have increased during last 35 years by 412, 485 and 672 percent, respectively. But, the pasture area is decreased by 34 percent. Finally, correlation between streamflow changes with simultaneous changes in climatic variables and land use showed it is significant in case of temperature and land use; and insignificant in case of precipitation. However, the determination coefficient of land use is higher than temperature.

Climate change by increasing concentrations of greenhouse gases, particularly carbon dioxide, has led to increase attention to the carbon sequestration through the restoration and protection of vegetation cover. In this regards, ecosystems of arid regions have a special importance. In this study the effects of reconstruction and conservation, on soil carbon sequestration of the region of the International Carbon Sequestration Project in Hussein Abad, South Khorasan province of Iran was investigated by a simulation approach using RothC model. In addition, the effects of climate change (increasing temperature and decreasing rainfall) on soil carbon sequestration potential was studied. In the studied area, replanting was done in 2004 and then soil samples were taken every two months during 2010-2011. After collecting the required input data for RothC model (climate, soil and management input data), the model was evaluated and validated for the study area. Moreover, soil carbon sequestration was studied under climate change condition. The simulation results revealed that the RothC model is applicable in rangelands of dry and warm regions, because it estimated the soil carbon changes over the time with proper accuracy. The amounts of model performance index, R2 and RMSE were 0.98, 98% and 0.01, respectively. Simulation study indicated that soil carbon storage will increase from 2011 to 2050 and will be affected by climate change and protection programs. Based on model estimation the amounts of soil carbon in preotected areas will be higher than non-protected areas. Moreover, in non-climate change scenario the amounts of soil carbon will be higher than climate change scenario in 2050.