Journal of Water and Soil Conservation
Year:2012 | Volume:19 | Issue:4|Papers Count:15

Soil temperature is one of the main characteristics of soil that its changes have a great impact on many processes such as growth, plants flourishing and soil formation. Nevertheless, temperatures throughout the soils profile are not measured continuously. As a result, we encounter the lack of statistics in soils temperature data, while meteorological parameters are being measured regularly. Since presented relationships in the previous investigations do not provide the appropriate accuracy to predict soils temperature, the objective of this paper is to introduce a high accuracy relationship based on comparison of regression methods and Artificial Neural Network (ANN) by using daily meteorological data of three stations located in Mashhad, Sabzevar and Shiraz. Solidarity coefficients indicated that ambient temperature, evapotranspiration and evaporation have the most solidarity with the soil temperature at a depth of 5 cm, respectively. According to solidarity coefficient and results of the 2 models, air temperature, evapotranspiration, humidity and effective precipitation with daytime lag of one day were regarded as the best input parameters, respectively. The results showed that second order regression with single variable had the lowest accuracy while the highest accuracy was observed in the ANN method. In the meantime, multiple regressions had a reasonable accuracy. In calculation of freezing depth we concluded that Finish equation has an acceptable accuracy, whereas by considering an added parameter related to the precipitation depth in the cold days to the equations order, the results of the Finish equations will improve dramatically. Maximum error of 15% was observed for the recommended equation in Shiraz station and count of error in Mashhad and Sabzevar 0.6% and 2% observed respectively.

The Urmia Lake is one of the important water bodies in the northwest of Iran that has a significant role in the economy and environment of the region. Recently, the lake is faced with a critical level reduction, which makes it important to evaluate the causes. In this regard understanding of the Lake's level behavior is necessary, which can be applied for mitigation measure to save it. This subject constructs objective of the present paper that applies the spectral analysis techniques to investigate harmonic periods of the Lake level time series. For this, a combination of Multi Taper Method of spectral estimation and Singular Spectral Analysis were implemented. The results showed significant long-term periods in time series. However due to limitation in the record length, the frequencies longer than about 20 years were applicable for the analyses. Also, comparing the reconstructed time series of harmonic series with the original time series showed that although, harmonic oscillations are effective on level behavior of the lake, but declines of the recent years are not completely describable by these periodicities.

Lateral intakes are hydraulic structures, which are used for flow diversion from river. Due to the fact that most of rivers are curved on their path and due to existence of secondary flow, the outer bank of the bend is suitable places for positioning the lateral intake. The sill structure at the entrance of lateral intake is often used for controlling the flow and sediment entry to intake. The present experimental study focuses on the investigation of side-weir discharge coefficient in the entrance of lateral intake at different positions of a 180 degree channel bend. Also the relations were presented for estimation of discharge coefficient in various positions of lateral intake. The result showed that by increasing the froude number and proportion of sill height to upstream flow depth, the discharge coefficient decreases. Also positioning of side weir on 90o and 150o lead to maximum value of discharge coefficient and positioning of side weir on 135o lead to minimum value of discharge coefficient.

Flow discharge determination in rivers is one the key elements in design of river engineering projects. By flow entering into the floodplains and sudden changes in river geometry, the common resistance equations are not applicable. Therefore, many approaches have been developed for modification of flow discharge computations. Most of these methods have satisfactory results in laboratory flumes but extending those to all hydraulic and geometric conditions such as natural rivers are very limited. In recent decades, due to ability of complex phenamena modeling, the artificial intelligent methods have very wide applications in many fields of water engineering. Genetic Programming, a branch of evolotionary algorithms, is able to optimize the model structure and its components and to derive an explicit equation based on the variables of the phenamena. In this study, using 394 laboratory and field stage-discharge data sets of 30 compound channels, a new equation has been derived for calculation of flood discharge, based on geometric and hydraulics parameters, using Genetic Programming. The modeling is conducted in training and testing phases that at these two phases, the agreement between computed and measured flow discharge was very good. The determination coefficient for the training and testing phases was 0.99 and 0.96, respectively.

Nowadays, the scientists and climate researchers have been focused on prediction of long-term climatic parameters caused by climate change. GCM models can predict climatic parameters as LARS-WG. This model can produce daily rainfall, radiation and temperature maximum and minimum daily. Model using of semi-empirical distribution will generate wet and dry days, daily rainfall and radiation. In this research, the possibility of using of LARS-WG model was evaluated to simulate some weather parameters in Sanandaj. The model was able to simulate maximum temperature, minimum temperature and radiation but it was not able to simulate rainfall data. So results showed that mean of minimum, maximum temperatures and rainfall will raise, 0.99, 0.01 oC and 6.95 mm during period from 2030 to 2011 in Sanandaj respectively. Also, solar radiation will decrease about 0.075 MJ/m2. Day and the greatest rainy days obtained in February (6.75 mm) and the lowest in March (3.95 mm). Also results showed that the hot days will increase in warm months and the highest mean will occur in June. The greatest of frost days occurred in January with 25.60 day as average. Therefore, considering the results presented and good accuracy of model in estimating the parameters, it can be used for evaluation and prediction of climate change in Sanandaj station.

Hydraulic flow analysis in rivers during floods by mathematical models is one of the initial activities for flood alleviation schemes. In this case, besides saving time and budget, the velocity and bed shear stress lateral distribution and sediment transport will be computed with suitable accuracy. One-dimensional mathematical models have been widely used by hydraulic engineers in river training works. Recently, application of quasi two-dimensional models is widespread. These two mathematical models have their individual limitations and strengths which should taking into account in interpretation of results. In this paper, by calibration of 1-D and quasi 2-D models, their ability in prediction of velocity lateral distribution in Gorganrood River at Aq-qalla hydrometric station are compared. This comparison showed that mean error of 1-D and quasi 2-D models in velocity lateral distribution are 9.5 and 4.5 percent, respectively.

In this paper flow pattern at 90o, rectangular channel junctions have been studied. Flow pattern in open channel junctions was studied both experimentally and numerically. Velocity measurements were taken using an acoustic doppler velocimeter and depth measurements were made using a point gauge over a grid defined throughout the junction channel region. Velocity distribution in various plates for six discharges ratio Q* was investigated. Results showed that there is a good agreement between the model simulation and the experimental measurements. Both experiments and numerical model showed that by combining two flows in the main and lateral channel, producing a helical flow in the main channel affecting flow pattern. This helical flow formed a separation zone at downstream of lateral channel and this separation zone affecting by discharge ratio. This zone has an inclination to the main right wall at upper layer and in lower layer has an inclination to the left wall. When decreasing Q* separation zone is also decreased in width and length. Longitudinal and vertical velocity vectors in the main channel have small magnitude at upstream main channel. By combining the lateral flow and main flow increasing the magnitude of transversal velocities results also indicate that maximum transversal velocities occur at maximum contraction of flow.

In recent years, urban development and industrialization have caused the accumulation of heavy metals in soil. Pollution of soils significantly reduces the environmental quality and affects the human health. Using chemical methods to evaluate soil pollution is both difficult and time consuming. In many recent studies, magnetic susceptibility measurements have been employed for pollution monitoring as a non-destructive and fast technique. The objective of this research was to determine the spatial variability of magnetic susceptibility and the concentration of selected heavy metals and the effect of land use on their variations in surface soils of the Isfahan region. A total of 158 composite surface soil samples (0-5 cm) were taken from an area of about 700 km2. Magnetic susceptibility was measured at low frequency (0.46 kHz) using a Bartington MS2 dual frequency sensor. The concentration of total lead (Pb), zinc (Zn) and copper (Cu) were measured in all the soil samples. The spatial variability of these variables was examined by kriging. No significant difference was found between uncultivated and agricultural lands. The concentration of Cu, Zn and Pb are positively correlated with magnetic susceptibility (clf). It appears that the major factor controlling the enhancement of magnetic susceptibility in the study area is anthropogenic activities. It appears that the concentration of Pb, Cu and Zn has been affected by anthropogenic sources such as traffic emissions and industrial activities. The results also suggest that magnetic methods could be used to estimate the heavy metal contamination from anthropogenic sources in soils.

High ratios of erosion and sediment in eastern area of Golestan province have reduced soil fertility and dams capacity. Temporal variation of chemical soil quality indicators has to be studied for evaluation of soil degradation by erosion. Therefore, this study was conducted to evaluate soil and sediment quality indicators in different seasons in loess derived soils, in the Eastern area of Golestan province. Soil samples were taken from each season to analyse chemical properties in Gharnaveh and yelcheshmeh watersheds. Samplings of sediments were monthly for one year from the outlet of watershed basins mentioned as Tamer hydrometric station. The results showed the highest total nitrogen (0.16%) and soil organic matter (3.6%), were observed in autumn. The effect of season on soil phosphorus and potassium was significant (P>0.05), so the maximum amount of phosphorus (5 mg/kg) and available potassium (108 mg/kg) were observed in summer. About the status of nutrients in the sediment, this study showed that total nitrogen in the autumn, have a maximum amount and there was a significant difference between spring and autumn. The maximum amount of phosphorus (amount 4.9 ppm) was observed in winter. Most of the sediment organic matter and available potassium were observed in summer and spring. The results showed that there was a correlation between although maximum of nitrogen and potassium in soil and sediment, but in universal view, changes in soil nutrients and sediment, during different months of the year is not consistent.

Area reduction method is one of the most common empirical methods to determine sediment distribution in dam reservoirs. In this method reservoirs were classified into four types that for each of them the parameters c, m and n are presented. Calibration of method for a reservoir based on these parameters can increase its accuracy. In this research, two computer programs in FORTRAN language were prepared based on SA optimization algorithms and area reduction empirical method. Then, a simulation-optimization model was obtained by combination of two mentioned programs with ability to determine optimal parameters of area reduction method. Using this model, optimal parameters of area reduction method is determined so that the least difference exists between computational and actual volume. Prepared model was used for Karaj Dam with three periods of actual area-volume-height information. Using actual data from two first periods, optimal empirical area reduction parameters were obtained and capability of SA algorithm determining the global optimal was tested by asymptotic method. The optimal values of c, m and n were obtained 0.052, 0.836 and 14.234 respectively. In order to indicate the ability of optimal parameters to increase accuracy of prediction, sediment distribution in the third period of the actual data was calculated with typical and optimal parameters and the results were compared with actual values. Results showed that using optimal parameters decrease the amount of error in the prediction of sediment distribution, significantly. Difference between estimated and actual volume of Karaj dam using optimal parameters in calibration and verification periods are 54% and 20% lower than the typical parameters respectively. Finally sediment distribution of reservoir was predicted for next years based on optimal parameters.

The aim of the present study is to monitor the drop of groundwater level in the Saveh aquifer. To achieve this goal, monthly precipitation from five weather stations, monthly flow in three gauging station, monthly volume of discharges and water table data in 63 wells were investigated. The results of assessing meteorological drought using Standardized Precipitation Index (SPI) in two stations (Imamabad and Ahmadabad) indicate that extreme drought has occurred in 1980, 1983 and 1985. The results of correlation coefficient between the Standardized Precipitation Index (with scales 1, 3, 6, 9, 12, 18, 24 and 48 months) and water table data (with lag time 1, 2, 3, 4, 5, 6, 12 and 24 months) indicate high compliancy, SPI with scale of 24 and 48 months and groundwater level with time delay of 5 months (0.806 and 0.762) respectively for two Station of Ahmadabad and Imamabad. Review of rainfall and surface flow data at Shah Abbasi, Razin and Jalayer show increasing decreasing trends in rainfall and flow, respectively. According to results of this study construction of Saveh dam on Qarechay River in 1994 is the main reason for drop of groundwater level in Saveh aquifer.

Rainfall-runoff models such as Watershed Modeling System (WMS) are suitable tools for watersheds hydrological simulation. In this research, different and effective parameters in hydrological modeling of Ghorve watershed were studied. Five storm Hyetographs and corresponding hydrographs were selected. Using the HEC-HMS sub model and SCS and Snyder methods, flood hydrograph was simulated and then calibrated and validated. The results in validation phase showed that for simulation of peak discharge, the SCS method has better agreement compared to observed data.

Management of natural resources such as water and soil is one of the important subjects in suppling food requirements of increasing population of the world. Soil salinization and sodification caused by salt accumulation are the common phenomena that manifest in irrigated agriculture in arid and semiarid regions. The aim of this research was study of desodification of saline and sodic soils at central region of Khuzestan province-IRAN. For this purpose, two experimental areas (S1, S2) were selected and four treatments with three replications by series of double rings were applied. The treatments included 25, 50, 75 and 100 cm water application. It was concluded that 39 and 55% of initial exchangeable sodium percentage in Pilot S1 and S2 was reduced by 100 cm water leaching at one meter layer of Soil respectively.

Dry farming is a part of agricultural practice in Golestan province. Increasing dry and irrigated lands is connected with rainfall. Dry farming is important in countries with developed economy and agriculture. Therefore modeling for estimation of annual rainfall is important. This research used data of daily rainfall (34 years) of 8 stations in Golestan region. Climate of stations were cold semi dry to temperate (mild). Results showed that in equation between t167.5 (data of rain value=167.5 mm from the first of autumn in mild climate) and t107.5 (cold dry climate) annual rainfall decreases. Some another parameters were not suitable for these equations.