Journal of Water and Soil Conservation
Year:2015 | Volume:22 | Issue:1|Papers Count:21

The physiographical and climatological attributes of basins and maximum annual flood statistics were obtained from 38 hydrometric stations of Mazandaran province with minimum and maximum statistical periods 13 and 56 years. The first, homogenous regions in the physiographic space based on neighborhood approach were determined by using physiographical space based interpolation (PSBI) method. The Principal Component Analysis was used to design physiographic space using the six physiographic variables affecting the flood. The exponential model had the best fit to semi-variogram model in 10, 20, 50 and 100 year return periods, and regional estimates obtained using ordinary Kriging technique based physiography space. In order to evaluated the accuracy results using L-moments method for regional flood frequency analysis. In this method Ward hierarchical clustering has been used to the determination of homogeneous regions. Homogeneity areas were adjusted by using homogenous and discordancy tests. Using goodness-of-fit Z DIST the Generalized Logistic distribution was selected for all clusters as the best regional distribution and regional estimates obtained by parameters selected distribution. Finally, performance methods evaluated using Jack Knife procedure and the four statistical indexes BIAS, BIASr, RMSE, and RMSEr. Results showed that the PSBI method provide better performance than the L-moments at the four indexes considered and improving estimated by increasing the return periods, while the L-moments offers better performance for short return periods.

Due to momentum exchange between main channel and flood plains, the flow hydraulic in compound channels is complicate. Most studies in this area are focused on prediction of the average cross sectional velocity and total flow discharge, while distribution of flow rate in the main channel and the flood plains is also important. In flood conditions and during the spill of water onto the flood plains, the bed load and suspended sediment load are transported mainly by the main channel flow discharge and floodplain flow has very little effect. Moreover, for simulation of river morphology, the individual velocity and shear stress in the main channel and floodplains are needed and utilizing the average cross sectional velocity led to erroneous results. In this study, using 102 laboratory stage-discharge data from canals with compound channel sections, the individual flow discharges in the main channel and floodplains are calculated with aid of two new optimization methods of Genetic Programming and Decision Tree Model and then compared with one-dimensional empirical methods. Results show that these two new methods with mean error of 2.1 and 6 %, respectively, have appropriate ability for main channel’s flow discharge prediction. Among the empirical methods, the vertical divided channel method with mean error of 19% has the largest error in this regard. For floodplain’s flow discharge prediction, in addition to Genetic Programming and Decision Tree Models, the vertical divided channel method has considerable accuracy.

Knowledge of soil erodibility and its evaluation is a useful indicators to assess soil erosion. Climate is one of the soil forming factors which has a major impact on this index. The present study was designed to determine the effects of different climates on the erodibility indices change of loess derived soils in Golestan Province. Two transects in the loess hillslope with different climatic conditions were chosen. Samples were taken from seven areas with six replicates and the depths of 0 to 30 and 30 to 60 cm along two transects. Wischmeier and Smith, Chen and Bouyoucos indices were measured. The results showed that characteristics measured in the first transect from north to south as well as second transect (East to West) Province follow the specific trend, so that, organic matter content and saturation percentage of moisture rose with increased rainfall and reduction temperature. Organic carbon average changes in both transcet from 0.4 to 3.5 percentage was variable. lime content and electrical conductivity decreased with increase in rainfall. Bouyoucos’ index changed from 2.09 to 14.2 and Chen’s index was from 59.05 to 447.61 cmol/lit and both indexes in both transcet were decreased. Soil erodibility indices have been changed from 0.040 to 0.083 Mgr.h/Mj.mm and in both transect were demonstrated a decreasing trend. Results showed that the particle size increased due to increase in weathering of loess derived soils. Knowledge of soil erodibility and its evaluation is a useful indicators to assess soil erosion. Climate is one of the soil forming factors which has a major impact on this index. The present study was designed to determine the effects of different climates on the erodibility indices change of loess derived soils in Golestan Province. Two transects in the loess hillslope with different climatic conditions were chosen. Samples were taken from seven areas with six replicates and the depths of 0 to 30 and 30 to 60 cm along two transects. Wischmeier and Smith, Chen and Bouyoucos indices were measured. The results showed that characteristics measured in the first transect from north to south as well as second transect (East to West) Province follow the specific trend, so that, organic matter content and saturation percentage of moisture rose with increased rainfall and reduction temperature. Organic carbon average changes in both transcet from 0.4 to 3.5 percentage was variable. lime content and electrical conductivity decreased with increase in rainfall. Bouyoucos’ index changed from 2.09 to 14.2 and Chen’s index was from 59.05 to 447.61 cmol/lit and both indexes in both transcet were decreased. Soil erodibility indices have been changed from 0.040 to 0.083 Mgr.h/Mj.mm and in both transect were demonstrated a decreasing trend. Results showed that the particle size increased due to increase in weathering of loess derived soils.

The first step in design and optimal management of flood control projects is appropriately identifying behavior of the river during the flood. When channel is subjected to overbank flow, interaction between the main channel and flood plains and momentum transfer at the interface between the two partial cross sections results in energy loss and cause the cross-channel to become more complex. Also the main distinction between compound and ordinary sections is due to this phenomenon. The purpose of present paper is to study geometric parameters and dynamic stability approaches of simple and compound alluvial channels. To this end a laboratory channel has been modeled with GSTARS4. This mathematical model performs based on theory of total stream power minimization. The calibration of this model was based on water surface elevation, cross section geometry, sediment transport equations and friction factor. Some of the data not used in the calibration were used to verify the model. The results show that bankfull channels changed initial hydraulic geometry and reached a stable state. Then stable channels subjected to overbank flow, they adjusted their conditions to achieve a new stability so that Increase in the longitudinal slope resulted in increase in relative depth and decrease in relative width with time. Also in experienced range of relative depths, show that discharge calculations as a single channel is more appropriate than rate of decomposition for Developed compound channel. Proportion of Apparent to average shear stress ratio in low relative depths was 4 times higher than greater relative depths.

Already various studies have been done on the mechanism of scour around hydraulic structures especially bridges. In the field of scour around bridges, researches are more focus on scour of piers in comparision with abutments. While the review of available information on the bridge required cost, the major problems are related to abutment. Therefore most costs have to spent in this regard. Literature review shows that abutment form has considerable impact on the scour depth around it. Among various abutment forms, the maximum scour depth occurs in the case of rectangular abutment. Therefore in this research rectangular form for abutment was selected and the effects of froude number and non dimensional abutment length (Width to length ratio) were investigated on scour development. Result shows, that increasing froude number and decreasing non dimensional abutment length, will increase the amount of scour. Following this research, three-dimensional components of velocities were determined with electromagnetic velocimeter and then used for drawing flow pattern. Result shows, that vertical vortex in upstream corner of abutment is an effective factor on maximum depth of scour at this point. Also result confirms that, down flow and generated vortex are effective parameters on abutment bridge scour.

In Combined weir - gate structures, interaction of flow over weir and through gate brings up intense mixing and change bed shear stresses distribution. Hence, simulation of flow pattern in downstream of these structures is very complex. The object of this research is numerical modeling of combined flow over weirs and through gates by Flow3D software. Flow3D is a high accurate model in computational fluid dynamics for simulation of problem with complex geometry on wide limits of fluid flows in open channel hydraulic. By applying VOF method and RNG K-Ɛ turbulent models, a series of simulation combined flow in weir - gate structure on rigid bed were performed and results were compared by some experimental data that carry out in this research. Results for the equation of Qup/Qin (equation 13) calculation error statistics software based on RMSE and R2 was evaluated and these values obtained 0.0994 and 0.992. Results of this research show that Flow3D with RNG K-Ɛ turbulent model is appropriate to simulation of combined flow in weir - gate structure and estimation of free surface profile and discharge ratio passed over weir to under the gate.

The aim of this study is the comparison of conditional and unconditional frequencies of drought in future climate change conditions with current climate. Two extreme climate of Iran, including Bandar Anzali and Bushehr were studied. The statistical downscaling of the future climate conditions was done based on LARS-WG model for the period of 2056-2100. The period of 1956-2005 was chosen as the base period of the study. Then, the modified standardized precipitation index was calculated and classified over three time scales of 3-month, 6-month and 12-month in the current and future periods. In order to compare the transmission frequencies of the future with the base period, it was necessary to evaluate the dependency of transmission frequencies on drought time scale and climate conditions. This was done using a four dimensional log-linear model, and the best log-linear model structure was determined based on the backward elimination method. The expected frequencies matrices were calculated based on the most appropriate log-linear model. The odds ratio test was performed for comparing the transition frequencies of the drought classes in terms of changing drought time scale and climate conditions. The results revealed the significant increase of the transition frequencies in Bandar Anzali station (transition from severe drought class to non-drought and vice versa) and the significant decrease in Bushehr station (consistency in severe drought class). Also, the frequency of the extreme drought class (in Bandar anzali station) and moderate drought class (in Bushehr station) will increase in the future compared with the current.

In this study daily river flow of Barandouz-Chai in the period of 1973 to 2009 has been forecasted using nonlinear time series and Genetic programming models and result have been analyzed with root mean square error and regression coefficient methods. After evaluating model by goodness of fit, nonlinear BL(1,11,1,1) with the minimum AICC selected for modeling daily river flow forecasting. For BL(1,11,1,1) model regression coefficient and RMSE calculated equal to 0.902 and 3.52 (m3/s) respectively. Genetic programming has been used for modeling river flow with consideration to memory of one, two, three and four days before. Results showed until three days memory accuracy of model is acceptable but after that accuracy of model decreased. Regression coefficient and RMSE of Genetic programming in the testing phase calculated equal to 0.928 and 2.863 (m3/s) respectively. As results showed, Genetic programming with 22.9 percent less error was better than Bilinear time series model in Barandpuz-chai river flow forecasting.

Water Erosion Prediction Project model» is one of the most prominent process-based model with physics base that are able to predict soil loss and sedimentation by using spatial-temporal distributional mechanisms and processes on hillslopes and inside of stream. This model can be used in agricultural, rangeland, forest and road land uses. The WEPP model may be used in both hillslope and watershed applications and is able to estimate runoff, erosion and sediment yield as sequence year or during a storm.The model is a distributed parameter, continuous simulation and erosion prediction model. The distributed input parameters include rainfall amounts and intensity, soil textural qualities, plant growth parameters, residue decomposition parameters, effects of tillage implements on soil properties and residue amounts, slope shape, steepness and orientation and soil erodibility parameters. The major inputs to WEPP are a climate data file, a slope data file, a soil data file and a cropping/ management data file. If the user is simulating irrigation, additional input files are necessary. Applying WEPP in a watershed application also requires additional input file which provide information in channel and impoundment characteristics as well as watershed configuration. The WEPP model as applied to hillslopes can be subdivided into nine conceptual components: climate generation, winter processes, irrigation, hydrology, soils, plant growth, residue decomposition, hydraulics of overland flow and erosion.Erosion prediction is used wildly and as an effective tool in designing and programming for soil protection. For running the WEPP model, the climate information should be converted to acceptable format by WEPP model that this process is a hard work especially in regions with luck of data. This problem has caused that many users of WEPP model use the similar station in US to build climate file and then make to reduce model efficiency rate in areas outside of US. Then, in this study, it has been to produce the climate file of the WEPP model using meteorological data of Sanganeh watershed and BPCDG program. The final file is used in WEPP Model and then it make to reduce errors for estimating the climatic parameters. For this purpose, after collecting the required data, the entrance files of BPCDG program was provided in Not pad format and was introduced to the wepp model. The obtained result shows that WEPP model is able to identify the climate file and read it properly. Finally, this process causes to improve the accuracy of the model output.

The study of sediments behavior and its impact on morphological changes of river and its hydraulics is highly important. Also, In order to explore sedimentation in reservoirs of dams the process of sediment transport in river must be studied. Since using mathematical models based on equations governing on the phenomenon of sediments transport and distribution is one of the suitable methods, in present study sediment transport in a certain part of GavehRoud River was simulated by using Gstars3 mathematical model. By applying the concept of stream tube, this model is able to simulate and predict changes of river bed in both longitudinal and transverse directions. The purpose of this study is choosing a suitable mathematical model for estimating sediment transport rate, such that the simulation with required accuracy in the river is possible. By using this mathematical model, the annual sediments were estimated 620,000 m3. The comparison between the results obtained from simulation and observed rates indicated that Young’s sediment transport function (1979) is the best equation for simulating sediments transport and it has a good correspondence with the conditions of river. At the end, the sensitivity of model to the change of parameters affecting the phenomenon of sediments transport and their impacts on the volume of sediments and longitudinal profile of river were measured. The results indicated that this model has the highest sensitivity toward the changes of sediments transport function.

Unethical and inequitable exploitation of groundwater resources has led to reduce the amount and the quality of these water. In this study Ordinary Kriging (OK) and Indicator Kriging (IK) methods were used as geostatistical approach for preparation of thematic maps of the groundwater quality in Bajestan plain for agricultural purposes. First each of the measured parameters was compared with the acceptable standard limits based on the FAO standard. Three parameters such as Na, SAR and EC were greater than their respective groundwater pollution cutoff value. First, data normality was investigated and Log-transformed was applied to some parameters. The variogram analysis for each parameter was calculated. The evaluation criteria were ME and RMSE with the Cross Validation method. Then OK was used to analyze the spatial variability and quantitative potential maps, whereas IK was used to analyze groundwater quality parameters equal to or greater than the pollution threshold values. The results showed that the parameters of EC, SAR, and Na in most wells were higher than the threshold value and the salinity and sodium adsorption ratio was high in most of the wells. Most of the groundwater in the study area is restricted to EC. More than 59 wells in which water quality is the most important factor in reducing and uncontrolled utilization of them for long time caused salinity and reduce soil permeability.

In the many of region the world special arid and semi-arid region, small earth dam construction is one of the effectively suggestion to solution difficult water deficit and contrast whit big floodwaters in the watery season. In this field RS (Remote Sensing) technique can provide useful information with high spatial and temporal resolution special region without data in place accessible. In this research steps and efficient criteria to for site selection to construction earth dams be suggested. Selection criteria divided defined two classes include quantitative and qualitative and based on the region analyses and be calculation by using a RS data (Image, DEM) and hydrology and geomorphology data. Qualitative criteria used to identify valley and based on visual explanation of satellite image and large scale maps. Quantitative criteria expressed in term of α, β and P. Morphology index (α) is the benefit to cost (B/C), Hydrology index (P) is based on participative watersheds analysis and rainfall pattern in the region. β index is combination of morphology and hydrology aspect. In the Kal Aji watershed of Golestan province, from 56 selected site, in the first step 27 site could passed suggested criteria and finally remaining sites prioritized based on Paired comparisons and Weighting whit Expert Choice software. Finally be assignable base of Weighting calculate software and field survey, 34, 24 and 42 site are contain upper prioritize in the region for construction small earth dam.

Precipitation is a highly variable Meteorological and hydrologicalmeteora. Investigate variation of spatio-temporal of precipitation for water resources planning and management in different parts of the catchment is essential.Autocorrelation of this kind of data however makes their analysis complex, but increases their analysis accuracy. The goal of this study is, modeling Spatio-temporal variationand interpolation of monthly precipitation in Golestan province. So, 30-yr monthly precipitation variations for 30 meteorology and rain gauge stations was studied. To analyse spatio-temporal precipitation,variance hemogenity and space/time stationarity was assessed. By examining different models of the Spatio-temporal variogram, SumMetric model with RMSE of 0.14 mm was selected as the most suitable spatio-temporal variogram model. Then, with this model, by different neighbors, interpolation was done.therefore, 360 monthly precipitation distribution maps was produced. Kriging interpolation with 20 neighborhoods minimum estimation error is revealed.The mean of kriging estimation error is close to zero. Based on the results, pattern of variation in precipitation in this maps with observed maps, haveSimilarity that show the suitability of the modeling approach.Results of this study can be used in determining precipitation in zones with no station in every time (under the influence of spatio-temporal autocorrelation).

A study was conducted to investigate the effect different methods of furrow irrigation and plant densities on quantity and quality of sugar beet yield in Aleshter city in planting year of 2010 in RCBD (split plot) design with four replications. Main plots included three levels, a1= single rows 50cm apart, all furrows irrigated, a2= single rows 50cm apart, alternate furrow irrigated and a3= double rows 75cm apart, all furrows irrigated. Sub plot include three density levels (b1=100,000, b2=80,000 and b3= 66666 plants/ hectare). Each plot has four rows with length of 40 m. Results showed that there is significant difference between main plot and sub plots in root yield, water consumption, sugar content, WUE on the basis of root yield, WUE on the basis of sugar yield, impurities potassium and highest WUE on the basis of sugar yield was obtained in treatment a3b1 for 1.496 kg/m3 with sugar yield with 11.240 ton. ha-1. Therefore the treatment a3b1 was selected as the best treatment.

In recent years application of intelligent methods has been considered in forecasting hydrologic processes. In this research, daily river flow of Ahar Chay, a river located in East-Azerbaijan province at the north-west of Iran, was forecasted using Artificial Neural Networks and Adaptive Neuro Fuzzy Inference System methods in Orang, Bermis and Tazekand stations. For the modeling of the next day flow, daily flow discharge data was used which was collected between 2002 and 2009 years. So that 6-year data set was selected as the training data and the rest as a test data. Determination coefficient (R2 and Root Mean Squared Error (RMSE) statistical criteria were used to evaluate the performance of the obtained results. The results showed that Adaptive Neuro Fuzzy Inference System (ANFIS) method gives a better daily river flow forecasting in Ahar Chay with R2=0.94 and RMSE=0.0318 m3/sec compared to Artificial Neural Networks (ANN) method with R2=0.92 and RMSE=0.0378 m3/sec.

Accurate prediction of the flow in the river is an important element in the management of surface water resources, especially by adopting appropriate measures in the event of flooding, and drought. In fact, ensuring proper and accurate methods for predicting the river flow can be considered as one of the challenges in management approach and water resources engineering. In this paper for Intelligent Modeling, time series of monthly flows of a 26 years period (1985-2011) were used. To achieve the best ANN structure, different structures were compared with those described for the optimization of weight connectivity between different layers of artificial neural networks, genetic algorithms was used. Learning rule which used in current study is Quick Learning, with advection Tan Axon function, objective function, Mean Square Error and type of Training is N times training. The results show that the best performance is for a condition which monthly precipitation input data, monthly flow, monthly temperatures was used for obtaining next month flow. Also, at each stage that one of the flow data or rainfall data entered as one of the inputs data network performance declined. As result, highest sensitivity is for monthly flow and Temperature has little effect on the estimated flow. The results of the correlation coefficient 0.84 Indicate high accuracy of artificial neural networks in the estimation of monthly flow in Shor river basin.

The present study was conducted to assess the extent of flooding potential in Gorgancity with 3652.85 Hectares based on hydraulic, vulnerability and environmental effects criteria’s using multi-criteria decision techniques and geographical information system.For performing the program, firstly the entrance vector layers including urban land use, floodways, channels, digital elevation layers, geology layer and groundwater level layer were imported to GIS environment software and then these layers were converted to raster format after the desired post-processing courses in study area context. In the next step, hierarchical structure was formed regarding to problem goal and then the weighted index of each information layers and their various class were surveyed based on weighted index AHP using Expert Choice software. The final potential flood map was classified based on accumulative curve of pixels frequency millstone in five classes of very low, low, moderate much and very much according to multi-criteria decision-making rules after weighting on each principle layers (vulnerability, hydraulic and environmental effects).So that 1.7% of the study area occurred in risk class 1, 11.6% occurred in class 2, 43.07% occurred in class 3, 24.3% occurred in class 4, and 19.1% occurred in class 5.