JWSS - Journal of Water and Soil Science

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The growing season climatic parameters, especially rainfall, play the main role to predict the yield production. Therefore, the main objective of this research was to find out some possible relations among meteorology parameters and drought indexes with the yield using classical statistical methods. To achieve the objective, ten meteorological parameters and twelve drought indexes were evaluated in terms of normality and their mutual influences. Then the correlation analysis between the barley yield and the climatic parameters and drought indexes was performed. The results of this study showed that among the drought indexes, Nguyen Index, Transeau Index, Rainfall Anomaly Index and Standardized Precipitation Index (SPI24) are more effective for prediction of barely yield. It was also found that the multivariate regression is better than the univariate regression models. Finally, all the obtained regression models were ranked based on statistical indexes(R,RMSE and MBE). This study showed that the multivariate regression model including wind speed, sunshine, temperature summation more than 10, precipitation and Nguyen index is the best model for prediction yield production in Miane. Average wind speed and Nguyen index were recognized to be the most effective parameters for yield production in the model.

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In order to study the effect of planting dates and genistein on nitrogen content and nodulation of three annual Medicago species (Medicago polymorpha cv. Santiago M. rigidula cv. Ragidula, and M. radiata cv. Radiata), an experimental study was conducted during 2004-2005 on the Research Farm of Faculty of Agriculture, Tarbiat Modares University, Tehran (35°43′N and 51°8′E). The factors were arranged as split-split plot in a randomized complete block design with four replications. Planting dates (February 20, March 1 and 11) were randomized to main plots and three annual medics were located in sub-plots, and genistein (0 and 20 μM) was randomized to sub-sub-plot units. Plant nitrogen contnt, nodulation and other traits were significantly different in species and M. polymorpha was better than other species in view of dry nodule weight, nodule number, nodule number in each cluster, nodule cluster number and nodule diameter. Medicago rigidula had more resistance to cold than other varieties, and its forage yield and nitrogen percentage were better than M. polymorpha. Therefore, M. rigidula may be better suited for cold zones. Twenty μmol genistein had remarkable effect on nodulation and nitrogen percentage of annual medics in comparison with control. The result showed that genistein modified negative effect of low temperature environment on nodulation and nitrogen percentage of annual medics. Nodulation and nitrogen percentage increased in all varieties at the first planting date. This finding emphasizes that genistein has a considerable effect on cold resistance establishment in varieties for improving nodulation and increasing plant nitrogen percentage in farm condition.

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Common kilka were chilled during 1, 2, 3, 4 and 5 days to determine the influence of such storage times of fish over the quality of the final canned product. For this propose, common factors for determination of fish quality (moisture, total lipid, free fatty acid, peroxide, thiobarbituric acid and fatty acid profile) were selected and compared with the formation of fluorescence compounds in fish tissue and filling media of canned kilka. In this work common indices showed higher oxidative and hydrolytic rancidity of canned samples compared to raw material but the trend of deterioration with the increase of chilled storage time was not well shown. However, filling media fluorescence compounds was significantly increased with the increase of chilled storage time and the decrease of fish primary quality (P< 0.05). According to the present results, fluorescence detection of interaction compounds can provide a good technique to assess quality differences in the final product as its relates to the quality of the raw material used.

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Climate change has important effects on earth environment and human life. Therefor, investigation and study of climate change is very essential. This study investigated rainfall, temperature, relative humidity and wind variability by analyzing data for annual and monthly climatic factors collected at 13 synoptic stations (industrial cities of Iran) by using Mann-Kendall test. The results of monthly rainfall trends showed that most of synoptic stations have significant positive and negative trends in winter and spring months. About 23% and 1.7% of stations have significant negative and positive trends, respectively, in annual trend of this factor. The results of monthly number of rainy days showed the major number of significant trends occurs in spring. In autumn (September, October and November) like as summer most of the stations have no significant trends. Analyzing the annual number of rainy days trends also showed that 4 stations have significant positive trends and 2 stations negative trends. Trend of greatest daily precipitation is low throughout the year, so there is not any significant trend in winter. Annual investigations confirm the seasonal investigations. The major number of significant trends in monthly mean maximum temperature occurs in summer but there are not any significant trends in winter and March. The trend of mean minimum temperature is approximately high in all of the seasons and the major number of significant trends occurs in summer and autumn and then in spring and ultimately in winter. In annual investigation, most of the stations showed positive trends and only Oroomieh station has negative trends. Trend of mean temperature is high except for winter. Most of the stations showed positive trend, indicating increasing trends in this factor. Annual studies vertify the positive trends and about 63% of stations have significant positive trends.

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Optimum allocation on inputs is more difficult when there are several objectives in agriculture activities. For this, it is necessary using methods that several objectives approximate to ideal point simultaneously. IN addition, no attention to farmer preferences in farm planning causes the troubles for farmers in accepting planning. So in present study it is tried to attention these subjects with using interactive multiple criteria decision making, in farm planning for Fars province. Maximization gross margin, minimization risk and, irrigation water selected for planning objectives. Results indicated that interactive cropping pattern is convenient to present pattern rather than compromise method. In interactive cropping pattern, risk decreased compare to present and compromise cropping pattern that it is indicated tend to risk diminish in region farmers. In addition, the results designated that interactive models have the results better than multi objective and compromise programming because to be attention to farmers preference. With attention to research finding can say that it is possible for reformation of values three objective maximization gross margin, minimization risk and irrigation water rather than present cropping pattern.

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In order to study the effect of air and root-zone temperature on yield, yield components, nodulation and nitrogen fixation of three annual medics, an experiment was conducted in controlled environment (growth chamber) at the Faculty of Agriculture, Tarbiat Modares University in 2006. The experiment was performed as a spilt split plot with the layout of completely randomized design with three replications. Air temperature at three levels including 15/10, 20/15 and 25/20ºC day/night, four levels of root-zone temperatures including 5, 10, 15 and 20ºC and three annual medics (Medicago polymorpha, M. radiata and M. rigidula) were randomized to main plot, sub plot and sub sub plot units, respectively. The results showed that there were significant differences among annual medics for dry matter production, yield components and nitrogen fixation. M. rigidula produced more leaves, stems and root dry matter, leaf and stem to root ratio, leaf number and area and forage yield than other annual medics. Also, three annual medics at 25/20ºC day/night air temperature (the highest one) produced more nodulation dry matter (8.85 mg/pot) and nitrogen fixation (7.7 mg/g dry matter) than other temperatures. Plants at the former temperature produced 8 and 2 times more nodulation and nitrogen fixation than 15/10ºC day/night air temperature (the lowest one), respectively. Low root-zone temperature up to 5ºC had severely negative effect on yield and nitrogen fixation in the three studied annual medics. Interaction among annual medics, air and root-zone temperatures showed that M. rigidula was better than other annual medics for yield, nodulation and nitrogen fixation at 25ºC air temperature and 15ºC root-zone temperature . The result showed that M. rigidula had normal growth and development compared with other annual medics at low root-zone temperatures. Thus, M. rigidula may be a better annual medic for cultivation in cold and moderate regions. Therefore, in the zones where soil temperature is lower than 5ºC during the season, cultivation of annual medics is not successful, but in the zones where soil temperature is greater than 10ºC, annual medics have normal growth and produce average yield due to better nitrogen fixation.

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In diversion flows, a portion of stream flow which enters the intake is diverted from upstream of the intake denoted by a surface and is called dividing stream surface (DSS). The amount of flow and sediment discharge entering the intake as well as design of submerged vanes to control sediment depends on determination of dividing stream width. In this study, the experimental tests were carried out at a 30 degree water intake from a trapezoidal section. Three components of velocity data were obtained for different flow conditions. Then numerical SSIIM2 model was calibrated and verified using tests data. More flow conditions such as the main channel with rectangular section were run using SSIIM2 model to get enough hydraulic data. From analysis of these datas it was found that the dividing stream width in different distances from the bed depends directly upon the diversion flow ratio. It was found that in comparison to the rectangular section, in trapezoidal cross section, the DSS dimensions are modified in such a way that its width is increases at the surface and reduced at the bed for the same flow conditions. Relations for predicting the dividing stream width and diversion flow ratio have been presented in this paper for intake from both rectangular and trapezoidal cross sections.

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This study performs trend analysis of hydroclimatic varibles and their possible effects on the water resources variability. Nonparametric Mann-Kendall and spearman tests were used to investigate trend analysis of mean annual and 24-hr maximum rainfall, flood and low flow parameters of 23 hydrometery and 18 synoptic stations in Sefid-Roud basin. The results showed that mean annual and 24-hr rainfall parameters are decreasing in few stations while most of stations representing negative trend for low flow and flood time series. Applying Sequential Mann-Kendall test revelad that this negative trend is started from 1965 to 1970 for rainfall parameters and from 1970 to1980 for flow (low flow and flood) parameters. Results show that climate change has probability affected variability of climatic variables, while changing of land use may have aslo affeteced extreme flow trends during recent decads. Therefor it can be noted that combination of climate chanege effects and human activities on water recources have affected the negative trend of hydroclimatics variables.

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Due to the important role of climatic parameters such as radiation, temperature, precipitation and evaporation rate in water resources management, this study employed time series modeling to forecast climatic parameters. After normality test of the parameters, nonparametric Mann-Kendall test was used in order to do trend analysis of data at P-value<0.05. Relative humidity and evaporation (with significant trend, -0.348 and -0.42 cm, respectively), as well as air temperature, wind speed, and sunshine were selected for time series modeling. Considering the Autocorrelation function (ACF) and Partial Autocorrelation function (PACF) and trend of data, appropriate models were fitted. The significance of the parameters of the selected models was examined by SE and t statistics, and both stationarity and invertibility conditions of Autoregressive (AR) and Moving average (MA) were also tested. Then, model calibration was carried out using Kolmogorov-Smirnov, Anderson- Darling and Rayan-Joiner. The selected ARIMA models are ARIMA(0,0,11)*(0,0,1), ARIMA(2,0,4)*(1,1,0), ARIMA(4,0,0)*(0,1,1), ARIMA (1,0,1)*(0,1,1), ARIMA (1,0,0)*(0,1,1) for relative humidity, evaporation, air temperature, wind speed and sunshine, respectively. The fitted models were then used to forecast the parameters. Finally, trend analysis of forecasted data was done in order to investigate the climate change. This study emphasizes efficiency of time series modeling in water resources studies in order to forecast climatic parameters.

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Underground water resources considered as a major source of fresh water. Increasing need to water in Iran, causing to immensely utilization and ground water balance disorder, so that state of ground water in many of area is negative.The purpose of this study is to investigate the trend of changes in some of the characteristics of groundwater during the period 1374 to 1387 is Segzi plain. For this purpose, data gathered from the Organization of regional water and homogenous test with Tom test (Run-test) at 95% confidence level was performed on the data. The independence of data evaluated by time series auto correlated functions (ACF), to do this, the amount of auto correlated data computed in different time delays and finally Mann- Kendall test used to evaluate the trend of time series properties in groundwater. The results of Run-Test showed that all of used series in this study were homogenous (P value< 0.05). The result of trend analysis test for region’s wells showed a significant increase in chlorine in underground water resources (P value< 0.05). Calcium has an increasing Trend too about 3 units. Results also showed that all used series in this study are random and Mann- Kendall trend analysis test can be an appropriate for trend evaluating in data series. As regard to irregular utilization of underground water resources by increasing depth of water level, amount of different salts such as chlorine and sodium increased, that causing to surface source degradation like soil and plant cover in agricultural area.

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The geographical location of Isfahan province has led the province to be at risk of drought. One of the ways to mitigate drought is evaluation and monitoring of drought based on indices that can determine its intensity and permanence in each region. In this research, for drought and trend analysis standard precipitation index and Mann-Kendall test were used, respectively. Also, monthly precipitation time series of Isfahan province was applied to forecast drought from 1970 to 2009. For this purpose, Box and Jenkins modeling approach (1976) was used which has three main steps, namely model identification, parameter estimation, goodness of fit test or time independency and normal test of residual. The results showed that most of the stations in Isfahan province were faced with severe drought in the year 2000 and this situation was repeated one more time in 2008. Also, the results brought forth multiplicative models in all the stations. ARIMA (1,0,0) (0,1,1) showed the highest correlations between control and forecast data in Isfahan, Meime and Ardestan stations, and the model ARIMA (0,0,1) (0,1,1) displayed the highest correlation between control and forecasted data in Naein, Freydoonshahr, Khansar and Natanz. These models were selected as the best models through which the amount of precipitation was predicted till 2015. The trend of forecast data across Isfahan province showed that in most months the trend is not significant.

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  Prediction of sediment load transported by rivers is a crucial step in the management of rivers, reservoirs and hydraulic projects. In the present study, in order to predict the suspended sediment of Taleghan river by using artificial neural

network, and recognize the best ANN with the highest accuracy, 500 daily data series of flow discharge on the present day, flow discharge on the past day, flow depth and hydrograph condition (respectively with the average of 13.83 (m³/s), 15.42 (m³/s), 89.83 (cm) and -0.036) as input variables, and 500 daily data series of suspended sediment, as the output of the model were used. The data was related to the period of 1984-2005. 80 different neural networks were developed using different combinations of variables and also changing the number of hidden-layer neurons and threshold functions. The accuracy of the models was then compared by R² and RMSE. Results showed that the neural network with 3-9-1 structure and input parameters of flow discharge on the present day, flow discharge on the past day and flow depth was superior (R²= 0.97 and RMSE= 0.068) compared to the other structures. The average of the observed data of sediment and that predicted by the optimal model (related to test step) were 1122.802 and 1184.924 (tons per day), respectively.

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Due to adhesion properties of fine sediments, chemical physics factors of fluid can cause changes in the behavior of sediments. In this study, the characteristics of sediment deposition with three levels of waste water, different shear stresses and initial sediment concentrations were investigated in the annular flume located at Hydraulic Laboratory of Shahrekord University. Sediments for experiments were taken from the Pirbalut dam reservoir. The velocity and the shear stress profiles were measured using an Acoustic Doppler Velocimeter (ADV).The results showed that the concentration of cohesive sediment was decreased with time and finally it reached an equilibrium concentration of sediment. The equilibrium concentrations to initial concentration (Ceq/C0) in special shear stress, for different initial sediment concentrations and different levels of waste water were almost the same. Equilibrium concentration was dependent on the initial concentration sediment. Threshold and full deposition shear stresses were increased in waste water. Shear stresses of full deposition for 0, 30 and 60 % wastewater were 0.053, 0.075 and 0.070 N/m², respectively. Also, for specified levels of waste water, the values

 were obtained 10, 15 and 17, in which the suspended sediments would remain.

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The objective of the current research was to prioritize effective factors in landslide occurrence and its susceptibility zonation using Shannon’s entropy index in North of Tehran metropolitan. To this end, 528 landslide locations were identified using satellite images such as Geoeye (2011-2012), SPOT-5 (2010), and field surveys, and then landslide inventory map was created for the study area in ArcGIS environment. Data layers such as slope degree, slope aspect, plan curvature, altitude, lithology, land use, distance of road, distance of fault, distance of drainage, drainage density, road density, sediment transport index (STI), stream power index (SPI), topographic wetness index (TWI), normalized difference vegetation index (NDVI), surface area ratio (SAR) and topographic position index (TPI) were created and the mentioned maps were digitized in GIS environment. Prioritization of effective factors by Shannon’s entropy index showed that the layers such as land use, lithology, slope degree, stream power index, and NDVI had the most effect on landslide occurrence. However, factors of topographic position index and plan curvature had the least effect. Also, landslide susceptibility zoning by the mentioned model and its accuracy assessment using relative operating characteristics (ROC) curve and 30 percent of landslide locations showed an accuracy of 82.83% with a standard error of 0.0233 in the study area.

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Since the development of surface water control needs accurate access to flow behavior of sediment rates, the lack of sediment measurement stations, the novelty of most stations and the lack of statistics on the deposit make it difficult to properly evaluate and simulate the flow behavior and their sediments. In a watershed, the morphological characteristics and sediment load of flow affect each other. It is, thus, important to know about the extent of this relationship to manage and control the flow in downstream areas. In the present study, using artificial neural networks and sediment rating regression methods based on the data from 136 events and also morphological parameters, we have attempted to predict the sediment load of Bagh Abbas basin. In the first step, we used flow data to predict the sediment load of both methods, and then basin morphological characteristics such as the compactness factor and form factor were added to the models. The results of this study showed that by using neural networks of Multilayer Perceptron (MLP) type with Levenberg – Marquardt algorithm and the stimulation function of tangent Sigmoid with two hidden layers and four neurons in each layer, we can predict suspended sediment discharge rate with a sufficient accuracy. Accuracy of the results obtained from the ANN method was higher than the accuracy of rating curve method. In the evaluation of NGANN & GANN network methods and SRC & MARS regression methods, correlation coefficients were respectively calculated as 0.94, 0.93, 0.767, 0.766, and root mean square errors (RMSE), 0.45, 0.49, 2.3 and 2.3. Nash coefficient (NS) was calculated respectively as 0.71, 0.58, 0.27 and 0.23. Therefore, the most efficient method among the four models is artificial neural network combined with morphological data (GANN). Furthermore, the findings of the study show that adding geomorphological parameters to sediment rating has little effect on the model performance.

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During the past few decades, the southern part of the Caspian Sea has more frequently experienced extreme climatic events such as drought and flood. Trend analysis of hydro-climatic variables was conducted using non-parametric Mann-Kendall test and regression test for Neka basin in the north of Iran.       Trends of precipitation and stream flow characteristics including maximum flow, mean flow and low flow indices were analyzed at the annual, seasonal and monthly time scales from 1358 to 1391 (34 years). Results showed a general decrease in annual and winter precipitation and decrease in daily maximum precipitation, with an increased trend in daily maximum precipitation of spring season. A decreasing trend was observed in 7-day low flow in summer for all sub-basins. Annual and monthly mean flows specifically in winter in all sub-basins decreased, but annual maximum flow increased from upstream to downstream. Land use changes showed that deforestation and urbanization increased during 34 years in the mid and downstream sub-basins. The analysis showed that low flow indices and mean flows are strictly sensitive to climate change. Overall, from hydrological perspective, these results indicate that the study region is getting dryer and facing more severe drought events. The results of this study can predict future droughts to make better decisions for irrigation planning and management of water resources.

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Water, as a limiting factor, has played a decisive role in shaping and development of Iranian culture and civilization. Water scarcity and a great variety of water users lead to conflicts in rivers' environment. Conflict resolution is conceptualized by the methods and processes involved in peaceful facilitating and ending of the conflict through active communication about their thinking and causes of disagreement as well as persistence in collective negotiations. Currently, the Zayandeh-Rud River basin (ZRR) has been facing severe water scarcity. The aim of this study is to evaluate the methods of water conflict resolution in the ZRR from the viewpoint of farmers and authorities. The statistical population of this study includes all farmers in ZRR and selected staff of Regional Water Authority and Agricultural Organization (Jahad-Keshavarzi) in both Isfahan and Chaharmahal & Bakhtiyari provinces. Data were collected through a sample of 171 farmers and census of authorities through face-to-face interviews based on a comprehensive structured questionnaire. Before the survey, the reliability and validity of the questionnaire was initially evaluated on a pre-test study respectively by using Cronbach’s alpha coefficient and Kaiser-Meyer-Olkin (KMO) criteria. The results showed that the main factors in creating the conflict are drought, increased water use in industry and increased water consumption in other provinces. Furthermore, the most suitable methods of water conflict resolution are the conditions where everybody is able to speak freely, mediation and negotiation. On one hand, in the current situation, farmers prefer violent manners and on the other hand, authorities consider negotiation as the most appropriate solution to the conflict.

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Landslide susceptibility mapping is essential for land use planning and decision-making especially in the mountainous areas. The main objective of present research is to produce landslide hazard zonation at Sarkhoun basin in Karoon basin using two statistical models such as an index of Shannon’s entropy and weight of evidence and to assess the obtained results. At the first stage, landslide locations were identified in the study area by interpretation of aerial photographs, image sattellites, and from field investigations and then landslide inventory map was created for study area. The landslide conditioning factors such as slope degree, slope aspect, altitude, lithology, land use,distance of road, distance of fault, distance of drainage, topographic wetness index (TWI), Convergence Index, and precipitation were extracted from the spatial database and they were digitized in GIS environment. With integrated variables, landslides were calculated in each variable class and ‎weighted in index of entropy and weight of evidence model. In the last, landslide hazard zonation map ‎were obtained with both of models. The results of landslide susceptibility mapps of both statistical models were indicated more than 70 percent the occurred landslides were located in very high and high zones that about half of the basin area (over 45 percent) constitute. Also, the results of both models together were revealed that land use, has the greatest impact on the occurred landslides. Resolution of the zones, based on the seed cell area index (SCAI) and frequency ratio (FR) were evaluated suitable for both statistical models. Finally, the ROC (receiver operating characteristic) curves for landslide susceptibility maps were drawn and the areas under the curve (AUC) were calculated. The verification results of both models were evaluated very well and showed that the index of entropy model (AUC=89%) performed slightly better than weight of evidence model (AUC=82%).

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Hydraulic jump is the most common method of dissipating water’s kinetic energy in downstream of spillways, shoots and valve. In this paper, Support Vector Machine (SVM) method, as a machine learning method, have been used to estimate hydraulic characteristics such as the sequent depth ratio, jump length and energy loss in three different sudden expansions stilling basins, and the rate of influence of input parameters in each jump has been analyzed. In order to evaluate the performance of proposed method, 936 sets of the observed data have been used for training and testing process of three kinds of expanding channel models. Furthermore, a comparison between semi-theoretical approaches and the data obtained from the best SVM models have been carried out. The results confirmed the efficiency of SVM method for estimating the hydraulic jump characteristics and proved that this method performed well in comparison to the semi-theoretical relationships. The obtained results revealed that the superior model for the sequent depth ratio and relative energy dissipation was the model with (Fr₁,h₁/B) parameters and the superior model for the length of hydraulic jump prediction was the model with (Fr₁, h₂/h₁) parameters.

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