نشریه علوم آب و خاک (علوم و فنون کشاورزی و منابع طبیعی)
سال بیستم شماره 2 (پیاپی 76، تابستان 1395)

At the river catchments, different strategies at the whole or different parts of the basin can be applied for water resources management. One of these strategies is optimal water allocation and crop pattern. In this study, an optimization model for water allocation and cropping pattern is presented based on the cooperative game theory. To measure the performance of the developed model, the cultivated area of Ordibehesht Canal in the Doroodzan irrigation network has been studied. First, using a fuzzy model and considering the fuzzy coefficients values in the objective function and constraints, the optimal crop pattern and allocated water has been determined for each crop. Second, benefits of stakeholder’s coalitions have been determined by developing a cooperative game model and based on the structure and properties of the irrigation water distribution network and water rights of each part. Then, the total net benefit has been reallocated to the different stakeholder in a rational and equitable way using Least Core games. The results show that by allocating more water to the sectors with more potential production, more profits are generated and water productivity increases. For example when players cooperate together and form the grand coalition, the net benefit increases from 8.906 billion Tomans to 9.724 billion Tomans that show an increase in the economic productivity of water.

In order to assess the status of the iron (Fe) chlorosis of plane trees in green space of Isfahan city, the chlorosis intensity of 73 trees in different regions was recorded as (1): low (less than 5% of leaves), (2): moderate (less than 50% of leaves), (3): severe (more than 50% of leaves), and (4): very severe (more than 95% of leaves). The whole leaf (with petiole) samples were taken from the top and bottom of each tree, separately, during 2008 and 2009. Then selected chemical properties of the leaves were analyzed. The results showed that in more than 95 and 71% of the young leaves, Fe concentration was less than the critical deficiency level (202 mg/kg). Concentration of Fe in the older leaves of all plane trees even those with slight symptoms of chlorosis was less than the critical level (382 mg/kg). No significant relationship was found between the leaf zinc concentrations and intensity of iron chlorosis. In more than 92 (in the first year) and 87% (in the second year) of the plane trees, Zn concentration of young leaves and in all trees, Zn concentration of old leaves were less than the critical deficiency concentration (23 mg/Kg). The comparison between concentrations of Cu in the leaves with its critical deficiency level showed that more than 90% of young and old leaves accumulated toxic levels of Cu in both sampling years. In regard with the sufficient range of P, about 79% of the trees in the first year and 53% in the second year accumulated excess levels of this nutrient in their young leaves. This condition was slightly modified for the older leaves so that excessive concentration of phosphorus in mature leaves was not observed in the first year and in the second year, only about 29% of the samples had concentrations higher than critical levels.

Heavy metals in dust can directly enter to the human body through ingestion and inhalation. They can pollute the water and soil resources via atmospheric precipitation and accumulate in the plant tissues and then enter human body through water and food. This research aimed to study the heavy metals concentration in dust in Kermanshah province and to identify their sources. 49 samples of dust were collected in the cities of Kermanshah, Songhor, Gilangharb, Ghasre-Shirin, Sahneh, Sarpolzahab, Kangavar, Paveh and Javanrood during the spring 2013. The concentration of Zn, Cu, Ni, Cr, Mn and Fe were determined using an atomic absorption spectrometer following the sample extraction with a mixture of HCL and HNO3 (3:1 ratio). The average concentrations of Zn, Cu, Ni, Cr, Mn and Fe were 182.3, 48.6, 115.3, 73.9, 428.1 and 23161 mg kg-1, respectively. Correlation, cluster and principal component analyses were used to identify probable natural and anthropogenic sources of contaminants, and the enrichment factor was used to identify probable effects of human activity on the concentration of heavy metals. The results indicated that metal concentrations, except for Fe and Mn, were higher in comparison with the world soils. Zn, Cu, Ni and Cr are mainly of anthropogenic origin, while Fe and Mn are mainly of natural origin. Zn and Cu are mainly of traffic sources and partly of industrial sources, and Ni and Cr are mainly derived from industrial sources, combustion processes, combined with traffic sources. The analysis of EF revealed moderate enrichment for Mn and Cr, and significant enrichment for Zn, Cu and Ni. Based on the results of this study, more attention should be paid to identifying and controlling the sources of contaminants such as heavy metals in dust in order to prevent their associated pollution.

The last two decades have seen increasing applications of digital terrain modeling in hydrological, geomorphological, pedagogical, and biological research, aided by rapid advancement of geographic information system (GIS). Hydrologic models are sensitive to change in the input values to the model, so the change of pixel size input data affects the output values of the model and produces different significant results. In this study, using topographic maps 1:25000 and 1:50000 and choosing ten pixel sizes (10, 15, 20, 25, 30, 50, 75, 80, 100, and 200) and software Arc GIS and HEC-HMS, output values of HEC-HMS model have been studied. Results of this study indicate that accuracy of peak discharge calculated by HEC-HMS model in the spatial scale map 1:50000 is more than the peak discharge calculated by HEC-HMS model in the spatial scale map 1:25000. Also accuracy of the calculated peak flows in a smaller pixel sizes (20 to 50) is more than the larger pixel sizes.

Digital soil mapping techniques which incorporate the digital auxiliary environmental data to field observation data using software are more reliable and efficient compared to conventional surveys. Therefore, this study has been conducted to use k- Nearest Neighbors (k-NN) and artificial neural network (ANN) to predict spatial variability of soil salinity in Ardekan district in an area of 700 km2, in Yazd province. In this study, 180 soil samples were collected in a grid sampling manner and then soil chemical and physical properties were measured in laboratory. Environmental auxiliary variables were included topographic attributes, remote sensing data (ETM) and apparent electrical conductivity (ECa). The result of the study showed that the K-mean nearest neighborhood had higher accuracy than ANN models for predicting soil electrical conductivity (ECe). Overall, k-NN models could provide significant relationships between soil salinity data and environmental auxiliary variables. The k-NN model had the root mean square and coefficient of determination of 12.10 and 0.92, respectively, between predicted and observed ECe data. Also, apparent EC, and remotely sensed indices and wetness index were identified as the most important factors for predicating the soil salinity in the studied area.

Nowadays, the increasing population and water demand in various sectors of agriculture, industry, drinking and sanitation has brought about tremendous pressure on groundwater resources. Changes in groundwater quality and salinity of the water resources are currently major threats to development, especially in the dry and too dry lands. The aim of this study is evaluation of the trend of changes in groundwater quality, both temporally and spatially, in Kashan plain over a period of 12 years (2002-2013) using geostatistical methods and classification methods namely Shouler and Wilcox. Thereby, Export Choice has been used and each parameter has been weighted according to its effect on water quality changes. Then, the weighted average of water quality parameters was used for zoning the drinking and agriculture water. The results showed that among the geostatistical methods, circular Kriging based on the correlation coefficient has more acceptable performance. Moreover, the results of spatial and temporal changes in water quality based on Shouler and Wilcox indicate a decrease of drink and agriculture water quality in the study area. Besides, 1.75 km2 of high quality drinkable water was annually decreased between 2002 and 2013 and replaced with moderate or poor quality water. Also, the same but more remarkable decline happened in agriculture water so that 11.06 km2 of high quality agriculture water annually diminished from 2002 to 2009 and plunged zero by 2009.

Precipitation is an important element of the hydrologic cycle and lack of this data is one of the most serious problems facing research on hydrological and climatic analysis. On the other hand, using satellite images has been proposed by many researchers as one of practical strategies to estimate precipitation. The present paper aims to evaluate the accuracy of satellite precipitation data, provided by PERSIANN and TRMM-3B42 V7 in Gorganrood basin, Iran. To achieve this aim, two sets of daily precipitation ground-based data, 2003 to 2004 and 2006 to 2007, from six stations of Gorganrood basin, named; “Tamer”, “Ramian”, “Bahalkeh-ye Dashli”, “Gorgan Dam”, “Ghaffar Haji” and “Fazel Abad” have been used in this paper. The evaluation indices have been calculated and analyzed in different time scales, including daily, monthly and seasonal. The results indicated that the two above mentioned satellite models are not accurate in daily scale. However, they showed reasonable accuracy in monthly and seasonal scales. The highest correlations between satellites and recorded data in daily and monthly scales, for TRMM-3B42 V7 in “Gorgan Dam” and “Bahlke Dashlei” stations, are 0.397 and 0.404, respectively. The comparison of measured and satellite data of winter showed better agreement for PERSIANN model. However, TRMM-3B42 V7 shows better correlation in other seasons. The results also indicated that while TRMM-3B42 data displays higher correlation with measured data, PERSIANN provids better results in predicting the number of rainy days.

To procure the status of groundwater level fluctuations in arid and semi-arid areas, it is necessary to obtain accurate forecast of fluctuations data. Time series as a linear model have been utilized to generate synthetic data and predict future groundwater level. Minitab17 software and monthly depth of groundwater level data of 20 years (1991-2011) for 25 piezometric wells of plain were used. Time series models of each well were selected and 5 years temporal forecasting was accomplished. The predicted depth of groundwater level data was converted to Groundwater level data using ARCGIS10 and GS.1.1 software. Ordinary kriging with a spherical variogram was selected for interpolation of groundwater level. Five years spatial forecasting was done and spatial forecasting and groundwater level drop forecasting maps were prepared. Forecasting results of groundwater level show that over the next 5 years, the area covered by two intervals of groundwater level, 1100-1140 m and 1140-1180 m, will increase and the area covered by three ranges of 1180 -1220 m, 1220-1260 m, and 1260-1300 m, will decline. Also, according to the 5-year groundwater level drop forecasting map of the plain, the highest level of groundwater level drop, more than 16 meters for Qasemabad bozorg areas, located in North East and central of the plain, and the lowest level of the groundwater level drop, about 0.5 m for Mohammad Abad Afkham Aldoleh Lands, located in outlet area of the plain, have been predicted.

In the ICSSDOM simulation-optimization model, simulated annealing algorithm is combined with a hydrodynamic simulation model named ICSS. In this model the ability of weighting of indicators is also considered. In this study, using this model the performance of the S-L-R5 canal in the DEZ irrigation network was evaluated in a period of 10 days. With presenting a proposed method for weighting the indicators and its various options, using parametric sensitivity analysis, optimal adjustment of intake and check structures was obtained. It was found if the coefficient of each index is selected as a direct ratio of the ideal improvement potential of the indicator, the percentage of the improvement is more than the other investigated options. In addition, due to the interaction of the indicators in the multi-objective functions, the consistency of the weighting method with the nature of the optimization problem in this study has been shown. Statistically, the adequacy of the 10-day period of study was confirmed. The model validation with mathematical asymptote method shows 6% error which indicates the model is valid. For example, on the first day, based on the option three (The optimal option), the optimal gate opening for 5 intakes and one check control was between 3.9 to 14.7 Cm. In this condition optimal delivery was between 46 to 178 liters per second.

Shortage of rainfall and also relatively high intensity precipitations in short-term are characteristics of arid regions of the world, such as central of Iran. Studies have indicated that massive flooding causes great loss of life and properties every year. Also, Water scarcity in arid and semiarid regions of the world will cause fragile living conditions in these areas. Therefore, it is needed to reduce runoff rates using actions such as dam construction or artificial recharge techniques. In this study, seven factors were applied such as the slope, surface permeability, transmissibility in alluvium, alluvial quality, land use, runoff volume and thickness of the unsaturated layer to determine suitable areas and site selection for flood spreading and artificial recharge in south of Kashan plain. After preparing the digital layers, criteria weights were determined using Fuzzy AHP. The weighted maps were acquired and merged together. Results indicated that land use criterion with the greatest weight (0.22) was determined as the first priority in the site selection for flood speading. The parameters of runoff volume, permeability, slope, depth of the unsaturated layer, alluvial quality, and transfer coefficient were accounted as the second to seventh priorities.

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 river's 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.

In this study, two different approaches of infiltration parameters estimation in traditional, variable and fixed alternate furrow irrigation, with and without cutback inflow, were performed and compared. Four usual methods including two-point (Elliott and Walker), Valiantzas one-point, Mailapalli one-point and Rodriguez and Martos optimization methods, as approaches based on advance data, and multilevel optimization method as an approach based on the advance, storage and recession data, were considered. Surface irrigation model: WinSRFR was used to simulate irrigation phases and infiltration value in each method. 13 furrow irrigation field experiments, from two case studies: Karaj and Urmia, were used to perform different methods. Based on the results, the multilevel optimization method predicted the advance and recession phases and runoff-infiltration with high accuracy for traditional, variable and fixed alternate furrow irrigation. The multilevel optimization method for traditional furrow irrigation, showed more accuracy than variable and fixed alternate furrow irrigation in advance and recession phases and the average root mean square error (RMSE) for predicting advance phase for the three furrow irrigation methods was 1.37, 1.8, and 1.57 minutes and for the recession phase was 3.76, 5.0, and 3.03 minutes, respectively. Also the multilevel optimization method for cutback options indicated high performance to advance and recession prediction and the average RMSE of advance and recession prediction were obtained 3.57 and 2.13 minutes for cutback option and 3.8 and 1.3 minutes for no cutback option, respectively. The multilevel optimization method indicated high performance in storage phase, too. The average of relative error (RE) of runoff estimation for traditional, variable and fixed alternate furrow irrigation was calculated 0.5, 0.4 and 0.4 percent, respectively. The runoff average RE of multilevel optimization method with cutback and no cutback option were obtained 1.85 and 0.85 percent, respectively; that showed high performance of this method for no cutback option in comparison with the cutback option. Therefore, the use of data of all irrigation phases to estimate infiltration parameters shows better performance in the prediction of irrigation and water balance components. (run-off and infiltration).

This study is aimed to investigate the spatial variation of soil macronutrients such as phosphorus, potassium and organic matter using different methods of Geostatistics and Geostatistical method combined with Fuzzy logic to estimate the values of this element to provide a spatial distribution map for the proper distribution of fertilizer in the plain of Uremia. Spatial variations in soil nutrients are natural but knowing these changes for careful planning and management particularly in the agricultural lands is simply inevitable. This information is necessary to increase the profitability and sustainable agricultural management. Therefore, to estimate the changes in the elements of places not sampled, the Kriging, Fuzzy Kriging, Cokriging and Inverse Distance Weighting methods have been used in GS . In this study, Matlab 9.1 software was used to fuzzification of the data and GIS was used for the final mapping. The parameters MAE, MBE and RMSE were used to compare these methods. The results showed that the combined method of Fuzzy Geostatistic with the mean absolute error values for the elements phosphorus, potassium and organic matter i.e. 0.17, 0.18 and 0.18, respectively, is recognized as the preferred method based on which zoning maps have been prepared for P, K and OC in GIS.

In this research, a comprehensive simulation model for water cycle and the nitrogen dynamics modeling including all the important processes involved in nitrogen transformations such as fertilizer dissolution, nitrification, denitrification, ammonium volatilization, mineralization, immobilization as well as all the important nitrogen transportation processes including nitrogen uptake by the plant, soil particles adsorption, upward flux, surface runoff losses and drain losses, was used for fertilizer management modeling in a sugarcane farmland in Imam Khomeini Agro-Industrial Company using a system dynamics approach. For evaluating the model the data collected from Imam Agro-Industrial Company equipped with a tile drainage system with shallow ground water and located in Khuzestan province, Iran, were used. The statistical analysis of the observed and simulated data showed that the RMSE for determining the accuracy of simulation of the nitrate and ammonium concentration in drainage water is 1.73 mg/L and 0.48 mg/L, respectively. The results indicated that there is good agreement between the observed and the simulated data. Nine scenarios of fertilization at different levels of urea fertilizer were modeled including one scenario of 400 kg/ha, two spilit scenarios of 350 kg/ha, two spilit scenarios of 325 kg/ha, two spilit scenarios of 300 kg/ha, one scenario of 280 kg/ha and one scenario of 210 kg/ha. Results of the modeling showed that the scenario of 210 kg/ha has the highest nitrogen use efficiency (52.3%) and the lowest nitrogen losses consisted of denitrification, ammonium volatilization and drainage losses (17.82, 7.16 and 92.59 kg/ha, respectively). The results revealed that increasing the consumption of urea fertilizer greater than 210 kg/ha increased the overall nitrogen losses and reduced the nitrogen use efficiency. Meanwhile, this model can be used for managing the fertilizer and controlling the nitrate and ammonium concentrations in the drainage water to prevent the environmental pollution. Also, the system dynamics approach was found as an effective technique for simulating the complex water-soil-plant-drainage system.

In this study the effect of temperature, evaporation or evapotranspiration, precipitation, hillside direction and altitudinal classes, texture and acidity of soil on organic carbon content in the depths of 15 and 45 cm were evaluated. Paired t-test results showed that there is a significant difference between measured parameters in two soil depths. After preparing required data and processing them, outlier's data were removed. Then, base maps for each of the information layers were prepared by Arc GIS9.3 software and all relatd information fit together by overlapping them. Pearson correlation between environmental factors and soil organic carbon values were calculated and it was found that in the depth of 15 cm, the correlation between soil organic carbon values and two environmental factors including temperature and altitude were significant at the level 0.01. As well the results of statistical analysis by using principal component analysis (PCA) method showed that the factors temperature, evaporation (1%), and silt and clay (5%) have had a significant effect on the amount of soil organic carbon. The first, second, and third axes with eigenvalues of 98/4, 78/3 and 92/1, respectively, explained the values 0.33, 0.25, and 0.13 % of correlation between organic carbon and environmental data.