مجله اکو هیدرولوژی
سال چهارم شماره 1 (بهار 1396)

Precipitation is considered as one of the most important factures in water cycle. Prediction of monthly Precipitation is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins.In this study we studied and evaluated gene expression programming to predict the Precipitation of the Kakareza river (in lorestan), and the results were compared with results of anfis and artificial neural network model. For this purpose, mean temperature, relative humidity, evaporation, wind speed rate at monthly scale during the period (2005-2015) as input and output parameters were selected as Precipitation . The criteria of correlation coefficient, root mean square error and of mean absolute error were used to evaluate and performance compare of models. The results showed that gene expression programming model has the highest correlation coefficient (0.978), the lowest root mean square error (0.026 mm) and the lowest mean absolute error (0.017mm) became a priority in the validation phase. The results showed that the gene expression programming model to estimate high minimum and maximum values of Precipitation .

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Since many time series are not normal, it is required to normalize data by transformation functions prior to any analysis and modeling. In this study, the next month rainfall of Abadeh County station was predicted using the average monthly rainfall, minimum and maximum temperatures and minimum and maximum humidity as inputs of MLP network, both normally and raw, at period 1976 to 2013. After scrutiny the existence or nonexistence of missing and outlier data, meteorological data were normalized using three normalization minimum-maximum, rank normalization and z- score. After obtaining the best network structure using try and error for each method, the minimum-maximum method with a three-layer network structure and 13 number of hidden layers of neurons chose as the best method with R=0.92 and MSE=0.13 compared to other methods. Also comparing the performance of the network in using raw and Pre-Processed data showed that Pre-Processing the data improved greatly network performance. The results of the sensitivity analysis showed the maximum sensitivity of model to remove maximum humidity parameter, and the second the maximum temperature had the greatest impact on precipitation forecast. Also comparing the performance of the network with the different numbers of inputs indicated that network with two inputs including minimum temperature and minimum humidity had good results (MSE = 0.13) compare with five inputs.

Today, many of the Subterranean and the threat of environmental pollution have been exposed Tehran's why environmental studies and water quality monitoring Subterranean as urban planning and management is an important issue. The purpose is of this research, monitoring water quality across the East Tehran Subterranean of environmental indicators. The research method to collect data primarily based on documentary research and field visits, sampling and testing done by other research groups are based. The results of this study indicate that, Subterranean Tehran East area in terms of water quality were comparable but somewhat more detailed look at some of the variables are qualitative differences. Important variables such as chemical water quality) cations, nitrate, sulfate, heavy metals (NH3 EC, TDS, PH, DO, shows that water quality in the Subterranean, in most cases than the WHO standards are desirable. And in some of the Dehkheyr Shahr Ray has no biological contamination are higher than allowed. The indices for agricultural purposes as well as test results indicate the desirability of its aqueducts Tehran East zone. Generally, the higher the Northeast to the South East of Tehran move forward due to the reduction of pollution of underground water and dissolve of water depth increases.

During recent years there has been increasing consciousness of, and concern about, groundwater water pollution and monitoring in Iran. In this context, a comprehensive review of the trace elements and heavy metals in groundwater of Oshtorinan Plain in northern part of Boroujerd has carried out to investigate the effects of weathering minerals, agricultural and industrial activities. Groundwater samples from ten wells, five qanats and a spring in both wet and dry seasons were collected and analyzed using a mass spectrometer (ICP_MS). Then, the results were compared with World Health Organization (WHO) standards. The measurement results show that from 63 elements measured, only the concentrations of Fe, Mg, Pb, Sr, V(0.4, 36.3, 62.9, 0.89 and 195.5 ppm, respectively) were above the permitted level. The amount of Pb, B and iron in groundwater samples in the study area indicates that concentrations of these elements from East and West are increasing toward the center. Also,increasing concentration of Sr. in the groundwater samples is mainly caused by processes such as the mineral weathering that occurs to igneous rocks, locating in the eastern parts of the plain. Engines wells in the area, abandoned wells, the steel alloy (in the northern entrance) pollution and mining activities are likely sources of potential pollution of heavy metals in groundwater and environmental threat to the region. Using principal component analysis, three main factors determine the quality of hydro chemical include the impact of major ions, trace elements and heavy metals, which collectively account for nearly 68% of the variance factors.

Kahman is the most beneficial river in Alashtar city for agriculture and aquiculture. As hydrology processes have random nature, statistics and probability are base of analysis of these processes and time series are used for this purpose. The first step in time series analysis includes parameters variation through time. Second step is to stationary data, third is normalization and forth is model parameters recognizing. Finally, for model accuracy evaluation in prediction, the root-mean square standardized error and Akaike information criteria are used. In this research, time variations trend of three parameters, PH, HCO3- and Na that are effective parameters on drinking and agriculture water, were studied at Darreh-tang station of Kahman river from 1366 to 1392 and then Based on the time-series graphs, as well as autocorrelation and partial autocorrelation plot, Multiplicative seasonal ARIMA model select and in XLSTAT and MINITAB software’s was used. For HCO3 and PH, ARIMA4(1¡1¡1)*(1¡1¡1) was recognized for prediction optimum model but for NA any of ARIMA models weren’t recognized suitable. HCO3 always have an ascending trend. On the base of time series diagram, optimum variations limit of PH is from 6.5 to 8.5. Because the formation in Kahman river watershed is calcareous and because of nonexistence of salty formations in studied region, Na has a constant trend and isn’t ascending.

Increasing development of engineering projects construction such as city subway needs appropriate investigation, management and control of groundwater. Therefore, precise estimation of hydrogeological parameters such as hydraulic conductivity is the most important factor in studies and modeling of groundwater and geotechnical issues. In recent decades, various laboratory and field methods exist for estimating this parameter, but estimation of hydraulic conductivity using these methods due to the heterogeneity and anisotropy hydrogeological environments is costly, time-consuming and inherent uncertain. In this study, three fuzzy inference methods, Sugeno (SFIS), Mamdani fuzzy inference model (MFIS) and Larsen Fuzzy Inference System (LFIS) that is suitable for handling the uncertain data, was adopted to estimate the hydraulic conductivity in Tabriz city subway area. After, the hybrid SOM-FL model was presented to improve efficiency of individual model and solve heterogeneity problem of the Tabriz city aquifer. Based the evaluation criterions R2 and RMSE the results of individual models are acceptable but the proposed hybrid model improved, R2 in train and test stage, 18% and 15.4 percent, respectively.

Increasing greenhouse gases in recent decades and increasing its resulting temperature has causes the imbalance of the Earth’s climate system and widespread climate changes in most regions of Earth planet. Development strategic policy in this area has been forced with a big challenge because of the need for water in the central region on the one hand and water resource constraints on the other hand. In this study, first, WetSpa rainfall-runoff model was calibrated for Bazoft-Samsami watershed as one of the important sub-basins of Karun basin. Then, values of temperature and precipitation for future period were downscaled based on climate change scenarios with atmospheric general circulation model outputs (HadCM3) for three scenarios of A1B, A2 and B2 using LARS-WG model. Then, to simulate the basin runoff, data were introduced to WetSpa model. The results verified the performance of LARS-WG model in estimating rain and temperature. Also, the results showed that runoff in statistical periods of 2011-2040 and 2071-2100 compared with observation period in all three scenarios has increased %8.86 and %4.83, respectively, and has decreased in 2041-2070 to the amount of %7.25. This subject indicates the impact of climate change on runoff in mid-term future period in studied watershed. So, considering the obtained results, the policy of programming in order to adapt to climate change is necessary in Bazoft-samsami watershed.

Surface. The development of gullies causes the loss of a great amount of soil and could be considered as one of the principal causes of geo-environmental degradation. In this research FAZI model introduced for gully erosion zonation in arid and semiarid area considered to calibration and validation in Kahkiloeh and Boyerahmad Province. Therefore, the ABGANDI watershed were selected by consideration of gully erosion distribution in Kahkiloeh and Boyerahmad Province. In this region the maps of lithology, slope, soil, rainfall, land cover and land use were extracted and thus selected the working units. In each of the units, gullies morphometric, soil penetration condition and soil conservation percent characteristics with survey investigated. Also, determinates the quantity value of six maps model input layer include (lithology, percent of slop, soil type, annual average precipitation, land use and percent of soil conservation) was determined. Finally, gully erosion mapping using overlay index, fuzzy algebraic sum, fuzzy algebra product and fuzzy gamma in GIS performed. Obtained result of different regions indicated that the fuzzy gamma model 0.8 is the proper method to gully erosion zoning in studied watershed.

The aim of this research is to analyze the performance of 8 drought’s index in Isfahan, Kerman and Yazd province and choose the best index. For this purpose, used monthly and yearly rainfall data in the period of 30 years (1985-2014) and also used 8 drought indexes in 20 meteorological stations of central Iran which the accuracy of each index in determining drought is examined. Also zoning in ARC GIS 9.3 has done for driest year in the time period. And it has performed according to the best selected index. For choosing the best index in annual and monthly scale has used the efficient measure of minimum precipitation occurrence year with severe droughts in region’s stations. The results showed that in the monthly scale only 6 and 12 months of SPI index in order to analyze the drought even in low rainfall months which confront with zero data contains. In this temporal scale, static indexes such as RAI and DI in all the stations showed the minimum precipitation year according to severe droughts and named as the best index. Also the weakest index belonged to NICHE that had not the ability of determining the drought intensity in all the study’s region. In comparison the performance of RAI and SPI determined which RAI index showed the severe drought in all the study’s region but SPI index could not show the severe drought category in the period of 30 year in the region of central Iran in some stations.

The soil bioengineering is an applied science that it is the composition of structural, biological and environment concepts for soil erosion, Sediment and flood control. Biotechnical engineering techniques rely on biological knowledge to build geotechnical and hydraulic structures and to secure unstable slopes and banks. The largest enhancement in development of new soil bioengineering methods happened in European and 1900s. The recorded document showed that the first documented experiences, including reports and publications, were produced in the areas of the Alps, Austria, Germany, and Switzerland. Soil bioengineering is the living plant materials that this use in engineering structures and apply sites treatment with problems including surface soil stability and soil erosion. In this study, some methods of soil bioengineering presented in water management such as Live Pole Drains, Live Silt Fences, Brush Layering, Live Fascine, Live Stake and etc. and Steep slope stabilization such as Wattle Fences, Modified Brush Layers, Brush Layers in a Cut ,Live Cribwall. Techniques such as wattle fences and modified brush layers can use for unstable slope or reducing slope angle and also help in vegetation establishment.

Shift changes and heterogeneity analyses of hydro-climatic variables is very important in water resources planning and management. In order to shift changes and heterogeneity analyses of Tmin and Tmax, precipitation and discharge, 2, 7 and 7 stations was used over the 40 years (1972-2011), respectively. The results of annual Tmin and Tmax series showed that both of two stations had the significant increasing trend in 1 significance level. The results of precipitation showed no specific spatio-temporal trend in four last decades and identifying the exact pattern of changes was difficult in compared with other variables. Among 7 hydrometric stations, 5 stations showed the significant increasing trend. However, discharge had the most decreasing trend among the studding variables. Shift changes analyses of hydro-climatic variables by four heterogeneity tests, generally indicated the 50.5 percent of Tmax series, 62.5 percent of Tmin series, 26.25 percent of precipitation series and 45 percent of discharge series had heterogeneity in 95% confidence level in the studding stations. Studding shift changes in Tmin and Tmax series showed that all of the changes were positive/ or increasing. In compare with temperature series, shift changes of precipitation as same as its trend have no specific trend. In general, temporally all of the changes occurred in 1990s.

Different approaches have been presented for estimating river environmental flow which hydrological approach has a lot addressed because of its need to access to limited data and moderately rapid assessment. This approach incorporates various methods therefore comparison between results of different methods is essential. The objective of this study is to investigate and compare the consequences of Tennant, flow duration curve shifting (FDC shifting), desktop reserve model and Tessman methods for environmental flow assessment of Zohreh river (Dehmolla hydrometry station) located in southwestern Iran. According to the long-term flow data the annual mean flow is 80.18 cms and August-October and February-April with 22.5 and 156.2 cms are low and high flow periods of the year. Investigation of consequences of different methods demonstrate FDC shifting is most admissible method for environmental flow assessment in this study because of its reasonable exhibited environmental flows in different months in comparison with monthly and annual mean flow, good compatibility of within-year patterns of monthly environmental and river flow, and lack of allocation of all river flow to environmental flow in all months of the year. Considering the results of the FDC shifting method the monthly environmental flow are estimated between 6.8 to 53.2 cms and its mean annual is 27.79 cms. The mean environmental flow for low and high flow periods are 7.7 and 49.3 cms respectively too.

Investigation of inter-storm variability of runoff and soil loss characteristics helps experts and decision makes better understanding of hydrological response. However, this important has been less considered in the world, especially developing countries. The present study was therefore planned to evaluate the effect of different rainfall intensities and slopes on inter-storm variability of Coefficient of Variation (CV) of runoff volume and soil loss in three replicates. To achieve the objectives, a set of laboratorial experiments were conducted using rainfall simulator and 6×1 m erosion plot with a depth of 0.5 m and a slopes of 5, 15 and 25 %. Rainfall intensities of 30, 60, and 90 mmh-1 were applied to a soil sampled from Kojour rangeland watershed, northern Iran. The results described an increasing trend in runoff volume and soil loss inter-storm CV with increase in rainfall intensity at slopes of 5 and 15%. While, no trend was distinguished for inter-storm CV for runoff volume and soil loss with increase in slopes and different rainfall intensities except soil loss inter-storm CV in rainfall intensity of 90 mmh-1 at different slopes. The lowest and the highest coefficient of variation were also respectively found in means for runoff volume (i.e., 4.80 and 17.10 %) and soil loss (i.e., 17.28 and 87.96 %). The results of the study emphasized the necessity of considering the inter-storm variability of runoff and soil loss components in different replicates with regard to appropriate rainfall intensity and slope for analyzing the watershed system processes.

Large-scale climatic signals including ocean-atmosphere interactions, are the main factors influencing the earth’s climatic oscillations and are the most important indices in predicting of climate variables. In this research, precipitation in the next month was predicted by applying artificial neural network (ANN), neuro-fuzzy network (NFN), and multiple linear regression (MLR) in Semnan synoptic station. For this purpose, monthly series of precipitation of Semnan synoptic station and signals of large-scale climate signals were used during a period of 45 years (1966–2010). From 540 monthly time series, the first 80% was used for training and the other 20% for testing. Performance of the models was compared by using correlation coefficient (R), mean absolute error (MAE), and root mean square error (RMSE) criteria. Results of the validation step showed that the obtained correlation coefficients (0.829, 0.793 and 0.767) are related to ANN, ANFIS and MLR models. Based on the results of this study, the next month’s precipitation of Semnan synoptic station could be predicted by ANN, NFN and MLR models, respectively.

Groundwater is one of the most important resources of water supply for various uses in many regions all over the globe including Iran. Different contaminants severely affect these resources and might render groundwater unsuitable for consumption. Groundwater contamination by nitrate is a well known globally growing problem due to the population growth and increase of demand for food supplies. This study was conducted to evaluate the nitrate concentration in water resources of Ardabil aquifer using Geographical Information System. Water samples were collected from 63 wells in Ardabil aquifer during the September 2014 and analyzed for nitrate concentration. The average nitrate concentration from the wells was 39.18 mgl-1. Based on the variography analysis, nitrate concentration showed a good spatial structure which may lead to the high performance of the ordinary kriging (R2=0.508) in predicting the groundwater nitrate spatial pattern. Nitrate concentration was very high at the western parts of the aquifer where the Ardabil city and its agricultural lands is located. These results clearly indicates that the anthropogenic sources from human activities and agricultural development are the main reasons of the nitrate pollution in this part of the aquifer.

In recent years, the water quality of Karun River, IRAN, has been affected by different pollutant loads such as agricultural drainages, municipal and industrial wastewaters.Water Quality Index (WQI) and GIS as an efficient tool can be used to provide necessary support for decisions of the management actions in this river and also capability of time series models can be beneficial for forecasting future changes. Therefore this paper aims to evaluate the water quality of Karun River, according to WQI and using GIS and modelling water quality time series. In this research, monthly data including pH, temperature, DO, BOD, TDS, PO43-, NO3-, turbidity and fecal coliform were analyzed during years 2008 to 2013. All the calculated indices were classified in medium class that means the river water can be used only by applying advanced treatment. Spatio-temporal distribution of WQI values and non-significance of its fluctuations indicate balance between the pollutants input and self-purification capacity. Modeling revealed adequate coefficients of determination of selected autoregressive models that vary between 0.69 and 0.85. Also man-made conditions realized as the dominant factor affecting river water quality. According to the results, Karun river water quality has increased slightly comparing to the past and after Dez river junction, relatively high decrease in WQI occurred that can indicate Dez River’s lower quality because of entering pollutant loads in Dezful station downstream and calls for control measures on the river.

The objective of this study is evaluation of topographic wetness index (TWI) using attraction model in northern of Fars province. The first attraction model was used to enhance the spatial resolution of digital elevation model (DEM). In this research to estimate of value of sub-pixels neighboring pixels, touching and quadrant neighboring models were used. After manufacturing output images for sub pixels in the 2, 3 and 4 scales with different neighborhoods, the best scale with most appropriate type of neighborhood was determined using ground control points then the values of RMSE was calculated for them. The total number of ground control points extracted from the mapping maintenance was 2118 points. The results showed that between scales with different neighborhoods, 3 scale and quadrant neighboring model have the most accuracy by the lowest value of RMSE for DEM 90 meter. Then using produced DEM from 3 scale and quadrant neighboring model, topographic wetness index for the study area was determined. The results showed that topographic wetness index (TWI) in the study area is variable between -4.45 to 6.06. Central zones of the study area have the highest values ​​of wetness. Compare of wetness index produced from attraction model (with more spatial resolution) with DEM 90 meter (with lower spatial resolution) showed that with using attraction model, more details of the amount of moisture in the study area, is visible.

One of the serious problems of Iran’s watersheds is soil erosion and can be considered as one of the main obstacles to achieve Sustainable Agricultural Development and Natural Resources. In most countries of the world, because of absence of accurate data for the sediment erosion, deposition utilizing models to estimate erosion is inevitable. In order to apply effective management in natural resources region, especially soil resources, it’s required to ranking the sub-basin region to be prioritized for protective operations. In this study, Ozroud’s sub-basins, situation has been studied by FSM method and morphometric analysis. The morphometric analysis of linear parameters include; drainage density parameters, bifurcation ratio, texture ratio, length and frequency of current flow as well as the formal parameters including slenderness ratio, compression ratio, the roundness, forming factor and coefficient basin forms were used, also in the FSM to determine the amount of annual precipitation scoring, seven parameters (topography, gully, vegetation, geology, climate and soil conservation) were used. For this purpose, Digital elevation model, OLI sensor images of Landsat 8, geological map, meteorological data and field visits were used. Results of analysis showed that the morphometric analysis, sub-Basins area of the drainage network and also the FSM method in terms of annual sediment sub-N has produced 6593.5tons, the most critical sub-basin, but with integrating results of 2 methods in 5 levels, it was found that first priority among sub-basin was H. Remarkably, these results can be helpful with development goals of agriculture and natural resources managers.

In this paper, Geographical Information System (GIS) is used as a support system for decision making in order to provide the map of high potential areas for the construction of greenhouses benefited from geothermal energy. The goal is to perform a geothermal energy resource assessment in Eastern Azerbaijan province as a base for further studies to achieve sustainable development objectives in the agricultural sector of the province.
A thorough study is conducted to determine the indices used for geothermal resource assessment. Then, using these indices and the data of the province, the conceptual model for geothermal resource assessment is provided. To do this, information layers are categorized in three geology, geochemistry and geophysics sections. Then, by means of programming in GIS, these layers are intersected to find the final map of areas with high potential of geothermal energy. The results showed that about 24% of the total area of the province are high potential areas. These areas can be used for the construction of greenhouses where geothermal energy can be utilized for irrigation and heating purposes.

Hydropower power generation is one of the most important sources of renewable energies. Small hydropower plants are becoming the most popular option of hydropower plants, which can be applied in small and remote places, and are able to produce cheap, clean and reliable electricity. In Iran and most developing countries, electricity transmission to remote regions for reasons such as high transmission costs and lack of proper supply of electricity, is faced with serious problems. Therefore, small hydropower plants can be considered as a suitable option to supply the power needed especially in rural and remote areas. This study aimed to study the feasibility and potential for generating electricity from small hydropower plants in the province of Kurdistan. Therefore, the catchment areas have been investigated and based on the average of tempreture, rain fall, and the catchment areas the amount of discharge is estimed. Then an appropriate locations to install hydropower plants are determined with respect to the intended technical, economic and environmental restrictions. Finally, the capacity of hydropowers is calculated. The results indicate the possibility to construct 3455 small hydropower plants in the province of Kurdistan, and finally, in the case of construction of small hydropower plants, in all the proposed areas it will be possible to produce 492 MW of electricity from hydropower in Kurdistan.

Today, water resources stored in reservoirs is one of the basic sources of drinking-water. The elements in the sediments of reservoirs are the most important factors affecting water quality. Unlike the primary plan, due to water shortage problems, nowadays, almost all the stored water in the Kardeh reservoir is allocated to drinking water. From the other side in the catchment area of this dam a lot of changes in terms of land use, the development of agricultural lands and the construction of the garden-Villa Has taken place. Therefore, Surveying the status of the reservoir sediment contamination by heavy metals is essential. In this research, first some cores of sediments from the reservoir was taken and the amounts of 9 heavy metals elements in the sediments were determined using ICP-OES. Reservoir sediment contaminations by heavy metals were studied, by using qualitative criteria of sediments. Then determine the aggregation of sediments by Nano particle size analiyzer machine, the relationship between the particle size with the amount and the type of heavy elements present in the sediments were studied. Based on the standards criteria, almost all the elements are at the acceptable ranges. It seems that the origin of these elements has been the local pollutants and not from sediments resulting from the transfer of the geological structure of the upstream areas. On the other hand trend of changes in particle size in the reservoir reflects the impact of flushing.