IRANIAN JOURNAL OF ECOHYDROLOGY
Year:2018 | Volume:5 | Issue:1 |Papers Count:21

Nowadays, groundwater depletion and the lack of replace water sources, one of the biggest problems is Nowadays, groundwater depletion and lack of enough water to replace it is one of the biggest problems considered all over the world. To solve this crisis as one of the major solutions, we can consider the artificial recharge of aquifers. Fatoieh plain of Hormozgan province is located in the central city district Bastak. Therefore groundwater is the major and only reliable source of water and due to severe drawdown; it is needed for artificial recharge of ground water aquifer of the region. Therefore, in order to identify areas suitable for artificial recharge some of the indicators consisting of nine hydrogeology and geographic parameters were chosen and presented in the form of maps in GIS environment. Meanwhile, we used fuzzy TOPSIS method and hierarchical fuzzy TOPSIS network analysis combined with GIS to integrate of different information layers and to obtain the most suitable sites for the implementation of artificial recharge of the Fatoieh plain. The results showed good potential for artificial recharge in southern parts of the plain. Meanwhile, the fuzzy TOPSIS network analysis presented better and acceptable results.

Whereas climatic parameters find importance due to their impacts on water resources, therefore this research was done carried out for investigating of meteorological drought and its impacts on Kerman groundwater resources in the eighteen-year’ s period (1997-2014). In this regard Standardized Precipitation Index (SPI) values in Kerman meteorological station and Groundwater Resource Index (GRI) of plain in different time scales (1, 3, 6, 9, 12, 18, 24 and 48 months) was calculated. The results of correlation test between GRI index in different time scales and SPI index in the time period under research without any delay and with a time lag of one to twelve months showed that 6 and 18 months GRI index have significantly related to 48 month SPI index with 0. 628 and 0. 631 Pearson coefficients, respectively and also 48 months GRI index was correlated to 48 months SPI index with 6 month lag time and its Pearson coefficient was 0. 686. The results of regression model showed that up to 57 percent of variations in GRI index explained and justified by SPI index. This is due to other factors such as uncontrolled exploitation of groundwater resources on the loss of groundwater and groundwater index linked. Iso-decline maps showed that the decline in groundwater levels across the plain, an average of 20 meters and rising in ground water levels in the range of Kerman city by 14 meters.

In this paper Kashkan basin from upstream to downstream water quality changes were evaluated. First, the process of long-term qualitative changes in two branches Kashkan (Khorramabad and Horod) was evaluated. Mann-Kendall test was used to determine Routing data. For examination of water quality AqQA software Schoeller diagram extracted and analyzed for each station. Information needed to assess water quality in terms of agriculture was transferred to the diagram Will Cox and Classification of water was determined. At all stations trend of discharge, negative and to further Water Quality Indicators the trend was positive. The results showed that in both branch water quality parameters Decreased. Water quality changes after joining the two branch Khorramabad and Herod At the station Poldokhtar was investigated. At the station Poldokhtar Many parameters were In a range between the value of them In two branches before joining But in some of them also was violated this law and increased At the station Poldokhtar. Due to the reduction in flow rate and increase of quality parameters, the basic premise was proven.

In flood conditions at the alluvial rivers with compound sections, due to momentum exchange between main channel and floodplains, flow discharge prediction by traditional methods is very erroneous. In this paper, a new method known as multi-stage gene expression programming has been used for computation of flow discharge in straight compound channels. For modeling, three dimensionless parameters of relative depth, coherence and relative calculated flow discharge, and one parameter of relative measured flow discharge were selected as inputs and output, respectively. Using 402 stage-discharge dataset from 31 laboratory and field compound channels, explicit relationships were developed for flow discharge prediction. The mean absolute errors of this method were obtained as 10. 2% and 11. 6%, respectively for training and testing phases. Hence compared with the Manning's formula (with mean absolute error of 19. 3%), the proposed method is quit outperform. Hence, application of this method is recommended for flood flow discharge in rivers having compound channel forms. Also, by incorporating this new idea with the computation procedures of the river water surface profiles and flood routing, the design of flood alleviation schemes will be improved.

The rivers are considered as a small part of flowing water and one of the basic sources of the world׳ s irrigation, drinking water industry and other uses. The aims of this study are division of water quality in three stations (Zawat, Walt and Roodbarak) which are situated in Sardabrood river by using qualitative water index (CWQI) and the Aquachem software. For this aim to calculate the indicator, calcium, magnesium, potassium, sodium, Chloride, Sulfate, The electrical conductivity (EC) and acidity (PH) based on the results, Zawat station is in a rather good rating for potation and in an excellent rating for irrigation and Walt and Roodbarak had bad ratings. All the Roodbarak stations are in bad conditions for raising aquatic amusement and are needed to be filtered and refined. Concerning to the analysis, the best and worst qualitative water is related to the Zawat and Walt and Roodbarak stations. The type of water by the Aquachem was Bicarbonate-Sodium (NaHCO3).

the performance criteria have used in this study is including mean square error (MSE), sum square error (SSE), Nash_Sutcliffe and correlation coefficient. The result indicated the best ANNa model is ANNa2 with MSE equal 0. 0017. Inputs in this model are Total Cation, Total Hardness and Calcium. The best ANNb model is ANNb3 with MSE equal 0. 0012. Inputs in this model are Sodium adsorption ratio, pH, Total Hardness and Calcium. Also, the results indicated that using ACO algorithm for finding the best input parameters had increased neural network performance, in ANNb models than ANNa for validation network and for test network we see with increases inputs the performance of network increases. According to results we can say that against try and error for finding the best inputs, we can use the parameter that those had a high correlation between target parameter as first step. But parameters that have high correlation between target parameter, necessarily don't the best inputs. But the parameter that those had a high correlation between target parameter as inputs of neural network. Also, we find that the ACO algorithm can be used as a method of input variable selection and that improved the performance of neural network.

The aim of this research is watershed prioritization using morphometric parameters and Multiple Criteria-Decision-Making (MCDM) by Geographic Information System (GIS) and Remote Sensing (RS) techniques. For this purpose, First digital elevation model (DEM) was developed of study area using low frequency radar data, then, 17 watershed extraction for prioritization in ArcGIS10. 2. After preprocessing and preparation of digital elevation model 14 morphometric parameters extracted including 5 Shape morphometric Parameters (Form factor, Elongation Ratio, Circularity Ratio, Compression ratio), 2 linear parameters (bifurcation ratio, Stream length), 5 areal parameters (Drainage Density, Drainage texture rate, Constant of channel maintenance, Stream frequency, Penetration ratio) and 3 topographic parameters (Relief ratio, Ruggedness number, Slope). The results of the evaluation of morphometric parameters by using AHP model showed that bifurcation ratio, Slope and Drainage Density With the most points (0. 227, 0. 174, 0. 135)points Were in very much Acute condition and other watershed also were in very Acute condition And requires watershed management practices to protect water and soil resources.

This research introduces a general framework (GARDLIF) for evaluate land subsidence potential of any area in the aquifers. This methodology evaluated in the Salmas aquifer. In the first, raster layers of the GARDLIF factors were prepared. Then, the layers were reclassified based on the GARDLIF framework criteria and modeling was carried out. The land Subsidence vulnerability map of the Salmas aquifer shows that the most land subsidence potential is related to the north-east of aquifer (Gharagheshlagh) which was consistent with the results of prior studies. In order to assessment the effectiveness of each factors in output layer, map removal sensitivity analysis was performed. The most changes in vulnerability index are associated with remove of the discharge (D) and land use (L) maps that average changes are 1. 62 and 1. 5, respectively. Due to high rating of aquifer media (A) and impact of aquifer thickness (I) in most parts of the aquifer, vulnerability index extensively changes by remove A and I factors. Based on sensitivity analysis, the least important factor is the Distance of fault (F) that its average variability index is 0. 4%.

Due to high spatiotemporal resolution of gridded data, reanalysis precipitation databases, have many applications in climate prediction, climate change modeling, water resources management and hydrological modeling, especially in areas without observational data. Therefore, in the present study, hydrological simulation was evaluated by SWAT model and spatial data mining for drought monitoring with SPI and SDI indexes over Maharlu Lake and assessing the temporal sense of Asfazari national database by observational stations as a reference on the spatial extent. The results showed high accuracy of Asfazari database in simulating of runoff in comparison with simulated runoff with observation database. The coefficient of determination and Nash efficiency presented the average accuracy of 0. 6 in the simulation. During the cold and rainy seasons, the performance of this database is higher than is the warm season. During rainy months of year, the correlation coefficient between observation and Asfazari is about 0. 85, and the POD index is more than 0. 9. Furthermore, subsequently the accuracy of monitoring drought by Asfazari is too high, so it can be said that the Asfazari database can be used as a reliable database in runoff simulating and drought monitoring, especially in areas with poor or no sufficient precipitation data.

In the present study the impacts of climate change on groundwater levels in the Gotvand Aghili aquifer was investigated. For this purpose, groundwater was simulated using the MODFLOW model in the GMS framework for a period of 2002-2012. After calibration of model the values of RMSE for steady and unsteady conditions were 0. 751 and 0. 852m respectively, and average correlation coefficient of 0. 82 was obtained for the verification of model. Then outputs of 10 AOGCM models under the RCP8. 5 emission scenarios, the latest assessment report of IPCC, were used to simulate the climate parameters and study their impact of groundwater levels in future. For this purpose, the periods of 2000-1971 and 2024-2015 were selected as the base forecast periods respectively. The 5 climate scenarios (at the risk of 0. 1, 0. 25, 0. 5, 0. 75 and 0. 9) were used for simulation of climate parameters for the future period. Then groundwater levels were predicted for the future period under these scenarios. Based on the results under the risk level of 0. 1 the aquifer will experienced the biggest drop of 1. 8m and under scenario with risk level of 0. 9, the groundwater level will increased 0. 48 meters during the future 10 years of 2024 to 2015.

Practical activities in controlling desertification must be based on current desertification situation and its severity. Based on this theory, in this study, the destructive ability of desertification was analyzed for the Bam Normashir and Rahmatabad (Kerman Province) plain aquifer using the IMDPA model and geographical information system (GIS). In this study, using the quantitative (water table depth) and qualitative (Electrical conductivity (EC), Cl and SAR) indicators as well as the soil erosion magnitudes in the studied locations, severity classes of degradation were evaluated. Then, the destruction map of the studied region was prepared by taking into consideration the maximum limitation in qualitative indices. Cluster analysis Ward and K-means method were utilized for testing the models. The results indicated that the desertification destructive in 90. 81% and 8. 61% of the aquifer is at severe hazard and very severe hazard class, respectively. Overall, 62% of the model results (IMDPA) was reported significant with clustering.

In the past few years, due to inappropriate management of surface and groundwater resource exploitation in the Behbahan plain, the water table has risen and caused to some problems such as the phenomenon of flooding in the urban area. Development of irrigation and drainage networks in a wide zone of the study area is one of the most effective factors causing this phenomenon is. In order to evaluate this, the water level of the observation wells as well as the amount of input water to irrigation networks were investigated in a long-term hydrological period (since 2003-2004 to 2015-2016) in the region. Using these data, the representative hydrograph, the iso-depth contour, iso-piez contour, and fluctuation maps of Behbahan plain were investigated in different parts of it. The results showed that the fluctuations in groundwater level of Behbahan aquifer and its storage depend on the input water from the irrigation networks in the study area. Among the irrigation networks, Boneh-basht irrigation network has more effective role in feeding of Behbahan aquifer and rising groundwater level in comparison with the northern and southern Maroon irrigation networks.

Evaluation of water requirement in designing irrigation systems and water supply in agriculture is important. The aim of this study was to estimate and determine the spatial pattern of water requirement of apple tree using weather stations statistics from 1985 to 2013 in apple tree cultivation areas in Iran. Initially, annual reference evapotranspiration was estimated based on the FAO, Penman-Monteith model, In the following, the stages of growth the summer apple Kohanz crab and autumn apple Red-Delicious were identified. Eto calculation annual results and water requirement of growth stages were identified using ArcGIS10. 2 as a spatial pattern for each variety. The results showed that the annual ETo in the North-Eastern and Southern regions of the apple cultivation area cultivar reaches more than 2000 mm. The summer apple Kohanz crab has less water requirement than autumn apple Red-Delicious varieties and the middle stage of growth in apple trees have the highest water requirement. The spatial changes in evapotranspiration and water requirement apple trees are due to altitude factor. From the north to the south and from the West to the East, the apple cultivation areas in Iran increases the amount of water requirement.

In order to evaluate the effects of watershed management practices on carbon sequestration and storage, Vegetation, litter and soil samples in each treatment were taken by systematic-randomly method from 10 areas of the basin that represents the variation of soil and vegetation along 10 transects and 100 plots (Except for small earth dams and biomechanical treatments which there were 2 small earth dams and 3 biomechanical treatments in this basin so samples were taken from all of them respectively along three and one transects). Also soil samples were taken at each transects randomly in two depths (0-10 cm and 10-50 cm), soil samples were tested in soil laboratory. Results indicate that in all treatments most amount of sequestered carbon was occurred in the soil (about 99% of whole carbon stocks in the ecosystem). Finally the results showed natural rangeland that have good conditions in terms of vegetation and soil have the most carbon stock in two soil depths and overall (soil + biomass + litter) with 647. 84 ton/ha up to a depth of 50 cm from the soil surface and mortar stone dams with 169. 35 ton/ha have the lowest carbon stock in this basin.

In this research, the effect of climate change on rainfall, runoff, temperature and water resource for Ziarat basin of Golestan province, was assessed. General ccirculation model, HadCM3, was used under three scenarios as A1B, A2 and B1 for 3 future time duration as 2011-2030, 2046-2065 and 2080-2099, respectively. In order to down scaling of HadCM3 output, ANFIS model was used. The predicted results showed increasing temperature as 0. 32-1. 77oC and decreasing precipitation as 1. 6-31. 46 mm for future durations. Then, the mentioned results, curve number map and physiographic parameters, basin and waterway slope, gained from Arc-GIS, as importing data to calibrated HEC-HMS model was made in order to simulate the discharge of climate future durations. Results presented the runoff volume and peak of discharge have decreased in all three scenarios for horizon 2020, 2055 and 2090 and for all mentioned horizons, the most of decreasing was related to A2 scenario. Percentage decrease in peak and discharge volume was obtained 1. 72 and 1. 83, 3. 06 and 3. 07, 4. 43 and 4. 48 for mentioned periods, respectively. Consequently, based on extracting information from models, no enough storage would happen in dams. Finally, some solution for this problem was presented.

In recent years, Urmia Lake faced with declining water level and shrinkig area of Lake due to reduced water inflow from sub basins. The Simeneh Rud and Zarrineh Rud Rivers comprise 51. 6 % of the long term total surface water inflow into the Lake. The main aim of this research is investigation climate behavior of basins in view of metrological drought during recent four decates. In this case drought condition was monitored by using Standardized Precipitation Index (SPI) in deferent time scaled in 31 meteorological stations in Southern basins of Urmia Lake. Spatial distribution of drought indices using by geostatics methods including ordinary kriging, Co-Kriging and inverse distance method (IDW) were calculated, and regional drought map zoning were provided for wet and drough years. The results show that studid area experienced two wet period and one drouth period during recent four decates. After domination of 3 years drough and again govering normal condition over basins, drying Urmia Lake was continued because more factors, mainly human activities, beside of climate effects. In many years, the ordinary kriging model was more appropriate than the Co-Kriging and IDW for mapping regional drought.

River flow, which temporarily and spatially changes, is a major hydrological variable in water resource planning. In research, on water resources, the perdition of the river flow based on historical data is a main step for watershed management. In this study three intelligent techniques including wavelet artificial neural networks, gene expression programming, and support vector machine (SVM-LS) were compared in river daily flow perdition at the Telvar basin. Daily recorded data from 2002-2012 were used in the modeling procedure. Data were divided to train (75%) and test (25%) groups. Results indicated that all three modeling methods have high performance in predicting daily flow using the two-day lag data. The correlation coefficients for wavelet artificial neural networks, gene expression programming, and support vector machine (SVM-LS) were 0. 9, 0. 94, and 0. 92 respectively. Therefore, it can be concluded that the gene expression programming has slightly better results in comparison with the other two modeling methods. The accuracy of the gene expression programming model increased due to the increasing of the lag data from 2 to 4 and five days.

To predict climate change and its effect on drought future situation in Tamar Basin, first daily output data of CanESM2 model downscaled and predicted by SDSM model and also RCP 2. 6 and RCP 8. 5 scenarios in the 2020-2049 period. Then, drought conditions evaluated by predicted data and SPI and SPEI indices in the future. Trend analysis of temperature and precipitation variables also carried out by Mann-Kendall non-parametric test. The results of trend analysis showed that precipitation changes is negligible and increase of temperature in most time series is significant. The performance of SDSM model to predict temperature and precipitation data is also very suitable and its outputs showed that temperature and precipitation have increased rather than that in the baseline period. The results of SPI index indicated that in both the periods the most droughts and wets have occurred at the late and first half of the two periods respectively. Evaluation of drought by SPEI index showed more severe drought rather than SPI index and according to increase of temperature trend in the baseline period and also temperature increase in the future can say the results of SPEI index are more actual and logical than the results of SPI index.

Rain simulation is one of the important methods for measuring hydrological and soil erosion processes. Rapid evaluation and high repeatability capabilities are the advantages of using the rainfall simulator. The weight of constructed simulator is approximately 20 kg, can simulate rainfall at 28 to 95 mm / h intensity on the plot area of one up to three square meters. The droplet diameter was measured using flour pellet method and stain method. Flour pellet method was selected due to higher determination factor, and then its results were applied to continue the study. The highest uniformity coefficient (96. 6%) was obtained at the intensity of 8. 3 cm/h and the lowest coefficient (90. 6%) was obtained at 9. 5 cm/h intensity, which is higher than the acceptable level. The average diameter of the droplets is from 0. 97 mm at intensity of 2. 8 cm/h to 1. 22 mm at 7. 1 cm/ h, which lies within the range of natural precipitation. Also, the range of velocity variations is from 3. 58 to 4. 21 m/s. According to the mentioned specifications, a suitable portable rainfall simulator was designed with acceptable accuracy for runoff, permeability, erosion and sedimentation studies in field.

Human environmental impacts on the earth can be examined in various fields. One of the areas of great importance is carbon dioxide emissions by human. One of the thousands of human activities that lead to carbon dioxide emissions into the environment is the supply of water. This paper examines the amount of carbon dioxide released by the drinking water supply system in Sepidan. This project took place within a year's time. The results of the surveyes show that in Sepidan, from one well with an energy consumption of 81318 kwh, one spring with an energy consumption of 102234 kwh, and the building of water and sewage organization with an energy consumption of 5491 kwh, amounting to 1067, 48, 769 and 3293 kilograms of carbon dioxide release per year. Also, the results showed that 38 grams of carbon dioxide is produced for the supply of one liter of drinking water in the Sepidan. The results of study showed that the supply of water from the spring at a higher altitude point than areas of the city due to the specific topography of the Sepidan, Which is in the form of sloping, requires much less energy, and releases less contamination or carbon Dioxide.

Multilispectral picture classification is one of the most important techniques for separating earth units. The phenomenon of global warming, expansion damming, water storage behind dams and excessive utilization of existing water for human uses has caused the drying of lakes, including Lake Bakhtegan. For this purpose, Landsat images of 1991, 2000, 2010, and 2017 were collected in Bakhtegan Lake and surrounding areas. These images were categorized based on educational samples in four classes of water, septicity, mountain and urban areas after pre-processing and corrections required by the supervised maximum likeness. The same image was then sorted by multi-layer perceptron neural network method in the above classes. Finally, for both methods, the error matrix was extracted and the overall accuracy and kappa coefficient were calculated. For the year 1991, the maximum probability and neural network method was 87% and 93%, and the kappa coefficient was calculated to be 0. 86 and 0. 90, respectively. . Therefore, due to the higher accuracy of Negative Network, images of the years 2000, 2010 and 2017 were categorized by this method. After classification, in order to evaluate it, Google Earth was considered as the test sample for each information class and the overall accuracy and kappa coefficient were 89% and 0. 85, respectively.