IRANIAN JOURNAL OF ECOHYDROLOGY
Year:2020 | Volume:7 | Issue:1|Papers Count:20

The purpose of this study is to predict climate change and investigate the effect of climate change on Growth Day-days and total days of wheat growth in Fars province. For this purpose, the climate data of three synoptic stations of Shiraz, Lar and Abadeh in Fars province and the data of two models HADGEM2-ES and EC-EART were scaled under RCP45 and RCP85 scenarios. LARS-WG statistical model was used for Downscaling. The results showed that the LARS-WG model has appropriate accuracy in Downscaling of Fars province climate, minimum and maximum temperature parameters. The minimum and maximum temperatures of all three stations of Shiraz, Lar and Abadeh increased under both RCP45 and RCP85 scenarios. The increase in the minimum temperature of the base period (1980– 2015) in Fars province relative to the period (2021– 2040) for the RCP45 and RCP85 scenarios is 1. 43 and 1. 65 ° C, respectively. The maximum increase in base temperature over this period for the RCP45 and RCP85 scenarios is 1. 51 and 1. 66 ° C, respectively. The amount of changes in the rainfall of the baseline period increased by 2. 93% and 1. 95% for the RCP45 and RCP85 scenarios, respectively. Then, using ADP equation, the number of day-index under two temperature thresholds of 4 and 25 ° C for the basic and future time interval (2021-2040) was calculated and the results showed the degree of days of wheat growth period (GDD) and total days’ number. The growth period (DAP) had an increasing and decreasing trend compared to the baseline period.

The Climate change can be a major threat to biodiversity and ecosystem integrity. Therefore, prediction of hydrological behavior of watersheds for conservation and reconstruction of ecosystems is necessary. In this research SWAT semi-distribution hydrological model was used to evaluate water flow and water balance by changing climate in Latyan dam near Tehran during 1988-2014. Also, the output of the CMIP5 series model is under two scenarios RCP 2. 6 and RCP8. 5 for the near future using the model, LARS-WG was introduced into the mode. The result of stimulation for 2021-2050 showed that mean temperature increases by 0. 75 C° for RCP 2. 6 optimistic scenario and 1. 45 C° for RCP 8. 5 pessimistic scenario. In addition, rain was reduced by 2 % in RCP 8. 5 and 5 % in RCP 2. 6. The result for water flow showed that high level of water flow decreases by 2. 4 cubic meter per second in May and increases by 1. 49 in April. The water flow in RCP 8. 5 scenario for May and June was greatly reduced which it can negatively affect level of water in dam until starting rain. Average evapotranspiration was increased by 3 mm in optimistic scenario and 8 mm in pessimistic scenario which it negatively affects the accessible water resource. Reduction of rain was predicted for two scenarios.

Nowadays, the improper distribution of rainfall and the decline in precipitation, in addition to the population growth, consequently increasing in water consumption and demand have made society dependent on the use of water resources development plans. Also, one of the long-term goals of the country water strategy is to strike a balance between the amount of water demand and existing water resources with regard to social, economic, and environmental considerations. Therefore risk analysis of water resource development plans based on sustainable development indicators is necessary. In the present study, for the first time, the Fault Tree Analysis (FTA) technique was employed in order to risk assessment of water resource development projects under the framework of sustainable development. After determining the top event, factors leading to its occurrence, including the failure of social, economic, environmental and water resources indices were identified. The proposed model was presented as a case study for water resources development plans of the “ district 4 of Mokran to Bandar Abbas” , Moreover, for different scenarios, a Vensim Model was used for simulate water resources and consumption in the study area. The probability of failure of the Sustainable Development Indicators was estimated based on Vensim output and used as input to the proposed Fault Tree. The results showed that the failure probability of the best, worst and existing condition scenarios was 38%, 90% and 50%, respectively. Finally, due to the calculated high risk, the base events were ranked based on their contribution on the top event occurrence.

Flood is one of the complex and destructive natural phenomena that causes heavy damage every year. River routing and spatial situation of the sub-catchments are effective factors on flood in catchment outlet. Hence, for performing the flood control projects in upstream parts of catchments, their effects on flood should be investigated. In this research, the priority of the sub-watersheds was considered for flood occurance in the Chenar-Soukhteh watershed using the HEC-HMS model. After providing the data needed for flood hydrographs, the SCS hydrological simulation methods was used. Prioritization of the sub-catchments for flooding was done by utilizing the HEC-HMS model. Model calibration was done by sensitive parameters incuding initial losses, curve number and lag time. In order to evaluate the effects of flooding, two indicators of physical criteria including flux peak flow and flow volume were considered in each step. By applying the repetitive method for individual removal of sub-catchment, flood hydrographs corresponding to its precipitation were calculated for each sub-catchment. Then, with successive elimination of sub-catchment, the effect of each one in the production of flood output was obtained. The results showed that in events that were calibrated in medium CN conditions, sub-catchment 5 had the first priority in terms of flooding, while in the case of wet-calibrated CN, sub-catchment 6 has the first priority.

The system of water resources is influenced by several factors affecting in a particular geographical environment or in a wider space. Sometimes, these effects are such that, the conditions for access to healthy water resources have been faced with massive problems and performances of water resource planning and management. The goal of water resource planning and management is to match the socio-economic system demand of water with the supply of the water system through administrative control and management, without damaging sustainability of ecosystem. This can be achieved by identifying effective and influential factors, both from water supply side, and demand side of the various sectors of the society. Therefore, in the present study, it was attempted to identify key factors and drivers affecting in the future of water resources of Tabriz County till 2041 vision based on the Integrated Water Resources Management. Meanwhile, to apply appropriate policy strategies. Based on some 46 primary factors were identified by the panel of experts by using the resource review and Delphi method. In order to determine the key factors and effective drivers in this system, 15 factors were introduced using the cross impact matrix. The final findings indicate that environmental and economic factors have the largest share as the main actors in this collection and will play a more effective role in the future of water resources and it is expected that driver affecting of County water resources to be one of the environmental and economic components.

Flooding hurts the environment, economy, human communities, and industry. Therefore, comprehensive knowledge on flood probability modeling is essential to identify sensitive areas and improve flood management systems. Advanced floods models usage has been grown dramatically today. That's why several researchers have integrated some models obtaining acceptable results to flood-prone areas recognition. Since numerous high-risk floods have occurred in Kalat Basin and no advanced techniques have been used to flood probability mapping, so the Frequency Ratio-Support Vector Machine (FR-SVM) ensemble model was selected to flood modeling. Accuracy and efficiency evaluation, consequently, has been compared with the standalone SVM model. By investigation, 73 floods points were recorded according to recent 2018 end months floods, and 15 conditioning factors including annual precipitation, geology, land use/land cover, slope length, river distance, analytical hillshading, elevation, convergence index, profile and plan curvatures, Slope, stream power index, topographic roughness index, topographic wetness index and valley depth were considered. Models were evaluated by various precision criteria such as kappa coefficient, root means square errors, receiver operating characteristics and precision-recall curve. The FR-SVM model with a precision-recall curve of 0. 8862 showed high accuracy and performance than SVM. These results can be used to manage flood-prone areas and other natural resource applications.

In this study, the prediction of fluctuations in groundwater level was influenced by stochastic models in Rafsanjan plain. Future precipitation was projected using the ARIMA model in EViews9 software for 2017-2023, then groundwater drainage was simulated using the groundwater model system (GMS) during the base period (2003-2016) and results from the ARIMA model for the upcoming period. The results of groundwater drainage simulation showed that in the whole region, groundwater abatement occurred in the upcoming period relative to the base period, and the most groundwater losses occurred in the southwest of the plain, and an annual increase of approximately 130 million cubic meters Groundwater resources are made. In general, groundwater has the highest level (upper level) at the beginning of the period and the lowest level (lowest level) at the end of the statistical period. After modeling the groundwater level for the base period, rainfall prediction from the ARIMA model was applied to the groundwater model with the assumption that the aquifer was operationally constant. The results showed that the aquifer volume deficit was 1021. 09 million cubic meters in the final model year (2023). Also, the changes in the level of the aquifer in the Rafsanjan Plain from 2003 to 2023 indicate that, given the estimated rainfall from the ARIMA model, it can be admitted that an average of 1 meter annual waterfall will occur in this plain.

Erosion and sediment transport are the important hydrodynamic processes in drainage basins that can affect many hydraulic and hydrologic systems such as rivers, beaches, ports, dams, bridges, roads, and farms. One of the most important sediment sources in Iran drainage basin is bank channel erosion that causes on-site and off-site effects. Therefore, investigating of channel/river band instability is necessary for engineering activities to stabilize the riverbank against bank erosion. Thus, the main objectives of this study were to investigate the instability coefficient of the Taleghan River and to find the engineering solution for its stabilization by using the Lin model. In view of this, all required parameters comprising slope, shear stress, slope angle, and satiability coefficient of grain are measured using filed study and Google earth imagery. Finally, bank satiability coefficient and effective rock size for revetment besides the riverbank is obtained in the study area. According to the results, the highest amount of bank erosion and consequently, the lowest stability coefficient and the largest stone at the threshold and effective on revetment are related to the 4th section. The lowest amount of erosion, as a result, the highest range of stability coefficient and smallest stone at the threshold and effective on revetment is related to the 1st section. The main reason could be the size of the grain size on the side, the slope of the basin, slope aside and bank full discharge width.

The development of energy supply from biomass to reduce greenhouse gas emissions has led to focus on producing important crops from energy perspective which culminated in water consumption increase. Therefore, in this study for analyzing the water and bioenergy nexus, an index called water footprint was used. In this regard, information about maize in the plains of Khuzestan province, was collected. Based on the calculations, it was found that the water footprint of maize crop in the province has an average of 3355. 6 m3/ton and the biomass water footprint is equal to 214. 9 m3/ton. Moreover, in the study of water footprint of maize biomass, it was found that the highest and the lowest water footprints devoted to Behbahan plain (27. 1 m3/GJ) and Abbas Abad plain (10 m3/GJ), respectively. Accordingly, Khuzestan province with an average of 13 m3/GJ, has better condition in terms of water consumption in compare to countries such as Zimbabwe, Brazil and the United States with a water footprint of 200, 39 and 18 m3/GJ, respectively. Mapping the biomass energy production potential with the water footprint approach also showed that water footprint in southeastern plains of the province (especially Behbahan, Omidieh, and Hendijan) are in the interval between 12 up to 27. 1 m3/GJ and have low priority for biomass production. In contrast, the northern and eastern plains (especially Abbas Abad, Andimeshk, Sidon and Qaleh Tal) with bioenergy water footprints of 10 to 10. 9 m3/GJ have high priority to the use of maize biomass for energy production.

Wetlands are the most important natural ecosystems on the earth, and assessing changes in them is one of essential nessesties in natural resource management of this valuable natural ecosystem. The aim of this study is to investigate water body changes using remote sensing water indices and Google Earth Engine (GEE) in study area of Poldokhtar wetlands, Lorestan province. Remote sensing water indices includes AWEInsh، AWEIsh، NDWI، mNDWI، NDWI plus VI، mNDWI plus VI and LSWI plus VI that were used TM, ETM+ and OLI Landsat satellite images, and Google Earth Engine were applied Landsat Water Product data. The results demonstrated temporo-spatial distribution of water body changes in the study area and they were compared to real data indicating AWEIsh and AWEInsh with overall accuracy of 99. 39 and 99. 19 and Kappa coefficient of 0. 94 and 0. 91 were the best water indices among all in enhancing water bodies, furthermore, GEE results showed overall accuracy of 87 and kappa Coefficient of 0. 86. These results indicate that water indices and GEE are useful tools in detection of increasing and decreasing trends in water bodies that can assist planner and policy makers in protecting and managing natural resources in the study area.

Awareness of salinity risk is of great importance for water resources management, especially in regions near the coast. In this study, it was attempted to develop a comprehensive framework for salinity risk assessment by combining statistical and chemical analysis for Sarkhoon aquifer, Hormozgan province. In the first step, the input layers required for the DRASTIC model were prepared to investigate the aquifer vulnerability and then these layers were combined based on the model procedure to obtain the vulnerability map. Then, the map of salinization hazard occurrence probability was obtained by using three machine learning models of Random Forest, XGBOOST, and BART with considering 12 factors affecting groundwater including topographic wetness, soil, vegetation and other factors. Evaluation of the modeling performance with the receiver operating characteristic (ROC) curve indicated that all three algorithms had very good accuracies with area under curve (AUC) values higher than 90%. Thus, all three models were combined based on their AUC values and the united map for the probability of salinization hazard occurrence was obtained. Finally, the map of salinization risk was generated based on the values for the vulnerability, salinity and hazard occurrence probability. The survey of the risk map showed that the eastern part of the aquifer has high salinization risk due to the high concentration of agricultural land in the area. The results of this study revealed that the achievement of a reliable map for assessing aquifer salinization risk is possible by combining machine learning models.

sustainable management of wetlands, in terms of their terrestrial and aquatic ecosystems composition and characteristics, requires scientific and multidisciplinary approaches. The purpose of this study was to develop Jazmourian wetland management strategies using multi-criteria decision making models. This study was an evaluation-analytical study that collected library and documentary data as well as field data. In this study, first, using DPSIR framework, the criteria were developed according to the theoretical framework and then WASPAS method was used to prioritize wetland conservation and restoration management strategies. Then, The Quantitative Strategic Matrix Planningmethod was used to extract strategies and determine the direction of water resources management strategies. Following on from the IFE and EFE matrices, the internal factors accounted for 0. 254 and the external factors of 0. 213 which indicates a high aggressive approach to profitability. Results from the WASPAS model for measuring and analyzing hierarchical management strategies indicate that, respectively, conservation of indigenous vegetation units with a weight of 0. 403, is the highest priority and at the top of hierarchical analysis, and intubation of streams with weight of 0. 146 is the lowest priority was.

In this research, the factors affecting land subsidence in the Shazand plain have been investigated using weighting model. In this model, seven effective parameters, aquifer environment, land use, pumping, feeding, aquifer thickness, distance from fault and groundwater loss were rated, classified and classified according to expert opinion and by combining these parameters in ArcGIS environment the vulnerability map was evaluated. The index ranged from 87 to 170. Then, for optimization and adaptation, seven layers effective on fuzzy subsidence were prepared and the final map was prepared. Then the final map of the subsidence potential was prepared using AHP method. Vulnerability of lowland subsidence was obtained by integrating layers in Arc GIS for a period of 2016-2017. InSAR satellite map was used to validate this model. Fuzzy and AHP methods were combined with weighting model to improve the results and optimize the weights applied. The results show that all three methods have almost the same correlation with satellite data and fuzzy method shows the highest correlation with satellite data and actual subsidence. Based on this model, the north and northwest regions are subject to subsidence. It should be noted that the Shazand refinery is located in a high subsidence potential area and management plans should be put in place to control the subsidence.

Most of the water consumption is in agricultural and irrigation uses, which accounts for about 70% of the world's total fresh water, and water resources are scarce worldwide due to rapid population growth, urbanization, and climate change. In the present study, the potential effects of water pricing on efficiency, equity and fairness and sustainability of irrigation water use were investigated. Required data were collected through questionnaires and face-to-face interviews with farmers in different areas where farmers pay for irrigation costs in the area. Part of the data was also obtained from landowners and buyers of water using electric or diesel pumps. The data were analyzed using Eviews and DEAP2 statistical software. Regarding the results for each production unit, the fully efficient units formed a small proportion and added most water units to various types. They consume. The results show a negative relationship between the technical efficiency with the excess water consumed due to the inefficiency of input use. The results of the Sustainability Index showed that if farmers and ranchers were more efficient in using water and consuming less water, the sustainability index would increase for them. The results of the VAR model show the long-run equilibrium relationship between pricing policy and agricultural output. In other words, the results show that pricing policy has increased agricultural production.

The main purpose of the research is to investigate the relationship between pathogenic mirco-organisms (total coliforms (TC) and fecal coliforms (FC)) with physical and chemical parameters of water in different depths of reservoirs. Samples were taken from different depths of the dam reservoir in June, , July and August, when the water was in maximum temperature, pH, TC, FC, electrical conductivity (EC), pressure (P), Total phosphorus (TP), total dissolved solids (TDS), dissolved oxygen (DO) and temperature (T) were measured. Preliminary results showed that pH, DO and T parameters decreased with increasing depth in the water column, while EC, TDS and TP increased. The results obtained from multivariate statistical analysis methods revealed that TC and FC were affected by P and TDS changes. By moving from the surface to the bottom of the dam reservoir, the distribution of the coliforms decreased, which is unbalanced, and no specific pattern of coliform distribution can be considered. Based on the analysis of the relationships, it was found that 58% of total coliform and 59% of fecal coliform changes were predictable if the total soluble and pressurized solids were quantified. Also, by Pearson correlation analysis, it was determined that total coliform and fecal coliform, in none of the four levels, were correlated with total soluble solids and pressure parameters, and none of these parameters had a significant direct effect on them. As a result, fecal coliform and total coliform are directly related to T, Do and pH and inversely related to EC, TDS, and strain.

Taleghan River is one of the most important rivers in the country because of its flow to Taleghan Dam, which supplies drinking water to this area as well as part of the city of Tehran. Long-term river discharge data are needed to design hydroelectric power stations and manage water resources. Regarding the existing monitoring stations are scattered and cannot provide sufficient hydrological data for the basin we employ rainfall-runoff models which are popular tools for expanding hydrological data over time and space. In this paper, the feasibility of applying a conceptual rainfall-runoff model called HYMOD to a part of Taleghan River Basin is investigated. The generalized probability estimation method was used for model calibration and uncertainty analysis. The results show that the observed discharges are satisfactorily consistent with the observations, indicating that the hydrological model is working well and applying HYMOD to estimate long time series of river discharge in the study area is turning reasonable results.

The drought characteristics are often highly correlated. But, the univariate drought analysis is not a proper approach since it doesn’ t involve the dependence structure of drought characteristics. Therefore, the multivariate drought analysis is used since it considers the dependence structure of drought characteristics in the model. The aim of this study is to analysis of multivariate hydrological drought in the Mehran and Sedij basins. For this reason, the empirical copula was used to compute the cumulative distribution function of the runoff and the joint deficit index. Then, the drought severity, duration and magnitude were extracted and several theoretical copulas belongs to the Archimedean and Elipticalfamilies were fitted to obtain the trivariate distribution of drought variables. Results of the JDI and SPI-12 evaluation in the study area represented that the JDI is a proper index of monitoring hydrological drought and provides a more precise estimation than the SPI-12. Furthere, results of joint return period indicated that the joint trivariate return period is larger than the conditional trivariate return period. So that, the joint or conditional probability with high or low return periods is important in predicting drought events. Because the under-estimation or over-estimation of drought risk have serious impact on environmental resources, soil moisture and water quality. Generally, the multi-dimentional copulas are useful approach in evaluating the complicated and non-linear relationship of variables and constructing a comprehensive index for evaluating drought condition.

Locating suitable areas for the construction of flood spreading structures and infiltration into underground aquifers for the purpose of storing runoff and increasing groundwater reserves to supply the water needed for various purposes and to control flood damage, Highlights the importance and necessity of these studies in protecting natural and human resources. In this study, it has been attempted to provide suitable locations for flood spreading in Khorramabad watershed. For this purpose, parameters: land use, elevation, drainage density, geology, distance from residential areas, river distance, distance from road, slope, soil classes, soil texture, electrical conductivity and unsaturated thickness were measured in ArcGIS10. 5. . At first the parameters were fuzzy-fuzzy between zero and one, and then, using hierarchical analysis, pairwise comparison of the variables was quantitatively classified, and then using Expert Choice software based on AHP method, Weight of each criterion was obtained. The most effective criteria in this study were the parameters of distance from residential areas, land use and unsaturated thickness. Finally, using ArcGIS10. 5 techniques and linear-weight combination, the location for flood propagation was determined. The results showed that according to the final map of flood spreading, 13. 99% of Khorramabad watershed has appropriate utility and 26. 04% of moderate utility for constructing flood spreading structures. These areas can be considered in planning the actions needed for flooding in the area.

Determining and forecasting groundwater quality can be a primary step for managing aquifer sustainability. This study investigates and forecasts groundwater quality in Zanjan Aquifer. In the previous studies, the GWQI index is a simple weighting based on expert opinions. Thus, in the developing new index (C-GWQI), for weighting, the Shannon entropy method and the COPRAS multi-criteria decision making technique were used. In this research, COPRAS Multi Criteria Decision Making Technique was used to develop the new index (C-GWQI). By defining two permissible and desirable points of drinking water according to WHO standard, aquifer quality was classified into three ranges including, desirable, permissible and non-permissible for drinking water. The results showed that in all periods of time, groundwater quality is lower in urban areas than in other areas. However, in most of the wells surveyed, the water quality was evaluated in desirable range for drinking. The developed index was forecasted using the Bayesian network model under eight structural strategies and the best-case strategy was selected according to mean absolute relative error (MARE) and correlation coefficient (R). The best strategy was forecasted next month's groundwater quality with MARE of training and test respectively of 1. 932% and 0. 992%. This strategy was able to forecast the following month with good accuracy with predictor parameters such as return water, discharge, precipitation, temperature, and quality of this month. The results of this study can assist managers to better conserve and manage aquifer.

The purpose of this study is to evaluate the evaporation and seepage losses in different dams' reservoirs operation policies. In the present study, in order to assess water losses, water supply deficiency and reservoir efficiency indices from 2012 to 2018, first, the operation policy of the Generalized Reduction Gradient (GRG) formulated, then the mentioned indices for the generalized reduction gradient, the current operation and the proposed rule curve estimated and compared. The Seep/w numerical model calibrated using vibrating wire piezometers to accurately estimate the seepage value. The results showed that the GRG improved the annual seepage, evaporation and deficiency indices by 67. 86%, 54. 24% and 67. 68%, respectively. Moreover, the improvement of the reliability, reversibility, vulnerability and flexibility indices were 368. 95%, 110. 26%, 67. 68% and 4750. 40%, respectively. This policy also improved the annual evaporation deficiency indices by 15. 88% and 41. 86% respectively, compared to the current operation policy. The improvement of this policy in terms of reliability, reversibility, vulnerability and flexibility indices obtained 25. 54%, 30. 34%, 41. 86% and 125. 15%, respectively. Interestingly, this policy had an 18. 65% growth in comparison to the current operation policy. Therefore, the GRG optimization policy is optimally effective in improving deficiency, evaporation losses, and reservoir's flexibility indices. This approach is recommended to be used for the assessment of reduction in evaporation and seepage losses and deficiency of water supply and also for the enhancement of reservoir performance for other reservoirs.