Flood is one of the most destructive and frequent natural disasters, causing extensive human and financial losses worldwide. This research aims to delineate floodplains and assess flood risk in the Qarah-Su River located in Kermanshah Province, Iran. In this study, the hydraulic model HEC-RAS was used in both Steady State and Unsteady (Unsteady) flow conditions to simulate floods with various return periods (2 to 1000 years). To estimate peak flood discharge in an ungauged area (Doab Qaranji), two methods, the Area-Discharge method and the SCS Unit Hydrograph method, were utilized. The geometric data required for the model were extracted from a Digital Elevation Model (DEM) using the RAS Mapper module. Furthermore, satellite imagery from Sentinel-1 (radar data), Sentinel-2, and Landsat-8 on the Google Earth Engine (GEE) platform, along with NDWI and MNDWI indices, were used to extract actual flood extents and compare them with the model results.   

Climate change or climate change means any distinct change in the expected patterns of average weather conditions, occurring over a long period of time in a specific region or for the global climate as a whole. Climate change refers to abnormal changes in the climate within the Earth's atmosphere and its consequences in different parts of the planet. Feedbacks from climate change are variable and may increase or decrease these internal factors. Many internal changes in climate systems occur with a delay. Because the Earth's climate system is so large and slow-moving, it responds to inputs with a lag. In the 1980s, the terms global warming and climate change became more common. Although the two terms are sometimes used interchangeably, scientifically, global warming refers only to the increase in the Earth's surface temperature, while climate change describes changes in the Earth's climate system as a whole. Scientists, politicians and the media now use terms like climate crisis or climate emergency to talk about climate change, and global warming instead of global warming. The Intergovernmental Panel on Climate Change (IPCC) says that the climate changes observed around the world are very likely caused by human-induced factors. The Synthesis Report of the IPCC Sixth Assessment Report (AR6) is a summary of the latest findings on climate change, its broad impacts and risks, and climate change mitigation and adaptation. The report is organized into three sections: 1. Current status and trends; 2. The future of climate change, risks and long-term responses; and 3. Short-term responses. It recognizes the interdependence of climate, ecosystems and biodiversity, and human societies; the value of different types of knowledge; and the close links between climate change adaptation, emission reduction, ecosystem health, human well-being, and sustainable development, reflecting the increasing diversity of stakeholders in climate action. In this study, according to the latest IPCC report, the sixth report of   2-4.5,   1-2.6,   5-8.5 and Historical reports will be studied at Kermanshah Synoptic Station for minimal, maximum temperature variables.    Key Words: Climate Change, Global Warming, Ecosystem, Synoptic    Climate change or climate change means any distinct change in the expected patterns of average weather conditions, occurring over a long period of time in a specific region or for the global climate as a whole. Climate change refers to abnormal changes in the climate within the Earth's atmosphere and its consequences in different parts of the planet.

December 2017, and the lowest chlorophyll a concentration in February 2017  

The Heshilan Wetland serves as a temporary resting place for migratory birds and plays a significant role in the growth of specific plant species, the nourishment of groundwater, and the climate of the province. The unique economic values of the wetland, such as the presence of small and large islands with recreational and tourism potential, the exploitation of reeds, pastures, and the promotion of agriculture and livestock farming, have attracted people to this natural environment. This study was conducted with the aim of calculating the environmental water needs of the Heshilan Wetland under various climatic conditions, based on a comprehensive method. In this study, all social, economic, ecological, and hydromorphological indicators were considered, and by valuing and selecting indicators for each section, the aquatic bird, the Eurasian coot, was chosen as the final ecological indicator due to its highest degree of importance. To estimate the area of the water surface and vegetation cover of the Heshilan Wetland from 2000 to 2024, Landsat satellite images and the software ENVI and ARC GIS were utilized. To calculate the environmental water needs of the wetland, the relationship between the area of the wetland's water surface and the number of Eurasian coots under targeted conditions was examined at three levels, resulting in the conclusion that the volume of water required to achieve optimal, acceptable, and minimum conditions is 1,240, 900, and 580 thousand cubic meters, respectively. The results indicated that to maintain the volume of the wetland under drought and normal conditions, in order to meet the minimum acceptable ecological conditions, approximately 5.40 and 0.3 million cubic meters of water per year will be needed in the first six months of the water year, while there will be no shortage during the first six months of the water year under wet conditions. Therefore, as a management strategy, by creating new water inflow sources to the wetland through the irrigation and drainage canal of the Gavshan Dam, the required water can be supplied without harming other consumers, bringing the water level of the wetland to the targeted ecological level. These results can assist policymakers and water resource managers in taking more effective actions to preserve and manage aquatic ecosystems in the Heshilan Wetland basin.   

      Determining changes in underground water reserves,especially in arid and semi-arid regions, is a vital issue for managing and planning underground water resources.GRACE sateiiite produces changes in water storage with a spatial resolution of 1degree by using the changes in the earth`s gravity field.In this research,it was tried in two cells of one square degree of Kurdistan province (Dehgolan and Qorveh plains and bijar plains), along the geography of 47 to 48 degrees east,which include a part of the total ares of the aquifer.Using the data of two   data processing centers of GRACE satellite named JPL and CSR ,the changes of monthly underground water level in the period of August 2002 to june 2022 have been evaluated.Using the values of ground water availability (TWS) produced from GRACE satellite data,snow equivalent water and water stored in the canopy of plants extracted from the GLDAS model , which has a spatial resolution of 1 resolutio   of   1 degree and Monthly statements are provided.to estimate the monthly changes in the underground water ievel.Also , an estimate of the monthly changes in the GLDA   model was obtained at a resolution of 0.25 degree in order to compare with the results of the GRACE satellite data.Monthly observation data from piezometric wells of the study area , which were used to validate the resultsThe results show that ,except for a few months, in most of the study period ,the estimation made by all the data of different GRACE processing centers is more than the values obtained from the observational piezometric weel data.It should be noted that values estimated by the GLDAS model show a more suitable estimate compared to the GRACE, data compared to the observational data.Also, based on the MAE and RMSE statistical indicators, it can be concluded that the data produced in the GLDAS model is a more accurate estimate and closer to the reality than the data of piezometric wells and the CSR processing center of the GRACE satellite.

 Abstract  Iron is one of the essential micronutrients necessary for thesurvival of plants, as it plays a crucial role in chlorophyll synthesis andmaintaining the structure and function of chloroplasts. This micronutrient actsas a component of vital enzymes such as cytochromes in the electron tra  ortchain. Due to the solubility and absorption capabilities of iron oxide andsilica-coated iron oxide nanoparticles in plants, they can be utilized aseffective nano-fertilizers for plant growth. In the present study, iron oxideand silica-coated iron oxide nanoparticles were evaluated as nano-fertilizerson the germination and growth characteristics of the Soheil variety of Camelinaunder completely randomized design (CRD) with three replications in both invivo and in vitro conditions. The synthesis of iron oxide nanoparticles wasperformed using the co-precipitation method, while silica-coated iron oxidenanoparticles were synthesized using the sol-gel method. Variouscharacterization analyses (SEM, EDX, FTIR, DLS, and Zeta potential) confirmedthe effective synthesis of nanoparticles. Germination traits includedgermination percentage, root length, shoot length, number of primary leaves, anddistance between primary leaves from cotyledons, while growth traits includeddays to budding, days to pod formation, days to maturity, plant height, numberof pods on the main stem, number of pods on side branches, number of pods perplant, number of branches per plant, and number of seeds per pod. Aftertreating Camelina seeds with different concentrations of iron oxide andsilica-coated iron oxide nanoparticles (20 to 100 mg/L) through nano-primingand planting seeds in MS medium for one week, the germination percentage wasmeasured. Results indicated an increase in seed germination percentage due totreatment with iron oxide and silica-coated iron oxide nanoparticles up to aconcentration of 100 mg/L in both in vivo and in vitro conditions. In Camelina plants,the maximum root length was observed at a concentration of 80 mg/L of ironoxide nanoparticles compared to the control. An inhibitory effect of highconcentrations of silica-coated iron oxide nanoparticles on root growth wasalso noted, with the lowest root growth observed at a concentration of 20 mg/L.According to this research's results, nano-priming treatment of Camelina seedsunder in vivo conditions showed positive effects on budding at concentrationsup to 80 mg/L for iron oxide nanoparticles and up to 60 mg/L for silica-coatediron oxide nanoparticles. Pod production on the main stem performed best atlower concentrations up to 60 mg/L for silica-coated iron oxide nanoparticlesand up to 20 mg/L for iron oxide nanoparticles on side branches. Seedproduction in Camelina also showed optimal performance at lower concentrationsup to 20 mg/L for silica-coated iron oxide nanoparticles and 40 mg/L for ironoxide nanoparticles. The production of side branches and the number of pods onthem increased with concentrations up to 20 mg/L for iron oxide nanoparticlesand 60 mg/L for silica-coated iron oxide nanoparticles. The results of thisstudy demonstrated that concentrations ranging from 20 to 80 mg/L for ironoxide nanoparticles and from 20 to 60 mg/L for silica-coated iron oxidenanoparticles have potential as nano-fertilizers in Camelina plants. Thisresearch indicates that iron oxide and silica-coated iron oxide nanoparticles

   One of the most important pests that attack agricultural and greenhouse plants and in case of severe damage causes changes in the shape of the fruit and leaves of the plant, is onion trips Thrips tabaci Lindeman (Thysanoptera: Thripidae). In the current research, population fluctuations and spatial distribution of this pest were investigated in the field conditions of the Canyon variety beans in Sanandaj city (Kurdistan province) in the years 1401 and 1402. Bean leaf was selected as sampling unit. Sampling was done on a weekly basis, and for this purpose, 52 bean plants were selected in each turn, and three lower, middle and upper leaves were selected from each bean plant, and the leaves were shaken on a white tray, and then the thrips inside the tray was transferred into Eppendorf containing 75% ethyl alcohol by a soft brush. The results of this study showed that the population of onion thrips was active in the field from July and gradually increased their activity and density so that the highest population of onion thrips in 1401, in the first week of August with Average (11.65±0.14) and in 1402 at the end of August with an average (11.29±0.23) thrips was observed in the sampling unit. Also, the highest mean number of onion thrips was observed with a significant difference in the lower leaves compared to the middle and upper leaves of beans. The results of the spatial distribution of the pest showed that according to both Taylor and Iowa methods, the spatial distribution of onion thrips was uniform. In general, the results of this study showed that onion thrips population reaches its peak in August in both years studied. Also, the Iowa method was evaluated as more suitable than the Taylor method for estimating the spatial distribution of the pest.

   Judas thrips, Thrips vulgatissimus Haliday is one of the species living on Judas trees and shrubs. In this study, in addition to the faunistic investigation of thrips associated with Judas trees, population fluctuation and spatial distribution of this species were studied in the Arghavan Strait located in Ilam city during the years 2022-2023. Four branches of 20 cm on each tree in different geographical directions were selected as the sampling unit. Sampling was done every three days, the branches of Judas trees were shaken on a white plastic tray, and then the thrips were transferred with a soft brush into an Eppendorf tube containing 75% ethyl alcohol. Totally, 10 thrips species belonging to six genera from four different families were collected and identified from the flowers of the Judas trees located in the Arghavan Strait. The results showed that the Judas thrips population has two population peaks. The first population of Judas thrips was observed on the first day of April 2023. The highest population density of Judas thrips was obtained in the first peak with an average of 30.60 ± 6.23 and the highest density in the second peak with an average of 73.75 ± 7.64 thrips per sampling unit. The results of spatial distribution based on Taylor’s power law methods showed that the spatial distribution was aggregated. In addition, geographical directions had no significant effect on the density of Judas thrips. In general, the results of this study showed that the population density of Judas thrips is higher at the beginning of the season and in the first generation, which is proportional to the flowering time of Judas trees.

   Oak forests located in the western part of country represent a significant ecological advantage due to their rich biodiversity. These forests include diverse species of oak, Quercus   . Mismanagement and adverse climatic factors make this valuable ecosystem prone to attack by pest insects and the pest insects also accelerate the process of forest deterioration. These pest insects not only cause damage to the forests but also expedite the process of forest deterioration. One of the major pests that target oak trees in the Zagros region is the acorn weevil, Curculio glandium Marsh (Col.: Curculionidae). The larvae of this insect feed on the internal contents of the oak fruits, leading to their damage. Consequently, this disturbs the natural process of the regeneration and hampers the forest's ability to regenerate naturally. This study was conducted in 2022-2023, simultaneously in Dalahu and Islamabad oak forests. From the beginning to the end of the growing season, oak trees were regularly visited and sampled. Oak fruits were randomly collected, than the data were collected and recorded. In the laboratory, infested samples were dissected under a microscope. The biological stages of the pest, such as the place and time of egg laying, the hatching time, the larval stages, the occurrence of the adult insect, morphological characters and natural enemies were investigated. Based on the collected data and climatological data of the region, the peak population in Dalahu was determined on the 20th of Mehr (2022) and in Islamabad West on the 12th of Mehr (2022).The acorn weevil, Curculio glandium, shows an annual life cycle, completing one generation per year. The spatial distribution pattern in Dalahu was determined to be of the cumulative type, while in Eslamabad-e  Gharb it was found to be of the random type. The results of this study are effective in improving management measures to control this acorn weevil pest. Keywords: Biological agents, Forest, Acorn feeders, Oak, Western country, Kermanshah

The quantitative and qualitative limitations of water resources and the increase in population are among the cases that show the need to pay attention to how water is consumed and deal with the problems caused by water scarcity by planning water resources and providing methods for their optimal use. make; Therefore, one of the pillars of water resources management is the optimal use of the reservoirs of the country's dams as the main sources of surface water, and this issue has a special importance and place in the science of dam engineering. In this research, first, using the new K-means clustering method, the flow >  

The quantitative and qualitative limitations of water resources and the increase in population are among the cases that show the need to pay attention to how water is consumed and deal with the problems caused by water scarcity by planning water resources and providing methods for their optimal use. make; Therefore, one of the pillars of water resources management is the optimal use of the reservoirs of the country's dams as the main sources of surface water, and this issue has a special importance and place in the science of dam engineering. In this research, first, using the new K-means clustering method, the flow >  

Abstract Research Aim: Floods cause extreme and irretrievable human and economic loss. Estimating flow of floods leads to designing hydraulic structures in order to prevent flooding. The aim of this thesis is to find a formula to predict the flow of floods using physiological parameters in ungagged stations. Research method: In this research at first the most important and effective factors to estimate peak flow would be investigated. Then the parameters would be probed through Exploratory factor analysis technique and the most sufficient ones would be chosen. In order to increase the accuracy of this investment, dimensionless parameters were used. Afterwards regression analysis relates a dependent variable, which is discharge, to explanatory variables and generates equations for estimating the peak flow. To achieve more complicated and more accurate formula and also increase coefficient of determination utilizing genetic programming algorithm is helpful. Findings: The most important factors to affect floods through some recurrence intervals included 2, 5, 10, 25, 50 and 100 years were examined and some formulas were presented as a way to predict peak flow. Conclusion: Efficacious factors in estimating peak flow are drainage area, storage, lake area, annual runoff and slope of watershed. Implementing dimensional analysis and genetic algorithm gives some equations to predict peak flow which the coefficient of determination is more than using regression. Keywords: Peak flow, Regression, Non-dimensional parameters, Factor analysis, Genetic Programming هدف از اين پژوهش پيش بيني دبي پيك در مناطق فاقد داده‌هاي آماري با استفاده از پارامترهاي بدون بعد مي¬باشد.

  The phenomenon of climate change can have many negative effects on various systems including water resources, environment, industry, health, agriculture and all systems that interact with the climate system, among which the resource system Water is one of the main ones. The phenomenon of climate change in recent years has led to a significant change in meteorological elements and as a result the condition of surface and underground resources in different places. On the other hand, the three sources of water, energy, and food are the three basic sources for human health, poverty reduction, and sustainable development, and they are among the most important sources in agriculture that both affect climate change and are affected by it, and are strongly dependent on each other. All three resources are very scarce and billions of people in the world do not have access to them, and the demand for all three resources is growing. Therefore, any action towards sustainability should consider the interaction and integration of these three sources in order to achieve sustainable development. According to these conditions, achieving sustainable management of available resources in agriculture in an effective and coordinated manner is a challenging issue. Therefore, if it is possible to increase the efficiency of water and energy to supply food, the emission of greenhouse gases and environmental pollution will also decrease, and after that, we can take steps towards sustainable development. In other words, if an approach towards the integrated management of three sources of water, energy and food is considered, both environmental pollution will be reduced and sustainable agriculture and sustainable development will happen. will follow; Because despite the interactions between these three sources and sustainability, focusing on one source without considering the relationship with other sources may cause unexpected acute and even unsustainable consequences. The aim of this research is to simulate and optimize the combined use of surface and underground water in the Kermanshah plain under the conditions of climate change based on the sixth report of the Intergovernmental Panel on Climate Change (IPCC-6). For this purpose, a coupled integrated model of surface and underground water will be prepared, in which the WEAP evaluation model is used to prepare the surface water model and the MODFLOW model is used to prepare the underground water model. Then the effect of climate change on surface and underground water modeling will be investigated in the integrated model. Finally, by connecting the gray wolf multi-objective algorithm (MOGWO) to the body of the coupled model based on objective functions based on the correlation of water, food and energy and social parameters and environmental factors, optimal solutions for the integrated management of water resources in the region under climate change scenarios will be investigated. And its effects on surface and underground water will be evaluated.

Fromthe past to the present, the need for water and its provision in different waysis one of the most important issues in human societies, and of course,atmospheric precipitation is of particular importance. In recent decades,satellite precipitation data has been considered by scientists and engineers ofhydrology.Consideringthat the data obtained using ground stations are point-by-point and also thereis not enough data in large areas and hard-to-reach areas, and due to globalwarming and decreasing rainfall, long-term rainfall forecasts are necessary forplanning and appropriate use of available water resources for the region.Inthis study, the accuracy of precipitation data of CHRIPS, ERA5, PERSIAN_CDR,GPM, GSM, TRMM, TERRA satellites obtained using Google Earth Engine cloudenvironment was obtained with data from 14 synoptic stations of Kermanshahprovince in three monthly, seasonal and annual scales in the period 2000 to2019.Then,precipitation prediction was performed using observational and satelliteprecipitation data in three modes of precipitation with one, two and three lagsin Orange software environment and using decision tree, support vector machineand random forest machine learning algorithems as well as delta downscalingwith canesm5 and KIOSTESM climate models, sixth report and scenario   5_8.5.Afterselecting the best prediction model, drought indices were calculated forobservational data, satellite, and prediction for Kermanshah province. Theresults showed that for Islamabad, Harsin, Gilan-e Gharb, Kermanshah, Kangavar,Ravansar and Sarpol-e-Zahab stations, TERRA satellite and for Sonqor, Sararoud,Sumar and Tazeh Abad stations, EAR5 satellite and for Qasre-shirin of TRMMsatellite has the best estimate.Accordingto observational data, prediction and reverse distance interpolation maps,precipitation in the north and northwest as well as southeast of the province,i.e. in Sar-e-Aroud, Javanrud and Ravansar stations, was more than other placesand in Harsin, Qasr-e-Shirin and Sumar stations had the lowest amount. Theresults of prediction showed that the decision tree model with appropriateerror criteria is better than the other two models and also according tointerpolation maps, the prediction with a delay has better estimated the lowrain and rainy areas in the observation period.This model has estimatedrainfall in most stations in October and November about 40% less thanobservations. The results of drought indices were calculated the   I, RAI and SPIindeces for different states and the results showed that 2015 estimated verysevere drought, severe drought and near normal drought, and for 2020, 2028 and2035, severe or moderate drought was estimated.  

    Water resources management planning is one ofthe most practical and necessary human measures to preserve and preserveavailable fresh water resources, since available freshwater resources arelimited, finding a balanced relationship between environmental needs and humanneeds is an important step in the sustainability of water resources. For properplanning for water resources management in the first place, having sufficientand reliable climatic parameters and hydrology based on which the mostappropriate planning can be necessary.In thisresearch, first, the existing data of the hydrometric stations under theGamasiab basin have been investigated by different methods and prepared forprediction, purification and reconstruction of the data, and differentdimensions of dependent variables, taking into account the spatial dimensions ortime dimensions of the parameters, have been created in two differentscenarios, in each scenario, 80% and 20% of the data have been used to trainand test the model, respectively. Also, using principal component reductionmethods, appropriate dimensions are selected and modeled by genetic algorithmin Python programming environment using known methods of machine learning andoptimization. Finally, according to the percentage of matching and validationof each of these methods, the most accurate option and prediction method havebeen selected.Theresults of prediction and data purification in the first scenario (by spatialmethod) showed that the results were more favorable in the conditions that thedata were standardized and also the results of the non-temporal approach werebetter than the time series in similar situations, so that the highestcoefficient obtained from NSE for the data of the training stage was 0.85 andfor the testing stage was 0.6. In general, the best result in this scenario isrelated to the non-temporal approach and by selecting the model feature by theSVR model optimized by genetic algorithm.Ingeneral, prediction and data purification are influenced by different factors,the results of this study showed that data processing, taking into account thetime sequence of data, reducing the input dimensions of the model and usinggenetic optimization algorithm have the greatest impact on obtaining thedesired result and with high accuracy for accurate prediction and purificationof data, respectively.

  امروزه اثرات تغيير اقليم و گرمايش جهاني به دليل افزايش گاز‌هاي گلخانه‌اي در جهان به اثبات رسيده‌است. وقوع اين شرايط، فرآيند‌‌هاي هيدرولوژيكي را كه از منابع اصلي تامين كننده آب حوضه است را تحت تاثير قرار مي‌دهد. در اين تحقيق مقادير ماهيانه دما، بارش و دبي سد جاميشان در سال‌هاي ????-???? به عنوان دوره پايه در نظر گرفته شده‌‌‌است. شبيه سازي منابع و مصارف حوضه آبريز سدجاميشان   با استفاده از مدل   WEAP و روش SVR با الگوهاي كشت موجود در منطقه مورد بررسي قرار گرفت. براي ارزيابي تاثير تغيير اقليم بر پارامترهاي بارش و دما در اين منطقه از خروجي‌هاي سناريو RCP8.5 مدل هاي HADGEM2_ES ، FLO_ESM، MIROC5 و CNRM_CM5 از سري مدلهاي گزارش پنجم   CMIP5 استفاده شد و خروجي اين مدل‌ها براي منطقه مورد نظر ريزمقياس شد. در اين پژوهش با استفاده از روش عامل تغيير داده‌هاي مدل اقليمي ريزمقياس شده و پارامترهاي ماهانه دما و بارش سد جاميشان براي دوره‌ي ????-????   توليد گرديد. به منظور بررسي رواناب منطقه مورد نظر در اثر تغييراقليم به بررسي و مقايسه‌ي مدل‌هاي SVM، GEP و IHACRES پرداخته‌شد. نتايج مدل‌ اقليمي به طور ميانگين افزايش دماي ?/? تا ? درجه سلسيوس را نشان مي‌دهد. همچنين نتايج بارش شبيه سازي شده نشان مي دهد كه   ميانگين بارش ماهيانه تحت سناريو ?/?   RCP در دوره آتي به جز در مدل HADGEM2_ES با كاهش بين ? تا ? درصدي نسبت به دوره پايه همراه بوده است كه بيشترين كاهش مربوط به مدل MIROC5 و كمترين كاهش مربوط به مدل CNRM_CM5 مي باشد. به طور كلي بررسي نتايج حاصل از پيش‌بيني دبي در هر سه مدل SVM، GEP و IHACRES حاكي از كاهش رواناب است كه بيشترين كاهش رواناب مربوط به SVM در مدل اقليمي FLO_ESM با ?/?? درصد و كمترين كاهش رواناب مربوط به IHACRES با ? درصد مي‌باشد و در اين پژوهش مدل‌هاي IHACRES و GEP نسبت به روش SVR از دقت مطلوب‌تري برخوردار است. شبيه‌ سازي الگو كشت‌هاي مختلف در WEAP نشان مي‌دهد بيش‌ترين تامين برابر با ?/?? درصد در مدل GEP و كمترين تامين برابر با ?? درصد در مدل SVR كه به ترتيب مربوط به الگوي كشت يك و الگوي كشت سه مي‌باشد. همچنين در شبيه‌سازي تحت سناريوي الگو كشت‌هاي مختلف در WEAP بيش‌ترين درصد پر بودن مخزن در الگوي كشت سه و برابر با ?/?? درصد و بيش‌ترين درصد خالي بودن مخزن در الگوي كشت يك و برابر با ?/?? درصد كه به ترتيب   مربوط به مدل‌هاي IHACRES و SVR مي‌باشد. . همچنين در اين پزوهش با استفاده از روش SVR   به پيش‌بيني تامين ماهيانه نيازهاي كشاورزي   پرداخته شد. نتايج تامين نيازهاي كشاورزي منطقه در همه ي مدل هاي اقليمي حاكي از آن است كه بيشترين تامين مربوط به مدل   GEP در الگوي كشت شماره سه(بيشترين ميزان درآمد) و كمترين تامين مربوط به مدل   SVR   الگوي كشت شماره يك(شرايط موجود) مي باشدواژه­هاي كليدي:

The average annual rainfall in Iran is less than one third of the average annual rainfall in the world. Therefore, in the coming years, it will face serious and risky problems in the field of water resources shortage. That is why the optimal use of these limited water resources is vital and important. One of the complexities in this field is the contradiction of goals in the issues of water resources Exploitation. In this research, for the optimal operation of Dez and Balaroud dams, the coupled simulator-optimizer method was used using the connection of WEAP simulator model and MOICA multi-objective optimizer algorithm. Also in this research, surface water resources in Dez river, from Dez regulatory dam to the end of the study area and near Bandaqir site were investigated quantitatively and qualitatively. exploratory algorithms have been considered by water resources planners due to their ability to solve complex and nonlinear problems. Data and information for two scenarios in a period of 30 years (1397-1367) were defined in the simulator model. In the first scenario, referred to as the reference scenario, without performing the process of optimizing the environmental flow downstream of the study area and near the site of Bandaqir, it was equated with the environmental flow by the Montana method. In the second scenario, called the optimal scenario, the simulator and optimizer models were connected with the aim of optimizing the amount of environmental requirements at the bitumen dam site. In this study, three goals were considered, The first goal is to maximize the total percentage of needs met throughout the system, The second goal is to minimize the amount of violation of the allowable values of quality parameters in the river route And the third goal is to minimize the penalties for violating the authorized capacity of the reservoirs. In the MOICA model with a population of 24 and 1000 replications, the optimal results were plotted on the Parato graph. The final results for each scenario were obtained and compared. The results obtained from the optimal scenario showed, That the supply of demand has increased And qualitative parameters in the river route have found a more favorable situation, Also, the status of reservoir volume changes has improved compared to the reference scenario. Therefore, applying the optimal scenario causes, That the condition of the tanks does not fail in the dry and watery months And do not cause much damage to the system. According to river water quality standards, The worst BOD pollutants are in the Haft Tappeh factory area And EC has been in the place of   Bandaqir and sugarcane Dehkhoda. The final results show The simulated-optimized coupled model has not only sought to increase the percentage of supply in the system It has also paid attention to the standard level of quality parameters in the river route and the status of reservoir reserves. Based on the reference scenario and the changes seen in the volume of the tanks, the volume of the tank has reached the minimum level of operation many times during the 30-year simulation period. However, during the optimization process, none of the tanks have reached the minimum level of operation. Using the simulated-optimized coupled model and using the WEAP model and MOICA  algorithm can be a suitable way to plan and manage water resources in the study area and taking into account all the demands in the area. In fact, in addition to providing acceptable needs, it also examines the trend of quality and pollution in rivers.

بارش از اجزاي اصلي چرخه آب­شناسي و ورودي مورد نياز بسياري از مدل­هاي آب و هوايي و آب­شناسي است. كمبود داده­هاي قابل اعتماد و كامل از مهم­ترين چالش­ها در واكاوي   بارش و پيش­بيني­هاي آب­شناسي در مديريت آب است. طي ساليان اخير تخمين بارش با استفاده از ماهواره­ها توانسته است به­عنوان يك راهكار نوآورانه مورد توجه قرار گيرد. داده­هاي ماهواره­اي با فراهم آوردن پوشش مكاني كامل، قادر به تخمين بارش براي كل جهان است. براي تبديل مقادير بارندگي مستخرج از تصاوير ماهواره­اي در ماههاي مختلف به سري مكاني-زماني مقادير بارندگي زميني، ابتدا دقت تصاوير ماهواره­اي TRMM و GPM نسبت به مقادير زميني ثبت شده مورد بررسي قرار گرفت. تصاوير GPM نسبت به TRMM همبستگي بيش­تري با داده­هاي زميني داشت. به­منظور شبيه­سازي مكاني- زماني بارش در كل دشت مدل­هاي مختلف شبكه عصبي مورد ارزيابي قرار گرفت و در آخر خروجي مدل ORELM داراي بهترين برازش با داده­هاي مشاهداتي با مجذور ضريب همبستگي برابر با 96/0 بود، همچنين داراي بهترين و نزديك­ترين پراكندگي نقاط در اطراف خط 45 درجه بود و از اين نظر دقيق­ترين مدل محسوب مي­شود. براي اطمينان از انتخاب درست مدل برتر از دياگرام تيلور نيز استفاده شد، نتايج نشان داد نزديك­ترين نقطه به نقطه مرجع مربوط به روش ORELM مي­باشد، لذا براي تبديل بارندگي حاصل از تصاوير ماهواره­اي به بارش زميني از اين مدل استفاده شد. در تحقيق حاضر سعي بر آن شده است كه با دست يافتن به اطلاعات حاصل از تصاوير ماهواره­اي در منطقه مطالعاتي بتوان اطلاعات جديدي از نوسانات منابع آب زيرزميني منطقه و منابع محرك در تغذيه و تخليه منابع آب زيرزميني دشت ميان­دربند به­دست آورد. هم­چنين به پيش­بيني تراز آب زيرزميني دشت با استفاده از تصاوير ماهواره­اي بارش و مدل كوپل شده WEAP-MODFLOW با هدف مديريت صحيح منابع آب پرداخته شده است. در اين تحقيق براي اولين بار تصاوير ماهواره­اي در يك مدل تلفيقي-ديناميك استفاده شده است. در مدل كوپل شده WEAP-MODFLOW مقدار بارندگي روي دشت و تغذيه ناشي از بارندگي و آب آبياري در سطح كل دشت با استفاده از شبيه­سازي ناحيه غيراشباع خاك(مدل رطوبت خاك) و براساس تركيب مدل شبكه عصبي مصنوعي ORELM و تصاوير ماهواره­اي در هر يك از مناطق همگن(60 ناحيه مختلف) در طول دوره شبيه­سازي(اكتبر 2000 تا سپتامبر 2020) محاسبه شد. نقشه تراز آب زيرزميني براي تمام ماه­هاي دوره شبيه­سازي مورد محاسبه قرار گرفت و براساس آن­ها تغييرات در ماه­هاي خشك و تر و حتي تحت تأثير وقايع حدي و بارش­هاي سنگين مورد بررسي قرار گرفت. نتايج نشان داد ميزان متوسط افت تراز آب زيرزميني با در نظر گرفتن كل سطح آبخوان كرمانشاه در پايان دوره بهره­برداري 20 ساله(اكتبر 2000تا سپتامبر 2020) حدود 3 متر است.

Abstract    Separate exploitation and management of groundwater and surface water resources can cause serious damage to any of the resources and cause problems such as lowering the water level, increasing harvesting costs, damage to the environment and, etc. These problems and the effects of climate change on water resources can exacerbate the damage. For this reason, in this study, at the first, climate change was extracted based on the output of CMIP5 series models in Kermanshah plain and then the interaction of groundwater and surface water was simulated through dynamic connection of surface and groundwater resources and coupling with climate parameters. In this method, data and results are circulated any monthly time step between MODFLOW and WEAP models and the output of CMIP5 series models, so that in the basic period, the values ??of harvest, runoff, river level from WEAP model were entered MODFLOW model to calculate the level and volume of aquifer storage, etc. and returned to the WEAP model. In this shuttle between the two models, the output of climate change models (AR5) is added that the coupled model be simulate and predict surface and groundwater resources in the situation of climate change. The base period was selected from October 1991 to September 2018, then the first three periods (2018-2045), the second (2045-2072) and the third (2072-2099) under four release scenarios RCP2.6, RCP4.5, RCP6.0, RCP8.5 were simulated. The results in the base period show that the average groundwater level at the end of the period decreased by 4.3 meters and the final balance of the plain is negative 9.37 (MCM/Year). Rainfall changes at RCP2.6 scenario respectively in the first, second and third periods, the highest increase in precipitation in March, December and March by 7.79, 1.81 and 4.87 mm and the largest decrease in February, April and May will be 4.42, 8.74 and 13.37 millimeters. The simulation results of the model coupled with this scenario show that the Kermanshah aquifer increased by 19 cm in the first period and the positive balance that is 56,000 cubic meters per year, and in the second and third periods respectively decreased by 0.81 and 1.9 meters and the negative balance of 3.6 and 5.8 (MCM/Year), Will experience. In RCP4.5 the highest increase in precipitation in the first period and March by 5.1 mm and the highest decrease in the first, second and third periods in May, April and May will be 6.3, 12.1 and 16.9 mm, and in the simulation results, the reduction of the level, that forecast is respectively, 0.45, 2.82 and 2.62 meters, and negative balances of 1.73, 9.12 and 9 (MCM/Year). In RCP6.0, the highest increase of precipitation in the first period and March will be 6.39 mm and the highest decrease in the first, second and third periods in May, April and May will be 9.89, 12.25 and 16.07 mm. In the simulation results, the reduction of the level is respectively predicted to 1.02, 3.27 and 2.79 meters, and the negative balance is predicted that 3.2, 10.4 and 9.7 (MCM/Year). In RCP8.5, the highest increase of precipitation in the first period and March will be 3.31 mm and the highest decrease in the first, second and third periods in February, February and May will be 6.37, 14.28 and 18.9 mm. And in the simulation results, the level decrease is respectively predicted to be 1.12, 4.41 and 3.35 meters, and the negative balance is predicted of 3.37, 13.4 and 11.73 (MCM/Year). Keywords: Climate Change, Fifth Report (IPCC5), Conjunctive use, Surface and Groundwater Interaction, MODFLOW, WEAP, Balance      

   Nowadays water resources are one of the great treasures of human beings, for which proper operation requires effective rules and management regarding the different demands, lacks and limitations in using the resources. Dams are applied for different purposes. Optimal operation of dam reservoirs is one of the important issues in water management. In this study, optimal operation of dam has been examined in order to supply maximum dam tailwater needs, in deterministic and probabilistic system. The case study is Qeshlaq dam constructed on Maryamnegar River, 15 Kilometer northwest of Sahneh in Kermanshah province. The aim of Qeshlaq reservoir dam construction is supplying drinking water demand in Sahneh, providing environmental and agricultural demands of Chemchemal valley and establishment of irrigation network in Sahneh city. Water management simulation and planning of this area was done by WEAP simulator software. Regarding the precipitation being indecisive and its direct effect on the inflow, probabilistic flow is more certainly. Therefore, the system probabilistic conditions were studied by making the inflow probabilistic and examining the effect of probabilistic cumulative distribution function (CDF) on demand supply. This probabilistic approach was codded in Lingo software based on definite optimization by linear planning under probabilistic limitations. In this approach, the inflow to reservoir was compared using two different ways including CDF calculation by Weibull distribution and the best fitness distribution. The results of simulation and optimization by deterministic approach shows that supplies in agricultural, drinking, and environmental demands are, respectively, 92%, 95% and 95%. Due to reservoir inflow decrease in probabilistic than deterministic approach, the reservoir optimal volume was, first, estimated considering the inflows and deterministic demands. It was 27.6 Million cubic meter which shows the high estimation in designing the reservoir of Qeshlaq dam than the reservoir designing volume (47.6 Million cubic meter). In addition, all demands are fully supplied in this condition.

   Due to population growth, the shortage and severe constraints of water resources in the country, one of the main steps in the management and planning of water resources   and Climate change phenomenon is to optimize reservoirs and change the cultivation pattern. In this study, simulation of the Harsin dam reservoir for Kamish River discharge from (40 years period) has used in the WEAP model. First, considering the different cultivated patterns, the reliability of domestic, industrial, agricultural and environmental was simulated in WEAP, and the crop pattern with greater sustainability of the system was selected. Then by using the LINGO model, optimization was performed with the aim of minimizing the percentage of unmet demands. According to the results, the annual average of the environmental demands, garden drip lands, sprinkler’s land and wastewater waterline, were estimated 98.98, 87.51, 89.79 and 95.63, while these values in the optimization model were equal to 100, 99.99, 99.21 and 99.12, which indicates that the percentage of shortcomings has been reached to less than 1%. The average of overflow volume in simulation and optimization models was 7.31 and 4.09 million m3/year respectively, which indicates that optimization model has the lower rate of wasted water comparing to simulation model. Finally, by applying the climate RCP scenarios, the results showed a decrease in the input flow of the Harsin Dam reservoir And the output of both HADGEM2-ao and FGOALS-G2 climatic models resulted in a maximum increase of 5 and at least 3 ° C in future periods. Based on the RCP8.5 scenario, the estimated runoff in future periods 2020-2059 and 2060-2099 is lower than the predicted runoff under RCP2.6 scenarios, which corresponds to the definition of these scenarios. Output runoff applied by the rainfall-runoff model under the RCP2.6 and RCP8.5 scenarios in the WEAP model reduced the reliability index of downstream dam requirements to below 80%. The highest reliability index for climate scenarios by HADGEM2-ao model under RCP2.6 scenario is related to industry needs, which is 77.08% in simulation mode, while this indicator in 88.42% is optimize. The lowest reliability index in the WEAP model was estimated to be 32.19%, compared to 52.71% in the LINGO model. Hence, with the appropriate planning and management, it is possible to deduct the amount of deficits significantly, especially in the field of agriculture.

  Water is a critical and critical source of harm. The increasing global population and the reduction of water resources are one of the most important challenges facing human today. Since water resources can directly affect social and economic development, it is considered to be the basis for developmental activity. One of the most important issues of the current century is the issue of global warming, which is exacerbated by the greenhouse effect and is expected to cause changes in climate variables. In the past, management decisions were made in the context of a future climate of the past. But now, a wide range of changes in the future climate is due to human activities, such as greenhouse gas emissions, by fossil and inhuman fuels such as volcanic activity. In this regard, understanding the constraints on planning water resources management and the proper understanding of the behavior of phenomena that affect the status of water resources and the implementation of policies that are appropriate and adapted to climate conditions are important. The purpose of this study was to investigate the effect of climate change on the quality and quality of the Khorramrud basin in Congarev County under RCP scenarios. For this purpose, at the outset, the output of four climatic models was extracted under RCP4.5, RCP6 and RCP8.5 scenarios for the baseline period from 2015 to 1983. The MOTP method was used to reduce uncertainty in climate models. Then, the results of the climate models were compared with the Moore period. The results indicate the proper performance of the models, and the weighted model of the model. Most climate models predict a declining trend for precipitation parameters. Long-term yields in RCP8.5 scenarios are reported to be lower than RCP 4.5 and RCP6. The results of the climate change of the temperature parameter also show an increase. The temperature changes in the period 2053 were more than the 2020 period. So, in the period 2020 under the scenario RCP4.5, RCP6 and RCP 8.5 were predicted to increase by 1, 1.5 and 2 ° C, and in the period 2053, 2, 3 and 4 ° C. In order to investigate the runoff condition of the catchment area, two models of artificial neural network and Eeyacher rainfall-runoff models were compared for the base period. The results indicate the superiority of rainfall-runoff model in Ahexers runoff simulation in Khorramrud basin. Then, in order to investigate the future runoff status of the basin, the outputs of climate models were used. The artificial neural network model was used to assess the qualitative status of the Khorramrod River catchment area. The quality parameters of total solvent solids (TDS) and sodium adsorption ratio (SAR) were calibrated for the 20 year base period. At the end of the output of the climatic models and Precipitation-Eichers runoff was used to predict the qualitative status of future river quality parameters

  Today, with the increase in population and the expansion of industrial activities, as a result of which the untapped use of water resources, the comprehensive and sustainable management of these resources is very important. The purpose of this research is to predict episodic series using ANFIS model in different climates. For this purpose, 14 series with different parameters in 7 different climates are considered for prediction with Genfis1,2,3 generators in the ANFIS model. In each modeling of the series, it is used to determine the time delays of its correlation graph.In the results of each time series in each climate, the parameter, and the different states of each of the three generators, its correlation curve is alternately cwd with ?Max=0.9. If the time delay is chosen, the correlation coefficient of the instability is Rmax>0.95. This is while reducing its pre-processing and converting its chart down to Rmax=0.75. In this series, if the time delay is chosen for the stability of the correlation graph, the prediction results are very poor and have a value of Rmax=0.2. In the parameter of precipitation this diagram in the series with ?Max=0.6 is the highest Rmax=0.62 in the series with ?Max=0.4. RMax=0.53 and in series with ?Max=0.2 the maximum is RMax=0.75.The maximum level of depth and depth of the groundwater with ?Max=0.79 is also the most maximum instabilities with R max=0.79. In the case of the Parameter Flood Parameters of the river ?Max=0.39, in the mode of the choice of time delays based on the maximum volatility, R max=0.15 occurs. And in this same series of parameters with a different climate with a maximum value of ?Max=0.62 in the case of the choice of time delays based on the maximum volatility with Rmax=0.75 occurs. Based on the results, So that the highest accuracy in a series with an alternating crossover diagram with a maximum amount of instability of close to 1 in a temperature series that is independent of the parameter occurs, and the least accurate accuracy of the series is associated with a stable graph which occurs in some indirect parameters

Using efficient policies in the operation of reservoirs has become very important due to the occurrence of periodic droughts and also limitation of water resources in Iran. The management of reservoirs is one of the most effective non-structural ways to overcome of these limitations such as water resources scarcity, water demands increasing and finally occurrence of drought. Using optimization techniques in optimal operation of water resource systems are one of the solutions that can reduce the effects of water shortages. In this study, optimal operation of Jamishan reservoir with the aim of optimal water allocation from reservoir is considered to supply the agriculture water demands of Dinavar and Chamchmal plains using stochastic and deterministic dynamic programing approaches. Applying of the water allocation priorities between release and storage targets to supply water demands in drought conditions is considered. In this study a 41-year hydrological period (from 1971 - 1972 to 2011-2012 years) has been used. Different interval of reservoir storage (3, 5, 7 and 10) and reservoir inflow (3, 5, and 7) were used for dynamic discretization of stochastic dynamic programming (SDP) model. The best reservoir and inflow and I=3 respectively. Stochastic dynamic programming was applied to Jamishan reservoir with these classes in seasonal and monthly period by several objective functions. Water allocation results and reservoir rule curve have been presented for each period. In case, 7 interval classes for reservoir storage and average monthly and seasonal reservoir inflow in each period were applied in dynamic programming (DP) model with several objective functions. The water allocation results were compared with SDP model. The results confirm that the SDP model had the better performance rather than the DP model in water allocation and reservoir rule curve with the least objective function.

  The objective of this study was to evaluate the effect of administration of equine chorionic gonadotrophin (eCG) and human chorionic gonadotropin ( hCG )   to improve Ovsynch protocol in dairy cows . Forty eight dairy cows with body condition scored ( BCS ) between 2.75 and 3.5 were divided into 6 groups in a completely randomized design: GPG group ( n = 8 ; GnRH - 7d   -   PGF2?   -   2d - GnRH - 16-20 h - TAI);   EPG group (n = 8    eCG - 7d - PGF2?   - 2d   - GnRH - 16-20 h - TAI);   GPH group (n = 8; GnRH - 7d -   PGF2? - 2d   -   hCG   - 16-20 h   - TAI)   EPH group (n = 8; eCG   - 7d   -   PGF2?   -   2d   -   hCG - 16-20 h   - TAI);   GPEG group (n = 8; GnRH - 7d   - PGF2? + eCG -   2d   -   GnRH   -   16-20 h   - TAI)   GPEH group (n = 8; GnRH   - 7d   -   PGF2? + eCG -   2d   -   hCG -   16-20 h   - TAI).   lood samples were taken on 13 day   after insemination and analysed for serum progesterone (P4) concentrations. Pregnancy diagnosis was performed 50 days post-insemination by means of rectal palpation . Our study clearly demonstrates that parity has a significant effect on pregnancy rate ( P < 0.1). Markedly   lower   pregnancy rate   was observed in animals of higher parity. Pregnancy rate at 50 days after insemination did not differ   (P > 0.05 ) between GPG, EPG, GPH, EPH, GPEG and GPEH groups. However, pregnancy rate was higher in the cows that received EPG, EPH and GPEG protocols ( 37%; 3/8)   than the cows that received   GPG, GPH and GPEH protocols (12%;1/8). Serum progesterone concentration 13 days after insemination for pregnant cows did not differ (P > 0.05) between treatments. Whereas, the serum progesterone concentratio   for pregnant cows were higher in the EPG and EPH groups tha   GPG, GPH, GPEG and GPEH groups. Serum progesterone concentration 13 days after insemination for non-pregnant cow   was found to be different (P < 0.05) between the GPG, EPG, GPH, EPH, GPEG, and GPEH groups. Furthermore, the serum progesterone concentratio   for non-pregnant cows were   higher (P < 0.05) in the EPH and EPG groups than the   GPG, GPH, GPEG and GPEH groups. Our results do show that the use of eCG   to induce ovulation in a timed artifical insemination protocol (Ovsynch ) may increase serum progesterone levels and improve fertility in dairy cows.     

     The reservoirs are operated and designed in several aims such as, water demand supply, hydropower energy generation and flood control reduction. Optimization of reservoir operation is one of the most important issues in water basin. In this study, optimization of reservoir operation to obtain the maximum agriculture water supply and hydropower energy production are considered. As the rainfall is the stochastic phenomenon and has the positive effect on reservoir inflow, hydropower optimization is applied by using chance constrained linear programming (CCLP). Maroon Reservoir is located on east western of Khozestan province and the aims of this reservoir are agriculture water supply of Jayazan, Behbahan,Shadegan and Khalafabad, flood controlling and hydropower generation about 150 Megawatt(MW). Monthly inflow of 52 years (1953-2004) is used to modeling of experimental Weibul probability distribution for each month. Annual energy production of Maroon reservoir is obtained by Lingo 16.0 software for a known agriculture water supply (P) and installed capacity 150 MW. Then, the best probability distribution of reservoir inflow is obtained by Easyfit software 6.0 for each month. The results showed that the maximum P are calculated 86% and 88% and also the annual hydropower energy are 114.86 and 111.55 Giga watt-hour(GWh) using experimental Weibul probability distribution and the best probability distribution of reservoir inflow, respectively. Thus, obtaining the best Inflow probability distribution does have insignificant effect on optimization results since in this study it’s less than 2% on agriculture water supply and hydropower generation. So, considering only the experimental Weibul probability distribution of reservoir inflow is sufficient in CCLP approach.

Weeds or invasive native plants that adverse effects on aquatic ecosystems, agriculture and forestry. In this study, weeds College of Agriculture and Natural resources include field bindweed, Convolvulus arvensis L .; licorice, Glycyrrhiza glabra L.; amaranth, Amaranthus deflexus L .; weed, Chenopodium album L .; datura, Datura stramonium L. , wild mustard, Sinapis arvensis L .; cocklebur, Xanthium strumarium L .; oats, Avena fatua L .; Gheyagh Sorghum halepense L. and Shlmy All. (Rapistrum rugosum (L. were studied. The aim of this study was to collect and identify insects associated with the above-mentioned weeds and insects for biological control of introduced species of weeds target. For this purpose, the sampling insects Tiny microscopic slides were prepared and were sent for identification to the relevant experts. based on the result of the result, 17 species of Svsk¬Hay families Chrysomelidae, (Radymna persica (Faldermann, 1837), Chaetocnema sp., Altica sp., Spermophagus sp. and Burchidius sp.), Curculionidae, (Alcidodes karelini (Boheman, 1844), Lixus sp., Ceutorhynchus sp. and Microlarius sp.) and Coccinelidae, (Scymnus frontalis (Fabricius, 1787)), Sn¬Hay family Tingidae , (Galeatus scrophicus (Saunders, 1876)); Anthocoridae, (Orius niger (Wolff, 1811)); thrips family Aeolothripidae, (Aeolothrips mongolicus (Pelikan, 1985)); Thripidae, (Chirothrips kurdistanus (zur Strassen, 1967) , Chirothrips manicatus (Haliday, 1836) and Chirothrips africanus (Priesner, 1932)) and Phlaeothripidae, (Haplothrips ganglbaueri (Schmutz, 1913)) were identified. As well as field bindweed seeds and Shyryn¬Byan in appropriate containers in the laboratory Ng·h¬Dary and seed insects and parasitoids were collected. Of the seeds respectively, field bindweed and Shyryn¬Byan weevil Alcidodes karelini (Boheman, 1844) and seed beetle Burchidius sp. Out. Also parasitoid sex Eurytomidae family through infected seeds beetles A. karelini and Burchidius sp. Collected and identified.

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