پژوهشنامه مدیریت حوزه آبخیز
پیاپی 23 (بهار و تابستان 1400)

In mountainous and snowy watersheds, runoff generated by snow melting is an important factor in changes in flow regime and plays an important role in stream water Supply and water resources. However, in such watersheds, hydrological and meteorological required data for simulation, especially snow survey data are usually not available. Therefore, there are many problems for simulation and forecasting runoff generated by snow melting. In this study, were used the degree-day and radiation base of SRM to estimate the runoff in the Beheshtabad watershed. The aim of this study was to evaluate the degree-day and radiation version of the model for estimating runoff from snow melting. Therefore, prepared the variables of classical and radiation SRM and snow cover was obtained from MODIS satellite images and then models were run for calibration period (2012-13) and validation period (2013-14). The efficiency factor (R2) in the validation period for SRM radiation model (0.71) is 13% more than the classic model (0.58) and the difference between total runoff volumes in the radiation SRM improved 7% compared to the classical model.

For the assessment and mapping of desertification and erosion models and methods were provided including, IMDPA, PSIAC and IRIFR. In this study, IMDPA model (as evaluation model of desertification potential) and PSIAC model (as evaluation model of water erosion) and IRIFR model (as also dedicated to wind erosion) has been used. Purpose of study is evaluation the water and wind erosion by IMDPA model and base on integration methods of geometric mean and maximum limitation. Then these models were compared to current state of degradation and IRIFR, MPSIAC models. Results show that proposed IMDPA model by maximum limitation has higher correlation to current state of degradation than IRIFR, MPSIAC models. Although both are significantly correlated well with the above criteria.  The results also show that erosion map conducted by IMDPA model base on geometric limitation doesn’t have significant correlation (R=-0.298) with current state of degradation, showing current method of IMDPA is not suitable. In verse, the result of the proposed model of IMDPA by maximum limitation (R=-0.925**) is the most suitable method for mapping of erosion in desert and arid regions.

The quantitative and qualitative management of urban runoff is a very complicated. Regardless of the economic and social impacts, water engineers always need to know how to respond to a citychr('39')s drainage system against different climatic conditions. In this research, the combination of ASSA and GIS models in the returns periods of 2, 5, 10 and 50 years were used to determine the flooding points in the 9th district of Mashhad municipality. First, the watershed boundaries, canals and nodes maps was extracted from the GIS environment. Then the ASSA model was simulated for a One-hour design for a different return period. Then, the outputs of the model were analyzed in the GIS software environment. The results showed that with increasing rainfall return period, 2806 nodes in underground and superficial networks of 114, 178 and 226 nodes were flooded and inundation during the return periods of 2, 5, 50 and 50 years, respectively. Field surveys, existing elevation digital maps of the urban runoff network and simulations have shown that the main cause of inundation is the small size of the cross section of the duct, as well as the low slope in some parts of the network. Adaptation of the results of the simulation of rainfall-induced waterlogging in the study area with what happens every year confirms indicates the correctness of the simulations of the model. Moreover, simulation results of the model also showed that there is a good agreement between the simulated results and the measurement.

One of the most important consequences increased radiative forcing due to anthropogenic activities is global warming, that created varied and challenging changes such as climate change on ecosystems. Predictions show that the increased radiative forcing will continue. Regarding to the existence of several climate models and error correction methods, selection of the right model is one of the key challenges. In this study, the accuracy and efficiency of the fifth report on regional climate models including CanESM2, CSIRO Mk3, EC- EARTH, IPSL, MIROC51, HadGEM2, MPI, NorESM1 and GFDL and statistical downscaling error correction methods including Linear Scaling (LS), Change Factor (CF), Distribution Mapping (DM),  Local Intensity Scaling(LI), Power Transformation (PT) and Variance Scaling (VS) Using T and F tests, the Taylor diagram and 10 statistical indices during two control (1956-2005) and validation (2006-2015) periods were assessed in Birjand station. The results show that; comparing the average of monthly period increases the efficiency of models and methods exaggeratedly. The best model is different based on statistical indicators and time series period. CF downscaling method is not accurate in validation period. LS and VS downscaling methods are appropriate selection for precipitation and temperature parameters respectively. Also, average accuracy of all models for both precipitation and temperature parameters is better than a single model. MPI and Earth climate models have good performance in simulating precipitation and temperature data.

Changes in plot size can be determine its effects on parameters changes of runoff and soil loss. On the other hand, the generated runoff in eroded soils is one of the most important obstacles and challenges of human in conservation of water and soil resources and it is also a threat to well-being and life. One of the most important of controlled factors of surface runoff and increasing soil infiltration is the application of conditioners or amendment materials on soil. But it should be noted that the size change can also control the runoff and soil loss variations. Therefore, the present study was carried for the effect investigating of size change in laboratory plots in two sizes of 0.5 × 0.25 and 1 × 0.5 m2 using application of organic manure with rates of zero (control treatment) and 62.5 and 125 g m-2 (conservation treatment) on changing time to runoff, runoff coefficient, soil loss and sediment concentration. The obtained results showed that the plots with size of 0.5 × 0.25 m2 and the application of organic manure with rate of 62.5 g m-2 had the little effect on the increasing time to runoff compared to control treatment. But, time to runoff increased with increasing plot size and also rate of organic manure. The effect of plot size on parameters of runoff coefficient, soil loss and sediment concentration, organic manure on parameters of time to runoff, runoff coefficient and soil loss and interaction effect of size change and organic manure on parameter of soil loss was significant at level of 99 percent. Also, in plot with area of 1.0 × 0.5 m2, the changes of time to runoff and runoff coefficient, soil loss and sediment concentration for organic manure with rate of 125 g m-2 toward 62.5 g m-2 were 72.83, 53.52, -212.27 and -142.92 2.12 percent, respectively. While, the changes of studied parameters for plot of 0.5 × 0.25 m2 were 594.24, -212.63, 4.06 and 13.70 percent, respectively.

drinking and industrial sectors are very emphasis in our country. Agricultural activities have a very high contribution in harvesting of groundwater aquifers. So, today, irregular extraction of these sources caused to decrees the quantitative and qualitative aquifers characteristics. The aim of this study was to investigate the effect of meteorological drought on groundwater quality and quantity in Lordegan plain in Chaharmahal and Bakhtiari province. For this purpose, quantity and quality of groundwater data (20 piezometric wells) and precipitation data (7 rain gauge stations) from the regional water supply company of the Chaharmahal and Bakhtiari province was obtained. Then, using Run-Test and Kolmogorov-Smirnov tests, homogeneity and normality of the data were tested. In the following, the DIP software was used to estimate the standardized precipitation index (SPI). Groundwater Resource Index (GRI) was calculated using Excel formulation software. The results of this study showed that the Groundwater Resource Index (GRI) for most years was mild and moderate, and less severe and very severe droughts. Also, based on the standardized precipitation index (SPI), most droughts were mild to moderate. Thus, according to SPI and GRI indices, the plain experienced meteorological and groundwater droughts. Spatial meteorological and groundwater drought maps indicate that drought has been occurred in central and eastern, also in eastern and northeast part of plain, respectively.

Land subsidence is a geo hazard that leads to slow or rapid decrease of ground level. Land subsidence presents a constant threat to the safety of surface infrastructures such as motorways, railways, power lines, and telecommunication cables. Arid and semi-arid countries like Iran are very susceptible to land subsidence phenomenon. Land subsidence has occurred in more of 300 plains of Iran, and Semnan Plain is one of the most important areas that face to this phenomenon. The purpose of this research was land subsidence susceptibility assessment using entropy model. In the first step, acquiring information about sixty-five land subsidence in the past was done. Twelve conditioning factors from different basic layers including topography, geology, land use, and ground water table were considered for modeling aims. The receiver operating characteristic (ROC) curve and area under the curve (AUC) were used to assess accuracy of the Entropy model. The AUC for the entropy model was 0.715 that showed this model is acceptable for land subsidence susceptibility mapping in the Semnan Plain. Results of this research can help to policy makers and planners for environment and urban management and planning.

Human societies face natural hazards, such as groundwater drainage as well as its effects. Underground water losses in various ways, directly and indirectly, affect human societies, but local communities, especially the agricultural sector, are the most dependent part of underground water, which in this study is the main focus of measuring adaptive capacity. Adaptation capacity is an essential characteristic for coping with challenges in complex socio-ecological systems. In this research, by field observation and questionnaire compatibility capacity in target areas in the Kazerun Plain was measured and analyzed in 150 farmers. The results of the research show that the compatibility capacity of local communities in the face of subsidence of groundwater in the Mehrjian villages is 3.80, Mashtan, 3.74 and Jambozorgi, 2.81. In general, the adaptive capacity of the villages surveyed is moderate (3.44). The results also indicate that the most consistent index of governance and the trust index to the government have the least impact on the level of capacity of the target community in meeting groundwater scarcity. The findings showed that most people in the area are looking for adaptive management in underground waterlogging situations, which are essential for the understanding of groundwater policy planners and service providers for rural development.

TThe industrialization of communities and the rise of greenhouse gases are causing an increase in the temperature of the earth and other climate parameters. This phenomenon is the most important problem of the planet in the present century, hence the assessment of the extent of its formation on a global and regional scale is of particular importance. So far, several General Circulation Model (GCM) has been designed to predict future climate change, but the outputs from these models cannot be used because of the localization on a local scale. So various methods have been developed to use the outputs of these models on a regional and local scale. In this research Statistical Downscaling Model (SDSM) was used to evaluate the changes in temperature indices in the Agh-Chay watershed. In order to, the efficiency of this model was evaluated for downscaling of the temperature indices in Khoy synoptic station and the indices were simulated until 2100. The SDSM model was calibrated and validated by using Khoy station observation temperature and national center environmental prediction data. For evaluating the model, mean absolute error and root mean squared error was used and after obtaining the efficiency of the model the outputs of the HadCM3 model, the duration of 2020-2050, and 2070-2100 under the A2 and B2 scenarios were downscaled with SDSM statistical model respectively. The results show the increasing of the minimum and maximum temperature in the study area in most of the months. The maximum temperature was up to 3.48 ° C in the period 2020-2050 and up to 5.6 ° C during the period 2070-2100 and the minimum temperature up to 3.45 ° C for the period 2020-2050 and up to 5.51 for the period 2070-2100. The results also show an increase in precipitation in most months of the year from 2050 to 2020 period (in the range of 0.1 to 95.74). Rainfall changes from 2100 to 2070 period are in the form of an increase in most months of the year with a maximum of 94.64 and a minimum of 1.34 percent.

Environmental challenges are increasing day by day which this is a result of the increasing human population and demand for natural resources. Mismanagement of natural resources causes instability in environmental indicators. Degradation of watersheds with soil erosion and sediment yield is one of the most important environmental issues in Iran. Therefore, it is necessary to prepare and complete the spatial information of the natural characteristics of the watersheds and their prioritization. Because it is used in comprehensive watershed management. The purpose of this study was to investigate the status of some indicators and prioritize sub- catchments in Karkheh watershed. So indices of sensitivity of rock units to erosion, modified fournier erosivity index, erosion intensity from EPM experimental model and sedimentation through logarithmic sediment delivery ratio and discharge data were extracted and analyzed. After calculating mentioned indices in the sub-cachtments of Karkheh watershed, the values of each indicator in the basin and sub basins were examined, standardized and compared and then sub- cachtments prioritization were performed. The clustering method was also used to group the sub- cachtments and the above mentioned indices and topographic indices. Investigation of the susceptibility of formations to erosion of Karkheh watershed showed that sensitive class to erosion is the most frequent in this basin (60 %). The largest similar category in sub- cachtments includes nine ones with codes2213, 2214, 2221, 2222, 2223, 2225, 2226, 2227 and 2228 and the coefficients of area and length of flow had the most similarity. The results of rainfall erosivity and average erosion also indicate that very high erosivity class and high erosion class have the largest area (49% and 52% respectively) in this basin which the average erosivity and erosion of the basin were 60.6 mm and 727 m3 / km, respectively. The results of the average ranking of the indicators of geological formation sensitivity, rainfall erosivity and erosion of each sub basin show that sub basins such as 2215 (Karkheh Bala) and 2224 (Khoramabad) are prioritized in terms of planning and practical measurments at the level of the basin at managerial levels and sub- cachtments such as 2211 (Karkheh Payab) and 2227 (Ab Aleshtar) are less priority than other sub- cachtments in the Karkheh watershed.

In this research, System Dynamics (SD) modeling was developed for facilitates the integrated and sustainable management of water and soil resources and improving the understanding of watershed systems in the Hableh-Rud River Basin. Reference diagrams were created to represent causal relationships and feedbacks. The conceptual model, included physical, economic, and social sub-systems, was created based by causal relationships and feedbacks. The model of stocks and flows run in the Vensim software environment. The model is comprised of Model verification was carried out through extreme condition tests and behavior reproduction test. Having the Nash-Sutcliff and R2 coefficients with greater values than 0.62 and 0.63, respectively, the SD model satisfactorily simulates all variables. Different scenarios of vegetation management, climate, water resources management, and cropping patterns were compared to the outputs of the existing condition. The results of scenario analyses for a 30-year period show that the agricultural water use efficiency scenario, as the best scenario, increases groundwater and water infiltration volume by 14.3 and 11.1 percent, respectively. With regard to the erosion and sedimentation variables, rangeland restoration activities were chosen as the best scenario, with 7.12 and 5.24 percent reduction. The greatest reduction in nitrogen and phosphorous loss, 8% and 6.4% reduction could be achieved by implementing the rangeland restoration scenario. From an economic perspective, payment for 50% of the ecosystem services, with about 46 percent improvement compared to the current condition, was determined as the best scenario. Stakeholders expressed their highest willingness to participate in the farm management activities with the accumulated score of 85.6 for public acceptance index. The SD model is a beneficial approach for stakeholders understanding of the causal relationships and feedbacks in the system.

GGroundwater is considered as one of the most remarkable sources of fresh water. The aim of the current research is to apply four machine learning models of Random Forest (RF), Support Vector Machine (SVM), Bioclim, and Domain to groundwater potential mapping in Kahurestan watershed, Hormozgan province. The innovation of the research is to employ Bioclim and Domain algorithms to groundwater potential simulation, to compare them with the two techniques of RF and SVM and to combine these four models by an innovative and new equation. For this purpose, 11 criteria including slope percent, slope aspect, plan curvature, profile curvature, soil adjusted vegetation index (SAVI), modified normalized difference water index (MNDWI), slope length and steepness factor (LS), stream power index (SPI), topographic wetness index (TWI), land use, and distance to streams were considered. Also, the data of 113 high-discharge wells were used for simulation (70%) and validation (30%)processes. The collinearity test was performed prior to modeling which indicated that there was no relationship between the variables. Evaluation of the modeling performance with the ROC curve showed that all four methods used had very good accuracies and AUC values higher than 90% for prediction. The survey on the weight of the criteria based on the RF method demonstrated that the land use/cover and distance to streams criteria has the highest weight. The final map revealed that 21.4% of the area under study has good groundwater potential.

OOne of the most important hydraulic parameters affecting soil quality is the infiltration of water into the soil. That, the direct measurement of infiltration process is difficult, time spending and expensive. Infiltration models play the main role in managing watershed. Therefore, it is necessary to study different infiltration models in order to compare and achieve the best infiltration model in the area. This research determined the best infiltration estimation model in the pasture, garden, agricultural land uses (in two textures of silty clay loam and clay loam), in the Charmahal and Bakhtiari province. In this study, infiltration measurements were carried out using the infiltrometer single ring (to the inner diameter 35 cm). The initial humidity measured were respectively in pasture land use in silty clay loam and clay loam tissues (3.71, 4.27), in garden land use (2.18, 3.46) and, in agriculture land use (1, 2.25). and then infiltration models of Philip, Kostiakov and Soil Conservation Service of America (SCS), used and thus evaluated by the coefficient of determination (R2), Nash-Sutcliffe sufficiency score (NSSS), root mean squared error (RMSE) and mean error (ME). The results of this study showed that in rangeland use, the infiltration of all parameters (cumulative infiltration, the final infiltration rate and infiltration rate), is less than the garden and agriculture land use. It also compares the models, in the rangeland, but Kostiakov Model was accepted as the appropriate model in the garden, pasture and agricultural land use (in two soil texture), by Nash-Sutcliffe efficiency coefficient 0.99 and R2 (0.99) and a smaller error than other models. The next good models that had high efficiency were the Philip model by Nash-Sutcliffe efficiency coefficient and (R2=0.99) and an error of (0.15) in garden land use in silty clay loam texture, and the SCS model in pasture land (in SCL texture) with an error of 0.18.

Since in the optimal allocation of water resources, the maximization of income, is the main purpose of modeling, researches in this case is just limited to approaches rooted in linear and structures in mental model or causes the inequitable resources allocation. Also, evaluation of these researches showed that there is low knowledge about long term dynamics behavior in river watershed. In this regard, in this study, evaluation of optimal cropping pattern based on water resources and demand in Tajan watershed by VENSIM in 1962- 2012 in monthly times step was carried out which domestic, industrial, environmental and agricultural demand were taken into account. This optimal cropping pattern could be the basis for water productivity in Tajan watershed. The calibration results showed not only outflow of dams is related to demands, but also dams coefficient is independent from agricultural demands coefficient. Also the results showed that large amount of domestic, industrial and environmental demand in this region is supplied and dams in Tajan watershed is enough for suppling. But there is significant deficit in agricultural part that regarding to low volume of groundwater in this region, changing crop pattern s inevitable. O the other hand, evaluation of optimal crop pattern is showed that orchards with maximum income per cost in the all region, is dedicated the most cultivated land area and after that citrus have second priority.

Land use optimization for proper utilization of land resources has always been one of the main issues in natural resource planning. To avoid the adverse effects of improper land use, management programs should be designed that incorporate land use optimization. In this research, land use optimization has been performed for the Chehelchay watershed, with an area of 25680 hectares in Golestan province, in order to prevent improper land utilization which threatens economic and social sustainability of the watershed. For this purpose, an optimal land use map was created using multi-criteria evaluation method together with economic evaluation of land uses based on the benefit-to-cost ratio. Proposed land uses and protection actions for the Chehelchay watershed include terracing, orchards, agroforestry, forage cultivation, afforestation and riparian forest buffers. To assess land suitability for different uses, several data layers were input and analyzed in Terrset software. Each of the factors (i.e. data layers) was standardized between zero and one. Then, the layers were combined using Multi-Criteria Evaluation (MCE) method to generate fuzzy suitability map for each land use. In the final map, suitability values range between zero (not suitable) and one (perfectly suitable). Also, considering the costs of establishment, maintenance and income of each of the proposed land uses during a 30-year planning horizon, benefit-to-cost ratio was calculated for each land use. The results of the economic evaluations indicated that all of the proposed land uses are profitable. Finally, based on the results of multi-criteria evaluation and economic evaluations, the optimized areas for each proposed land use were determined across the watershed.

Different models have been proposed to describe and predict the hydrology of the watershed which are different in terms of objectives and spatial and temporal scales. In this study, the SWAT model was used to simulate the hydrologic response of the doiraj basin. The main inputs of the model, which include meteorological data, a basinchr('39')s elevational digital model map, a soil map and land use map, are entered into the model. The model was implemented according to the curve number method, then, using the SWAT_CUP model, the performance of the model increased with entering the observation data of the discharge from the basin and performing the calibration steps during the period from 1996 to 2008. And then the validation step from 2009 to 2012 confirmed the modelchr('39')s ability to simulate rainfall-runoff and its use for study purposes. Long-term mean soil moisture in 1996, 2008, and 2013 was 524.24, 337.59, and 468.77 mm, respectively. The study of the simulated water balance components showed that for 1996, despite heavy rainfall, the water balance was almost zero, indicating a loss of water in the basin in the basin, with major evapotranspiration losses. The water balance is positive for 2008 and 2013 because the sum of evapotranspiration, river flow, lateral flow, infiltration and surface runoff are lower than the sum of precipitation.

Iran is one of the countries in the Middle East that is facing a shortage of renewable water resources. As one of the governmentchr('39')s socio-economic policies, the emphasis has been on the optimal use of renewable resources, in particular refined human and industrial wastewater. One of the limiting factors of using these wastewater is the presence of heavy metals in them. Therefore, soil remediation is important to reduce this pollution or to deactivate heavy metals.  This study was conducted to investigate the effect of bentonite modification on soil elements concentration irrigated with municipal wastewater under cultivation of Alfalfa and clover in a completely randomized design. In this study, essential and toxic elements of the plant, soil properties and elements in soil under different effluent ratios (0%, 25%, 50%, 75% and 100%) were investigated. Also, due to the presence of heavy metals in wastewater, bentonite modifier was used as immobilizer of heavy metals in soil at two levels of 1% and 3%. The results showed that 100% effluent-3% bentonite treatment had the highest amount of soil organic carbon, organic matter, lime, pH and EC for both alfalfa and clover species (p<0.05). Also, increasing the level of effluent application significantly increased the concentration of essential elements (NPK) in soil and plants. On the other hand, application of 3% bentonite resulted in a significant decrease in the toxicity of lead and cadmium in plants and soils. In general, it can be concluded that application of proper wastewater treatment can be used as a potential source of water to enhance plant growth and yield, as well as the use of bentonite as an immobilizing agent of heavy metals in wastewater in forage production methods.

Engaging people to conserve natural resources is the most rational way. This by reducing the running costs will guarantee the success and implementation of the projects more effectively. For this purpose, the present study was conducted to identify and prioritize the effective indices and sub-indices on the lack of sustainable participation of rural communities in aquifer management projects from the beneficiarychr('39')s viewpoint in Bishezard watershed of Fars province. In this research, 83 stakeholders and residents of the watershed was chosen as statistical population using Cochran formula. To collect data, a questionnaire consisting of four indices and twelve sub-indices with Likert scale was used. The significance of indices and sub-indices was determined by SPSS software (version 23) using t-test and the Friedman nonparametric test was used to prioritize the effective indices and sub-indices. The results showed that in the prioritization of indices from the beneficiarychr('39')s point of view "educational-promotion", "design-executive", "social" and "economic" indices were ranked with an average of 9.75, 9.49, 6.98 and 5.93 as effective indicators, respectively and in sub-indices, "Lack of attention to local force in project implementation (employment)" and "Late-yielding projects" with an average of 11.40 and 5.74 had the highest and lowest priority in non-participation in aquifer management projects, respectively. This finding indicates that if employment is resolved in this watershed, people are willing to take the time accomplish projects. It is recommended that managers of natural resources plan and implement practical training and promotion activities related to natural resources and aquifer management issues.

Precipitation estimation in areas without recorded meteorological data is of great importance in hydrological studies and flood forecasting. Due to the lack of high-altitude meteorological stations with long-term recorded data in Mazandaran province as well as stochastic attribute of rainfall data, using statistical methods based on covariates and comparison with geostatistical methods for interpolating monthly and annual rainfall data in this province is Inevitable. For this purpose, precipitation data from 21 meteorological stations over a 13-years recorded period (2004-2013) were used. In order to determination of appropriate interpolation method of rainfall data, six models including Ordinary Kriging, Cokriging, Inverse Distance Weighting, spline, three-dimensional linear gradient and regression-kriging were investigated. Evaluation of the methods was also performed on the basis of root mean square error, mean bias error and regression analysis. Variography analysis showed spherical and exponential models as the best theoretical semivariogram models. The results of error indices analysis showed the Spline model has the lowest efficiency and the three-dimensional linear gradient was found as the most appropriate interpolation model of rainfall data which in comparison with other models reduced the rainfall estimation error from 100 to 200 mm(about 40 to 60 percent). However, its accuracy is reduced in hot and humid months. Investication of rainfall maps illustrates the accuracy of covariate based interpolation methods in detecting low rainfall and high rainfall points of the province. So that high rainfall district is located on the west coast of the province and by moving east the amount of rainfall decrease. Due to the similarity of the rainfall map and the digital elevation model, it is noted that the amount of precipitation in valleys is very different from precipitation in the highlands of this province. The results of this study showed that in areas with complex topography, the use of covariates leads to a significant increase in the accuracy of rainfall maps.

In this paper, the precipitation and runoff time-series data of the Shaharchay River basin from 2000 to 2017 were simulated by using a novel hybrid artificial intelligence (AI) technique. In order to develop this AI model, the extreme learning machine (ELM), differential evolution (DE) and wavelet transform (WT) are combined and then the SAELM and WASAELM hybrid models are provided. Initially, the most effective lags of the time-series data are distinguished using the autocorrelation function. After that, using these lags, seven artificial intelligence models are defined for each of the SAELM and the WSAELM models. Additionally, 70% of the observational data are employed for training the artificial intelligence models and the rest (30%) for testing them. For WSAELM7 as the best model, the values of R2, the scatter index (SI), and the Nash-Sutcliff efficiency coefficient (NSC) for simulating precipitation are yielded 0.967, 0.208 and 0.965, respectively. Furthermore, a sensitivity analysis exhibits that the lags (t-1), (t-2) and (t-12) are regarded as the most effective input lags. Ultimately, an uncertainty analysis is carried out for the superior models.

TThe amount of runoff entering the dam’s reservoirs are continuously affected by climatic parameters, which influenced by the climate change phenomenon. In this study, the climate change parameters were obtained based on CANESM2 climate model using the SDSM4.2 statistical downscaling model. Then the rainfall-runoff process was simulated by ANFIS model with Sugeno structure and subtractive clustering at the entrance of Golestan dam reservoir in climate change conditions. Finally, the Improved Multi-Objective Whale Optimization Algorithm (MOIWOA) which is a combination of Whale V (WOA) and the Differential Evolution (DE) is used to extract the optimal operation rules of Golestan Dam Reservoir in Golestan province. The results of the uncertainty analysis indicated that the simulation results of the climate change period were in the 95% confidence band - in both calibration and validation phases. Also optimization of Golestan reservoir in baseline (March 2005-September 2018) and climate change (April 2021-October 2033) periods showed that the vulnerability changes in the baseline and climate changes are in the range of 18-45% and 10-39%, respectively, and the reliability ranges over 52 to 89.5% and 28 to 90%, respectively, in both baseline and climate change phases. And for 80% reliability, the baseline and climate change conditionschr('39') vulnerability are obtained as 31% and 27%, respectively. Comparison of the optimal rules derived from the baseline conditions with the optimized ones from the climate change showed that the plan water demand is met by 80% reliability index. In addition, the release volume in climate change conditions is higher than its baseline one, which can be due to the increased volume of water demand in climate change conditions. On the other hand, comparing the performance of the reservoir to meet the irrigation demands of downstream land at the Pareto point (80% reliability) in terms of baseline and climate change also suggests a greater adaptation of reservoir release to demand in climate change period.

In this study, the effect of agricultural water productivity for optimization of the cultivation pattern in the irrigation network of Doosti Dam has been investigated. For this purpose, the amount of costs and revenues from the sale of agricultural products and the water demand of these products were used as the main parameters. In this regard, the study area (Doosti Dam Irrigation Network) was divided into six areas in terms of catchments, social context, scope of activities of aquifers and productivity index according to field surveys for all Areas were identified. The results show that with the implementation of the proposed plan, income in the whole area will increase by 20% and the irrigation system of the region will be optimized. Also, the annual water demand and unmet water demand of each area of the study area were calculated according to the available water resources and also based on the use of WEAP model functions. As a result, irrigation efficiency increased and water demand of agricultural products decreased until the project horizon (2030). The results of this study in the study area, can provide a good management approach to make future decisions for policy makers and stakeholders in the field of water in this area.

Accurate estimation of reference crop evapotranspiration (ETo) is important in hydrological studies and water resource management that can influence the planning and policies for optimal allocation of agricultural water resources. For this purpose, in the present study, sensitivity analysis was employed to evaluate the effects of the changes in meteorological parameters (vapor pressure deficit (VPD), Mean Temperature (Tmean), net solar radiation (Rn), wind speed (u) and actual vapor pressure (ea)) on reference crop evapotranspiration (ETo) within the possible range of ±20% on a daily and growing season scale. ET0 was calculated by The Food and Agriculture Organization of the United Nations (FAO) 56 Penman-Monteith approach using long-term climate data from 13 meteorological stations of Khorasan Razavi province in northeast Iran. The sensitivity analysis indicated that ETo changes positively with vapor pressure deficit, mean temperature, net solar radiation and wind speed, while it changes negatively with actual vapor pressure. Also, over the whole period, ETo was most sensitive to vapor pressure deficit (VPD), followed by mean temperature (Tmean), net solar radiation (RN), actual vapor pressure (ea) and wind speed (WS). In the the warm growing season, ETo was most sensitive to vapor pressure deficit (VPD), followed by mean temperature (Tmean), net solar radiation (RN), wind speed (WS) and actual vapor pressure (ea) while, in the cool growing season, ETo was most sensitive to vapor pressure deficit (VPD), followed by actual vapor pressure (ea), Mean Temperature (Tmean), net solar radiation (RN) and wind speed (WS). The results showed that the sensitivity of ETo in different stations and different growth periods is different. The findings of this study showed that the importance of effective parameters on the reference crop evapotranspiration (ETo) was different between the hot and cool growing season of the region, which should be considered in sustainable planning of water resources and management of agriculture in Khorasan Razavi regions for development of adaptation strategies in arid climatic conditions.

As one of the most important pillars of the land organization, the Forest Road Network plays a key role in the management of forest resources, and on the other hand, roads have the highest rate of administrative and environmental costs. Road construction on unstable forest soils will increase road maintenance costs in the future, as well as irreparable environmental damage, including soil erosion. The aim of this study is to assess the risk of landslides in the Challeir Forest in the Khairud Forest in order to study the design of forested roads, to high-risk road distances as part of a linear complication, identified and with double attention, from irreparable damage to environmental repairs and costs. In this study, designed and projected roads in the Chellir district of Khairud forest with an area of more than 1720 hectares have been studied, in the study area, 38 km of roads have been predicted and 14 km of which have been constructed. Initially, slope factors, direction, distance from the fault, distance from the road, distance from the streams, geological structure, and soil type were identified as effective factors in landslides and with the help of the hierarchical analysis process, were evaluated and weighted according to experts. In the next step, the required maps were prepared in the Arc GIS and classified according to previous studies, and the slips in the area, which were harvested using the field study (GPS), were compared. Then, the sub-maps of the sub-criteria were weighted according to the characteristics of the slips (according to the slip area in each floor) by the density area model, then the map of the sub-criteria was weighted according to the sub-criteria measured by the hierarchical analysis process. The Arc GIS was integrated with each other and the landslide hazard zoning map of the study area was prepared on five classifications from high risk to low risk. Finally, by placing the road map made and designed on the obtained zoning map, the distance of the roads on different classes of the hazard was extracted. The prioritization results of the factors showed that the slope and distance from the waterway with weights of 0.22 and 0.19 they had the greatest impact and distance from the fault and distance from the road with weights of 0.096 and 0.085 had the lowest effect on landslides. Also, the results of road analysis showed that out of about 38 km of road designed, about 21 km is located in high and very high-risk classes and 11 km is in low and very low-risk classes, a distance of about 6 km from this road network is also in the middle-risk class, indicating the importance of domain sustainability studies in this area, including grain seeding, soil kneading rate, and other mechanical properties, before any construction operations.

Optimizing the parameters of hydrological routing methods has a special place in increasing the accuracy of estimating outflow hydrograph and also calculating the peak area of flood hydrograph in engineering works. In the present study, since the range of changes in the inflow of the third flood (computational flood) is between the range of changes of the inflow of the first and second floods (base floods), For this reason, in order to increase the flood routing accuracy by using hydrological routing methods (linear Musking method, Working values, convex and modified Att-Kin), instead of using the parameters (X, K, ∆t) of a baseline flood, the arithmetic mean and the geometric of the two baseline flood parameters is discussed in 8 different modes using the Particle Swarm Optimization (PSO) algorithm. In other words, the use of all 8 modes presented in the present study has increased the accuracy of hydrological routing methods in estimating the peak area of flood hydrographs between Mollasani (upstream) and Ahwaz (downstream) hydrometric stations of the Karun River. Thus, in the best case presented in the present study (mode 8), the mean relative error of the computational flood peak area relative to the conditions in which the first baseline flood is used alone, for the mentioned methods are 66, 66, 25 and 18%, respectively, and in conditions When the second baseline flood is used alone, it has improved by 43, 43, 4 and 9%, respectively.