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Showing 45 results for Climate
Optimization of Dam Reservoir Operation Using Metaheuristic Algorithms under Meteorological Drought Conditions (Case Study: Aydoghmoush Dam)
E. Taheri, F. Mousavi, H. Karami,
Volume 27, Issue 2 (9-2023)
Abstract
One of the basic steps in water resources management and planning according to population increase and lack of water resources in Iran is to optimize the use of dam reservoirs. In this research, the effect of meteorological droughts on the optimization of the Aydoghmoush dam reservoir in the northwest of Iran was evaluated by applying metaheuristic algorithms under the impact of future climate change. Three models and two scenarios of SSP2-4.5 and SSP2-8.5 of the sixth IPCC report, and the LARS-WG downscaling model were used for Aydoghmoush dam weather station for the base period (1978-2014) and future periods of 2022-2040 and 2070-2100. The inflow and outflow of the dam, as well as the optimal utilization of the dam reservoir, were evaluated using standalone, and hybrid mode of genetic, slime mold, and ant colony algorithms. Results of the best release scenario (SSP2-8.5) showed that the annual rainfall in the future periods will decrease by 8.9 mm, and 14.5 mm, respectively, compared to the base period. The objective function of optimizing the use of the dam reservoir was defined as minimizing the sum of squared relative deficiencies in each month and maximizing the reliability in the statistical period of 2011-2021. The results showed that in terms of time reliability, vulnerability, and stability, the hybrid slime mold-genetic algorithm was better than other algorithms with values of 0.73, 0.32, and 28.78. Prediction of the dam's inflow and outflow using the hybrid slime mold-genetic algorithm indicated high accuracy compared to other models by 13% and 19% errors, respectively.

Temporal and Spatial Estimation of Quality Variables of Groundwater Resources Based on Intelligent Methods
A.r. Emadi, R. Fazloula, S. Zamanzad-Ghavidel, R. Sobhani4, S. Nosrat-Akhtar,
Volume 27, Issue 3 (12-2023)
Abstract
As one of the most necessary human needs, groundwater resources play a key role in the economic and political processes of societies. Climatic and land-use changes made serious challenges to the quantity and quality of groundwater resources in the Tehran-Karaj study area. The main objective of the present study is to develop a method based on individual intelligent models, including adaptive neural-fuzzy inference system (ANFIS), gene expression programming (GEP), and combined-wavelet (WANFIS, WGEP) methods for temporal and spatial estimation of total hardness (TH), total dissolved solids (TDS), and electrical conductivity (EC) variables in the groundwater resources of the Tehran-Karaj area for statistical period of 17 years (2004-2021). The results showed that 
combined-wavelet models have higher performance than individual models in estimating three selected variables. So that the performance improvement percentage of the WANFIS model compared to ANFIS and WGEP model compared to GEP, taking into account the evaluation index of root mean square error (RMSE) were obtained (23.713%, 18.018%), (12.581%, 33.116%), and (6.433%, 12.995%) for TH, TDS, and EC variables, respectively. The results indicated a very high spatial and temporal compatibility of the estimated values of the WGEP model with the observed values for all three qualitative variables in the Tehran-Karaj area. The results showed that the concentration of qualitative variables of groundwater resources from the north to the south of the study area has an upward trend for all three qualitative variables. In urban areas, pollution caused by sewage and population increase, as well as in agricultural areas, the use of chemical fertilizers and their continued infiltration into groundwater resources and 
over-extraction of groundwater resources aggravate their pollution. Therefore, in the study area, climatic changes and the type of land use are strongly related to the quality of groundwater resources.
Evaluation of the Effect of Land Use Change on Runoff Using the Markov Chain in Shiraz Nahre Azam Basin
A. Mahdavi, S. Soltani Koopaei, R. Modares, M. Samiei,
Volume 27, Issue 4 (12-2023)
Abstract
Land use changes are one of the main factors in the amount of surface runoff changes in watersheds. Therefore, it is necessary to investigate it to reduce the damages (human and financial) caused by floods and to modify watershed management. The watershed of Nahre Azam is located in the north of Shiraz city and a lot of loss of life and money to the residents of Shiraz due to floods has occurred in previous years. The present research was conducted to investigate the relationship between land use change and runoff in the Nahre Azam watershed in Shiraz using the SWAT model in the period of 2004-2020. The model was calibrated using data from 2004 to 2014 and validated for 2015 to 2020. These images were classified into 6 main land uses using the supervised classification method after performing necessary pre-processing, and a land use map was prepared for 2040 using the Markov chain method. Then, the effect of the land use change in 2003 and 2040 on the amount of simulated runoff was evaluated with the recalibrated model. The calibration results of Nahre Azam watershed for the values of statistical parameters in the calibration step for the coefficient of determination, P-Facor and R-Facor are 0.77, 0.72, and 2.43, respectively, and for the validation step we obtained 0.69, 0.65, and 2.3 respectively. The analysis of the land use map showed that the main land use change in the region related to the conversion of pastures to agricultural land and urban land, which caused a decrease in pastures. Also, the results of the model simulation using the land use maps of 2003 and 2040 indicated that the amount of runoff decreased. The results revealed that if all the uncertainties are minimized, the calibrated SWAT model can produce acceptable hydrological simulation results for the user, which is useful for water resource and environmental managers and politicians as well as city managers of Shiraz.

Climate Change Assessment of Hablehroud Watershed Using Downscaling of CanESM2 General Circulation Model Data
M. Naderi, V. Sheikh, A. Bahrehmand, C.b. Komaki, A. Ghangermeh,
Volume 27, Issue 4 (12-2023)
Abstract
Greenhouse gases and the occurrence of climate change have occurred with the development of technology and the industrialization of human societies. long-term forecasting of climate parameters has always been interesting due to the importance of climate change for the earth and its inhabitants. General Circulation Models (GCMs) are one of the most widely used methods for evaluating future climate conditions. In the present study, the results of three general circulation models including the American model of GFDL-CM3, the Canadian model of CanESM2, and the Russian model of inmcm4ncml for the study area were evaluated and the CanESM2 model was selected as the superior model. The RCP scenarios 2.6, 4.5, and RCP 8.5 were used with the CanESM2 model to assess climate change conditions across the Hablehroud River basin for the period 2020-2051. According to the results, the total monthly precipitation shows an increasing trend in the coming decades 2020-2051 period compared to the period 1986-2017. The results of the study of temperature changes in the period 2020-2051 in the Hablehroud River basin also indicate an increase in the monthly average of maximum and minimum temperatures in the coming decades. The consequences of these conditions are of great hydrological importance in the study area, this condition necessitates the adoption of climate change adaptation policies in this watershed.

Impacts of Climate Change and Land Use on the Discharge of Kashfrood Basin Using SWAT Model
I. Kazemi Roshkhari, A. Asadi Vaighan, M. Azari,
Volume 28, Issue 1 (5-2024)
Abstract
Due to climate change and human activities, the quality and quantity of water have become the most important concern of most of the countries in the world. In addition, changes in land use and climate are known as two important and influential factors in discharge. In this research, four climate change models including
HADGEM2-ES, GISS-E-R, CSIRO-M-K-3-6-0, and CNRM-CM5.0 under two extreme scenarios RCP2.6 and RCP8.5 were used as climate change scenarios in the future period of 2020-2050. The future land use scenario (2050) was prepared using the CA-Markov algorithm in IDRISI software using land use maps in 1983 and 2020. The SWAT model was calibrated to better simulate hydrological processes from 1984 to 2012 and validated from 2013 to 2019 and was used to evaluate the separate and combined effects of climate change and land use on discharge. The prediction of the climate change impact on discharge showed a decrease in most of the models under the two scenarios RCP2.6 and RCP8.5. The average maximum decrease and increase under the RCP2.6 scenario is 60 and 30 percent, respectively. This significant reduction is greater than that predicted under the RCP8.5 scenario. Examining the combined effects of climate and land use change revealed that the average decrease in discharge in the months of October, November, December, and January under two scenarios is 46.2 and 58%, respectively. The average increase in discharge is predicted to be 47% under the RCP8.5 in the months of April and May in the HadGEM2ES.

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