JWSS - Journal of Water and Soil Science

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.

Evapotranspiration variations (ET₀) were investigated and analyzed using Minitab16 software for the 2010-2019 period using the Nizab system's data in Yazd province, and then ET₀ was predicted until 2027. Based on the results, the increase of ET₀ in cities of Yazd province was affected by the enhancement in wind speed and weather temperature, and the decrease in relative humidity from 2010 to 2019. To determine the appropriate model, Ardakan, Abarkooh, and Taft cities were selected as a representative in each climatic group, and ET₀ data for the years 2010 to 2015 were considered as the input data of the software and ET₀ data for the years from 2016 to 2019 were used to validate the determined model. The prediction of the determined models showed an increasing trend of ET₀ for cold seasons in Ardakan and Abarkoh by 2027. Also, the model prediction showed a decreasing trend of ET₀ for hot seasons in Taft by 2027. Also, the ET0 will not change significantly in cold seasons. In Abarkoh and Ardakan cities, autumn-spring crops such as wheat and in Taft city, spring-summer crops such as sunflower will be more affected by ET₀ variations.

Astragalus is the vegetation of many mountains of Iran's plateau and plays a major role in providing ecosystem services due to its pillow shape and deep rooting system, they facilitate the control and penetration of precipitation into the soil. The correlation of Astragalus ecosystems with arid and semi-arid climates has made them vulnerable to climate change. In this study, a runoff yield map based on the Budyco curve under current and future conditions of climate change (2050) was prepared using climate and temperature data from the Chelsea site (CanESM2 GCM) in TerrSet software and by using maps of sub-watersheds, annual precipitation, annual potential evapotranspiration, soil depth, plant accessible water and the current and future "Land Cover - Land Use" map, with a combination of field methods and species distribution models at the local scale of the Shur River watershed of Dehaghan (Central Zagros). Finally, the excess runoff damage produced due to climate change was estimated using the replacement cost method. The results indicated an increase in the annual runoff volume of the watershed from 70 million cubic meters to 105 million cubic meters under climate change conditions for the RCP26 scenario in 2050. Taking into account the cost of 10 million Rials for controlling 530 cubic meters of runoff through various watershed management projects, preventing the damages of excess runoff produced requires a credit amounting to 660 billion Rials based on the present value. This study proved the ability of TerrSet software to predict and produce an ecosystem service map of runoff yield under climate changes or land use changes and with the purpose of valuation on a local scale. Also, the above valuation can be the basis for planning and providing credit for the study and implementation of watershed management projects to deal with the threats of climate change.

This study aims to investigate the possibility of hydrological simulation of the Azna-Aligoudarz area, which is located in the upper reaches of Karoun Bozorg basin and in the east of Lorestan province. To carry out this research, the daily meteorological data related to the Aligoudarz synoptic station and the rainfall of Kamandan and Dareh Takht rain gauge stations in the period of 1991-2023, the observational discharge related to the Marbareh hydrometric station in the period of 1991-2021, soil map, land use and digital elevation map of Azna-Aligoudarz basin was used. The period of 1991 and 1992 was considered for warm up the model, the validation period from 1993 to 2016, and the validation period from 2017 to 2021. Based on the simulation done in this area, the model had weakness in simulation. After the initial simulation, the model was calibrated. After analyzing the sensitivity of different parameters, 22 effective parameters were selected and the model was calibrated. The evaluation results showed that the NSE value of 0.60 and 0.56 and the R² coefficient value of 0.61 and 0.78 respectively were obtained for the calibration and validation stages. Based on the coefficients obtained in both calibration and validation stages, it was found that the model had a satisfactory accuracy in the hydrological simulation of Azna-Aligoudarz area.
 

The effect of climate change on agricultural productivity and efficiency is a major concern and challenge for the agricultural industry. Different hydrometeorological variables, such as extreme temperature, precipitation, and their variations, affect the growth and yield of agricultural products. Saffron is one of the most important agricultural products in Iran. Iran produces the largest amount of Saffron globally, and Hamadan Province is one of the major saffron-producing regions in Iran. This study uses different Artificial Intelligence methods not only for clustering and sensitivity analysis of the hydroclimatological variables but also for evaluating the impacts of climate change on Saffron yield in Hamadan Province. Results indicated that the Random Forest algorithm performs the best for sensitivity analysis among all algorithms. Extreme climate change indices, particularly those related to the monthly maximum and minimum temperatures, have the highest negative impact on saffron yield compared to other hydroclimatological indices. Furthermore, the minimum temperature has a more significant negative impact on saffron yield compared to the maximum temperature. Additionally, the counties of Malayer, Nahavand, and Asadabad, located in the south and west of Hamadan Province, exhibited the highest accuracy in sensitivity analysis. The findings suggest that monthly extreme temperatures can be used to assess the risk of saffron production, increase agricultural productivity, and improve decision-making for the cultivation of this product.