مجله اکو هیدرولوژی
سال نهم شماره 3 (پاییز 1401)

Damghan plain located in Semnan province and due to lack of water resources need to study the status of water resources for better management. Water resources used in this area supplied from springs and wells. the present study aimed to prepare a spatial distribution map of groundwater quality parameters and compare them in different parts of the aquifer surface using geostatistical methods. Measurement parameters in wells, springs and qanat are (TDS, pH, EC, HCO3-, Cl, Ca++, Na+, %Na, SO42-). The results of descriptive statistics in deep well showed that the highest percentage of changes related to Mg and SO42 variables and the lowest percentage of changes were related to pH. The highest percentage of changes in the semi-deep well is related to HCO3 variable and in the spring it is related to Cl. Also, the highest percentage of changes in Qanat is related to chlorine and calcium, while the lowest percentage of changes is related to TDS. The highest percentage of changes in semi-deep well was allocated to bicarbonate anion and the lowest percentage of changes was related to pH. Among the underground water sources, the spring showed better results in terms of regression coefficients and variogram models. The results of the time changes indicated that the measured qualitative parameters had the most changes in autumn and late spring. The general result of this research indicates that the kriging method with spherical semi-variograms is a suitable method for spatial evaluation of groundwater quality variables in Damghan plain.

Evapotranspiration is a complex phenomenon that depends on many factors and data, so determining it is very difficult and costly. In most methods mainly aimed at estimating evapotranspiration, point measurements have been used to estimate this variable. Therefore, it is only suitable on a local scale and cannot be extended to large basins due to the dynamics and regional changes of evapotranspiration (ET). One of the remote sensing algorithms for estimating real evapotranspiration is the Surface Energy Balance Algorithms for Land (SEBAL). In this algorithm, by estimating all energy components on the land surface such as pure radiation flux, soil heat flux, and tangible heat flux, using the energy balance equation, evapotranspiration is used. The aim of this study is to compare the estimation of real evapotranspiration using SEBAL algorithm in wheat and rapeseed crops with the results of estimating evapotranspiration by Penman-Monteith-FAO method in the field of Esmaeil Abad Agricultural Research Station in 2019-2020. Single-sample T-test of ground surface temperature reflection index showed that the spectral reflection of wheat and rapeseed crops during phenological growth period had a significant difference. The results showed that the computational values of the two models are relatively good and the mean value of square root of error (RMSE) in estimating real evapotranspiration for wheat and rapeseed plants was 3.04 and 2.09 mm/day, respectively, and the coefficient of explanation (R2) was 0.78 and 0.81, respectively. The results showed that SEBAL algorithm model in comparison with Penman-Monteith-FAO model (based on up-to-date meteorological data) The amount of evapotranspiration for wheat and rapeseed plants is lower.

The location of Tehran as the largest consumer of urban water in the country and also the different uses of water in this city, has led to the flow a significant volume of surface water resources in streams and canals in the southern regions of Tehran. These polluted surface runoffs are currently used in combination with underground water sources in agriculture in south of Tehran, which has adverse environmental consequences. The Surface water organization project in the south of Tehran in the Regional Water Company of Tehran has been explored to tackle the problem. Hence in this study, the economic and environmental effects of treated wastewater use in agriculture in the South of Tehran have been surveied in terms of project implementation and comparing the results with existing conditions in the region that uses polluted water for agricultural lands irrigation. According to the results, if the plan is implemented, the average amount of runoff has decreased from 201 to 84 cubic meters per hectare, and the amount of nitrates in the runoff has decreased from 14 to 0.1 kg per hectare. Also, by entering the wastewater into the plan area and using the fertilizer potential of the wastewater, the amount of nitrogen fertilizer consumption can be reduced by 5039 tons, which will reduce the costs of the farmers in the area by 55431 million Rials. As a result, the implementing the Surface water organization project in the south of Tehran will bring positive environmental effects.

Water resources play a very important role in the life of humans, plants and animals. Extracting and monitoring the extent of changes in water areas can be effective in predicting many problems. Today, many methods and algorithms have been introduced using remote sensing data to monitor water changes, so it is very necessary to study the accuracy of these methods. In this regard, the aim of the present study is to evaluate the accuracy of remote sensing methods for monitoring the water of Zarebar Lake over a period of 33 years (1984 to 2017). Therefore, after images preprocessing, water body of Zaribar Lake was extracted using maximum likelihood algorithms, minimum distance, Mahalanobis distance, support vector machine and NDWI, MNDWI and AWEI indices in ENVI5.3 and ArcGIS10.4 softwares, then these method was validated using ground control points. According to the results, all methods have an accuracy of 80%, but the support vector machine and maximum likelihood algorithms have a higher accuracy with a kappa coefficient above 85%. Also, the results of the study of lake water changes show that during the period 1984 to 2017, the water body based on support vector machine and maximum likelihood algorithms has decreased by 738.46/ha (46.83 percent) and 613.06/ha (42.45 percent), respectively. Also, in the same period, based on support vector machine algorithms and maximum likelihood algorithm 47.35% and 36.22% have been added to the reed bed on the lake. Due to the decreasing trend of lake and invasion of vegetation, it is necessary to consider a plane to prevent the lake water body for future.

Due to population growth, increasing welfare, development of industries and agriculture along with climate change, groundwater resources are always changing in terms of quantity and quality. Therefore, it seems necessary to study the quantitative and qualitative changes of groundwater to manage. For this purpose, in the present study to study the groundwater quality changes in Bijar-Divandere plain, in terms of sedimentation and corrosion, using the information received in the years 2009 to 2018 and each year for the two months of June and October as water months and Water scarcity has been addressed using the Geographic Information System (GIS). Also, by evaluating various indicators to determine corrosion and sedimentation, valid indicators such as Langelier, Reisner and Pocorius for industrial use and sedimentation and corrosion analysis were studied in this study. The results of the mentioned indicators showed that the groundwater of the western areas of the plain is prone to corrosion and the eastern areas were prone to sedimentation and the Reisner index showed the water quality of part of the center of the plain was neutral. It was suggested to use aeration to remove iron and manganese, cathodic protection, priming, glazing and painting of the desired facilities in the western parts of Bijar-Divandere plain to prevent water corrosion. Also, for the central regions to the east of the plain with water deposition properties and adverse effects on agriculture, industry and health of the region, the use of sedimentation inhibitors such as the use of phosphate compounds and less harvesting of water resources was recommended.

Urban gardens are important not only in terms of landuse but also in terms of the urban infrastructure, and their protection is an intergenerational responsibility. In recent decades, urban growth, inability to adapt ecological potential to the horizontal development of the city, weak integrated land management, inconsistencies in legal principles, lack of water resources and land trade, have led to the destruction of gardens and Irregular construction in them. The continuation of this process will face a crisis in urban life. Accordingly, the mechanism of protection of urban gardens has become a serious issue. This paper aims to explain the importance of urban gardens as urban green infrastructure, based on Water Footprint Protection and planning experiences and legal principles and by examining the special plan of Nazhvan lands as one of the successful experiences in this field, to introduce a desirable model to prevent the decline of urban ecosystem. This paper in terms of orientation is an applied research and in terms of the nature and subject of the research is descriptive and explanatory-predictive. The strategy of the research is based on qualitative research and case study, and data gathering has been done through documentary study and focus group. In this paper, ‘Nazhvan Special Plan’ has been analyzed using strategic analysis (SWOT) method based on the criteria of Plan-Process-Results (PPR) evaluation model and its orientations and intervention methods have been analyzed based on green infrastructure principles. The results of the analysis indicate that in Nazhvan Special Plan, the garden is seen as a part of the integrated structure of Isfahan green infrastructure and the main proposals of the plan are expressed in four types of protection, support, development and organization in order to maintain and expand the gardens. Evaluation of Nazhvan Special Plan shows that this plan has acted in acceptable quality in 50% of the criterias including Internal coherence, Interpretation of planning system, Relevance, external coherence and Direction, 30% of the criterias need to be completed and 20% of the criterias need to be modified and revised to be used in similar future experiences.

In the present study, in order to investigate climate change in the western basin of Jazmourian Wetland, the fifth report model of the CanESM2 Intergovernmental Panel on Climate Change and new scenarios of release in the near future (2021-2050) were used. Drought severity classes were followed. Finally, Mann-Kendall no[1]n-parametric test was used to elucidate the trend of annual changes in precipitation component. The results of CanESM2 model show that the average rainfall at Delfard and Dehroud stations has decreased by 0.019 and 0.036% under RCP2.6 scenario. On the other hand, in Kahnooj and Miandeh stations of Jiroft, in this scenario, the rainfall in the next period compared to the base period has increased by 0.085 and 0.17%. These changes in other scenarios have similar decreasing and increasing changes. The results of the rainfall trend indicate that in a number of stations, the trend is significant and in some non-trendy trends that have a downward or upward trend. Also, the results of SPI drought index in the region indicate an increase in drought from humid to more acute conditions. In this index, the highest frequency is related to normal class and the lowest frequency is related to very severe drought. As its situation is more acute in the future. Due to the fact that rainfall has decreased in most stations and on the other hand, the drought in the region has been intensified.

In this study, the effects of climate change on meteorological parameters in the Horrood river in lorestan Province, using CanESM5 model under RCP scenarios (RCP2.6, RCP4.5 and RCP8.5) was evaluated based on the sixth IPCC report in three time periods including the near future (2026-2050), the middle future (2051-2075) and the distant future (2076-2100). The statistical downscaling model (SDSM) was used to predict precipitation and mean temperature in the baseline period 1970-2005 at Kaka Reza and Dehno synoptic stations. The results of this study, in both Kaka Reza and Dehno stations, indicated a decreasing in precipitation and an increasing in average temperature under the all three RCP scenarios over the future period, so that in the distant future (2076-2100), under the RCP8.5 scenario (i.e. the pessimistic one), at Kaka Reza and Dehno synoptic stations, the precipitation showed the highest decreased by 36 and 39 percent in monthly scale and 30.36 and 33.35 percent in annual scale respectively and the mean temperature showed the highest increased by 17.5 and 17.1 in monthly scale and 9.32 and 9.06 in annual scale respectively. Finally, the results of this study showed that the climate change will affect precipitation and temperature in the Horrood river basin.

This study was conducted with the aim of estimating and modeling the green and blue water footprint of wheat crop using machine learning models in irrigated lands during (2004-2016). Therefore, using climatic and crop data and the fuzzy cluster method, the irrigated wheat cultivation areas in Fars province were divided into four homogeneous regions. Blue, green and gray water footprints were estimated in each region based on the Hoekstra framework. Then, the water footprint in the homogeneous climate was divided into two categories: training (70%) and testing (30%) and using the neural network model and two kernel such as log logistic and hyperbolic tangent (50 input combinations), random forest model and support vector regression (Sigmoid kernel function) was predicted with climatic and plant variables and the results of the models were compared with error evaluation indices and Taylor diagram. The results showed that the best model for estimating the water footprint of wheat in Fars province is the artificial neural network model with logistic log function with a correlation coefficient of more than 0.72 and an average absolute error of less than 0.48. This model can help improve the decision-making process for water managers and planners in the agricultural sector.

The paper examines the impact of climate change on the cooling and heating load of a sample building in 1000 locations across Iran. Although climate change affects the behavior of residents, building layers, tariffs of energy carriers, and other goods in addition to changing weather conditions, in this study only the effects of changing weather conditions on cooling and heating load have been studied. The results can be utilized to obtain a fair price for energy carriers in different climates, plan energy carriers' supply chains, and check the appropriate technologies to reduce energy consumption (insulations, water heaters, and other similar cases). In order to quantify the impact of climate changes on cooling and heating load, engineering software has been used. Investigating the cooling load and heating calculated shows that the range of the heating load is far greater than the range of the cooling load, and in general, the average cooling load is higher than the heating load. The maximum, average and minimum heating load was 198 , 7.2 , and close to zero, respectively. Moreover, the maximum, average and minimum cooling load was 166 , 67 , and 3.6 , respectively.