دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Combination of Fuzzy and Boolean logic and MCDM Methods for Investigating Suitable Areas for Artificial Groundwater Recharge (Case Study: Chenaran Watershed in Razavi Khorasan Province) Combination of Fuzzy and Boolean logic and MCDM Methods for Investigating Suitable Areas for Artificial Groundwater Recharge (Case Study: Chenaran Watershed in Razavi Khorasan Province) 10 1 114048 FA میثم قواهی MSc. Graduated of Watershed Management, Islamic Azad University Maybod Branch محمود حسن زاده نفوتی Dept. of watershed management, Maybod Branch, Islamic Azad University, maybod, Iran علی اکبر جمالی Dept. of watershed management, Maybod Branch, Islamic Azad University, Maybod, Iran Journal Article 2018 03 05 More than two-thirds of Iran have been located in arid and semi-arid regions. Overuse of groundwater water resources has decreased the groundwater level in these areas. Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. Investigating suitable areas for optimal use of water floods is one of the most important factors in recharging underground water tables in dry lands where the agricultural and rangelands are vulnerable. Hence, this study proposes a methodology to delineate artificial recharge zones and identify favorable artificial recharge sites using integrated Fuzzy logic, Boolean logic and multi-criteria decision-making (MCDM) methods for augmenting groundwater resources in Chenaran Watershed facing water shortage problems. The thematic layers considered in this study are infiltration rate, slope, geology, geomorphology, land cover, distance to river, distance to road and distance to Qanats and wells, which were prepared using satellite imagery and conventional data. Then, by applying the limiting layer as a combination of four criteria of lithology, land use, slope and geomorphology, the final map of recharge suitable areas was prepared and prioritized from highly suitable to unsuitable. The final obtained map divided the study area into five zones according to their suitability for artificial groundwater recharge. The results were then examined against the existing water spreading site to estimate their accuracy. The artificial recharge suitable zone of the final map was found to be in agreement with the map of water spreading project performed by the Ministry of Agriculture Djehad (accuracy was more than 78%). The results of this study could be used to formulate an efficient groundwater management plan for the study area and other similar areas. More than two-thirds of Iran have been located in arid and semi-arid regions. Overuse of groundwater water resources has decreased the groundwater level in these areas. Artificial recharge plays a pivotal role in the sustainable management of groundwater resources. Investigating suitable areas for optimal use of water floods is one of the most important factors in recharging underground water tables in dry lands where the agricultural and rangelands are vulnerable. Hence, this study proposes a methodology to delineate artificial recharge zones and identify favorable artificial recharge sites using integrated Fuzzy logic, Boolean logic and multi-criteria decision-making (MCDM) methods for augmenting groundwater resources in Chenaran Watershed facing water shortage problems. The thematic layers considered in this study are infiltration rate, slope, geology, geomorphology, land cover, distance to river, distance to road and distance to Qanats and wells, which were prepared using satellite imagery and conventional data. Then, by applying the limiting layer as a combination of four criteria of lithology, land use, slope and geomorphology, the final map of recharge suitable areas was prepared and prioritized from highly suitable to unsuitable. The final obtained map divided the study area into five zones according to their suitability for artificial groundwater recharge. The results were then examined against the existing water spreading site to estimate their accuracy. The artificial recharge suitable zone of the final map was found to be in agreement with the map of water spreading project performed by the Ministry of Agriculture Djehad (accuracy was more than 78%). The results of this study could be used to formulate an efficient groundwater management plan for the study area and other similar areas.

https://deej.kashanu.ac.ir/article_114048_62660a019c813f3e1f72c596b13e34cc.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Comparison of artificial neural network and multiple linear regressions efficiency for predicting soil salinity in Yazd -Ardakan plain, central Iran Comparison of artificial neural network and multiple linear regressions efficiency for predicting soil salinity in Yazd -Ardakan plain, central Iran 20 11 114049 FA فاطمه روستایی Combat to desertification, Natural Resource Faculty, Ardakan University, Yazd, Iran شمس اله اتوبی Department of soil science, College of Agriculture, Isfahan University of Technology, Isfahan, Iran مجتبی نوروزی Department of Soil Science, College of Agriculture, Shahid Chamran University of Ahvaz, Khuzestan, Iran Journal Article 2017 12 22 The study was conducted to evaluate the efficacy of artificial neural network (ANN) and multivariate regression (MLR) analysis to predict spatial variability of soil salinity in central Iran, using remotely sensed data. The analysis was based on data acquired from EOS AMI remote sensing satellite. The two methods was used to study linear and non-linear relationship between soil reflectance and soil salinity. In MLR analysis, stepwise method and neural network were applied using sensitivity coefficient by arranging inputs through the backward propagation, and then modeling was done. The R2 and RMSE were 0.23 and 0.33 for MLR, and 0.79 and 0.11 for ANN, respectively. Digital values of VNIR1 and NDVI48 were identified as the most important factors in MLR, whereas Sum19 and SWIR6 were recognized as the most important data to predict soil salinity using ANN. The results indicated that ANN model is used to detect non- linear relationship between soil salinity and ASTER data at the study area. The study was conducted to evaluate the efficacy of artificial neural network (ANN) and multivariate regression (MLR) analysis to predict spatial variability of soil salinity in central Iran, using remotely sensed data. The analysis was based on data acquired from EOS AMI remote sensing satellite. The two methods was used to study linear and non-linear relationship between soil reflectance and soil salinity. In MLR analysis, stepwise method and neural network were applied using sensitivity coefficient by arranging inputs through the backward propagation, and then modeling was done. The R2 and RMSE were 0.23 and 0.33 for MLR, and 0.79 and 0.11 for ANN, respectively. Digital values of VNIR1 and NDVI48 were identified as the most important factors in MLR, whereas Sum19 and SWIR6 were recognized as the most important data to predict soil salinity using ANN. The results indicated that ANN model is used to detect non- linear relationship between soil salinity and ASTER data at the study area.

https://deej.kashanu.ac.ir/article_114049_0806c5dc2c16fbdcdc163048778c96c9.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Assessment and Application of Two General Circulation Models (HadCM3 and MPEH5) for Investigating Climate Change (Case Study: Khorramabad Synoptic Station, Iran) Assessment and Application of Two General Circulation Models (HadCM3 and MPEH5) for Investigating Climate Change (Case Study: Khorramabad Synoptic Station, Iran) 21 36 114050 FA آسیه بیاتی Department of Natural Resources, Agriculture Faculty, Ilam University, Ilam, Iran محسن توکلی Department of Natural resources, Agriculture faculty, Ilam university, Ilam, Iran ایمان باباییان پژوهشکده اقلیم شناسی، سازمان هواشناسی کشور، مشهد. فاطمه درگاهیان سازمان تحقیقات، آموزش و ترویج کشاورزی، موسسه تحقیقات جنگلها و مراتع کشور Journal Article 2023 12 01 A popular method for climate change prediction are General Circulation Models which are at coarse spatial resolution and must be downscaled. In this study, observed data of temperature, precipitation and potential evapotranspiration over a base period under two emission scenarios in three time intervals were used to implement SDSM as a downscaling tool for HadCM3 model output. From another standpoint, MPEH5 model predicts data under three emission scenarios for three future periods. Results indicated that all parameters would increase in comparison to the base period. Predictions for all periods under all emission scenarios indicated an increasing trend for all parameters, although it is predicted almost as constant precipitation trend for the future. According to predictions by both models, the greatest increase has been estimated for 2080s under A2 scenario. In SDSM model, the greatest increases in mean monthly temperature would be respectively 6.9, 4.5, 6.2 °C for July and for potential evapotranspiration would be in June by 1.08 mm per day, which are predicted in the 2080s under A2 scenario. For precipitation, the greatest reduction under the same conditions, would be in May by 0.9 mm per day. In LARS-WG model, the greatest increase in mean monthly temperature in the studied station was predicted respectively by 5.5, 5.5, 5.6 °C for August. The greatest reduction in precipitation, would be in February (by 0.88 mm per day). The future uncertainty results of predicted parameters in both models and various scenarios show that uncertainty of the predictions increase towards the end of the century. A popular method for climate change prediction are General Circulation Models which are at coarse spatial resolution and must be downscaled. In this study, observed data of temperature, precipitation and potential evapotranspiration over a base period under two emission scenarios in three time intervals were used to implement SDSM as a downscaling tool for HadCM3 model output. From another standpoint, MPEH5 model predicts data under three emission scenarios for three future periods. Results indicated that all parameters would increase in comparison to the base period. Predictions for all periods under all emission scenarios indicated an increasing trend for all parameters, although it is predicted almost as constant precipitation trend for the future. According to predictions by both models, the greatest increase has been estimated for 2080s under A2 scenario. In SDSM model, the greatest increases in mean monthly temperature would be respectively 6.9, 4.5, 6.2 °C for July and for potential evapotranspiration would be in June by 1.08 mm per day, which are predicted in the 2080s under A2 scenario. For precipitation, the greatest reduction under the same conditions, would be in May by 0.9 mm per day. In LARS-WG model, the greatest increase in mean monthly temperature in the studied station was predicted respectively by 5.5, 5.5, 5.6 °C for August. The greatest reduction in precipitation, would be in February (by 0.88 mm per day). The future uncertainty results of predicted parameters in both models and various scenarios show that uncertainty of the predictions increase towards the end of the century.

https://deej.kashanu.ac.ir/article_114050_ab8915ecb6f26f7078e7cbc8527ba1b0.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Landscape Function Analysis to Assess the Grazing Effect on Some Soil Features in Arid Ecosystem Landscape Function Analysis to Assess the Grazing Effect on Some Soil Features in Arid Ecosystem 42 37 114051 FA رضا دهقانی بیدگلی Department of Watershed & Rangeland Management, University of Kashan, Iran علی کشاورزی Laboratory of Remote Sensing and GIS, Department of Soil Science, University of Tehran, P.O.Box: 4111, Karaj 31587-77871, Iran Journal Article 2018 04 24 Sustainable rangelands management continues to be one of the main challenges facing arid ecosystem. The function of a rangeland ecosystem depends on the conservation of resources within the ecosystem. Finding the rangeland ecosystem functions requires the knowledge of soil and vegetation characteristics to understand the ecosystem's capabilities. In this research, in order to identify the damaged areas in arid regions, the effect of grazing on the ecosystem function was investigated using the distance from the water resources. Thus, in the present study, around 3 water resources in 4 principal geographical directions and 172 plots with 4 m2 were installed. In each plot, 11-soil surface indexes were estimated by the landscape function analysis (LFA) method. Then, using 11 soil surface indexes, three soil functional properties include stability; permeability and nutrient cycle were calculated. In order to determine the sensitivity of the LFA method and separate the functional and structural characteristics SPSS software V.19 were used and the analysis of variance and comparing the mean of common features conducted by Duncan's method. Multivariate analysis of variance and correlation showed that the three functional features had no significant relationship with the four geographical directions (P <0.01) but had a significant relationship with the distance from the water resources (P <0.01). These results indicated that the ecosystem functions increases with distance from the water resources. Also, the results of Duncan's test showed that the high grazing intensity near the water resources caused a critical range of 150m from the water resources. Sustainable rangelands management continues to be one of the main challenges facing arid ecosystem. The function of a rangeland ecosystem depends on the conservation of resources within the ecosystem. Finding the rangeland ecosystem functions requires the knowledge of soil and vegetation characteristics to understand the ecosystem's capabilities. In this research, in order to identify the damaged areas in arid regions, the effect of grazing on the ecosystem function was investigated using the distance from the water resources. Thus, in the present study, around 3 water resources in 4 principal geographical directions and 172 plots with 4 m2 were installed. In each plot, 11-soil surface indexes were estimated by the landscape function analysis (LFA) method. Then, using 11 soil surface indexes, three soil functional properties include stability; permeability and nutrient cycle were calculated. In order to determine the sensitivity of the LFA method and separate the functional and structural characteristics SPSS software V.19 were used and the analysis of variance and comparing the mean of common features conducted by Duncan's method. Multivariate analysis of variance and correlation showed that the three functional features had no significant relationship with the four geographical directions (P <0.01) but had a significant relationship with the distance from the water resources (P <0.01). These results indicated that the ecosystem functions increases with distance from the water resources. Also, the results of Duncan's test showed that the high grazing intensity near the water resources caused a critical range of 150m from the water resources.

https://deej.kashanu.ac.ir/article_114051_84abd1d29b26a8354cfbf21bca9c3116.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Hydrological Impacts of Large Reservoir Dam and Land Subsidence on Downstream Groundwater Resources using Mathematical Modeling Hydrological Impacts of Large Reservoir Dam and Land Subsidence on Downstream Groundwater Resources using Mathematical Modeling 43 52 114052 FA رضا قضاوی کاشان دانشگاه کاشان دانشکده منابع طبیعی حیدر ابراهیمی Dept of watershed management, faculty of natural science,University of Kashan Journal Article 2018 05 28 Spatial and temporal change of groundwater recharge is crucial for effective groundwater resources management especially in arid and semi-arid regions. Human activities such as reservoir construction commonly interrupt the balance of the subsurface system. The main aim of this study was to investigate the interaction impacts of land subsidence and dam construction on Mosian aquifer located at the north-west of Iran. Groundwater mathematical model (MODFLOW), Geographic Information System (GIS), and stochastic weather generator model (LARS WG) were used for predict the impact of dam construction on groundwater balance of the study area. According to results, from 1991 to 2014, groundwater level declination and land subsidence at the downstream area of the dam were 11.22 and 0.45 meter respectively. Constructed dam has different effects on some components of water balance. River recharge decrease by 65 percent, whereas, recharge through return water increase by 50 percent. The results of the prediction indicate that groundwater level will decrease continually, as the annual groundwater declination will be 0.58m for the period of 2015 to 2030.The results also show that dam construction should decrease the trend of the groundwater declination. Predicted average of groundwater declination was 0.58 and 0.65 m when simulation was implemented for dam and no dam condition respectively. The effect of land subsidence on groundwater declination was not noticeable compared to effects of the groundwater discharge. Spatial and temporal change of groundwater recharge is crucial for effective groundwater resources management especially in arid and semi-arid regions. Human activities such as reservoir construction commonly interrupt the balance of the subsurface system. The main aim of this study was to investigate the interaction impacts of land subsidence and dam construction on Mosian aquifer located at the north-west of Iran. Groundwater mathematical model (MODFLOW), Geographic Information System (GIS), and stochastic weather generator model (LARS WG) were used for predict the impact of dam construction on groundwater balance of the study area. According to results, from 1991 to 2014, groundwater level declination and land subsidence at the downstream area of the dam were 11.22 and 0.45 meter respectively. Constructed dam has different effects on some components of water balance. River recharge decrease by 65 percent, whereas, recharge through return water increase by 50 percent. The results of the prediction indicate that groundwater level will decrease continually, as the annual groundwater declination will be 0.58m for the period of 2015 to 2030.The results also show that dam construction should decrease the trend of the groundwater declination. Predicted average of groundwater declination was 0.58 and 0.65 m when simulation was implemented for dam and no dam condition respectively. The effect of land subsidence on groundwater declination was not noticeable compared to effects of the groundwater discharge.

https://deej.kashanu.ac.ir/article_114052_3e3cb4649476329d12266bc14887abf5.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Comparative Functioning of Photosynthetic Apparatus and Leaf Water Potential in Zygophyllum eurypterum (Boiss & Bushe) During Phenological Phases and Summer Drought Comparative Functioning of Photosynthetic Apparatus and Leaf Water Potential in Zygophyllum eurypterum (Boiss & Bushe) During Phenological Phases and Summer Drought 60 53 114053 FA ابوالفضل رنجبر فردویی Department of desert control and management Journal Article 2018 06 22 Background: In arid regions, seasons are often marked by differences in rainfall, with life-history events, along with phenological stages. Materials and Methods: Three phenological phases were distinguished as vegetative phase (VP), flowering phase (FP) and seeding phase (SP). Chlorophyll fluorescence parameters (Chl. FPs) such as maximum quantum yield of PSII photochemistry (Fv/Fm), photochemical efficiency of photosystem II (ΦPSII), effective quantum yield (Fv'/Fm'), photochemical dissipation of absorbed energy (qP) and non-photochemical dissipation of the absorbed energy (NPQ) along with pigment contents and predawn leaf water potential (ΨL) were determined. Results:All Chl. FPs changed along drought stress gradient and phenological phases, with signiﬁcant changes at SP. Discussion: A significant change in the mentioned parameters explains the happening of severe photoinhibition because of photo-inactivation of the PSII reaction centers, or expresses thermal dispersion from the antenna pigment-protein compound. A remarkable alteration in pigment content was noticed at the SP. Decrease in the chlorophyll content under drought stress can be due to a reduction in synthesis of pigment complexes encoded by the cab gene family or destruction of light harvesting chlorophyll ‘a’ or ‘b’ pigment protein systems. Conclusions: we can say that Z. eurypterumcan protects the PSII reaction center from damage at the middle stage of drought stress (end of July) and can be qualified as a drought tolerant species. Background: In arid regions, seasons are often marked by differences in rainfall, with life-history events, along with phenological stages. Materials and Methods: Three phenological phases were distinguished as vegetative phase (VP), flowering phase (FP) and seeding phase (SP). Chlorophyll fluorescence parameters (Chl. FPs) such as maximum quantum yield of PSII photochemistry (Fv/Fm), photochemical efficiency of photosystem II (ΦPSII), effective quantum yield (Fv'/Fm'), photochemical dissipation of absorbed energy (qP) and non-photochemical dissipation of the absorbed energy (NPQ) along with pigment contents and predawn leaf water potential (ΨL) were determined. Results:All Chl. FPs changed along drought stress gradient and phenological phases, with signiﬁcant changes at SP. Discussion: A significant change in the mentioned parameters explains the happening of severe photoinhibition because of photo-inactivation of the PSII reaction centers, or expresses thermal dispersion from the antenna pigment-protein compound. A remarkable alteration in pigment content was noticed at the SP. Decrease in the chlorophyll content under drought stress can be due to a reduction in synthesis of pigment complexes encoded by the cab gene family or destruction of light harvesting chlorophyll ‘a’ or ‘b’ pigment protein systems. Conclusions: we can say that Z. eurypterumcan protects the PSII reaction center from damage at the middle stage of drought stress (end of July) and can be qualified as a drought tolerant species.

https://deej.kashanu.ac.ir/article_114053_8ad375355f8d5a08c1a908ee5d354d21.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 7 شماره 1 انگلیسی 2018 08 23 Effect of storage conditions and storage periods on seed germination of Kochia prostrata (L.) Schrad Effect of storage conditions and storage periods on seed germination of Kochia prostrata (L.) Schrad 65 61 114054 FA مجید محمد اسمعیلی Dept of Range management, Gonbad kavous University مسعود صمیعی Dept of Range management, Gonbad kavous University Journal Article 2023 12 01 Seed storage of range species especially for key species and palatable is inevitable for improvement and development of rangelands. After gathering seeds within the site and separating litters and defect seeds, they are kept in oven at a temperature 30°C and when their humidity is about 10 percent, we take them out. Now in 44 containers all with their shutters, put in each 150 random seeds and put to them four treatments: 0-5, 5-10, 15 and 20 °C. We put each of the eleven containers in separate storage areas and using a germination machine, measuring the germination capacity will be possible. Results show that all of the temperatures have a significant difference at 5% and maximum ratio of germination achieves at 0-5 °C during 6 months. Interaction between storage conditions and storage periods shows that storage periods of seeds till 9 months for temperatures 0-5 and 5-10°C, the percentage of germination capacity will increase and then will decrease. But of treatments 15 and 20 °C with an increase in time of storage, the germination of K. prostrata will decrease. It seems that temperature is one of the factors that decrease the after-ripening period but this factor in a short time has a severe effect on the germination capacity of K. prostrata. Seeds of K. prostrata can sustain more than 50% of their germination capacity at temperatures 0-5 and 5-10 °C during 24 months. Seed storage of range species especially for key species and palatable is inevitable for improvement and development of rangelands. After gathering seeds within the site and separating litters and defect seeds, they are kept in oven at a temperature 30°C and when their humidity is about 10 percent, we take them out. Now in 44 containers all with their shutters, put in each 150 random seeds and put to them four treatments: 0-5, 5-10, 15 and 20 °C. We put each of the eleven containers in separate storage areas and using a germination machine, measuring the germination capacity will be possible. Results show that all of the temperatures have a significant difference at 5% and maximum ratio of germination achieves at 0-5 °C during 6 months. Interaction between storage conditions and storage periods shows that storage periods of seeds till 9 months for temperatures 0-5 and 5-10°C, the percentage of germination capacity will increase and then will decrease. But of treatments 15 and 20 °C with an increase in time of storage, the germination of K. prostrata will decrease. It seems that temperature is one of the factors that decrease the after-ripening period but this factor in a short time has a severe effect on the germination capacity of K. prostrata. Seeds of K. prostrata can sustain more than 50% of their germination capacity at temperatures 0-5 and 5-10 °C during 24 months.

https://deej.kashanu.ac.ir/article_114054_9f56d7734877860bdc8d26ce9b6c3c60.pdf