Gorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Analysis of factors affecting the consumption of medicinal plants and their products113762810.22069/ijerr.2026.22054.1420ENMohamad RahimForouzehAssoci. Prof. Dept. Rangeland Management, Gorgan University of Agricultural sciences & Natural ResourcesHassanYeganehAssociate Professor, Gorgan University of Agricultural Sciences and Natural ResourcesAbbasHosseinimaneshGorgan University of Agricultural Sciences and Natural resources, Gorgan, IranJournal Article20240101Medicinal properties, market demand, and satisfaction level are among a medicinal plant's most important economic indicators. Therefore, it is necessary to investigate the factors affecting the consumption of medicinal plants to analyze the behavior of consumers to implement management strategies in this field. Accordingly, the present research investigated the factors affecting the use of medicinal plants in Shiraz City one of the important metropolises of Iran. This study used a survey and questionnaire with approved validity and reliability. The required data were collected from 385 people in 11 municipal districts of Shiraz using a random sampling method. A set of demographic, economic, social, and cultural factors on the consumption of medicinal plants and their products was investigated. A logit model was used to analyze the data. The results showed that the studied factors, except for gender and income level, positively affected people’s decisions to use medicinal plants. Variables of education, age, awareness about medical properties of plants, fewer side effects, advertisement, family knowledge, doctor’s prescription, personal experience (trial and error), effective distribution marketing channels, consumption experience, anxiety caused by infectious diseases, unwillingness to attend the clinic, and the belief that medicinal plants are more compatible with the body were among the factors influencing people’s choice of medicinal plants. Regarding the tendency to use medicinal, policymakers must pay attention to the factors affecting the use of medicinal plants. By knowing the behavior of consumers, more appropriate policies could be implemented in the medicinal plant industry.https://ijerr.gau.ac.ir/article_7628_20936ee34cdce1e1893ab312f6208e95.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Analyzing social trust network in human-large carnivores conflict management, Case study: Golestan National Park1527762910.22069/ijerr.2026.22245.1428ENZahraEbrahimi MonfaredDepartment of Environmental Sciences, Faculty of Fisheries and Environmental Sciences, Gorgan University of Agricultural Sciences and Natural Resources, Iran.HamedMirkarimiHannanehMohammadi KangaraniDepartment of Forestry Faculty of Forest Sciences, Gorgan University of Agricultural Sciences and Natural ResourcesMahmoodSoofiDepartment of Conservation Biology, Georg-August University of Goettingen: Goettingen, GermanyJournal Article20240228Protected areas play a vital role in biodiversity conservation. However, human-large carnivore conflict (HCC) is a common problem in PAs and threatens long-term conservation goals. Socioeconomic factors are a significant aspect of HCC, and addressing these factors is crucial for achieving human-large carnivore coexistence. Trust and appropriate communication between all stakeholders are introduced as key factors in the HCC management, but they have remained unclear. The purpose of this study is to investigate stakeholders’ social networks in the HCC around the Golestan National Park (GNP), using social network analysis to address this gap. We identified a social trust network in support and information exchange in HCC. The data have been collected through a questionnaire and 292 face-to-face interviews with the residents of 30 villages around the GNP from April to November 2022. Indices of degree centrality, betweenness centrality, and Multi-dimensional scaling (MDS) were analyzed. Our findings show that local communities trust family members the most for receiving support and they trust the most in rangers in information exchange. On the other hand, villagers and village councils have an insignificant role in the social network. The results reveal the significant centrality of rangers in the social network and introduce them as important social capital and key actors in the HCC mitigation strategies. The findings of this research led to the clarification of the interactions in stakeholders’ social networks and demonstrated that conflict mitigation strategies require a multidisciplinary approach, and different social aspects of conflicts should be considered in conflict management programs.https://ijerr.gau.ac.ir/article_7629_6e326f56f8b872a0c5d9ecbf2d09d0d8.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Applicability of diatom based indices for water quality assessment in Iran ecosystems: case study Gorganrud subbasin (NE Iran)2937763010.22069/ijerr.2026.23422.1492ENAliHeshmatpourDepartment of Range and Watershed management, Faculty of Natural Resources, Gonbad Kavous University, Gonbad Kavous, Iran.JamilehPanahy MirzahasanlouDepartment of Biology, Faculty of Basic Science, Gonbad Kavous University, Gonbad Kavous, Iran.MarziehNikjouicDepartment of watershed Management, Gorgan University of Agricultural Sciences and Natural Resources, Gorgan, Iran.ArsalanBahalkehDepartment of Fisheries, Faculty of Agriculture and Natural Resources, Gonbad-Kavoos University, Gonbad-Kavoos, IranSeyyed AsgharHoseyniDepartment of Chemistry, Faculty of Basic Science, Gonbad Kavous University, Gonbad Kavous, Iran.Journal Article20250310Diatoms are one of the most important food resources in aquatic ecosystems extensively used in water quality assessments; however, use of diatom-based indices for water quality assessment is very scarce in Iran. In the present study applicability of diatom assemblage in monitoring ecological status in four tributaries of Gorganrud River, one of the main rivers in northeast Iran, evaluated. In this regard, water and diatom samples were collected monthly. In total 73 diatom taxa belong to the 30 genera identified. Achnanthidium minutissimum, A. gracillimum, Cymbella excisa, Diatoma moniliformis, Gomphonema olivaceum, Nitzschia dissipata and Rhoicosphenia abbreviata were the most dominant taxa in majority of the samples in all stations. The relationship between measured water quality indices (IRWQIsc and NSFWQI) and diatom index values (TDI and GDI) was assessed. Although results of the diatom indices and water quality indices were rather similar, however there were no significant correlations and relationships between indices. It seems further works are needed to clarify the usefulness of diatom indices in water quality assessments in Iran.https://ijerr.gau.ac.ir/article_7630_4e21fb8183000e861be4ea19c12162e3.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Mathematical approaches to enhancing crop efficiency in water-limited environments3950763110.22069/ijerr.2026.23542.1502ENEhsanGolafraDepartment of Agricultural Systems Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.MohammadGhahderijaniDepartment of Agricultural systems engineering, Science and Research branch,
Islamic Azad, Tehran, Iran.BabakBeheshtiDepartment of Agricultural Systems Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.MortezaAlmassiDepartment of Agricultural Systems Engineering, Science and Research branch, Islamic Azad University, Tehran, Iran.Journal Article20250416Due to the extensive border areas and varied climates across the country, establishing an effective cultivation pattern is essential for maximizing the use of production factors and resources. This is particularly important in addressing the significant issue of water scarcity. In recent decades, mathematical planning models have become increasingly popular for crafting agricultural policies, optimizing cultivation strategies, and managing agricultural resources. A study conducted in Mazandaran province utilized a two-stage simple random sampling technique, which is known for its reliability, allowing results to be generalized to the entire population when principles are correctly applied. This method aligns with the Iranian Statistics Center's practices, ensuring consistency in statistical methodologies. The study utilized an ideal planning model, specifically goal programming, to integrate diverse and sometimes conflicting objectives, guiding decision-makers toward optimal outcomes. The findings suggest that adopting sustainable practices could streamline crop cultivation in the region, potentially phasing out certain products from the current agricultural system. This transition is projected to boost gross revenue by 775,000 $ compared to existing models. Additionally, the research indicates that the use of fertilizers could decrease: phosphate by 102.12 tons, nitrogen by 65.02 tons, and potash by 38.5 tons, alongside significant reductions in chemical substances like herbicides, insecticides, and fungicides.https://ijerr.gau.ac.ir/article_7631_3f2eafdcf41139a223a9c7745f26569f.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Evaluation of energy and exergy efficiency of different rice planting methods in Khuzestan province, Iran5167763210.22069/ijerr.2026.23598.1506ENJafarHabibi AslResearch Assistant Professor, Agricultural Engineering Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center (AREEO), Ahwaz, Iran.PeymanVarjavandResearch Assistant Professor, Agricultural Engineering Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center (AREEO), Ahwaz, Iran.Journal Article20250429This study examines the efficiency and sustainability of various rice planting methods in Khuzestan province, focusing on their energy consumption and exergy indicators. Findings reveal notable differences in energy use and cumulative exergy among methods. Notably, the no-tillage approach has the lowest Cumulative Exergy Consumption (CExC) due to reduced diesel fuel use, while transplanting is the most energy-intensive, relying heavily on manpower and electricity for irrigation. The greatest Cumulative Energy Consumption (CEnC) arises from electricity for irrigation and chemical fertilizers. The analysis highlights fuel and electricity as primary contributors to CExC across treatments. Efficient irrigation methods yield higher Energy Return ratios and lower energy intensities, signifying better energy input efficiency. Data show varying cumulative energy demands, with direct dry seeding and no-tillage exhibiting higher energy efficiency. Cumulative Production Energy (CDP) values reveal differences in the energy performance of planting systems. The Renewability Index (RI) indicates Treatment 5 has the minimal environmental impact. Direct dry seeding on raised beds is favorable for production energy, while dry bed no-till-drill methods excel in exergy efficiency and renewability. Overall, the research underscores the need for improved irrigation management to enhance water and electricity efficiency in rice production, advocating for the adoption of more efficient irrigation techniques to boost energy usage and sustainability in rice cultivation.https://ijerr.gau.ac.ir/article_7632_91756d17ff0829e8b4d4c94e81139092.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Exploring main drivers of ecological culture of stakeholders in semiarid ecosystems6980763310.22069/ijerr.2026.23688.1511ENAzamKhosraviDepartment of Ecological Engineering, Faculty of Natural Resources, University of Jiroft, Jiroft, Iran.MohsenSharafatmandradDepartment of Ecological Engineering, Faculty of Natural Resources, University of JiroftJournal Article20250522Stakeholders' hop spots for conservation are crucial for preserving current arid ecosystems and halting the projected trend of habitat loss. In managing arid environments, stakeholder culture for ecosystem conservation has received little attention. The aim of this study was to assess ecological culture and its main drivers in the context of dry ecosystem conservation. Cultural indicators were used to map ecological culture in study region. Questionnaires were used to collect data. Results showed that forests were among the most important land covers in terms of ecological culture (p<0.05). Using PCA, the most important drivers affecting ecological culture were identified, and then the contribution of each driver to ecological culture was identified using structural equation model (SEM). The results showed that in total, the direct and indirect relationships of urbanization (p<0.001) and agriculture (p<0.01) negatively and climate (p<0.01), topography (p<0.01) and income (p<0.01) positively affected ecological culture. Results in this study can be used by policymakers to identify social hotspots where people-led landscape conservation could be feasible with controlling main drivers.https://ijerr.gau.ac.ir/article_7633_66a56613210a40a1bdb309f63f1c60a4.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Analysis of temperature and precipitation parameters using the general atmospheric circulation model, sixth report (Case study: Aleshtar synoptic station)8194763410.22069/ijerr.2026.23777.1523ENMohsenAdeli SardooeiDep. of Agricultural Economics, university of JiroftHamedEskandari DamanehUniversity of TehranHadiEskandari DamanehResearcher of Desert Research Division, Research Institute of Forests and
Rangelands, Agricultural Research Education and Extension Organization (AREEO), Tehran, Iran.MarziehRezaiDepartment of Natural Resources Engineering, Faculty of Agriculture and Natural Resources, University of Hormozgan, Bandar Abbas, Iran.SosanSalajeghehDepartment of Planning – Management and HSE, College of Environment, University of Tehran, IranJournal Article20250614Land-use change is a primary driver of global environmental degradation, with wetlands experiencing severe impacts, as 30–90% of global wetlands have been lost or significantly altered. Despite their critical ecological role, wetland land-use dynamics remain understudied, necessitating urgent conservation efforts aligned with three key 2030 global agendas. In Iran, agricultural overexploitation emerges as the predominant threat to wetland ecosystems, surpassing other factors such as climate change. This study investigates the drivers of land-use change and farmers’ conservation behaviors in the Bakhtegan and Tashak wetlands of Iran through a two-phase approach. Phase one employs remote sensing and GIS to quantify land-use transformations from 2000 to 2020, revealing a significant expansion of bare lands surrounding these wetlands. Phase two surveys local farmers to assess the socio-psychological factors shaping their willingness to support wetland conservation, analyzed using ENVI 5.3, ArcGIS 10.3, SPSS 20, and AMOS 20. Results indicate that positive attitudes and subjective norms significantly influence farmers’ behavioral intentions toward conservation (p < 0.05). These findings underscore the need for targeted policy interventions that integrate socio-psychological insights with land-use monitoring to enhance wetland conservation strategies.https://ijerr.gau.ac.ir/article_7634_c1b41ec243ce3272f712415a7eb89ef5.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Analysis of temperature and precipitation parameters using the general atmospheric circulation model, sixth report (Case study: Aleshtar synoptic station)95108763510.22069/ijerr.2026.23806.1526ENAliKakavandphd studentHamidrezaBabaaliAssociate Professor of Civil EngineeringJournal Article20250623Research and evaluation of these changes in each region are crucial for accurately understanding future challenges and related planning strategies.Accordingly, this study investigates the impact of climate change on meteorological parameters at the AleshtarSynoptic Station in Lorestan Province, Iran, using the CanESM5.0 climate prediction model from the Sixth Assessment Report (CMIP6). The research employs recorded temperature and precipitation data (1977–2022) and projects future climate conditions under three emission scenarios: optimistic (SSP1-2.6), intermediate (SSP2-4.5), and pessimistic (SSP5-8.5), for two 20-year periods (2031–2050 and 2051–2070). The LSRS-WG downscaling method was applied to enhance accuracy.The results show that in the SSP126 scenario, compared to the base period, the minimum temperature and precipitation have a decreasing trend and the maximum temperature has increased. The results also show that the simulated temperature under the SSP1-2.6 emission scenario has an increasing trend in the two future periods studied in the months of June to October. The results also showed that the precipitation parameter has an increasing trend in the future periods studied in the months of January to June and October to December. Overall, the results of the seasonal studies showed that the temperature parameter in the spring and summer seasons has an increasing trend and the precipitation parameter in the autumn and winter seasons follows this trend. In general, the results of this research can help in future water resources management, creating effective programs to combat climate change, and provide a basis for informed decision-making and appropriate planning.https://ijerr.gau.ac.ir/article_7635_8a7ed2b9670f92b21ee38e86b3e697ba.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Daily PM2.5 prediction and pollution episode detection using MLP neural networks across urban monitoring sites with varied land uses109127763610.22069/ijerr.2026.23813.1528ENMohamad JavadZoqiDepartment of Civil Engineering, University of Birjand, Birjand, IranAliasgharDehqanpour AliaqaApplied Climate and Weather Forecast Office, Iran Meteorological Organization, Atmospheric Science and Meteorological Research Center (ASMERC), Mashhad, IranSeyed JavadRasouliApplied Climate and Weather Forecast Office, Iran Meteorological Organization, Atmospheric Science and Meteorological Research Center (ASMERC), Mashhad, IranMohammad RezaMansouri DaneshvarApplied Climate and Weather Forecast Office, Iran Meteorological Organization, Atmospheric Science and Meteorological Research Center (ASMERC), Mashhad, IranJournal Article20250628This research presents a data-driven approach for forecasting daily PM2.5 concentrations using a multilayer perceptron (MLP) neural network across three urban monitoring sites in Mashhad, Iran—Sajjad, Torogh, and Vila—each reflecting a unique land-use profile. The study utilized daily datasets collected from 2018 to 2023, and a dedicated MLP model was trained for each station. Various training algorithms were assessed to identify the most suitable configuration, with model complexity fine-tuned by adjusting the number of neurons in the hidden layer. Key input features included meteorological variables from the preceding day (such as wind speed, ambient temperature, precipitation, solar radiation, and relative humidity), the previous day's PM2.5 concentration, and calendar-based temporal factors. To improve the network’s predictive capability and prevent overfitting, data normalization and early stopping strategies were applied. The best predictive performance was recorded at the Sajjad station, where the model achieved an R2 value of 0.79 and an MAE of 6.77 µg/m3. While the Torogh station yielded moderate predictive accuracy, the Vila station exhibited weaker performance. The models demonstrated strong capability in identifying pollution episodes, with true positive rates between 66% and 74%, and a minimum false alarm rate of 0.18 at the Sajjad station. Spatial disparities in model performance were attributed to localized environmental and climatic factors, including terrain variation and emission source intensity. Overall, the findings confirm the potential of MLP-based models as practical tools for daily air quality prediction and support their integration into urban pollution alert systems. .https://ijerr.gau.ac.ir/article_7636_e5e4b5c1f7916ae9e8db7b25ca288639.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Simulation of river discharge upstream of Dez dam using metaheuristic models128142763710.22069/ijerr.2026.23898.1535ENEbrahimNohaniMaterials and Energy Research Center, Dez.C., Islamic Azad University, Dezful, IranHamidrezaBabaaliAssociate Professor, Department of Civil Engineering, Islamic Azad University, Khorramabad branch, IranJournal Article20250721Measuring river discharge has always been one of the fundamental challenges in river management. The use of accurate tools for its calculation is essential. Numerical, analytical, artificial intelligence, and empirical methods are the most common approaches for measuring daily river flow. This study develops a hybrid intelligent model based on the Support Vector Regression (SVR) approach for simulating river discharge. For this purpose, three optimization algorithms—Wavelet, Whale Optimization, and Particle Swarm Optimization—were utilized to simulate river discharge. The modeling was based on data and statistics from the hydrometric stations in the Dez basin, including Tireh Marouk, Cham Chit, Sezar, and Tang-e Panj, as a case study. Four combined input parameter scenarios from 2012 to 2022 were applied. To evaluate the performance of the models, statistical indices including correlation coefficient, root mean square error (RMSE), mean absolute error (MAE), and Nash-Sutcliffe Efficiency were used. Additionally, scatter and Taylor diagrams were employed for result analysis. Results showed that the combined scenarios in the examined models improved model performance. The evaluation metrics indicated that the SVR-Wavelet model achieved a correlation coefficient of 0.898-0.985, root mean square error (m³/s) of 0.088-0.008, mean absolute error (m³/s) of 0.040-0.004, and Nash-Sutcliffe Efficiency of 0.951-0.995 during the validation phase. Overall, the results demonstrated that the use of intelligent models based on the Support Vector Regression approach could be an effective method for ensuring the sustainability of river engineering.https://ijerr.gau.ac.ir/article_7637_613a44565dc19a2998e915c21f908bf8.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Assessment of the economic, social, and environmental impacts of drought on the stakeholders of the Karganeh watershed in Iran143160763810.22069/ijerr.2026.23957.1543ENEbrahimKarimiAssistant Professor, Soil Conservation and Watershed Management Research Department, Lorestan Agricultural and Natural Resources Research and Education Center(AREEO), Khorramabad, IranSeyed HosseinAramiAssistant Professor, Forests and Rangelands Research Department, Khuzestan Agricultural and Natural Resources Research and Education Center, Agricultural Research Education and Extension Organization (AREEO), Ahvaz, IranRezaDehghaniPhD in Water Sciences and Engineering, Department of Soil Conservation and Watershed Management, Lorestan Province Agriculture and Natural Resources Research and Education Center, AREEO, Khorramabad, IranAliDastranj,Assistant Professor, Soil Conservation and Watershed Management Department, khorasan Razavi Agricultural and Natural Resources Research and Education Center (AREEO), Mashhhad. IranMehranZandSoil Conservation and Watershed Management Research Institute (SCWMRI), Agricultural Research, Education and Extension Organization (AREEO), Tehran, Iran.MahshidBahadoriExpert of Rural and Nomadic Women’s affairs in Agricultural JAHAD Khorramabad CountyJournal Article20250810Drought is a creeping phenomenon characterized by a gradual reduction in precipitation and increased temperatures, whose cumulative effects often manifest over extended periods. This study employs a quantitative approach to analyze the economic, social, and environmental impacts of drought on stakeholders in the Karganeh Watershed, Iran. A sample of 130 stakeholders (including farmers, pastoralists, nomads, and local council members) was selected via simple random sampling from a total population of N = 197, using Cochran's formula for precision. Data were collected through a researcher-administered questionnaire, validated by an expert panel, and demonstrating high reliability (Cronbach’s α = 0.829). Data analysis using the Friedman test revealed the following ranked impacts: Socio-Economic Impacts: The most severe consequences were a significant decrease in agricultural and horticultural income (mean rank = 16.13), a reduction in crop yield (mean rank = 16.01), and a decrease in orchard yield (mean rank = 16.09). Environmental Impacts: The most critical impact was the destruction of springs and drying of wells (mean rank = 9.36), followed by the reduction of groundwater and surface water resources (mean rank = 7.51) and an increase in pests and diseases affecting orchard trees (mean rank = 6.74).The findings quantitatively demonstrate that water resource depletion constitutes the primary environmental challenge, while severe reductions in income and agricultural productivity are the foremost socio-economic concerns. These results underscore the critical need for integrated water resource management and economic diversification strategies to enhance resilience in the watershed.https://ijerr.gau.ac.ir/article_7638_567f5601308101e835a90cca5622c73f.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Scenario-based modeling of water yield under future climate conditions using the InVEST model (Jajrud watershed, Iran)163174779910.22069/ijerr.2026.24129.1575ENAbolfazlMohammadniaDepartment of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.GholamrezaNabi BidhendiSchool of Environment, College of Engineering, University of Tehran, Tehran, IranSayed AbbasHosseiniDepartment of Civil Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.Journal Article20251001The increasing intensity of climate change and the accelerated urban expansion of cities in recent years have posed significant challenges to water resources in semi-arid regions such as the Jajroud watershed, located east of Tehran. This study applies a two-stage framework to assess the impact of future climate change on the basin’s water yield. In the first stage, historical and future climate conditions were examined using observational data and the results of the CMIP6 General Circulation Models (GCMs). The LARS-WG model was used for downscaling and bias correction, and the MRI-ESM2-0 model was selected as the best-performing GCM based on statistical criteria. In the second phase, the Water Yield model from the InVEST suite was used to estimate the spatial distribution of water yield under present (2024) and future (2040) conditions, using climate projections under scenarios SSP2-4.5 and SSP5-8.5. Model inputs included precipitation, reference evapotranspiration (ET₀), root-limiting depth, plant-available water, land use/cover, and a GIS-based biophysical table. Results indicate that water yield increased from approximately 80 MCM in 2014 to about 110 MCM in 2024, mainly due to higher recent precipitation. However, future projections reveal a strong decline, with total water yield decreasing to about 60 MCM under SSP2-4.5 and further dropping to 44 MCM under SSP5-8.5 by 2040, representing nearly a 60% reduction compared with current conditions. Besides climatic drivers, land-use changes—especially expansion of built-up areas and reduction of vegetation cover—further intensify water loss by limiting infiltration and increasing evaporation.https://ijerr.gau.ac.ir/article_7799_a3c09448fd69ed1fdbd5406a3946105a.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Agricultural water deficit and wastewater reuse potential in Patiala district, Punjab175184780010.22069/ijerr.2026.24194.1586ENSanjoyoGoraiAssistant Professor, Department of Chemistry and Environmental Sustainability, School of Sciences, IILM University, Greater Noida, India, 201306ManojKumarAssistant Professor, Department of Mathematics, School of Sciences, IILM University, Greater Noida, India, 201306Journal Article20251024The study examines future rainfall patterns, runoff generation, and net water deficits in the Patiala district of Punjab for 2024, 2030, 2035, and 2040, with a particular focus on agricultural water demand. Projections reveal a steady rise in average annual rainfall, increasing from 735.99 mm in 2024 to 757.27 mm by 2040, which translates into higher runoff, from 2.37 to 2.44 billion m³. Despite this positive trend, water scarcity remains a pressing concern. Under minimum irrigation consumption scenarios, the net water deficit declines moderately from 0.252 billion m³ (9.61%) in 2024 to 0.183 billion m³ (6.99%) in 2040, suggesting slight relief. However, under maximum consumption scenarios, the deficit persists at alarming levels, decreasing only marginally from 1.57 billion m³ (39.93%) to 1.51 billion m³ (38.19%) over the same period. These results indicate that even with marginal increases in rainfall, rapidly growing agricultural demand will continue to place severe pressure on water resources. The study emphasizes the urgent need for sustainable water management, including efficient irrigation systems, groundwater recharge, wastewater reuse, and rainwater harvesting. Reuse of wastewater can fulfil upto 33.2% of the deficit from rainfall. Therefore, the study suggests to reuse the wastewater generated from the rural area of the study after some basic treatments which will reduce the load on groundwater as well reliance on rainfall.https://ijerr.gau.ac.ir/article_7800_ff9a148d104b2e2988cdc2d2fdc65efa.pdfGorgan University of Agricultural Sciences and Natural ResourcesEnvironmental Resources Research2783-483214120260101Assessing the visual quality of forest park landscapes: A case study of the Barajin park in Qazvin's suburb area, Iran185196763910.22069/ijerr.2026.24257.1597ENRezaJafarihaDepartment of Architecture, Imam Khomeini International University (IKIU), Qazvin, Iran.Journal Article20251105The visual assessment of forest park landscapes is of great importance for planning their design, organization, conservation and management. In this study, the visual quality of Barajin Forest Park located in the suburban area of Qazvin, Iran, has been examined based on the conceptual framework developed by Tveit et al. Seven visual criteria of sense of order, coherence, disturbance, visibility, imageability, diversity, and naturalness were assessed using an online survey with photography representation. Collected data from respondents were coded and analyzed using SPSS into Expert and Non-expert respondents. Results show that naturalness, coherence, visibility, and imageability were the most important parameters of visual quality. Little difference was found between the perceptions of Experts and Non-experts. These results highlight the importance of including visual landscape metrics in planning and management of urban forest parks for optimizing visitor experience and ensuring ecological sustainability. By applying the Tveit et al. framework to a non-European context (Iran), this study tests its international relevance. Key outcomes indicate a strong convergence between expert and public perceptions, and highlight the critical role of 'naturalness' as an indicator in a comparatively dry suburban park.https://ijerr.gau.ac.ir/article_7639_d7c2a21006137453211dbfca0ae9f9f5.pdf