دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Impact of Profitability Policies on Capital Outflow in Zanjan Province تأثیر سیاست سودآوری بر جریان خروجی استان زنجان 1 24 115165 ‎10.22052/deej.2025.257357.1116 FA شهلا پایمزد اراک دانشگاه اراک دانشکده کشاورزی گروه مهندسی آب حسین جیریایی شراهی گروه مهندسی آب دانشگاه اراک Journal Article 2025 08 06 Introduction: Water resources are critical yet finite, supplying a vast number of consumers. Their management, therefore, demands meticulous planning and heightened sensitivity. As human life and ecological stability depend on the reliable availability of these resources in specific quantities, locations, and times, strategic and foresighted approaches to water storage and allocation are paramount. The decisions made by policymakers and managers in this realm—whether for the short or long term—carry profound consequences, ranging from detrimental to highly beneficial. In a society characterized by one-sided and predominantly exploitative practices, the emergence of water-related disputes and challenges is not merely a possibility but an inevitability. This study investigates this critical balance through a dynamic simulation. We defined 16 distinct scenarios for the agricultural sector to model the impact of two key policy levers—profitability incentives and water supply restrictions—on the outflow of water resources from Zanjan Province. The simulation was conducted on a monthly scale, covering a 30-year period from 1993 to 2023, to capture both seasonal variations and long-term trends. Materials and Methods: The methodology of this study is grounded in System Dynamics (SD), a simulation approach specifically designed for modeling complex, non-linear, and multi-variable systems. Unlike static models, SD captures the dynamic interplay of variables over time, making it an effective tool for supporting complex decision-making in resource management. Following the collection and verification of historical statistics and data, a system dynamics model was developed to simulate the effects of two key policy interventions—profitability incentives and water supply restrictions—on agricultural planning. The model explicitly represents how these policies influence the selection of cultivated areas for two key crops, wheat and alfalfa, and subsequently impact the hydrological balance of the province, measured as the ratio of water outflow to inflow. The simulation was built upon a set of interconnected equations that dynamically determine crop yield and, consequently, the allocation of cultivated area through feedback mechanisms. These relationships were encoded in detail within the model structure. The statistical period (1993–2023) was divided into two phases to ensure model robustness: Calibration and Validation: The first segment of the data was used to calibrate the model parameters and verify its efficiency in replicating observed historical behavior.Policy Testing: The second segment was used to test and evaluate the outcomes of the 16 predefined policy scenarios. Finally, for each of the 16 scenarios, the model simulated output values for key variables, including total cultivated area, crop yield, economic benefit, and the critical water balance indicator—the ratio of the province's total water outflow to inflow. Results: Following the simulation of the two policy types and their associated scenarios, key outcomes for cultivation patterns, economic benefit, and water balance were observed. Impact of Profitability Policy (Price Increase): Cultivated Area: A doubling of the selling price for a crop led to a significant expansion in its cultivated area, with a weaker cross-effect on the competing crop. Wheat: Cultivated area increased by an average of 43% (Note: The original text had a discrepancy between average (43%) and maximum (40%). This version uses the average. Please verify your data). Alfalfa: Cultivated area increased by an average of 37%. Crop Yield (Performance): Contrary to area expansion, crop yields decreased under the profitability policy. Wheat: Yield decreased by an average of 20%. Alfalfa: Yield decreased by an average of 11% when its price was doubled. Economic and Hydrological Outcomes: When prices for both crops were doubled, the model resulted in: A 71% increase in total profit. A 48% increase in the total cultivated area of the province. A 30% decrease in overall crop performance. A 69% decrease in the province's water outflow ratio. Impact of Water Supply Limitation Policy: Cultivated Area: Imposing water supply limitations significantly reduced cultivation. When applied to both crops, the wheat cultivation area decreased by an average of 71% and the total provincial cultivated area decreased by an average of 68%. A single-crop limitation proved ineffective. For instance, limiting only wheat led to a 75% decrease in wheat area but induced competitive cultivation of alfalfa, making it an unsuitable strategy for water conservation. The same dynamic held true for alfalfa. Crop Yield: Under supply limitations, yields increased, likely due to a concentration of limited water on a smaller area. Wheat yield increased by 42%. Alfalfa yield increased by 25%. Economic and Hydrological Outcomes: Compared to the baseline, the supply limitation policy resulted in: A 44% decrease in agricultural benefit. A 23% increase in the province's water outflow. Policy Comparison and Synthesis A direct comparison between the two policies reveals a clear trade-off: The profitability policy boosted economic returns (+71% benefit) and improved water retention (-69% outflow). The supply limitation policy reduced economic output (-49% benefit) and worsened the water outflow situation (+76% outflow). The scenario analysis further contextualizes farmer behavior. The maximum simulated cultivated area (141,979 hectares in the "wh Bnf & al Bnf 2-2" scenario) is lower than the actual recorded area of 161,544 hectares. This suggests that real-world farmers are operating at a profitability level equivalent to 2.3 times the base benefit, which aligns with a significant 84% decrease in the outflow ratio. Consequently, implementing the profitability policy would result in a relative outflow of just 16% of the baseline conditions. Conclusion and Discussion: The simulation results underscore a critical dilemma: while a profitability policy aligns with farmer incentives, its long-term implementation in the face of finite water resources risks causing irreversible damage to the region's hydrological system. The model clearly demonstrates that a profitability policy, which is naturally preferred by farmers, leads to a dramatic reduction in provincial water outflow—exceeding 80%. This occurs because farmers, operating under the assumption of abundant water, prioritize profit maximization by expanding their cultivated area. This expansion compensates for the associated decrease in crop yield, making the strategy financially rational from an individual perspective, but hydrologically detrimental at a systemic level. Conversely, a policy of mandatory water supply limitation forces a reduction in the total cultivated area. While this may seem restrictive, it induces a more efficient and sustainable agricultural model. The simulation confirms that this policy leads to: Increased Crop Yield: A concentration of limited water resources on a smaller area enhances productivity per unit of land. Reasonable Economic Benefit: Farmers can maintain viable operations through higher efficiency rather than sheer scale. Significant Water Conservation: It directly curbs the irrational withdrawal and waste of water, preserving the resource base. In essence, by forgoing the short-term appeal of the profitability policy and implementing managed supply constraints, farmers are guided toward a more sustainable equilibrium. This approach secures better yields through improved management and prevents the over-exploitation that threatens the province's water future. The findings lead to an unequivocal recommendation for policymakers: maintaining the status quo is not an option. Without a decisive shift away from purely profit-driven water allocation toward an integrated strategy that balances economic incentives with physical supply limits, the cumulative damage to Zanjan Province's water resources will be severe and irreversible. نتایج حاصل از نگرش تصمیم‌گیرندگان در کوتاه‌مدت یا بلندمدت عواقب سوء یا سودمندی را در حوزۀ مدیریت منابع آب به‌ همراه خواهد داشت. در جامعه‌ای یک‌سونگر و منحصراً بهره‌بردار، بروز مناقشات آبی و چالش‌های مرتبط، دور از انتظار نبوده و قطعاً رخ خواهد داد. در تحقیق حاضر با تعریف 16 سناریو در بخش کشاورزی،‌ تأثیر دو سیاست سودآوری و محدودیت عرضۀ منابع آب بر جریان خروجی استان زنجان با دیدگاه دینامیکی طی سال‌های 1372 تا 1402 در مقیاس ماهانه شبیه‌سازی شد. نتایج سیاست سودآوری نشان داد با افزایش قیمت دوبرابری گیاهان،‌ 71%‌ سود با 48% افزایش سطح زیر کشت کل استان و 30% کاهش عملکرد حاصل شده است. این امر 69% کاهش جریان خروجی نسبی استان را به‌ همراه داشته است. به عبارتی بهتر، 69% کاهش خروجی نسبی استان به بهای 71% سود بخش کشاورزی نتیجه شده است. این خسارت بسیار جبران‌ناپذیر بی‌توجه به بهای آب نتیجه شده است. لذا مدیریت منابع آب ازطریق سیاست اعمال محدودیت عرضۀ منابع آب، اجرا و نتایج نشان داد با اعمال سیاست محدودیت عرضه، نسبت به سیاست سودآوری، سطح کشت کل استان، به‌طور متوسط 68% کاهش، عملکرد 33% افزایش و درنهایت،‌ متوسط مقدار سود 49% کاهش و خروجی 76% افزایش داشته است. در همین راستا، اعمال محدودیت عرضه، در شرایط قیمت پایه، 23% افزایش جریان خروجی را به‌ دنبال خواهد داشت. نتایج حاصل از شبیه‌سازی مقادیر سطوح زیر کشت فعلی استان نشان می‌دهد کشاورز با سودی حدود 3/2 برابر سود پایه اقدام به کشت نموده است. این امر معادل 84% کاهش نسبت جریان خروجی است.

https://deej.kashanu.ac.ir/article_115165_326a95a25f1682de4d4bc26edf50f041.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Comparative Evaluation of Soil Erosion and Sediment Yield Estimation in the Dowlatabad Watershed Using the EPM, MPSIAC, and IntErO Models ارزیابی مقایسه‌ای برآوردهای فرسایش خاک و تولید رسوب در حوزۀ آبخیز دولت‌آباد با استفاده از مدل‌های EPM، MPSIAC و IntErO 25 40 115176 ‎10.22052/deej.2025.256485.1099 FA جبار هادی قورقی مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی کردستان، کردستان، ایران سعید درختی دانش‌آموخته دکتری، گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران، زهرا عبداللهی هیئت علمی مرکز تحقیقات و آموزش کشاورزی و منابع طبیعی زنجان، زنجان لیلا غلامی دانشیار گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه علوم کشاورزی و منابع طبیعی ساری، ساری، ایران عبدالواحد خالدی درویشان دانشیار گروه مهندسی آبخیزداری، دانشکده منابع طبیعی، دانشگاه تربیت مدرس، نور، ایران Journal Article 2025 03 09 Introduction: Soil is a vital, non-renewable resource fundamental to ecosystem stability and human subsistence. However, this resource is under constant threat from soil erosion—the detachment, transport, and deposition of earth materials by water or wind. This process degrades agricultural productivity by stripping fertile topsoil, impairs water resources through reservoir siltation and pollutant transport, and inflicts significant socio-economic costs. Given its status as a critical global environmental challenge, the accurate quantification of soil erosion is a prerequisite for effective watershed management and conservation planning. Empirical models offer a practical and efficient methodology for such assessments. This study therefore aims to conduct a comparative evaluation of three prominent empirical models—the EPM, MPSIAC, and IntErO for estimating soil erosion and sediment yield within the Dowlatabad Dehgalan watershed. Materials and Methods: This study employed three empirical modelsof -the MPSIAC, EPM, and IntErO- to estimate soil erosion and sediment yield in the Dowlatabad watershed. The Modified Pacific Southwest Inter-Agency Committee (MPSIAC) model was applied by systematically quantifying its nine governing factors, which include surface geology, soil, climate, runoff, land cover, and land use. The overall erosion and sedimentation status of the watershed was subsequently determined based on the cumulative scores assigned to these parameters. The Erosion Potential Method (EPM) was then implemented. This required the evaluation of four key coefficients across distinct land units: the coefficient of watershed erosion and rock permeability (Ψ), the land use coefficient (Xa), the average land slope (I), and the soil and rock erodibility coefficient (Y). These coefficients were integrated to calculate the erosion intensity and resultant sediment yield. Finally, the IntErO model was utilized. As a comprehensive algorithm for predicting erosion and sediment transport, it integrates topographic, soil, geological, and land use data, supplemented by meteorological inputs such as precipitation and temperature, to simulate erosion processes and quantify potential sediment yield. Results and Discussion: The evaluation of the governing parameters within the MPSIAC model revealed that land use (Factor Y7, score: 12.04) exerted the most substantial influence on soil erosion within the watershed. In contrast, surface runoff (Factor Y4, score: 1.78) was identified as the least significant factor. A comparative analysis of the three models yielded distinct estimates for the average annual soil erosion rate. The MPSIAC model estimated a rate of 9.034 t ha-1 yr-1, while the IntErO model produced a closely aligned estimate of 10.01 t ha-1 yr-1. The EPM model, which reports its output in volumetric terms, estimated 1068 m³ km-2 yr-1 (equivalent to approximately 10.68 t ha-1 yr-1, assuming a standard bulk density). Despite these differing erosion rates, the models demonstrated a notable convergence in their predictions of specific sediment yield, with values of 2.74, 2.88, and 2.65 t ha-1 yr-1 for the MPSIAC, IntErO, and EPM models, respectively. A key point of divergence among the models was the calculated Sediment Delivery Ratio (SDR). The EPM model predicted a substantially higher SDR of 0.420, indicating a more efficient transport of eroded material from its source to the watershed outlet. Conversely, the MPSIAC and IntErO models yielded lower and more conservative SDR estimates of 0.247 and 0.210, respectively. This discrepancy highlights the differing theoretical approaches and structural assumptions of each model regarding sediment transport and deposition processes within the catchment. Conclusion and Suggestions: Accurately quantifying soil erosion and sediment yield through direct measurement is often prohibitive due to technical, environmental, and economic constraints. Consequently, empirical models are indispensable tools, though their application necessitates a robust understanding of erosional processes and a critical evaluation of their accuracy under specific regional conditions. This study applied the EPM, MPSIAC, and IntErO models to the Dowlatabad watershed, revealing a significant methodological divergence in assessing erosion severity. While both the MPSIAC and IntErO models classified the region within a moderate erosion class, the EPM model indicated a severe erosion class. This discrepancy underscores the inherent uncertainty in model selection and the urgent need for proactive watershed management and soil conservation measures in the area. Regarding sediment yield, the estimated values were 451.026, 144.179, and 142.59 m³ km-2 yr-1 for the EPM, MPSIAC, and IntErO models, respectively. The close agreement between the MPSIAC and IntErO models suggests a higher degree of reliability for these estimates in this context. In contrast, the EPM model's substantially higher sediment yield and previously noted high sediment delivery ratio (SDR) point to its more extreme and less conservative predictive behavior. Based on these findings, the following recommendations are proposed: Promote the Application of the IntErO Model: Given its performance, which closely aligns with the established MPSIAC model, the IntErO algorithm is recommended for further application and validation in watersheds of varying scales across Iran. This would help broaden the national toolkit for rapid and reliable erosion assessment. Prioritize Conservation Planning: The consensus among the models that the area falls within at least a moderate erosion class necessitates the immediate planning and execution of integrated soil and water conservation programs to mitigate ongoing land degradation. Implement Ground-Truthing Studies: To calibrate and validate these empirical models for local conditions, future work must correlate model outputs with direct sediment measurement techniques, such as systematic field monitoring and sediment sampling. فرسایش خاک ازجمله مشکلات مهم محیط‌زیستی است که می‌تواند کشور را تحت‌تأثیر قرار دهد؛ به همین دلیل، برآورد فرسایش خاک می‌تواند برای تصمیم‌گیران کمک‌کننده باشد. ازطرفی، یکی از روش‌های برآورد فرسایش و رسوب استفاده از مدل‌هاست. بنابراین هدف این پژوهش ارزیابی مقایسه‌ای برآورد فرسایش خاک و تولید رسوب در حوزۀ آبخیز دولت‌آباد دهگلان در استان کردستان، با استفاده از مدل‌های EPM، MPSIAC و IntErO است. برای این منظور، عوامل نه‌گانۀ مؤثر در مدل MPSIAC ارزش‌گذاری شدند. سپس با استفاده از مجموع این 9 عامل فرسایش و رسوب حوضه محاسبه شد. در مرحلۀ بعد، برای برآورد میزان فرسایش و رسوب حوزۀ آبخیز با استفاده از روش EPM چهار مشخصه شامل ضریب فرسایش حوزه ( )، ضریب استفاده از زمین (Xa)، شیب متوسط حوزه (I) و ضریب حساسیت سنگ و خاک به فرسایش (Y) در واحدهای مختلف اراضی بررسی گردید. درنهایت، مدل IntErO که از نقشه‌های ‌توپوگرافی، خاک، زمین و کاربری اراضی و همچنین داده‌های هواشناسی برای برآورد فرسایش و رسوب استفاده می‌کند، اجرا شد. نتایج نشان داد که متوسط فرسایش به‌دست‌آمده در سه مدل MPSIAC، EPM و IntErO به‌ترتیب برابر 034/9 تن در هکتار در سال، 88/13 تن در هکتار در سال و 01/10 تن در هکتار در سال است و مقدار رسوب سالانۀ مدل‌های MPSIAC، EPM و IntErO به‌ترتیب برابر 74/2، 65/2 و 88/2 تن در هکتار در سال است. براساس نتایج این پژوهش، مدل‌های MPSIAC، EPM به‌ترتیب 03/0 و 12/0 کم‌برآوردی و مدل IntErO 11/0 بیش‌برآوردی، در برآورد رسوب سالانه دارند. بنابراین به‌دلیل سادگی و صرفه‌جویی در زمان و هزینه، استفاده از این مدل‌ها در برآورد فرسایش خاک و رسوب توصیه می‌شود. هرچند پیشنهاد می‌شود که مدل IntErO در حوزه‌های آبریز بزرگ کشور هم برای بهینه‌سازی مورد استفاده قرار گیرد.

https://deej.kashanu.ac.ir/article_115176_6d12ab0f201d3408a4075df31fa90f9e.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Measuring Behavioral Tendencies of Ecotourists Using the Ecotourist Evaluation Scale (EIS): A Case Study of Maranjab Desert سنجش تمایلات رفتاری اکوتوریست‌ها با مقیاس ارزیابی اکوتوریست (EIS) مطالعۀ موردی: کویر مرنجاب 41 56 115196 ‎10.22052/deej.2025.257680.1121 FA محسن شاطریان گروه آموزشی جغرافیا و گردشگری دانشکده منابع طبیعی و علوم زمین دانشگاه کاشان مناسادات سیدهاشمی دانشجوی کارشناسی ارشد طبیعت گردی گروه آموزشی جغرافیا و گردشگری دانشکده منابع طبیعی دانشگاه کاشان Journal Article 2025 09 30 Introduction: Tourism is one of the world's most dynamic economic sectors, playing a pivotal role in the development of many societies (Lenao & Basupi, 2016; Ranasinghe et al., 2020). For its contribution to be sustainable, however, the industry must align with the principles of sustainable development (Stylidis, 2014). The pressures of mass tourism, driven by rapid urbanization and transportation, often threaten natural destinations. In response, more sustainable alternatives have emerged, among which ecotourism has gained significant prominence. Defined by its commitment to environmental protection, cultural respect, and the preservation of natural resources, ecotourism presents a sustainable model distinct from conventional tourism (Wondirad et al., 2020). Although a relatively recent field, it has attracted scholarly attention across disciplines such as sociology, anthropology, and planning, influencing tourism policies globally (Veleshkaei et al., 2016). Over the past two decades, global interest in ecotourism has surged, with nature-based tourism now accounting for over 30% of international travel (World Tourism Organization, 2020). When systematically managed, it can generate substantial economic benefits while simultaneously supporting conservation efforts (Gitinji, 2006). The sector's growth—estimated at 10–30% annually compared to 3–4% for overall tourism—highlights its increasing importance (Jiao et al., 2013). The ecotourism framework involves three key stakeholders: suppliers (local communities, resource managers, and service providers), demanders (the tourists themselves), and regulators (governmental and policy institutions) who balance resource use (Abdollahi, 2007). Understanding the demanders—the ecotourists—is critical. Consequently, academic research increasingly focuses on the behavioral dimensions of ecotourists to inform effective management and development strategies. This study investigates these behavioral tendencies in the context of the Maranjab Desert, a pristine ecotourism destination in Iran known for its unique desert and mountain ecosystems. Located at 34°07' N and 51°48' E, the area has seen a notable increase in visitors, making the understanding of tourist behavior essential for sustainable management. Utilizing the Ecotourist Evaluation Scale (EIS), this research tests the following five hypotheses, positing that each dimension significantly influences ecotourists' behavioral tendencies: Awareness Environmental Sustainability Economic Sustainability Socio-cultural Sustainability Affinity with Nature Materials and Methods: This study adopts an applied research objective and a descriptive-survey methodology. The target population consisted of tourists visiting the Maranjab Desert during September 2022. The sample size was determined using Cochran's formula, resulting in the selection of 384 participants through a random sampling method. Data were collected using a structured questionnaire based on the Ecotourist Evaluation Scale (EIS). The instrument was designed to measure the five key constructs of the model: Awareness, Environmental Sustainability, Economic Sustainability, Socio-cultural Sustainability, and Affinity with Nature. The questionnaire was validated, and reliability tests confirmed acceptable internal consistency for all measured items. Statistical analyses were performed using SPSS, SmartPLS, and LISREL software. Descriptive statistics were utilized to summarize the demographic profile of the respondents. Confirmatory Factor Analysis (CFA) was employed to assess the validity of the measurement model, and Structural Equation Modeling (SEM) was applied to test the research hypotheses regarding the relationships between the independent variables and ecotourists' behavioral tendencies. Analysis of demographic data revealed that the majority of respondents were male (73.7%, n=283), while 26.3% (n=101) were female. The largest age cohort was 25-40 years old (38.5%, n=148), and the smallest was tourists over 55 years of age. In terms of educational attainment, most participants held an associate or bachelor's degree (54.7%), followed by a master's degree (38%), a doctorate (3.9%), and a high school diploma (3.4%). The Confirmatory Factor Analysis (CFA) validated a model comprising six latent constructs (the five independent variables and the dependent variable, behavioral tendencies), measured by 34 observed indicators. All factor loadings exceeded the 0.30 threshold, demonstrating adequate correlations between the observed variables and their respective latent constructs. Furthermore, significance tests based on t-values indicated that all hypothesized relationships were statistically significant, exceeding the critical value of 1.96 at the 0.05 confidence level, thus confirming the robustness of the measurement model. Discussion: The demographic profile of visitors to the Maranjab Desert reveals that ecotourism in this region is predominantly driven by young, highly educated individuals. This finding aligns with global ecotourism trends, where younger, educated demographics consistently show a greater propensity for adventure and nature-based travel that combines recreational and educational value. The testing of the research hypotheses yielded significant insights into the behavioral drivers of these ecotourists: Awarenesswas validated as a critical determinant of responsible behavior. Tourists who proactively sought information from guides or local communities demonstrated a stronger commitment to sustainable practices. This suggests that awareness not only equips ecotourists to make informed decisions but also fosters a deeper respect for the local environment, ultimately cultivating advocates for conservation. Environmental Sustainabilityemerged as the most influential predictor of ecotourist behavior. Respondents showed a clear preference for eco-friendly accommodations, trained guides, and sustainable facilities, with a pronounced willingness to adhere to conservation protocols. This underscores that environmental protection is a primary motivation, not merely a secondary concern, for visitors to this fragile desert ecosystem. Economic Sustainabilitywas confirmed, as tourists recognized the importance of contributing to the local economy through purchasing handicrafts and utilizing local services. This economic participation enhances community resilience and fosters positive host-guest relationships. However, the observed variability in the level of financial engagement indicates a need for more structured and visible mechanisms to channel tourist expenditure into local enterprises. Socio-Cultural Sustainabilityproved to be a significant factor, with respondents emphasizing respect for local traditions, appropriate attire, and culturally sensitive behavior. This cultural respect is fundamental to building mutual trust, reducing potential social friction, and strengthening the overall sustainability of the tourism model. Affinity with Naturewas a prominent characteristic, as tourists reported strong emotional connections to the landscape and its biodiversity. Their consistent preference for natural destinations and a demonstrated willingness to protect ecosystems strongly supports the role of biophilia—an innate human connection to nature—as a core driver of ecotourism behavior. In conclusion, the results reinforce the interconnectedness of environmental, economic, and socio-cultural dimensions in shaping ecotourist behavior. For the Maranjab Desert—a fragile and sensitive ecosystem—these findings highlight the necessity for a holistic management strategy. Such a strategy must carefully balance growing tourist demand with the imperative for long-term environmental conservation, ensuring that the ecotourism model remains truly sustainable. Conclusion: This study successfully applied the Ecotourist Evaluation Scale (EIS) to investigate the behavioral tendencies of ecotourists in the Maranjab Desert. The findings robustly confirm that five key dimensions—awareness, environmental sustainability, economic participation, socio-cultural respect, and affinity with nature—are significant determinants of ecotourist behavior in this context. The research makes several key contributions to the field of sustainable tourism: It establishesawareness as a fundamental driver, underscoring that informed tourists are more likely to engage in sustainable practices. It validatesenvironmental protection as the central and most powerful motivator for ecotourists, reinforcing the core ethos of the sector. It highlightsthe synergistic role of tourism in generating both economic resilience for host communities and fostering socio-cultural exchange. It identifiesa strong affinity with nature as a critical underlying psychological factor that fuels demand for ecotourism experiences. For policymakers and destination managers, these findings translate into clear imperatives. Tourism strategies must be designed to: Enhance Environmental Educationthrough interpretive programs and trained guides. Invest in Eco-Friendly Infrastructureto minimize the ecological footprint of tourism. Create Structured Channelsfor tourist spending to directly benefit local economies, such as community-based tourism enterprises and local handicraft markets. Promote Cultural Sensitivityto ensure respectful host-guest interactions and preserve local traditions. For the Maranjab Desert specifically, adopting a systematic and inclusive planning approach that incorporates the perspectives of local communities is paramount. This will ensure that tourism development generates tangible economic benefits while simultaneously safeguarding the fragile desert ecosystem. Ultimately, this study affirms that the long-term sustainability of ecotourism hinges on a holistic alignment of tourist behavior, management policies, and industry operations with the interconnected principles of ecological integrity, economic equity, and socio-cultural respect, all nurtured by a profound human connection to the natural world. گردشگری فعالیتی پاک است که می‌تواند در حفظ طبیعت برای نسل‌های آینده مـؤثر باشد و به کشورهای درحال‌توسعه در حل مشکلاتی نظیر بیکاری و فقر بـا تحرک‌بخشی به پتانسیل‌های این کشورها کمک می‌کند. یکی از گونه‌های گردشگری پرطرفدار کنونی، اکوتوریسم است. این نوع گردشگری به‌رغم نوپا بودن، پایداری بیشتری نسبت به گردشگری انبوه دارد، زیرا حفظ محیط‌زیست، اصل محوری در اکوتوریسم است. هدف این پژوهش بررسی سنجش تمایلات رفتاری اکوتوریست‌ها با مقیاس ارزیابی اکوتوریست (EIS) در کویر مرنجاب است. شاخص‌های اصلی آن شامل آگاهی، پایداری اقتصادی، پایداری اجتماعی فرهنگی، پایداری زیست‌محیطی و طبیعت‌دوستی هستند. روش پژوهش توصیفی‌پیمایشی و ابزار پژوهش، پرسش‌نامه است. جامعۀ آماری شامل گردشگرانی است که در سال 1401 به کویر مرنجاب وارد شده‌اند. حجم نمونه با استفاده از فرمول کوکران 384 نفر انتخاب گردید و نسبت به توزیع پرسش‌نامه اقدام گردید. برای تجزیه‌وتحلیل داده‌ها از نرم‌افزار Lisrel بهره گرفته شد. نتایج حاصل از این پژوهش با بارهای عاملی 55/0 برای متغیر آگاهی در تمایلات رفتاری، 73/0 برای متغیر پایداری زیست‌محیطی، 42/0 برای متغیر پایداری اقتصادی، 69/0 برای متغیر پایداری اجتماعی و فرهنگی و 60/0 برای متغیر طبیعت‌دوستی نشان داد که تمامی‌متغیرهای مورد پژوهش بر تمایلات رفتاری اکوتوریست‌ها تأثیرگذار است؛ اما مهم‌ترین یا تأثیرگذارترین عامل براساس آزمون، پایداری زیست‌محیطی با مقدار 73/0 بیشترین بار عاملی معرفی شد.

https://deej.kashanu.ac.ir/article_115196_6182b547f2f7b72819566d71911a2683.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Assessing Soil Organic Matter Composition and Key Influencing Factors in a Reclaimed Rangeland, Ghahavand Plain ترکیبات ساختمانی مادۀ آلی خاک و شناسایی برخی عوامل مؤثر بر آن در مراتع احیاشدۀ دشت قهاوند 57 72 115195 ‎10.22052/deej.2025.256798.1105 FA مریم حمیدی گروه مهندسی طبیعت، دانشکده منابع طبیعی و محیط زیست، دانشگاه ملایر بهناز عطائیان گروه مهندسی طبیعت، دانشکده منابع طبیعی و محیط زیست، دانشگاه ملایر، ملایر، ایران لیما طیبی گروه علوم و مهندسی شیلات، دانشکده منابع طبیعی و محیط زیست، دانشگاه ملایر، ملایر، ایران. Journal Article 2025 05 11 Introduction: Increasing the soil organic carbon (SOC) stock is critically important for mitigating climate change. Soil carbon sequestration is governed by complex interactions between the atmosphere, soil properties, tree species, the chemical composition of litter, and environmental management. Management practices, particularly grazing and enclosure, can significantly alter the chemical composition of SOC. For instance, grazing pressure has been shown to increase the proportion of more readily degradable carbon compounds, such as cellulose. Despite the recognized significance of carbon sequestration in rangeland ecosystems, the chemical composition of soil organic matter (SOM) and its relationship with soil physicochemical properties remain poorly studied. The rangelands in the Qahavand Plain have experienced severe degradation due to unsustainable exploitation and overgrazing. Compounding this issue, recurrent droughts have accelerated soil erosion and desertification in the region. In response, restoration initiatives were implemented in degraded rangelands using the species Atriplex canenses and Nitraria schoberi, followed by enclosure management. Materials and Methods: This study was conducted to investigate changes in organic carbon storage and its relationship with soil organic matter components—specifically cellulose, hemicellulose, and lignin—in the surface and subsurface soils of the restored rangelands in the Qahavand Plain. Sampling was carried out in 2016. A total of 60 soil samples were collected systematically and randomly from two depth intervals: 0-10 cm (surface soil) and 10-30 cm (sub-soil). Various physicochemical properties of these samples were measured. Prior to statistical analysis, the data were tested for normality using the Kolmogorov-Smirnov test. Variables that violated the assumption of normality were normalized using appropriate transformations: inversion for cellulose, cosine for clay and lignin, and square root for silt and hemicellulose percentages. Subsequently, a t-test (Proc ttest procedure in SAS v.9.4) was employed to identify significant differences in organic carbon content and other soil properties between the surface and sub-soil layers. Finally, correlation analysis and Principal Component Analysis (PCA) were performed using R and Brodgar software to examine the relationships between organic matter compounds and stored organic carbon. Results and Discussion: The results demonstrated that soil depth had a significant effect on all measured physical and chemical parameters. Notably, the concentrations of organic matter, cellulose, and lignin were significantly higher in the subsurface soil (10-30 cm) compared to the surface layer (0-10 cm), with increases of 34.75%, 79.12%, and 67.57%, respectively. Several parameters, including pH, electrical conductivity (EC), bulk density, cellulose, hemicellulose, and lignin, were strongly correlated with soil organic matter (SOM) across both depths. Among these, lignin exhibited the strongest positive correlation (r = 0.84), followed by pH (r = 0.78), hemicellulose (r = 0.72), and cellulose (r = 0.71). The 34.75% increase in the average SOM content in the subsurface soil represents a significant change, underscoring the positive impact of vegetation restoration. This accumulation is likely driven by increased aerial biomass and litter input from the established Atriplex canenses and Nitraria schoberi, a finding that supports our initial hypothesis. The significant relationships observed between SOM and the physicochemical parameters reinforce the central role of organic matter in soil ecosystems. SOM serves as the primary source of carbon and energy for decomposer and heterotrophic microorganisms. Consequently, any reduction in organic matter input can disrupt microbial activity and impede the decomposition process, creating a feedback loop that further limits soil organic carbon sequestration. Conclusions: In conclusion, this study demonstrates that rangeland rehabilitation in the Qahavand Plain plays a crucial role in enhancing soil organic carbon (SOC) stability and mitigating desertification. The observed relationships between organic matter composition and soil properties, particularly the significant accumulation of the more recalcitrant lignin fraction in the subsurface soil, support this finding. The decomposition process of plant litter typically occurs in two stages: an initial, rapid phase where soluble compounds like cellulose and hemicellulose are broken down, followed by a slower phase governed by the decay of lignin and nitrogen mineralization. Our results, showing a strong correlation between lignin and stable SOC, align with this model and confirm the success of the restoration efforts in building a more stable carbon pool. Given the context of ongoing climate change, it is recommended that the effects of vegetation restoration on SOC storage be further investigated across other rangeland and forest ecosystems. Furthermore, to enhance carbon sequestration potential and ecosystem resilience in degraded areas like the Qahavand Plain, future restoration programs should consider incorporating alternative native species alongside Atriplex. افزایش ذخیرۀ کربن آلی خاک برای تعدیل تغییرات اقلیمی، اهمیت ویژه‌ای دارد. ‌‌این پژوهش با هدف بررسی تغییرات ذخیرۀ کربن آلی و ارتباط آن با میزان ترکیبات مادۀ آلی خاک (سلولز، همی سلولز و لیگنین) در دو عمق سطحی (۰-۱۰ سانتی‌متر) و زیرسطحی (۱۰-۳۰ سانتی‌متر) در مراتع احیاشدۀ دشت قهاوند در سال 1395 انجام شد. آنالیزهای آماری داده‌های حاصل با استفاده از آزمون نرمالیتی Kolomogrov-Smirnov بررسی گردید و سپس از رویۀ Proc ttest برای بررسی تغییرات معنی‌دار میزان کربن آلی و سایر خصوصیات خاک سطحی و زیرسطحی استفاده شد. نتایج حاصل از این مطالعه نشان داد که تغییرات عمق بر پارامترهای فیزیکی و شیمیایی اندازه‌گیری‌شده، تأثیرات معنی‌داری داشته است وافزایش معنی‌دار مادۀ آلی، سلولز و همی‌سلولز در خاک زیر سطحی به‌ترتیب معادل 2/3، 02/5 و 6/2 برابر مشاهده شد. افزون‌ بر این، بین مادۀ آلی خاک و برخی ویژگی‌های فیزیکوشیمیایی اسیدیته، هدایت الکتریکی و درصد رس و سیلت همبستگی مثبت مشاهده شد. این یافته‌ها بیانگر آن است که احیای پوشش گیاهی و مدیریت قرق، با بهبود ورودی بقایای گیاهی و تثبیت ترکیبات سلولزی، می‌تواند به افزایش پایداری کربن آلی و بهبود کیفیت خاک در اکوسیستم‌های نیمه‌خشک منجر شود.

https://deej.kashanu.ac.ir/article_115195_5b058c4e1eceda032c6626a6d1938607.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Spatiotemporal Prediction of Precipitation Distribution in the Urmia Basin Using an EEMD-SVM-LSTM Hybrid Model پیش‌بینی توزیع مکانی-زمانی بارش در حوضۀ ارومیه با استفاده از مدل هیبریدی EEMD-SVM-LSTM 73 92 115199 ‎10.22052/deej.2025.257075.1111 FA بهنوش فرخ زاده گروه مهندسی طبیعت، دانشکده منابع طبیعی و محیط زیست، دانشگاه ملایر، ملایر، ایران. رسول ایمانی دانشکده منابع طبیعی و علوم زمین، دانشگاه کاشان، کاشان سپیده چوبه دانشکده منابع طبیعی، دانشگاه ارومیه، ارومیه، 0000-0002-2849-5485 Journal Article 2025 06 22 Introduction: Accurate prediction of monthly rainfall is crucial for water resource management and risk mitigation in semi-arid regions, particularly under climate change. The Lake Urmia Basin in northwestern Iran has faced significant environmental degradation in recent decades, driven by climatic variability, unsustainable agriculture, and inadequate water management. Forecasting future rainfall patterns is therefore essential for developing adaptive strategies to restore ecological balance and ensure sustainable development. However, traditional statistical models often fail to capture the nonlinear and non-stationary characteristics of hydrological data. This limitation has prompted the exploration of advanced machine learning and deep learning techniques. Hybrid models that integrate signal decomposition with intelligent algorithms have shown superior performance in time series forecasting by improving feature extraction and reducing noise. This study introduces a novel hybrid framework that combines Ensemble Empirical Mode Decomposition (EEMD), Support Vector Machine (SVM), and Long Short-Term Memory (LSTM) networks to simulate and predict monthly rainfall in the Lake Urmia Basin. The proposed EEMD-SVM-LSTM model leverages the complementary strengths of each component to capture both short-term fluctuations and long-term trends, thereby significantly enhancing predictive accuracy. Materials and Methods: Monthly rainfall data from four synoptic stations—Urmia, Khoy, Tabriz, and Saqez—were collected for the period 1980–2020 for model development and validation. Future projections were then generated for the 2030–2050 period under a business-as-usual scenario. The proposed methodology involved decomposing the original rainfall time series into several Intrinsic Mode Functions (IMFs) and a residual component using the Ensemble Empirical Mode Decomposition (EEMD) method. This decomposition facilitated a multi-resolution analysis by isolating distinct frequency components, thereby simplifying the modeling of complex, non-stationary rainfall dynamics. The high-frequency IMFs, which represent short-term noise and rapid fluctuations, were modeled using a Support Vector Machine (SVM) algorithm, selected for its effectiveness with nonlinear relationships and limited data. Conversely, the low-frequency residual component, encapsulating the long-term trend, was predicted using a Long Short-Term Memory (LSTM) network, chosen for its ability to learn and retain long-term dependencies in sequential data. The final integrated prediction was obtained by summing the forecasted results from all SVM and LSTM components. Model performance was quantitatively evaluated using Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). To demonstrate the superiority of the hybrid approach, its predictive accuracy was benchmarked against standalone SVM and LSTM models. Results: The EEMD process successfully decomposed the rainfall signals into distinct intrinsic mode functions, enabling a more targeted modeling approach. The hybrid EEMD-SVM-LSTM model demonstrated superior predictive performance compared to the standalone SVM and LSTM models. This was evidenced by consistently lower error metrics across all stations during both training and validation phases. The RMSE values for the hybrid model ranged from 0.07 to 0.11 mm, outperforming the standalone SVM (0.10–0.29 mm) and LSTM models. Projections for the 2030–2050 period revealed spatially variable changes in rainfall across the basin. Khoy station exhibited the highest annual rainfall increase (+18.8%), whereas Saqez experienced the most significant decrease (–14.9%). At the basin level, the mean annual rainfall is projected to decline by approximately 4%, from 334.5 mm to 320.7 mm. Spatially, the analysis indicated a northward shift in precipitation concentration, with increases projected over Tabriz and Urmia, and decreases in the southern and western parts of the basin. Temporally, a shift toward a more uniform seasonal distribution was observed, characterized by a relative increase in winter and spring precipitation and a more pronounced decline in late-summer rainfall. Discussion and Conclusion: This study demonstrates that the hybrid EEMD-SVM-LSTM framework effectively captures the multi-scale dynamics of rainfall by integrating signal decomposition with machine learning. The model's superior predictive accuracy over standalone ML and DL models underscores the value of a hybrid approach for processing complex, non-stationary hydrological data, a finding consistent with previous research (e.g., Diop et al., 2020; Yeditha et al., 2023; Jyostna et al., 2025). The projections indicate a concerning 4% decline in the basin's mean annual rainfall, coupled with a significant spatial redistribution toward northern and central sub-basins. This pattern implies a substantial shift in the regional water balance, potentially increasing flood risks in receiving areas while exacerbating drought and water stress in the southern and western zones. These spatially heterogeneous changes highlight the urgent need for adaptive water resource management. Key strategies should include optimizing irrigation efficiency, updating reservoir operation rules, and revising agricultural cropping calendars to align with the new hydrological regime. Despite its robust performance, this study is subject to the inherent uncertainties of climate projections and data-driven modeling. Future research should enhance model robustness by incorporating additional climatic predictors—such as temperature, and large-scale circulation indices like ENSO and NAO—as well as high-resolution satellite-based rainfall products to improve spatial representativeness. In conclusion, the EEMD-SVM-LSTM model provides a powerful and generalizable framework for high-fidelity rainfall forecasting in semi-arid regions. It serves as a critical tool for informing climate-resilient planning and promoting sustainable water resource management in the Lake Urmia Basin and other similarly vulnerable ecosystems worldwide. پیش‌بینی دقیق بارش ماهانه برای مدیریت منابع آب و کاهش خطرات ناشی از نوسانات اقلیمی در مناطق نیمه‌خشک اهمیت ویژه‌ای دارد. هدف از این پژوهش، توسعه و ارزیابی یک مدل هیبریدی ترکیبی بر پایۀ تجزیۀ تجربی حالت تجمعی (EEMD)، ماشین بردار پشتیبان (SVM) و شبکۀ عصبی حافظۀ بلندمدت (LSTM) به‌منظور شبیه‌سازی و پیش‌بینی بارش ماهانه در حوضۀ آبریز دریاچۀ ارومیه است. در این راستا، داده‌های بارش ماهانۀ چهار ایستگاه خوی، سقز، تبریز و ارومیه طی دورۀ ۱۹۸۰ تا ۲۰۲۴ گردآوری و برای آموزش و اعتبارسنجی مدل استفاده شد؛ سپس بازۀ زمانی ۲۰۳۰ تا ۲۰۵۰ برای پیش‌بینی آینده بررسی گردید. نتایج نشان داد که مقدار RMSE در ایستگاه‌های مورد بررسی برای مدل SVM بین 07/0 تا 11/0 میلی‌متر و برای LSTM بین 10/0 تا 29/0 میلی‌متر متغیر بود. بالاترین میزان افزایش بارش سالانه در دورۀ آینده در ایستگاه خوی (82/18 درصد) مشاهده شد، درحالی‌که ایستگاه سقز با کاهش حدود 14 درصدی بارش مواجه شد. به‌طور میانگین، بارش سالانۀ کل حوضه در سناریوی آینده نسبت به دورۀ پایه حدود 4 درصد کاهش خواهد یافت. یافته‌ها نشان داد مدل هیبریدی EEMD-SVM-LSTM می‌تواند روندهای پیچیدۀ بارش را با دقت بالا شبیه‌سازی و پیش‌بینی کند و برای بهبود مدیریت منابع آب و برنامه‌ریزی سازگار با تغییرات اقلیمی در مناطق مشابه، رویکردی کارآمد محسوب می‌شود.

https://deej.kashanu.ac.ir/article_115199_27db65d02266d04e0a7d227312e28f66.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 Assessing the Effect of Vegetation Condition on its Interaction with Soil Surface Moisture in a Semi-Arid Region ارزیابی تأثیر وضعیت پوشش گیاهی بر ارتباط متقابل آن با رطوبت سطحی خاک در مناطق نیمه‌خشک 93 110 115203 ‎10.22052/deej.2025.257621.1119 FA فهیمه رستمی 1- گروه مرتع و آبخیزداری، دانشکده کشاورزی، دانشگاه ایلام، ایلام، ایران. مرزبان فرامرزی دانشگاه ایلام، دانشکده کشاورزی، گروه مرتع و آبخیزداری رضا امیدی پور 1- گروه مرتع و آبخیزداری، دانشکده کشاورزی، دانشگاه ایلام، ایلام، ایران. Journal Article 2025 09 19 Introduction: Vegetation cover and soil moisture are fundamental, interdependent components of terrestrial ecosystems, playing a crucial role in maintaining ecological balance. This relationship is particularly critical in arid and semi-arid regions, where soil moisture—primarily derived from precipitation—is a key limiting factor for plant growth and survival. Conversely, vegetation significantly influences the hydrological cycle; dense cover enhances water infiltration and soil water retention capacity, thereby creating a positive feedback loop. A reciprocal relationship between vegetation cover and surface soil moisture (0–10 cm) is therefore well-conceptualized. However, the precise nature and strength of this linkage, and how it is modulated by varying vegetation conditions, have not been directly and comprehensively examined at a regional scale. This study aims to address this gap by first quantifying the general relationship and then assessing how different vegetation conditions affect this critical interaction. Materials and Methods: This study was conducted in the semi-arid regions of Ilam Province, Iran. Landsat 8 Operational Land Imager (OLI) satellite imagery was employed as the primary data source. Remote sensing technology was used to calculate two key indices: vegetation condition and soil surface moisture. The Normalized Difference Vegetation Index (NDVI) and the Modified Soil Adjusted Vegetation Index (MSAVI) were utilized to assess vegetation cover. For soil moisture, the Normalized Difference Water Index (NDWI) and the Land Surface Water Index (LSWI) were calculated. The derived NDVI and MSAVI maps were classified into distinct vegetation condition categories based on predefined value thresholds. The relationship between these vegetation indices (NDVI, MSAVI) and the soil moisture indices (NDWI, LSWI) was then analyzed using linear regression. All spatial and statistical analyses were performed using the TerrSet 2020 software system. Results: The analysis revealed that the MSAVI index was more suitable for representing vegetation conditions in the semi-arid study area, as it demonstrated reduced sensitivity to soil background reflectance. Linear regression between the vegetation and soil moisture indices showed strong, positive relationships. The highest overall correlations were observed between NDVI and NDWI (r = 0.75) and MSAVI and NDWI (r = 0.75). A more detailed examination across different vegetation condition classes showed that the strength of this relationship was directly influenced by vegetation cover. Areas classified as having "excellent" vegetation cover exhibited the strongest correlation with soil moisture (maximum r = 0.91 between the NDVI class and moisture indices). In contrast, the "no cover" class showed the weakest relationship (minimum r = 0.25 between the MSAVI class and LSWI). Discussion and Conclusion: This study successfully quantified the dynamic relationship between vegetation cover and surface soil moisture in a semi-arid region using remote sensing indices (NDVI, MSAVI, NDWI, LSWI) and linear regression analysis. The key finding was the superior performance of the MSAVI index in characterizing vegetation conditions, attributable to its algorithm's correction for soil background reflectance, a common source of noise in sparsely vegetated, semi-arid landscapes. The results confirm a strong, positive correlation between vegetation cover and soil moisture. Crucially, this relationship was found to be non-uniform; it intensified with increasing vegetation density. This finding empirically validates the established ecological principle that denser vegetation enhances water retention capacity, suggesting a positive feedback loop between plant growth and soil water availability. In conclusion, these findings underscore the critical role of vegetation management in the hydrological dynamics of semi-arid ecosystems. The methodologies applied demonstrate the utility of remote sensing as a powerful tool for monitoring these interactions. Therefore, we recommend the integration of such indices into sustainable land and water management strategies to guide restoration efforts and combat desertification effectively. این تحقیق با هدف بررسی رابطه متقابل پوشش گیاهی و رطوبت سطحی خاک و تاثیر تغییر در کلاس وضعیت پوشش گیاهی بر نوع و شدت ارتباط بین پوشش و رطوبت خاک در شهرستان ایوان در استان ایلام انجام گرفته است. در این راستا و با استفاده از تصاویر ماهواره‌ای لندست 8 OLI و با بکارگیری شاخص‌های پوشش گیاهی (NDVI و MSAVI) و رطوبت خاک (NDWI و LSWI)، ارتباط بین پوشش و رطوبت با استفاده از رگرسیون خطی مورد بررسی قرار گرفت. بر اساس نتایج، بررسی ارتباط پوشش و رطوبت خاک نشان داد ارتباط مثبت و معنی‌داری (P-value < 0.05) بین شاخص‌های پوشش گیاهی و رطوبت وجود دارد. ضریب همبستگی پیرسون بین شاخص NDVI با شاخص‌های NDWI و LSWI به‌ترتیب برابر 75/0 و 73/0 و بین شاخص MSAVI با شاخص‌هایNDWI و LSWI به‌ترتیب برابر 75/0 و 74/0 بود. بررسی تاثیر کلاس وضعیت پوشش گیاهی بر ارتباط پوشش و رطوبت خاک نشان داد، در شاخص NDVI بیشترین همبستگی مشاهده شده با شاخص‌های NDWI و LSWI در کلاس وضعیت متراکم (بطور مشابهی r=0.91 and P-value < 0.001) و کلاس وضعیت خوب (به‌ترتیب r=0.75 and , P-value < 0.001, r=0.72 and , P-value < 0.001) بود. بطور مشابهی، شاخص MSAVI نیز بیشترین ارتباط مشاهده شده مربوط به دو کلاس وضعیت خوب و متراکم بود (برای هر دو شاخص NDWI و LSWI به‌ترتیب (r=0.88 and , P-value < 0.001, r=0.72 and , P-value < 0.001). در حالیکه کمترین ارتباط در طبقات بدون پوشش و پوشش فقیر دیده‌شد.

https://deej.kashanu.ac.ir/article_115203_3ff071090c485c58cf7e8331914d7b0e.pdf

دانشگاه کاشان مهندسی اکوسیستم بیابان 2538-6336 14 48 2025 12 22 The Morphology and Morphodynamics of Aeolian Landforms in the Jazmurian Erg: An Analysis of Environmental Controls ارزیابی وضعیت مورفولوژی و مورفودینامیکی لندفرم‌های بادی و ارتباط آن با عوامل محیطی (مطالعۀ موردی: ریگ جازموریان) 111 127 115207 ‎10.22052/deej.2025.257208.1113 FA مهران مقصودی استاد ژئومورفولوژی، دانشگاه تهران، تهران، ایران، حمید گنجائیان دکتری ژئومورفولوژی، دانشگاه تهران، تهران، ایران Journal Article 2025 10 03 Introduction: Sand dunes are distinctive features of arid landscapes, notable both for their tourism potential and the environmental hazards associated with their dynamic morphology. In Iran, sand dunes are widespread and cover extensive areas. Given their active morphodynamics, these dunes can pose significant risks to nearby infrastructure and land use, including agricultural areas and residential zones, many of which are situated in close proximity to dune fields. In recent years, sand dunes have been increasingly recognized as mobile elements of desert systems. Understanding their characteristics is essential to deciphering the complex processes that drive their activity and evolution. Despite the considerable extent of dunes across Iran's deserts, they remain inadequately studied, with a notable lack of comprehensive research on their morphological diversity and behavior. This gap underscores the need for detailed investigation into the morphology of Iran's sand dunes. The present study aims to address this by not only identifying and analyzing the dynamic state of dunes and the factors influencing them but also by proposing a localized classification framework tailored to specific ergs. Such a classification would enable systematic categorization of dunes within each sand sea. The Jazmurian Erg, one of the largest dune fields in Iran, was selected as the study area due to its considerable size and proximity to population centers such as Iranshahr and Bampour. Assessing the morphological and morphodynamic status of its dunes is therefore of considerable practical importance—an objective that this research seeks to fulfill.. Materials and Methods: This study employed multiple data sources, including MODIS and Landsat satellite imagery, Google Earth images, and statistical data on wind speed and direction. The primary analytical tools consisted of ArcGIS for spatial mapping, Google Earth Engine for generating vegetation density and dust concentration maps, and Google Earth for creating shapefiles and assessing sand dune dynamics. The research was conducted in three sequential stages: The precise boundaries of the Jazmurian Erg were delineated using Google Earth imagery. Following this delineation, a comprehensive morphometric analysis was conducted. Based on morphological characteristics, the erg was systematically classified into distinct dune types. To evaluate dune mobility, 81 sample points were strategically selected across the study area. Using time-series imagery from Google Earth and Landsat platforms, the displacement rates of individual dunes were quantified over a 15-year period (2005-2020). To investigate the relationship between dune dynamics and environmental conditions, vegetation density maps were generated using MODIS satellite data processed through Google Earth Engine, applying the Normalized Difference Vegetation Index (NDVI). Additionally, dust concentration patterns were analyzed through Aerosol Optical Depth (AOD) index calculations derived from MODIS imagery spanning 2018-2023. Results and Discussion: The Jazmurian Erg, spanning an area of 4,261 km², constitutes a significant geomorphic feature within the Jazmurian Basin. Classification of dune morphologies reveals that compound linear dunes are the dominant landform, covering 1,649 km² (37.7% of the total erg area). Additional extensive forms include sand sheets of medium thickness and simple linear dunes, occupying 669 km² (15.7%) and 577 km² (13.5%) of the erg, respectively. Displacement analysis conducted between 2005 and 2020 indicates dune movement ranging from 2 to 47 meters across the study area. The most significant migration rates (>40 meters) were observed in central, western, and certain eastern sectors of the erg, while remaining areas showed more modest displacement of less than 20 meters. This translates to an annual migration rate varying between 0.15 and approximately 3 meters, highlighting considerable spatial variation in dune activity across the Jazmurian Erg. Conclusion: This study demonstrates that the Jazmurian Erg represents a significant geomorphological feature, covering an extensive portion of the Jazmurian Basin and ranking among Iran's largest sand dune systems. The erg exhibits considerable morphological diversity, with dune forms classified into 12 distinct types influenced by varying climatic and topographic conditions. Analysis confirms that the Jazmurian dunes maintain active dynamics, showing a significant correlation with environmental parameters, particularly vegetation density and dust concentration. The notably low NDVI values across the erg indicate sparse vegetation cover, creating conditions favorable for dune mobility. Furthermore, areas exhibiting higher aerosol optical depth (AOD) values, particularly in central sectors, correlate strongly with observed increases in dune displacement rates. The findings collectively indicate that environmental factors drive active dune dynamics within the Jazmurian Erg. Given the potential for these mobile sediments to generate dust sources and encroach upon agricultural lands and human infrastructure, the implementation of targeted stabilization measures is strongly recommended to mitigate environmental and socio-economic impacts. موقعیت جغرافیایی ایران سبب شده است تا بخش زیادی از مناطق بیابانی آن را ریگزارها در بر گیرد. ازجمله ریگزارهای بزرگ ایران، ریگ جازموریان است. ریگ جازموریان که شامل انواع مختلفی از لندفرم‌های بادی (تپه‌های ماسه‌ای) است، دارای دینامیک فعالی است و با توجه به اهمیتی که در برنامه‌ریزی‌های محیطی دارد، در پژوهش حاضر به مطالعۀ آن پرداخته شده است. در پژوهش حاضر، از تصاویر گوگل ارث و تصاویر ماهواره‌های مادیس و لندست به‌عنوان داده‌های اصلی پژوهش استفاده شده است. مهم‌ترین ابزارهای پژوهش، سامانۀ گوگل ارث انجین، گوگل ارث و ArcGIS بوده است. در پژوهش حاضر، ابتدا محدودۀ دقیق ریگ جازموریان ترسیم و سپس براساس مورفولوژی تپه‌های ماسه‌ای طبقه‌بندی شده است. در ادامه، نرخ جابه‌جایی تپه‌های ماسه‌ای محاسبه و سپس ارتباط آن با وضعیت محیطی منطقه ارزیابی شده است. نتایج پژوهش حاضر نشان داده است که ریگ جازموریان km24261 وسعت دارد و دارای اشکال متنوعی از تپه‌های ماسه‌ای است. در بین تپه‌های ماسه‌ای ریگ جازموریان، تپه‌های خطی مرکب با حدود 38%، دارای وسعت بیشتری هستند. همچنین براساس نتایج به‌دست‌آمده، تپه‌های ماسه‌ای منطقه در طی سال‌های 2005 تا 2020 بین m‌2 تا m47 حرکت داشته‌اند. آنالیز مکانی جابه‌جایی صورت‌گرفته نشان داده است که بیشترین میزان جابه‌جایی مربوط به مناطق میانی ریگ جازموریان بوده است و به همین دلیل در این مناطق، بالاترین ضریب غلظت گردوغبار وجود داشته است.

https://deej.kashanu.ac.ir/article_115207_b759a02f73e8fb7d1c0e9a25881cd64f.pdf