Iranian Jornal of Watershed Management Science&Engineering

fa بررسی تأثیرات تغییر کاربری اراضی بر رواناب در مناطق خشک و نیمه خشک (مطالعه موردی: حوضه میمه، ایلام) Assessing the Impacts of Land Use Changes on Runoff in Arid and Semi-Arid Regions (Case Study: Meymeh Watershed, Ilam) تخصصي Special پژوهشي Research <div>در سال‌های اخیر، منابع آب به‌عنوان مؤلفه‌ای حیاتی در توسعه و محیط زیست با فشارهای فزاینده‌ای مواجه شده‌اند و تغییرات اقلیمی، رشد جمعیت و مداخلات انسانی، ازجمله تغییر کاربری اراضی، چرخه هیدرولوژیک را مختل کرده و پایداری منابع آب را تهدید می‌کنند. این مطالعه با هدف بررسی اثرات تغییرات کاربری اراضی بر رواناب سطحی و جریان پایه در حوزه آبخیز میمه واقع در استان ایلام، با اقلیم نیمه‌خشک و ناهمواری زیاد، انجام شد. برای این منظور از مدل SWAT جهت شبیه‌سازی فرآیندهای هیدرولوژیکی و از مدل CA–Markov برای پیش‌بینی تغییرات کاربری اراضی تا سال ۲۰۳۰ استفاده شد. مدل واسنجی شد و در دوره ۲۰۱۰–۲۰۱۶ شاخص‌های NSE برابر 0/73، R²  برابر 0/81 و PBIAS معادل 45/4- درصد به دست آمد و در دوره اعتبارسنجی ۲۰۱۷–۲۰۲۰ شاخص‌های NSE برابر 0/65، R²  برابر 0/68 و PBIAS معادل 53/2- درصد بود که نشان‌دهنده تطابق قابلقبول مدل با داده‌های مشاهده‌شده است. تحلیل تغییرات تاریخی کاربری اراضی بین سال‌های ۱۹۸۶ تا ۲۰۱۹ کاهش ۴۹۰۰ هکتار جنگل و ۸۹۰۰ هکتار مرتع و افزایش ۱۲۴۱۳ هکتار اراضی کشاورزی و ۶۵۰۰ هکتار اراضی بدون پوشش را نشان داد. پیش‌بینی برای سال ۲۰۳۰ حاکی از کاهش جنگل به ۷۵۷۲۶ هکتار، مراتع به ۲۹۵۰۵ هکتار و افزایش اراضی کشاورزی به ۱۶۷۷۲ هکتار و بدون پوشش به ۲۵۳۶۳ هکتار است. اثر تغییرات کاربری بر رواناب شامل افزایش 1/6 درصدی رواناب سالانه و افزایش میانگین دبی سطحی از 5/53 به 6/56 مترمکعب بر ثانیه بود، درحالی‌که جریان پایه حدود ۸ درصد کاهش یافت. بیشترین افزایش رواناب در ماه‌های فروردین و اسفند مشاهده شد و نسبت رواناب به بارش از 0/36 به 0/41 رسید که نشان‌دهنده کاهش نفوذ و تهدید منابع زیرزمینی است. نتایج بیانگر تأثیر مستقیم گسترش اراضی کشاورزی و مناطق بدون پوشش بر نوسانات دبی، پایداری جریان‌ها و افزایش خطر سیلاب است. یافته‌ها بر ضرورت مدیریت کاربری اراضی، احیای جنگل‌ها و مراتع و کنترل توسعه کشاورزی برای حفظ پایداری هیدرولوژیکی تأکید دارند. این پژوهش راهنمای عملی برای سیاست‌گذاران و مدیران منابع آب جهت کاهش مخاطرات ناشی از تغییر کاربری فراهم می‌کند.  </div> Extended Abstract Introduction In recent decades, water resources, as one of the most vital environmental and developmental components, have been subjected to increasing pressures. Climate change, population growth, and human interventions, including land use changes, have disrupted the natural hydrological cycle, leading to increased surface runoff, reduced infiltration, and threats to the sustainability of water resources. Due to its semi-arid climate and high evaporation, Iran is one of the regions highly sensitive to land use changes, where even minor alterations in land cover can have profound effects on surface and base flows. In this context, hydrological simulation models provide the capability to analyze water cycle components, including precipitation, runoff, evapotranspiration, and baseflow, with high precision. Additionally, land use change prediction models enable the assessment of future trends and spatial patterns of land transformation. Despite these advances, in the Maimah watershed located in Ilam province, due to its semi-arid climate, significant topographic variation, and notable human pressure, there has not yet been a comprehensive study that integratively examines the impact of land use changes on runoff. This scientific gap provides an opportunity to use spatial data, advanced modeling, and scenario analysis to identify past trends and assess the future outlook of the region under potential land use changes, with results applicable for sustainable water resource management. Materials and Methods The study area, Maimah watershed in Dehloran County, Ilam Province, covers an area of 1,633 km² with elevations ranging from 216 to 2,486 meters above sea level. It comprises two main regions: mountainous and hilly areas. The climate of the watershed is semi-arid, with an annual average rainfall of 433 mm and an average temperature of 27°C. Land cover includes forests, rangelands, agricultural lands, and residential areas. To simulate hydrological processes, the SWAT model was employed. By dividing the watershed into sub-basins and Hydrological Response Units (HRUs), SWAT calculates precipitation, surface runoff, baseflow, and groundwater recharge. Meteorological data, streamflow records, soil characteristics, DEM, and land use maps were prepared and input into the model. Model calibration was performed for the period 2010–2016 and validation for 2017–2020 using NSE, R², and PBIAS indices, and sensitive parameters were optimized. Land use changes were identified using Landsat satellite imagery for five time periods: 1986, 1997, 2005, 2013, and 2019. Future land use for 2030 was predicted using the Markov and CA–Markov models. Transition probability matrices between land use classes and cellular automata algorithms were used to simulate the spatial distribution of changes. The 2030 predicted map was used as input for SWAT to analyze the effects of land use changes on runoff and baseflow. This integrated approach allowed examination of both spatial and temporal impacts of land use changes and the assessment of sustainable management scenarios. Results and Discussion SWAT model results indicated that during the calibration period (2010–2016), NSE was 0.73, R² was 0.81, and PBIAS was -45.4%, demonstrating a good fit between the model and observed data. In the validation period (2017–2020), NSE was 0.65, R² was 0.68, and PBIAS was -53.2%. Analysis of land use changes showed that from 1986 to 2019, medium forests decreased by 4,900 ha and medium rangelands by 8,900 ha, while agricultural lands increased more than fivefold (12,413 ha) and barren lands increased by approximately 6,500 ha. Predictions for 2030 indicate 75,726 ha of sparse forests, 29,505 ha of medium rangelands, 25,363 ha of barren lands, 16,772 ha of agricultural lands, and 614 ha of residential areas. The impact of land use change on runoff in 2030 includes a 6.1% increase in annual runoff and an increase in average surface flow from 5.53 to 6.56 m³/s, while baseflow is projected to decrease by approximately 8%. These changes reflect reduced infiltration, increased surface runoff, and threats to groundwater resources. Runoff increases were most pronounced in Farvardin (March–April) and Esfand (February–March), with the runoff-to-precipitation ratio rising from 0.36 to 0.41. The results indicate that land use changes, particularly the expansion of agricultural and barren lands, directly affect flow fluctuations, streamflow sustainability, and flood risk, emphasizing the need for land use management to maintain hydrological stability. Conclusion This study showed that land use changes in the Maimah watershed significantly affect surface runoff, baseflow, and soil infiltration capacity. The reduction of forests and rangelands, alongside the expansion of agricultural and barren lands, leads to increased annual runoff and decreased baseflow in the 2030 projection. These changes indicate reduced infiltration and threats to groundwater resources, which could challenge sustainable water management. Additionally, the use of SWAT and CA–Markov models enabled the evaluation of spatial and temporal effects of land use changes and future trend prediction, highlighting that the nature of land use changes, particularly agricultural expansion and barren lands, is the main driver of flow fluctuations and increased flood risk.Limitations of this study include the quality of meteorological and land use data, the assumption of stationary Markov matrices, and the simplification of physical processes in SWAT, which may affect prediction accuracy. To improve water resource management, it is recommended to use higher-resolution satellite data and integrated hydro-climatic models and plan land use according to the watershed’s natural capacity. Protective measures such as forest and rangeland restoration and control of agricultural expansion can reduce surface runoff and enhance groundwater recharge. The findings provide practical guidance for policymakers and water resource managers to achieve sustainable management and mitigate risks associated with land use changes.   پوشش زمین, جریان رودخانه , شبیه سازی, مدل SWAT, مدل CA–Markov, Land cover, River flow, Simulation, SWAT model, CA–Markov model 35 0 http://jwmsei.ir/browse.php?a_code=A-10-1743-2&slc_lang=fa&sid=1 Samira Foladvand سمیرا فولادوند s.foladvand@ilam.ac.ir 100319475328460018910 100319475328460018910 No Mohsen Tavakoli محسن توکلی m.tavakoli@ilam.ac.ir 100319475328460018911 100319475328460018911 Yes Haidar Ebrahimi حیدر ابراهیمی h.ebrahimi33@gmail.com 100319475328460018912 100319475328460018912 No Haji Karimi حاجی کریمی h.karimi@ilam.ac.ir 100319475328460018913 100319475328460018913 No