نوع مقاله : مقاله پژوهشی
نویسندگان
1 گروه پژوهشی منابع آب، پژوهشکده تالاب بین‌المللی هامون، پژوهشگاه زابل.
2 گروه پژوهشی اکوسیستم های طبیعی، پژوهشکده تالاب بین‌المللی هامون، پژوهشگاه زابل
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
This study aimed to analyze and quantify land use/land cover changes in the transboundary Hirmand River basin over the past 30 years and to predict probable changes for next 20 years. Land cover maps of 1992, 2002, and 2022 were generated using Landsat images of TM and OLI sensors. The Random Forest algorithm was employed for classification and identification of land use classes. The overall accuracy and Kappa index for all classified maps were over 80% and 0.78, respectively. CA-Markov model was used to predict the changes using the land use maps first simulated for 2022, after validation, the future maps of 2030 and 2040 projected. The Kappa index of 0.82 indicated the model's high ability to simulate land use and cover changes in the basin. Water bodies experienced a 97% reduction from 1992 to 2022, with a significant portion of the remaining water body related to the Hamoun Wetland. This trend is expected to reverse slightly, with the water body area increasing from 0.05% in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests have lost 20% of area, and this decline is likely to continue. Dense rangelands have lost approximately 75% of their areas by 2022, and it is projected that they will decline to 34% by 2040, while poor rangelands have increased by around 2%. Meanwhile, agricultural land has expanded by approximately 115% by 2022, increasing from 2.72% to 5.88%. It is anticipated that agricultural land will experience a further increase of 20–30% by 2040.
کلیدواژه‌ها [English]
Land use and land cover (LULC) changes, particularly in arid and semi-arid regions, play a critical role in sustainable development and environmental stability. Given the strategic importance of the transboundary Hirmand River Basin and the environmental crises in recent decades, such as severe droughts, dust storms, vegetation loss, and desertification, precise and up-to-date assessment of land use and land cover changes is essential as a basis for effective land management studies. This study aims to analyze and quantify the patterns of land use/land cover (LULC) changes over the past 30 years (1992–2022) and predict them for the next 20 years using the CA-Markov model.
Numerous studies have demonstrated the effectiveness of remote sensing (RS) and geographic information systems (GIS) in monitoring LULC changes. The studies highlighted the potential of RS and GIS tools to analyze and predict LULC changes effectively, providing insights into sustainable land management. Based on the search results, no study has comprehensively analyzed land use and land cover (LULC) changes across the entire Hirmand Basin using remote sensing and GIS techniques. Most research has focused on specific sub-regions, such as the Hamoun Wetlands or the impacts of climate change and human activities on the Hirmand River. This indicates a gap in the literature, highlighting the novelty of your study, which uniquely integrates satellite imagery analysis and predictive modeling to examine LULC transitions across the whole basin. This makes the contribution of the study both innovative and crucial for informed regional planning and sustainable resource management.
This study employs Landsat satellite images of TM and OLI sensors to generate LULC maps for 1992, 2002, and 2022. The Random Forest algorithm was used for image classification, ensuring high accuracy in differentiating land cover types. Nine land use classes were identified. The overall accuracy and kappa coefficient indicated high classification accuracy. For predicting future LULC changes, the CA-Markov model was applied, integrating historical LULC data to simulate spatial and temporal dynamics. Land use maps were first generated for 2022 for validation (kappa coefficient of 0.86) and then simulated for 2030 and 2040. Additionally, Google Earth Engine facilitated data preprocessing, while ArcGIS Pro and IDRISI TerrSet supported advanced spatial analysis and visualization.
The results revealed that from 1992 to 2022, water bodies lost 97% of their area. Notably, a significant portion of the remaining water body is part of the Hamoun International Wetland. This trend is expected to slightly reverse, with the area increasing from 0.05% of the basin in 2022 to 0.36% and 0.37% in 2030 and 2040, respectively. Forests lost 20% of their area, shrinking from 0.21% in 1992 to 0.16% in 2022, and a continued decline is projected for 2030 and 2040. Dense rangelands have also experienced a sharp reduction, losing about 75% of their areas by 2022, decreasing from 4.83% to 1.18%. By 2040, an additional 34% reduction is expected. Meanwhile, agricultural land increased by approximately 115% by 2022, expanding from 2.72% to 5.88%. With ongoing policies in Afghanistan, agricultural land is expected to increase by an additional 20–30% reaching 23.93% by 2030 and 34% by 2040. It is expected that built-up areas will experience minimal growth, remaining around 0.23% by 2040 due to socioeconomic and political factors. The significant reduction in water bodies and rangelands, coupled with the expansion of agricultural land, emphasizes the complex interplay of environmental, socioeconomic, and political factors. The decline in water resources is attributed to both climatic factors (reduced precipitation and increased droughts) and human activities. Also, poor urban planning, political instability, and insufficient infrastructure have limited urban expansion.
This study highlights the critical changes in LULC in the Hirmand River Basin over the past 30 years and projects significant future transformations by 2040. The findings emphasize the urgent need for integrated land-use planning for sustainable land management strategies to mitigate the adverse effects of LULC changes. Without proactive management, continued degradation of rangelands and water bodies is inevitable, posing serious ecological and socio-economic risks.
M.E.: Writing original draft, Formal analysis, Conceptualization, Data curation, Methodology, Software, Validation. R.K.: Writing – review & editing.
Not applicable
This manuscript is a part of the research project (Project code: PR-RIOZ-1401-5091-1). The authors would like to thank the Research Institute of Zabol for their support.
The study was approved by the Ethics Committee of Research Institute of Zabol. The authors avoided data fabrication, falsification, plagiarism, and misconduct.
The author declares no conflict of interest.
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