Estimating the severity of landscape degradation in future management scenarios based on modeling the dynamics of Hoor Al-Azim International Wetland in Iran-Iraq border

Author:

Joorabian Shooshtari SharifORCID,Jahanishakib FatemehORCID

Abstract

AbstractTemporal and spatial changes in land cover in wetland ecosystems indicate the severity of degradation. Understanding such processes in the past, present, and future might be necessary for managing any type of development plan. Therefore, this research has monitored and analyzed the Hoor Al-Azim International Wetland to determine the orientation of its changes in various future scenarios. Wetland status modeling was conducted using developed hybrid approaches and cellular automata along with evaluating the accuracy of the modeled maps. The dynamics of the landscape were simulated using a higher accuracy approach in three scenarios—Water Conservation, Water Decreasing, and Business-as-Usual- to get the level of degradation of the wetland. The results showed that the amount of water in the wetland has decreased in all three periods, and the salt lands and vegetation have undergone drastic changes. The water bodies experienced a reduction of 148,139 ha between 1985 and 2000, followed by a decrease of 9107 ha during the 2000–2015 period. However, based on the results, these developments are expressed better by the developed hybrid approach than the CA-MC approach and are more reliable for future simulation. The figure of merit index, which assesses the hybrid model's accuracy, yielded a value of 18.12%, while the CA-MC model's accuracy was estimated at 14.42%. The assessment of degradation in hexagonal units showed the least degradation in the water conservation scenario compared with the other two scenarios in 2030.

Funder

Agricultural Sciences and Natural Resources University of Khuzestan

Publisher

Springer Science and Business Media LLC

Reference75 articles.

1. Li, K. et al. Driving factors and future prediction of land use and cover change based on satellite remote sensing data by the LCM model: A case study from Gansu province, China. Sensors 20(10), 2757. https://doi.org/10.3390/s20102757 (2020).

2. Mitsch, W. J. & Gosselink, J. G. Wetlands (John Wiley & Sons, 2015).

3. Eskandari Damaneh, H., Khosravi, H., Habashi, K., Eskandari Damaneh, H. & Tiefenbacher, J. P. The impact of land use and land cover changes on soil erosion in western Iran. Nat. Hazards 2022, 1–21 (2022).

4. Ghoochani, O. M., Eskandari Damaneh, H., Eskandari Damaneh, H., Ghanian, M. & Cotton, M. Why do farmers over-extract groundwater resources? Assessing (un) sustainable behaviors using an Integrated Agent-Centered framework. Environments 10(12), 216 (2023).

5. Makrouni, S., Sabzghabaei, G. R., Yousefi Khanghah, S. & Soltanian, S. Detection of land use changes in Hoor Al Azim wetland using remote sensing and geographic information system techniques. J. RS GIS Nat. Resour. 7(3), 89–99 (2016).

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3