Sawaid Abbas , Aqeela Mobeen Akhter , Muhammad Mushtaque , Raja Muhammad Usama , Ansir Rasool , Muhammad Umar , Muhammad Uzair Mahmood , Marryam Malik
{"title":"在干旱牧场通过铺水堤坝和旱地造林提高植被覆盖度:将遥感指标与实地考察相结合","authors":"Sawaid Abbas , Aqeela Mobeen Akhter , Muhammad Mushtaque , Raja Muhammad Usama , Ansir Rasool , Muhammad Umar , Muhammad Uzair Mahmood , Marryam Malik","doi":"10.1016/j.scitotenv.2025.179382","DOIUrl":null,"url":null,"abstract":"<div><div>Arid rangelands worldwide are increasingly threatened by degradation due to climate change stress and unsustainable land-use practices. This study combines field-based observations with remote sensing indicators to investigate the effectiveness of water spreading bunds (WSBs) in facilitating vegetation growth and improving soil water content in an arid rangeland ecosystem in Dera Ghazi Khan, Pakistan. More than 9500 WSBs were developed over 1922 ha from 2014 to 2023 under various rangeland restoration initiatives complemented by dry afforestation and grass reseeding. These efforts achieved significant improvements in rangeland health, with nearly 100 % ground cover on 15 % of the intervention sites. To assess and monitor the efficacy of these interventions a suite of remote sensing-based indicators was applied. We used post-monsoon (September–October) annual composites of the Normalized Difference Vegetation Index (NDVI) from Sentine-2 images acquired from 2016 to 2024. Temporal trends were analyzed to evaluate vegetation growth followed by micro-environmental changes. For this, the linear regression analysis of Land Surface Temperature (LST), from the Moderate Resolution Imaging Spectroradiometer (MODIS), and soil water content, from the Soil Moisture Active Passive (SMAP), was performed to establish a quantifiable relationship with vegetation growth indicators. The results showed significant improvements in the NDVI with an average net gain of 0.153 and a consequent decrease in the LST (average net change of 5.2 °C) and an increase in root zone soil moisture content (average change of 0.047 φ). It implies that vegetation growth has not only reduced evaporation losses but also enhanced infiltration and soil structure, which improves the water-holding capacity of the soil. This is critical for semi-arid regions, where water availability is a limiting factor for vegetation and agricultural productivity. The interventions have enhanced vegetation cover through dry afforestation and WSBs in the arid rangelands, aligning with Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land), indicating the potential of nature-based solutions for rainwater harvesting to restore degraded ecosystems, offering actionable insights for policymakers and practitioners.</div></div>","PeriodicalId":422,"journal":{"name":"Science of the Total Environment","volume":"978 ","pages":"Article 179382"},"PeriodicalIF":8.0000,"publicationDate":"2025-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Enhancing vegetation cover growth through water spreading bunds and dry afforestation in arid rangelands: Integrating remote sensing indicators with field insights\",\"authors\":\"Sawaid Abbas , Aqeela Mobeen Akhter , Muhammad Mushtaque , Raja Muhammad Usama , Ansir Rasool , Muhammad Umar , Muhammad Uzair Mahmood , Marryam Malik\",\"doi\":\"10.1016/j.scitotenv.2025.179382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Arid rangelands worldwide are increasingly threatened by degradation due to climate change stress and unsustainable land-use practices. This study combines field-based observations with remote sensing indicators to investigate the effectiveness of water spreading bunds (WSBs) in facilitating vegetation growth and improving soil water content in an arid rangeland ecosystem in Dera Ghazi Khan, Pakistan. More than 9500 WSBs were developed over 1922 ha from 2014 to 2023 under various rangeland restoration initiatives complemented by dry afforestation and grass reseeding. These efforts achieved significant improvements in rangeland health, with nearly 100 % ground cover on 15 % of the intervention sites. To assess and monitor the efficacy of these interventions a suite of remote sensing-based indicators was applied. We used post-monsoon (September–October) annual composites of the Normalized Difference Vegetation Index (NDVI) from Sentine-2 images acquired from 2016 to 2024. Temporal trends were analyzed to evaluate vegetation growth followed by micro-environmental changes. For this, the linear regression analysis of Land Surface Temperature (LST), from the Moderate Resolution Imaging Spectroradiometer (MODIS), and soil water content, from the Soil Moisture Active Passive (SMAP), was performed to establish a quantifiable relationship with vegetation growth indicators. The results showed significant improvements in the NDVI with an average net gain of 0.153 and a consequent decrease in the LST (average net change of 5.2 °C) and an increase in root zone soil moisture content (average change of 0.047 φ). It implies that vegetation growth has not only reduced evaporation losses but also enhanced infiltration and soil structure, which improves the water-holding capacity of the soil. This is critical for semi-arid regions, where water availability is a limiting factor for vegetation and agricultural productivity. The interventions have enhanced vegetation cover through dry afforestation and WSBs in the arid rangelands, aligning with Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land), indicating the potential of nature-based solutions for rainwater harvesting to restore degraded ecosystems, offering actionable insights for policymakers and practitioners.</div></div>\",\"PeriodicalId\":422,\"journal\":{\"name\":\"Science of the Total Environment\",\"volume\":\"978 \",\"pages\":\"Article 179382\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-04-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Science of the Total Environment\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0048969725010186\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of the Total Environment","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0048969725010186","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Enhancing vegetation cover growth through water spreading bunds and dry afforestation in arid rangelands: Integrating remote sensing indicators with field insights
Arid rangelands worldwide are increasingly threatened by degradation due to climate change stress and unsustainable land-use practices. This study combines field-based observations with remote sensing indicators to investigate the effectiveness of water spreading bunds (WSBs) in facilitating vegetation growth and improving soil water content in an arid rangeland ecosystem in Dera Ghazi Khan, Pakistan. More than 9500 WSBs were developed over 1922 ha from 2014 to 2023 under various rangeland restoration initiatives complemented by dry afforestation and grass reseeding. These efforts achieved significant improvements in rangeland health, with nearly 100 % ground cover on 15 % of the intervention sites. To assess and monitor the efficacy of these interventions a suite of remote sensing-based indicators was applied. We used post-monsoon (September–October) annual composites of the Normalized Difference Vegetation Index (NDVI) from Sentine-2 images acquired from 2016 to 2024. Temporal trends were analyzed to evaluate vegetation growth followed by micro-environmental changes. For this, the linear regression analysis of Land Surface Temperature (LST), from the Moderate Resolution Imaging Spectroradiometer (MODIS), and soil water content, from the Soil Moisture Active Passive (SMAP), was performed to establish a quantifiable relationship with vegetation growth indicators. The results showed significant improvements in the NDVI with an average net gain of 0.153 and a consequent decrease in the LST (average net change of 5.2 °C) and an increase in root zone soil moisture content (average change of 0.047 φ). It implies that vegetation growth has not only reduced evaporation losses but also enhanced infiltration and soil structure, which improves the water-holding capacity of the soil. This is critical for semi-arid regions, where water availability is a limiting factor for vegetation and agricultural productivity. The interventions have enhanced vegetation cover through dry afforestation and WSBs in the arid rangelands, aligning with Sustainable Development Goals 13 (Climate Action) and 15 (Life on Land), indicating the potential of nature-based solutions for rainwater harvesting to restore degraded ecosystems, offering actionable insights for policymakers and practitioners.
期刊介绍:
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.