云计算和空间水文学用于监测科特迪瓦的 Buyo 和 Kossou 水库

IF 3.8 Q2 ENVIRONMENTAL SCIENCES Remote Sensing Applications-Society and Environment Pub Date : 2024-09-19 DOI:10.1016/j.rsase.2024.101353
Valère-Carin Jofack Sokeng , Sekouba Oulare , Koffi Fernand Kouamé , Benoit Mertens , Tiémoman Kone , Thibault Catry , Benjamin Pillot , Pétin Edouard Ouattara , Diakaria Kone , Massiré Sow
{"title":"云计算和空间水文学用于监测科特迪瓦的 Buyo 和 Kossou 水库","authors":"Valère-Carin Jofack Sokeng ,&nbsp;Sekouba Oulare ,&nbsp;Koffi Fernand Kouamé ,&nbsp;Benoit Mertens ,&nbsp;Tiémoman Kone ,&nbsp;Thibault Catry ,&nbsp;Benjamin Pillot ,&nbsp;Pétin Edouard Ouattara ,&nbsp;Diakaria Kone ,&nbsp;Massiré Sow","doi":"10.1016/j.rsase.2024.101353","DOIUrl":null,"url":null,"abstract":"<div><div>The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.</div></div>","PeriodicalId":53227,"journal":{"name":"Remote Sensing Applications-Society and Environment","volume":"36 ","pages":"Article 101353"},"PeriodicalIF":3.8000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire\",\"authors\":\"Valère-Carin Jofack Sokeng ,&nbsp;Sekouba Oulare ,&nbsp;Koffi Fernand Kouamé ,&nbsp;Benoit Mertens ,&nbsp;Tiémoman Kone ,&nbsp;Thibault Catry ,&nbsp;Benjamin Pillot ,&nbsp;Pétin Edouard Ouattara ,&nbsp;Diakaria Kone ,&nbsp;Massiré Sow\",\"doi\":\"10.1016/j.rsase.2024.101353\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.</div></div>\",\"PeriodicalId\":53227,\"journal\":{\"name\":\"Remote Sensing Applications-Society and Environment\",\"volume\":\"36 \",\"pages\":\"Article 101353\"},\"PeriodicalIF\":3.8000,\"publicationDate\":\"2024-09-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Remote Sensing Applications-Society and Environment\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352938524002179\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Remote Sensing Applications-Society and Environment","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352938524002179","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

布约水库和科苏水库对科特迪瓦的供水、农业灌溉和水力发电至关重要。然而,气候变化增加了降雨量的变化,延长了干旱期,加剧了极端天气事件,从而威胁到这些水资源的稳定性和可用性。这些挑战凸显了对水位和地表面积进行精确和持续监测以确保可持续管理的必要性。由于测量站稀缺,本研究的目标是利用云计算技术以及测高和卫星数据对水库进行有效监测。EO-Africa 计划的创新实验室和谷歌地球引擎 (GEE) 等工具以及 PyGEE-SWToolbox 和 AlTis 等先进的图像处理软件被用来处理来自哨兵-1、哨兵-2 和哨兵-3 卫星的大型数据集。这些卫星提供了大量高分辨率图像和测高数据,对监测储层的变化至关重要。处理后的数据经过现场测量验证,均方根误差(RMSE)小于 0.4 米,相关系数超过 0.90。研究结果突显了 2016 年至 2022 年的水面和水位变化,其下降趋势和季节变化与现场测量结果密切吻合。研究还发现,水位与水面面积之间的关系受到降水量以及班达马河和萨桑德拉河水文系统的影响,这表明了这些水库水动态的复杂性。这项研究强调了将空间水文学与云计算工具相结合,对大型水库进行快速、准确监测的有效性。这些先进技术的使用提供了近乎实时、可靠和易于获取的数据,为科特迪瓦的水资源管理提供了重要优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Cloud computing and spatial hydrology for monitoring the Buyo and Kossou reservoirs in Côte d'Ivoire
The Buyo and Kossou reservoirs are crucial for water supply, agricultural irrigation, and hydroelectric power generation in Côte d'Ivoire. However, climate change threatens the stability and availability of these water resources by increasing rainfall variability, extending drought periods, and intensifying extreme weather events. These challenges underscore the need for precise and continuous monitoring of water levels and surface areas to ensure sustainable management. Due to the scarcity of gauging stations, the objective of this study is to leverage cloud computing technologies along with altimetric and satellite data, for effective reservoir monitoring. Tools like the EO-Africa program's Innovation Lab and Google Earth Engine (GEE), along with advanced image processing software such as PyGEE-SWToolbox and AlTis, were used to process large datasets from the Sentinel-1, Sentinel-2, and Sentinel-3 satellites. These satellites delivered extensive, high-resolution imagery and altimetric data, crucial for monitoring changes in the reservoirs. The processed data were validated with in-situ measurements, yielding a Root Mean Square Error (RMSE) of less than 0.4 m and a correlation coefficient exceeding 0.90. The results highlighted water surface and level changes from 2016 to 2022, with downward trends and seasonal variations closely aligning with in-situ measurements. The study also revealed that the relationship between water levels and surface areas is influenced by both precipitation and the hydrological regimes of the Bandama and Sassandra rivers, demonstrating the complexity of water dynamics in these reservoirs. This research emphasizes the effectiveness of integrating spatial hydrology with cloud computing tools for fast and accurate monitoring of large reservoir. The use of these advanced technologies provides near real-time, reliable, and easily accessible data, offering a significant advantage for water resource management in Côte d'Ivoire.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
8.00
自引率
8.50%
发文量
204
审稿时长
65 days
期刊介绍: The journal ''Remote Sensing Applications: Society and Environment'' (RSASE) focuses on remote sensing studies that address specific topics with an emphasis on environmental and societal issues - regional / local studies with global significance. Subjects are encouraged to have an interdisciplinary approach and include, but are not limited by: " -Global and climate change studies addressing the impact of increasing concentrations of greenhouse gases, CO2 emission, carbon balance and carbon mitigation, energy system on social and environmental systems -Ecological and environmental issues including biodiversity, ecosystem dynamics, land degradation, atmospheric and water pollution, urban footprint, ecosystem management and natural hazards (e.g. earthquakes, typhoons, floods, landslides) -Natural resource studies including land-use in general, biomass estimation, forests, agricultural land, plantation, soils, coral reefs, wetland and water resources -Agriculture, food production systems and food security outcomes -Socio-economic issues including urban systems, urban growth, public health, epidemics, land-use transition and land use conflicts -Oceanography and coastal zone studies, including sea level rise projections, coastlines changes and the ocean-land interface -Regional challenges for remote sensing application techniques, monitoring and analysis, such as cloud screening and atmospheric correction for tropical regions -Interdisciplinary studies combining remote sensing, household survey data, field measurements and models to address environmental, societal and sustainability issues -Quantitative and qualitative analysis that documents the impact of using remote sensing studies in social, political, environmental or economic systems
期刊最新文献
Improving the estimation approach of percentage of impervious area for the storm water management model — A case study of the Zengwen reservoir watershed, Taiwan Multilayer optimized deep learning model to analyze spectral indices for predicting the condition of rice blast disease A review of the global operational geostationary meteorological satellites Assessing drivers of vegetation fire occurrence in Zimbabwe - Insights from Maxent modelling and historical data analysis Analysis of spatiotemporal surface water variability and drought conditions using remote sensing indices in the Kagera River Sub-Basin, Tanzania
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1