Joshua Culpepper, Sapna Sharma, Grant Gunn, Madeline R. Magee, Michael F. Meyer, Eric J. Anderson, Chris Arp, Sarah W. Cooley, Wayana Dolan, Hilary A. Dugan, Claude R. Duguay, Benjamin M. Jones, Georgiy Kirillin, Robert Ladwig, Matti Leppäranta, Di Long, John J. Magnuson, Tamlin Pavelsky, Sebastiano Piccolroaz, Dale M. Robertson, Bethel G. Steele, Manu Tom, Gesa A. Weyhenmeyer, R. Iestyn Woolway, Marguerite A. Xenopoulos, Xiao Yang
{"title":"湖泊冰研究中整合方法学方法的100个基本开放问题","authors":"Joshua Culpepper, Sapna Sharma, Grant Gunn, Madeline R. Magee, Michael F. Meyer, Eric J. Anderson, Chris Arp, Sarah W. Cooley, Wayana Dolan, Hilary A. Dugan, Claude R. Duguay, Benjamin M. Jones, Georgiy Kirillin, Robert Ladwig, Matti Leppäranta, Di Long, John J. Magnuson, Tamlin Pavelsky, Sebastiano Piccolroaz, Dale M. Robertson, Bethel G. Steele, Manu Tom, Gesa A. Weyhenmeyer, R. Iestyn Woolway, Marguerite A. Xenopoulos, Xiao Yang","doi":"10.1029/2024wr039042","DOIUrl":null,"url":null,"abstract":"The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.","PeriodicalId":23799,"journal":{"name":"Water Resources Research","volume":"36 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2025-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"One-Hundred Fundamental, Open Questions to Integrate Methodological Approaches in Lake Ice Research\",\"authors\":\"Joshua Culpepper, Sapna Sharma, Grant Gunn, Madeline R. Magee, Michael F. Meyer, Eric J. Anderson, Chris Arp, Sarah W. Cooley, Wayana Dolan, Hilary A. Dugan, Claude R. Duguay, Benjamin M. Jones, Georgiy Kirillin, Robert Ladwig, Matti Leppäranta, Di Long, John J. Magnuson, Tamlin Pavelsky, Sebastiano Piccolroaz, Dale M. Robertson, Bethel G. Steele, Manu Tom, Gesa A. Weyhenmeyer, R. Iestyn Woolway, Marguerite A. Xenopoulos, Xiao Yang\",\"doi\":\"10.1029/2024wr039042\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.\",\"PeriodicalId\":23799,\"journal\":{\"name\":\"Water Resources Research\",\"volume\":\"36 1\",\"pages\":\"\"},\"PeriodicalIF\":5.0000,\"publicationDate\":\"2025-05-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Water Resources Research\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1029/2024wr039042\",\"RegionNum\":1,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Water Resources Research","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1029/2024wr039042","RegionNum":1,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
One-Hundred Fundamental, Open Questions to Integrate Methodological Approaches in Lake Ice Research
The rate of technological innovation within aquatic sciences outpaces the collective ability of individual scientists within the field to make appropriate use of those technologies. The process of in situ lake sampling remains the primary choice to comprehensively understand an aquatic ecosystem at local scales; however, the impact of climate change on lakes necessitates the rapid advancement of understanding and the incorporation of lakes on both landscape and global scales. Three fields driving innovation within winter limnology that we address here are autonomous real-time in situ monitoring, remote sensing, and modeling. The recent progress in low-power in situ sensing and data telemetry allows continuous tracing of under-ice processes in selected lakes as well as the development of global lake observational networks. Remote sensing offers consistent monitoring of numerous systems, allowing limnologists to ask certain questions across large scales. Models are advancing and historically come in different types (process-based or statistical data-driven), with the recent technological advancements and integration of machine learning and hybrid process-based/statistical models. Lake ice modeling enhances our understanding of lake dynamics and allows for projections under future climate warming scenarios. To encourage the merging of technological innovation within limnological research of the less-studied winter period, we have accumulated both essential details on the history and uses of contemporary sampling, remote sensing, and modeling techniques. We crafted 100 questions in the field of winter limnology that aim to facilitate the cross-pollination of intensive and extensive modes of study to broaden knowledge of the winter period.
期刊介绍:
Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.