Global Observatory of Lake Responses to Environmental Change (GloboLakes)

全球湖泊对环境变化反应的观测站 (GloboLakes)

• 批准号: NE/J023345/2
• 负责人: Christopher Merchant
• 金额: $ 31.93万
• 依托单位: University of Reading
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2013
• 资助国家: 英国
• 起止时间: 2013 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=NE%2FJ023345%2F2
• 关键词: Global; Observatory; Lake; Responses; Environmental

There are around 304 million lakes globally. These provide essential resources for human survival and are an important component of global biogeochemical cycles. Lakes are also fragile systems that are sensitive to multiple pressures including nutrient enrichment, climate change and hydrological modification, making them important 'sentinels' of environmental perturbation. However, traditional monitoring has only produced data from a tiny fraction of the global population of lakes and disentangling the causes of change requires consistently-produced data from a large number of lakes, along with measurements of possible causes of change. Satellite observations (remote sensing) and the establishment of a global lake observatory would produce a step-change in our ability to detect and attribute the causes of changes in lakes world-wide. This is now possible for three reasons: (1) the improved wavebands, spatial resolution and frequency of data collection from satellite sensors is now sufficient to monitor inland waters; (2) formulae to correct for atmospheric properties and to convert the detected reflected light to useful lake properties have been developed; and (3) computing power has increased to the point that allows near real time and archived information from satellites to be processed. GloboLakes will analyse 20 years of data from more than 1000 large lakes across the globe to determine 'what controls the differential sensitivity of lakes to environmental perturbation'. This is an ambitious project that is only possible by bringing together a consortium of scientists with complementary skills. These include expertise in remote sensing of freshwaters and processing large volumes of satellite images, collation and analysis of large-scale environmental data, environmental statistics and the assessment of data uncertainty, freshwater ecology and mechanisms of environmental change and the ability to produce lake models to forecast future lake conditions. The eight objectives of GloboLakes are to:(i) develop remote sensing algorithms to estimate lake biogeochemical and physical parameters;(ii) make these algorithms operational and process satellite data;(iii) compile integrated spatio-temporal information on climatic and catchment data for >1000 lakes;(iv) integrate data and assess uncertainty in data sources;(v) detect spatial and temporal patterns in lake water quality;(vi) attribute the causes of lake response to environmental conditions;(vii) forecast lake sensitivity to environmental change;(viii) apply data to lake management and the monitoring of freshwater resources.The project will focus on the retrieval of surface water temperature as this has a fundamental effect on lake ecology, the concentration of coloured dissolved organic matter and suspended solids that derive largely from the catchment, the abundance of phytoplankton measured as the concentration of the pigment, chlorophyll a, and the abundance of cyanobacteria (blue-green algae) that can potentially be toxic. Knowledge of the conditions of lakes and their sensitivity to change is also extremely valuable for the management of lakes and reservoirs and GloboLakes will provide information and products specifically for environmental managers. A satellite due to be launched during the course of the project, called Sentinel 2, will provide even greater spatial resolution allowing data to be collected and exploited from even smaller lakes. This will be investigated by GloboLakes and incorporated into the framework of a global lake observatory.

全球约有3.04亿个湖泊。它们为人类生存提供了必要的资源，是全球生物地球化学循环的重要组成部分。湖泊也是脆弱的系统，对多种压力敏感，包括营养丰富、气候变化和水文变化，使它们成为环境扰动的重要“哨兵”。然而，传统的监测只从全球湖泊人口的一小部分中产生了数据，要弄清变化的原因，需要从大量湖泊中始终如一地产生数据，以及对可能的变化原因进行测量。卫星观测(遥感)和建立全球湖泊观测站将使我们发现世界各地湖泊变化的原因并确定其原因的能力发生阶段性变化。现在有可能做到这一点，原因有三：(1)从卫星传感器收集的数据的波段、空间分辨率和频率现在足以监测内陆水域；(2)已经制定了对大气性质进行校正并将探测到的反射光转换为有用的湖泊性质的公式；(3)计算能力已增加到能够处理来自卫星的近实时和存档的信息。“环球湖”将分析全球1000多个大型湖泊20年来的数据，以确定“是什么控制了湖泊对环境扰动的差异化敏感性”。这是一个雄心勃勃的项目，只有将具有互补技能的科学家联盟聚集在一起才能实现。这些领域包括淡水遥感和处理大量卫星图像的专门知识、大规模环境数据的整理和分析、环境统计和数据不确定性评估、淡水生态和环境变化机制以及制作湖泊模型以预测未来湖泊状况的能力。全球湖泊的八个目标是：(1)开发遥感算法以估计湖泊的生物地球化学和物理参数；(2)使这些算法具有可操作性并处理卫星数据；(3)汇编关于1000个湖泊的气候和集水区数据的综合时空信息；(4)综合数据和评估数据来源中的不确定性；(5)探测湖泊水质的时空模式；(6)确定湖泊对环境条件作出反应的原因；(7)预测湖泊对环境变化的敏感性；(Viii)将数据应用于湖泊管理和淡水资源的监测。该项目将侧重于表层水温的恢复，因为这对湖泊生态、主要来自集水区的有色溶解有机物和悬浮固体的浓度、以色素、叶绿素a的浓度测量的浮游植物的丰度以及可能有毒的蓝藻(蓝藻)的丰度有根本影响。了解湖泊的状况及其对变化的敏感性对于湖泊和水库的管理也是极其宝贵的，GloboLake将专门为环境管理人员提供信息和产品。该项目期间将发射一颗名为哨兵2号的卫星，它将提供更高的空间分辨率，允许从更小的湖泊收集和利用数据。这将由环球湖进行调查，并纳入全球湖泊观测站的框架。

项目成果

Adaptive smoothing to identify spatial structure in global lake ecological processes using satellite remote sensing data

利用卫星遥感数据进行自适应平滑识别全球湖泊生态过程的空间结构

• DOI: 10.1016/j.spasta.2022.100615
• 发表时间: 2022
• 期刊: Spatial Statistics
• 影响因子: 2.3
• 作者: Gong M

Global climatology of surface water temperatures of large lakes by remote sensing

• DOI: 10.1002/joc.4299
• 发表时间: 2015-12-01
• 期刊: INTERNATIONAL JOURNAL OF CLIMATOLOGY
• 作者: Layden, Aisling;Merchant, Christopher;MacCallum, Stuart
• 通讯作者: MacCallum, Stuart

Satellite-derived multivariate world-wide lake physical variable timeseries for climate studies.

• DOI: 10.1038/s41597-022-01889-z
• 发表时间: 2023-01-14
• 期刊: SCIENTIFIC DATA
• 影响因子: 9.8
• 作者: Carrea, Laura;Cretaux, Jean-Francois;Liu, Xiaohan;Wu, Yuhao;Calmettes, Beatriz;Duguay, Claude R.;Merchant, Christopher J.;Selmes, Nick;Simis, Stefan G. H.;Warren, Mark;Yesou, Herve;Mueller, Dagmar;Jiang, Dalin;Embury, Owen;Berge-Nguyen, Muriel;Albergel, Clement
• 通讯作者: Albergel, Clement

Datasets related to in-land water for limnology and remote sensing applications: distance-to-land, distance-to-water, water-body identifier and lake-centre co-ordinates.

• DOI: 10.1002/gdj3.32
• 发表时间: 2015-11
• 期刊: Geoscience data journal
• 影响因子: 3.2
• 作者: Carrea L;Embury O;Merchant CJ
• 通讯作者: Merchant CJ

Supplementary material to "Determining lake surface water temperatures (LSWTs) worldwide using a tuned 1-dimensional lake model (<i>FLake</i>, v1)"

补充材料

• DOI: 10.5194/gmdd-8-8547-2015-supplement
• 发表时间: 2015
• 作者: Layden A