A Multi-Scale Approach for Predicting River Temperatures and Thermal Habitats.

预测河流温度和热栖息地的多尺度方法。

• 批准号: RGPIN-2018-06015
• 负责人: Curry, Ranald
• 金额: $ 2.62万
• 依托单位: University of New Brunswick
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=648437
• 关键词: Multi; Scale; Approach; Predicting; River

The goal of my NSERC Discovery programme is to advance our knowledge of river ecosystems through a better understanding of temperature and how it creates and sustains aquatic habitats. My long-term objectives are to identify the spatial features that best predict river temperatures and then link the predicted temperature to habitats for biota in the river. My work uses varied types of images collected at different wavelengths from satellites, aircraft, and drones to map landscape and riverscape features such as hills and valleys, stream channels, and in-river water temperatures, depths and flows. The next 5 years of my NSERC Discovery Grant builds on my current working hypotheses that we can predict the spatial pattern of river temperatures (its thermal regime) from landscape characteristics, we can model a river ecosystem from its thermal regimes, and we can predict the potential impacts of changing land uses and climate on river ecosystems. My short-term objectives are: 1) to improve our current models with advanced image acquisition and processing and statistical approaches; 2) to predict where and when in-river features such as temperature anomalies are actual habitats for biota by using hyperspectral image applications (coupled with biological data); and, 3) to continue building applications based on these remotely-sensed data to predict the impacts of changing landscapes and climate for river ecosystems, i.e., decision making tools for resource planners and managers. My research unravels the links from landscapes to temperature to aquatic habitats for fish and other biota in rivers. As our understanding improves, I am beginning to better predict how human activities impact river ecosystems directly, e.g., changes in landscapes such as forestry practices as well as indirectly via climate change.

我的NSERC发现计划的目标是通过更好地了解温度以及它如何创造和维持水生栖息地来提高我们对河流生态系统的认识。我的长期目标是确定最能预测河流温度的空间特征，然后将预测的温度与河流中生物群的栖息地联系起来。 我的工作使用从卫星、飞机和无人机上以不同波长收集的各种类型的图像来绘制景观和河流景观特征，如山丘和山谷、河道、河中水温、深度和流量。 我的NSERC发现补助金的未来5年建立在我目前的工作假设，我们可以从景观特征预测河流温度的空间格局（其热态），我们可以从其热态模拟河流生态系统，我们可以预测土地利用和气候变化对河流生态系统的潜在影响。 我的短期目标是：1）利用先进的图像采集和处理以及统计方法改进我们目前的模型; 2）通过使用高光谱图像应用，预测河流中的特征（如温度异常）何时何地是生物群的实际栖息地（与生物数据结合）;以及3）继续建立基于这些遥感数据的应用程序，以预测景观和气候变化对河流生态系统的影响，也就是说，资源规划者和管理者的决策工具。 我的研究揭示了从景观到温度到河流中鱼类和其他生物的水生栖息地的联系。 随着我们的理解的提高，我开始更好地预测人类活动如何直接影响河流生态系统，例如，景观的变化，如林业做法，以及间接通过气候变化。