Collaborative Research: ABI Innovation: Improving high performance super computer aquatic ecosystem models with the integration of real-time citizen science data

这项研究旨在让公众参与数据收集和开发溪流流量、溪流温度和水生物种栖息地预测模型。通过使用基于公民的溪流高度和溪流温度观测，这一方法将展示公民派生的观测如何有助于预报溪流流量、溪流温度和确定淡水鱼栖息地。淡水鱼在整个美国具有重要的生态、经济和娱乐重要性。然而，淡水物种是北美最濒危的生物群之一，主要是由于人类活动的影响。需要准确描述淡水物种的栖息地，以制定平衡社会需要和保护淡水资源的办法。这可以通过政府和研究组织收集观测数据或通过对栖息地进行计算机模拟来实现，由此模型的质量取决于观测数据的可用性。然而，由于资金减少，淡水系统的观测数据量一直在下降。现有的数据一般集中在对城市社区很重要的大河流(即洪水、供水)，这些河流的位置并不总是与淡水物种有关，这些物种的栖息地往往出现在较小的源头溪流中。当地的休闲用户社区和他们的移动电话提供了一个机会，通过公民科学来缩小这种数据可用性差距。作为共享资源的经常使用者，如溪流和水道，户外爱好者对特定地点有着宝贵的知识。科学界对这一知识的利用严重不足。该项目将利用当地社区成员收集的信息和数据，开发一种收集、存储数据的方法，并与可以预测径流、溪流温度和淡水物种栖息地的计算机模型相结合，从而有助于这些资源的可持续管理。美国密歇根州的博伊恩河流域将被用作试验地点，但这些技术可以用于世界各地的流域。这项研究的目标是开发将公民科学水文学和水流温度数据与生态水文学模型相结合的技术。具体地说，这项研究旨在充分结合公民参与开发实时河流流量、温度和水生物种栖息地预测模型框架。该项目将在整个博伊恩河流域安装Crowd水文(收集水文数据的公民科学网络)设备。然后，当地社区可以(通过手机)将水流水位和水流温度数据发送到Crowd水文平台。然后，这些公民科学数据将被转换并输入生态水文模型，用于近乎实时地模拟溪流、溪流温度和水生物种栖息地。这种方法将展示公民派生的观测如何有助于溪流流量、溪流温度和水生物种栖息地的建模。模型模拟和预报(提前一周)，包括河流流量、温度和栖息地分布，将以表格和简单的空间图的形式提供，可在皇冠水文学网站(http://www.crowdhydrology.com))下载

This research is designed to engage public participation in data collection and the development of a stream discharge, stream temperature, and aquatic species habitat forecasting model. Through the use of citizen-based observations of stream height and stream temperature, this approach will demonstrate how citizen-derived observations can contribute to forecasts of stream discharge, stream temperature, and identification of freshwater fish habitat. Freshwater fishes have significant ecological, economic, and recreational importance across the United States. However, freshwater species are among the most endangered groups of organisms in North America, largely due to the impact of human activities. Accurate representations of freshwater species habitat are needed to develop approaches to balance the needs of society with the conservation of freshwater resources. This can be accomplished through the collection of observed data by government and research organizations or by computer modeling of habitat, whereby the quality of the model depends upon the availability of observed data. However, the amount of observed data for freshwater systems has been declining due to decreases in funding. The data that do exist are generally focused on large rivers that are important for urban communities (i.e., flooding, water supply), which are locations not always relevant to freshwater species whose habitat often occurs in smaller headwater streams. Local communities of recreational users and their mobile phones offer an opportunity to close this data-availability gap through citizen science. As regular users of shared resources, like streams and waterways, outdoor enthusiasts have valuable knowledge of specific locations. This knowledge is vastly underutilized by scientific communities. This project will harness information and data collected by members of local communities and develop an approach for data collection, storage, and integration with computer models that can predict streamflow, stream temperature, and freshwater species habitat, which can then aid in sustainable management of these resources. The Boyne River Basin in Michigan, USA will be used as a test location, but the techniques can be used in watersheds throughout the world. The goal of this research is to develop techniques that integrate citizen science hydrology and stream temperature data with eco-hydrological models. Specifically, this research is designed to fully couple citizen participation in the development of a real-time stream discharge, temperature, and aquatic species habitat forecasting model framework. The project will install CrowdHydrology (a citizen science network that collects hydrologic data) equipment throughout the Boyne River Basin. The local community can then text (via cellphone) stream level and stream temperature data to the CrowdHydrology platform. These citizen science data will then be transformed and input into an eco-hydrological model for near real-time simulations of streamflow, stream temperature, and aquatic species habitat. This approach will demonstrate how citizen-derived observations can contribute to the modeling of stream discharge, stream temperature, and aquatic species habitat. The model simulations and forecasts (one week ahead), including stream flows, temperatures, and habitat distributions, will be presented in tables and simple spatial plots available for download on the CrowdHydrology website (http://www.crowdhydrology.com)