Modeling water and pollutant connectivity in pristine and human-impacted landscapes

生态水文学家试图更好地理解、预测和缓解各种具有社会和经济意义的环境问题，包括洪水、干旱和水污染。虽然这些问题是由不同的过程产生的，但它们都可以通过连接的视角进行检查。事实上，“连通性”是指特定景观位置“a”将水和其他物质（例如污染物或生物群）传输到另一个位置“B”的能力，它是陆地和水生生态系统健康的关键指标。鉴于在连通性度量方面缺乏科学共识，模型被视为估计和测试有关连通性假设的实用工具。然而，虽然现有的降水-径流模型用于连通性估计，但很少有模型明确地考虑到这一目标，这引发了对其预测可靠性的质疑。大多数现有模型依赖于隐式连通性模拟方法，其中只有与连通性相关的一些景观属性通过空间聚合代理度量来考虑。相反，明确的连通性模拟方法很少：它们应该考虑到大量的景观属性，并允许它们对连通性的影响在空间和时间上变化，要么通过基于方程的建模（EBM），要么通过从复杂系统理论引入的方法，如基于代理的建模（ABM）。后者在生态学中相对常见，但在水文学中较少。因此，提出的研究计划的目标有四个方面：1)比较现有降水-径流模型在连通性隐含模拟中的表现；2)利用基于方程的建模原理建立水和水介导的污染物连通性的空间明确模型，这在水文学中是典型的；3)利用借鉴生态学的基于智能体的建模工具创建空间明确的连通性模型；4)评估混合连通性建模方法在不同时空尺度上的价值。重点将放在从小型集水区到位于加拿大和世界其他地区的森林、农业和城市地区的大型流域的地点上：这将确保考虑到各种各样的景观，并评价与模型数据要求和计算效率有关的空间可变问题。鉴于该研究项目非常重视原始和人类影响景观的数据模型整合，该研究项目将为未来的生态水文学家提供独特而重要的培训机会。

Ecohydrologists seek to better understand, predict and mitigate various environmental issues of societal and economic significance, including floods, droughts and water pollution. While those issues are created by different processes, they can all be examined through the lens of connectivity. Indeed, “connectivity” refers to the ability of a given landscape location “A” to transmit water and other materials (e.g., pollutants or biota) to another location “B”, and it is a key indicator of terrestrial and aquatic ecosystem health. Given the lack of scientific consensus on connectivity measures, models are seen as pragmatic tools for estimating and testing hypotheses about connectivity. However, while existing precipitation-runoff models are used for connectivity estimation, few were explicitly designed with this goal in mind, raising questions about the reliability of their predictions. Most existing models rely on implicit connectivity simulation approaches, whereby only some of the landscape properties relevant to connectivity are considered through spatially aggregated proxy measures. Conversely, explicit connectivity simulation approaches are rare: they should account for a large number of landscape properties and allow their influence on connectivity to vary in space and time, either via equation-based modelling (EBM) or through methods imported from complex systems theory, such as agent-based modelling (ABM). The latter are relatively common in ecology but scarce in hydrology. The goal of the proposed research program is, therefore, four-fold: 1) compare the performance of existing precipitation-runoff models in their implicit simulation of connectivity; 2) create spatially explicit models of water and water-mediated pollutant connectivity using equation-based modelling principles, as is typical in hydrology; 3) create spatially explicit models of connectivity using agent-based modelling tools borrowed from ecology; and 4) assess the value of hybrid connectivity modelling approaches at different spatial and temporal scales. The focus will be on sites ranging from small catchments to large watersheds located in forested, agricultural and urban regions of Canada and other parts of the world: this will ensure that a good variety of landscapes is considered and spatially variable issues related to model data requirements and computational efficiency are appraised. Given its strong emphasis on data-model integration in pristine and human-impacted landscapes, the proposed research program will provide unique and vital training opportunities for future ecohydrologists.