Climate change and watershed process interactions: Large-scale Anthropogenic changes to freshwater and nearshore coastal biogeochemical cycles

河流是淡水循环的重要连接点，淡水循环通常被认为是大陆的“动脉”。它们每年为人类和生态系统提供价值超过4万亿美元的基本服务，包括饮用水、运输渠道、食品安全、废物同化和水净化。河流系统也蕴藏着超过10%的已知生物多样性，尽管只占地球表面的不到1%。磷(P)、氮(N)和碳(C)等基本营养元素沿着河流系统从源头输送和转化到海洋，形成湖泊、河流、湿地、水库和泛滥平原淡水食物网的基础，并最终形成河口和沿海环境中海洋食物网的基础。不断增长的人口和资源密集型的生活方式正在推动对清洁水的需求增加，同时淡水生态系统的退化正在加速。营养物质负荷的增加、城市化、土地利用的变化、河流的渠化和筑坝，极大地改变了营养物质的通量。这些变化的后果在世界各地都可以看到，表现为有毒的藻类大量繁殖、鱼类死亡和饮用水供应受到威胁。仅在英格兰和威尔士，有害的藻类水华每年造成的经济影响估计在75-1.143亿GB之间。同时，气候变化的影响威胁着国际上的安全供水。虽然许多研究集中在流域水平的人类对河流系统的影响，如农业径流或污水处理厂增加的营养负荷，但很少有研究集中于确定气候驱动对营养循环的影响的性质和程度。虽然有广泛的证据表明，气候变化将在很大程度上改变水文流量和陆地生物地球化学循环，但大多数致力于研究气候变化对营养循环的影响和随后的水质变化的研究都是以当地为基础和/或仅仅侧重于单一的影响，如降水增加。只关注单一过程的研究的陷阱是，调节或加剧营养负荷大小的反馈周期被忽视了。这些反馈因整个淡水连续体的额外气候变化影响而进一步加剧。因此，迫切需要大陆或全球规模的模式来捕捉营养循环的再分布，特别是那些含有温室气体和大气成分的模式。对全营养循环的大规模分析能够解开气候驱动的从源头到海洋的营养负荷变化，并能够预测整个河流网络和沿海地区对生态系统健康的影响。这项研究项目将结合河流集水区空间显式计算机模拟的进展，新的全球尺度水文数据集(优点-水力和等级)，以及人工智能技术，以量化气候变化和直接人类变化(土地利用，筑坝)对全球淡水营养循环的相互作用的多种压力因素的影响。由此产生的高分辨率、全球营养模型提供了限制从局部到全球范围内相关的比例定律的前景。然后，流域管理者可以利用这种知识的阶段性变化来解决/扭转与历史性的河流集水区修改有关的问题。如果不了解整个LOAC的这些相互影响，昂贵的集水区管理干预措施对水生生态系统健康、水质和可获得性的当地后果的误判的可能性仍然高得令人无法接受。

Rivers are the great connectors of the freshwater cycle, often considered the continents' "arteries." They provide essential services to humans and ecosystems valued at over $4 trillion USD annually, including drinking water, transportation channels, food security, waste assimilation, and water purification. River systems also harbour more than 10% of known biodiversity, despite accounting for less than 1% of the Earth's surface. Essential nutrient elements such as phosphorus (P), nitrogen (N), and carbon (C) are transported and transformed along river systems from source to sea, forming the basis for freshwater food webs in lakes, rivers, wetlands, reservoirs, and floodplains, and ultimately for marine food webs in estuarine and coastal environments. Rising human populations and resource-intensive lifestyles are driving increased demand for clean water at the same time as freshwater ecosystem degradation is accelerating. Enhanced nutrient loading, urbanization, land use change, and river channelization and damming have massively altered the fluxes of nutrients. The consequences of these changes can be seen worldwide, in the form of toxic algal blooms, fish kills, and in jeopardized drinking water supplies. In England and Wales alone, the annual economic impact of harmful algal blooms has been estimated to be between £75 - 114.3 million. Concurrently, the effects of climate change threaten secure water supplies internationally.While many studies have focused on watershed-level human impacts to river systems like enhanced nutrient loading from agricultural runoff or wastewater treatment plants, very little research has been focused on determining the nature and extent of climate-driven impacts on nutrient cycles. While there is widespread evidence that climate change will massively alter hydrological flows and terrestrial biogeochemical cycles, most studies dedicated to investigate climate change effects on nutrient cycles and subsequent water quality changes are locally based and/or just focus on a single impact such as increased precipitation. The pitfall of studies that focus only on single processes is that feedback cycles that either modulate or exacerbate the magnitude of nutrient loads are neglected. These feedbacks are further compounded by additional climate change effects along the entire freshwater continuum. There is thus a strong need for continental or global-scale models that capture the redistribution of nutrient cycles, particularly those with greenhouse gas and atmospheric components. Large-scale analysis of full nutrient cycles enables the untangling of climate-driven changes to nutrient loads from source to sea, and allows prediction of consequences to ecosystem health along the entire river network and in receiving coastal zones.This research project will couple advances in spatially-explicit computer simulation of river catchments, new global-scale hydrological datasets (MERIT-Hydro and GRADES), and AI techniques, to quantify the effects of interacting multiple stressors of climate change and direct human alterations (land use, damming) on global freshwater nutrient cycles. The resulting high-resolution, global nutrient models offer the prospect of constraining scaling laws that are relevant from the local to global scale. Such a step-change in knowledge could then be utilised by watershed managers to address/reverse problems associated with historic river catchment modifications. Without an understanding of these interacting effects along the entire LOAC, the potential for miscalculating local consequences of costly catchment management interventions to aquatic ecosystem health, and water quality and availability, will remain unacceptably high.