Understanding Runoff and Erosion Dynamics

水土流失正在导致世界粮食生产用地加速流失，威胁到全球粮食安全。模型是试图了解农业过程、土地利用和气候变化对土壤侵蚀影响的重要组成部分。然而，目前模拟土壤侵蚀的方法，尽管有很长的历史，但在预测能力方面几乎没有全面的改进。所有的模型都受到它们所依赖的实验基础的限制，其中许多关于土壤侵蚀的实验和技术可以追溯到一代人以前。到目前为止，技术上的限制限制了实验工作的稳定状态测量，实际上是一个高度动态的过程。例如，导出土壤侵蚀模型参数的实验通常使用恒定强度的降雨，然后将这些参数应用于随时间变化的自然降雨下的侵蚀模型，尽管我们现在有证据表明，以这种方式导出的参数将对随时间变化的自然降雨做出不正确的预测。摆脱这种僵局的一个方法是使用机械工程领域发展起来的光学诊断技术，它可以研究高度动态的多相流。脉冲激光照明光源和数码相机技术的最新发展使得记录粒子/流相互作用的速率高达每秒20,000帧。利用这些技术，现在有可能在我们对土壤侵蚀过程动力学的理解上迈出一步。本研究将(1)改进现有的高速、高分辨率成像和PIV技术，以同时跟踪代表土壤侵蚀的浅层坡面流中0.063 mm至2.0 mm的沉积物颗粒；（ii）利用这些改进的技术开发高分辨率和高精度的数据集，这些数据集将描述浅层上陆流中分离、运输和沉积过程的不同组成部分的动力学特征；将这些数据集提供给更广泛的土壤侵蚀界，供他们开发和测试自己的模型；（iv）利用获得的数据在现有的土壤侵蚀模型（MAHLERAN）中开发子模型，该模型是我们之前开发的，能够代表侵蚀过程的动态特性，而不是稳态条件；(v)针对非定常条件下的现有数据集测试修订后的MAHLERAN。这项工作将对NERC战略的关键领域作出重要贡献，例如与环境变化共存和分析环境变化对生态系统服务的影响，以及在可持续性、全球贫困和碳封存方面的后果。这项研究还将为环境管理人员提供更有效的工具，以便按照现行立法（如欧盟水框架和硝酸盐指令）的要求实施综合流域管理实践。

Soil erosion by water is leading to an accelerated loss of the world's food-producing lands, threatening global food security. Models are a vital component of attempts to understand the impact of agricultural processes, land-use and climate change on soil erosion. However, current approaches to modelling soil erosion, despite a long heritage, have shown little overall improvement in their predictive capability. All models are constrained by the experimental base upon which they rests, much of which, for soil erosion, dates from experiments and technologies of a generation ago. Thus far, technological limitations have constrained experimental work to steady-state measurements for what is actually a highly dynamic process. For example, experiments to derive the parameters of soil-erosion models typically use constant-intensity rainfall and then apply these parameters to model erosion under temporally varying natural rainfall, although we now have evidence that parameters derived in this way will make incorrect predictions for temporally varying natural rainfall. A way out of this impasse is to use optical diagnostic techniques, developed in the field of mechanical engineering, which enable the study of highly dynamic multiphase flows. Recent developments in pulsed laser-illumination sources and digital camera technology allow the recording of particle/flow interactions at rates up to 20,000 frames per second. Using these techniques it is now possible to make a step change in our understanding of the dynamics of processes of soil erosion. This research will (i) refine existing high-speed, high-resolution imaging and PIV techniques to track sediment particles of 0.063 mm to 2.0 mm simultaneously in shallow overland flows that typify soil erosion; (ii) use these refined techniques to develop datasets of high resolution and high accuracy that will characterize the dynamics of the different components of the detachment, transport and deposition processes in shallow overland flows; (iii) make these datsets available to the wider soil-erosion community for their own model development and testing; (iv) use the data obtained to develop submodels within an existing soil-erosion model (MAHLERAN) which we have previously developed that are capable of representing dynamic properties of erosion processes, rather than steady-state conditions; and (v) test the revised version of MAHLERAN against existing datasets for unsteady conditions. The work will provide an important contribution to key NERC Strategy areas such as Living with Environmental Change and the analysis of the impact of environmental change on ecosystem services, with consequences in terms of sustainability, global poverty and carbon sequestration. The research will also lead to the production of more effective tools for environmental managers to implement practices of integrated river-basin management as required under current legislation such as the EU Water Framework and Nitrates Directives.