Innovative Analysis of Large River Topography and Dynamics (Ref:4243)

河流系统的可持续性对于全球河流泛滥平原和三角洲的5亿河岸居民来说至关重要，这需要了解和理解陆面随时间的变化，以应对人为和气候压力。与这种理解密切相关的是能够量化表面形态和变化的高质量地形数据，这对于理解低地沉积系统对这些强迫的响应是必不可少的。然而，全球地形数据的质量和分辨率不足，给管理大型冲积河流中的低地河流-泛滥平原复合体带来了重大挑战。这种地形数据的匮乏尤其适用于低坡度热带河流：1)缺乏准确的地形测量数据，2)洪泛平原有大量植被，无法通过卫星观测地表，3)以前的全球数据(如SRTM)在地貌应用的准确性和分辨率方面受到技术限制。TanDEM-X高分辨率合成孔径雷达任务(directory.eoportal.org/web/eoportal/satellite-missions/t/tandem-x)提供了一种前进的方法，特别是当与遥感数据和机器学习统计方法结合使用时。我们在亚马逊和东南亚的高分辨率(~12米)TDX产品的探索性工作已经确定了使用层析分析、遥感和机器学习的组合来移除树木的方法-使用GPU产生河流系统的裸地DEM，这些DEM可以在我们拥有实地调查和激光雷达数据的地点得到验证，这些数据来自以前和当前的国家科学研究中心、国家科学基金会和美国国家航空航天局资助的项目。这位博士生将专注于这些新数据和技术的改进和应用，以量化项目河流-湄公河下游和亚马逊大部分地区的地形和演变，这些主要河流系统可用于校准和测试这些方法，与正在进行的NERC资助的研究相协调。在对现有数据进行验证和提炼之后，学生将与指导团队合作，为更多的研究地点确定和研究一系列有趣的科学问题，从而为博士生提供灵活性和智力独立性，以实现他们自己的兴趣并追求新的变革性研究机会。项目目标和方法在利用合适的现场数据改进研究区域的分析方法后，博士研究将专注于量化驱动研究地点水流、泥沙输送和河流演变的泛滥平原地形和坡度，为河流系统的功能提供新的科学见解。为了进一步评估观察到的关系，学生将与指导团队密切合作，设计他们的博士研究提醒。例如，可以使用河流地貌动力学模型(标准模型和埃克塞特研究模型)来测试为研究河流确定的潜在原因机制。测量和预测可以与可用于研究系统和其他地方的广泛的埃克塞特现场数据集进行验证，并有可能进行现场工作。这一博士学位的最终目标将是产生关于大型河流系统功能和复杂演变的一般性发现，这些发现适合发表在著名期刊上，为学生进一步的职业成功做好准备。

Fluvial system sustainability is vital for a half billion riparian residents of global river floodplains and deltas, and it requires knowledge and understanding of the land surface changes through time in response to anthropogenic and climatic forcing. Germane to such understanding are high quality topographic data enabling the quantification of surface morphology and change, which are essential for understanding responses of lowland sedimentary systems to these forcings. However, global topographic data are of insufficient quality and resolution, creating major challenges for managing lowland river-floodplain complexes in large alluvial rivers. This scarcity of topographic data is especially applicable to low-gradient tropical rivers where 1) accurate topographic survey data are scarce, 2) floodplains have significant vegetation precluding satellite observation of surfaces, and 3) previous global data (eg., SRTM) are technically limited in terms of accuracy and resolution for geomorphic applications. The TanDEM-X high-resolution SAR mission (directory.eoportal.org/web/eoportal/satellite-missions/t/tandem-x) offers a way forwards, especially when paired with remote sensing data and machine learning statistical methods.Our exploratory work with the high-resolution (~12m) TDX product in Amazonia and SE Asia has identified means to remove trees using a combination of tomographic analysis, remote sensing, and machine learning using GPUs - producing bare earth DEMs for fluvial systems that can be verified for locations where we have field survey and Lidar data from prior and current NERC, NSF, and NASA-funded projects. The PhD student would focus on the refinement and application of these novel data and techniques towards quantifying the topography and evolution of project rivers - the lower Mekong River and large portions of the Amazon, major river systems that can be used to calibrate and test these approaches in coordination with ongoing NERC-funded research. Following this verification and refinement against available data, the student would work with the supervisorial team to identify and pursue a range of intriguing scientific questions for additional research locations, thus providing the PhD candidate flexibility and intellectual independence to realize their own interests and pursue new opportunities for transformative research. Project Aims and MethodsAfter refining the analytical methods for study areas with suitable field data, the PhD research would focus on quantifying the floodplain topography and gradients that drive flow, sediment transport, and river evolution for research sites, providing novel scientific insight into the functioning of fluvial systems. To further evaluate observed relationships, the student would work closely with the supervisorial team to design the reminder of their PhD research. For example, potential causal mechanisms identified for study rivers could be tested using models for fluvial morphodynamics (both standard and Exeter research models). Measurements and predictions could be verified against extensive Exeter field datasets available for the study systems and elsewhere, with possibilities for fieldwork. The ultimate aim of this PhD will be to produce generic findings about the functioning and complex evolution of large river systems that are suitable for publication in prominent journals, preparing the student for further career success.