Numerical investigation of the inhibiting effects of tides and waves on delta development

三角洲约占地球表面积的0.6%，但包含世界人口的4%(约3亿人)，这一比例超过了世界人口增长(每年1.6%对1.1%；Edmonds等人，2017，EGU，Geo)。Reas.Abs，19)。然而，这些地区特别容易受到海平面上升(SLR)、地面下沉(通常是通过取水)以及气候和其他极端事件(通常是龙卷风，但也有海啸)的影响，这些影响既可以直接影响人类人口(洪水)，也可以间接影响人类人口(例如，沉积物侵蚀，因此三角洲退缩)(Renaud等，2013，Curr。作业环境5(6))。相反，三角洲的定义是来自河口的自然泥沙堆积区域，通过建立潮间带植被来稳定河口。个别三角洲的脆弱程度取决于这些过程的平衡，包括大坝上游的泥沙蓄水。位于泰国湾上游的湄南河三角洲就是一个很好的例子。最近的研究利用长期的历史数据，确定该三角洲的后退主要是由于下沉，红树林的损失、沉积物输入的枯竭和单反是加剧因素(Bidorn，2016，佛罗里达州立大学博士论文)。该项目的目标是(1)建立三角洲撤退/形成的数学模型，其中SLR和地面沉降是规定的背景强迫，并通过Chao Phraya数据集进行验证；(2)利用SLR和地面沉降的不同情景进行敏感性研究，以探索上游泥沙输入(自然洪水或大坝疏浚)和红树林补种可以缓解这些影响；(3)利用本研究中观察到的依赖性和行为，推断可能被视为(热带)三角洲地貌动力学的一般行为，因此这对于评估这些地区的长期可持续性将是有价值的。在第一年，学生将进行泥沙输送过程的文献搜索(3个月)，然后(大约4个月)学习和运行现有的代码(Dodd等人，2008，Coast Eng，55)，包括验证测试。此后，现有模型将通过包括植被(最初通过改变底床摩擦系数，尽管将考虑其他方法)、通过包括河流沉积物输入(基于Dodd等人的工作，2008)以及通过将沉积物描述扩展到粘性沉积物(通过改变动员和沉降的阈值)来扩展(通过改变动员和沉降的阈值(Pritchard和Hogg，2003，J.GePhys)。结果，108)。然后，学生将在项目进行15个月后，构建用于模型中的湄南河三角洲的离散化表示。这将有助于对曼谷朱拉隆功大学进行为期8周的访问，以熟悉现场(Sriariyawat博士将陪同学生实地访问三角洲，进行最新调查，并采集沉积物岩心)，以及熟悉现有的验证数据集(2个月)。此后将进行验证测试(3个月)。然后，将参照上述当地数据和全球预报，确定SLR/下沉的可能情景。在这些背景条件的支持下，将通过多次模型运行来探索对沉积物输入和红树林范围的敏感性，并填充变量空间以记录相关性，特别是推断非线性反馈。在此期间，在掌握三角洲知识的基础上，学生还将评估其他热带三角洲(如黄色、长江、尼罗河、伊洛瓦底江、湄公河)，以了解Chao Phraya测试案例的一般性程度。这将导致一般性的结论，学生的书面报告，包括期刊出版物

Deltas cover about 0.6% of the Earth's surface area, but contain 4% of the world's population (about 300,000,000 people), a proportion that is outpacing world population growth (1.6 vs 1.1% per annum; Edmonds et al, 2017, EGU, Geo. Res. Abs., 19). Yet these regions are peculiarly vulnerable to sea level rise (SLR), land subsidence (often through water extraction), and the effects of climate and other extremes (typically cyclones, but also tsunamis), which can both impact on human populations directly (flooding), or indirectly (e.g. erosion of sediments and therefore deltaic retreat) (Renaud et al, 2013, Curr. Op. Env. Sust., 5(6)). Conversely, deltas are, by definition, areas of natural sediment accumulation, from river estuaries, which are stabilised by the establishment of inter-tidal vegetation. How vulnerable individual deltas are depends on the balance of these processes, including any upstream impoundment of sediment in dams. A case in point is the Chao Phraya delta, located in the upper Gulf of Thailand. Recent work, using long-term historical data, identifies retreat of this delta as being due primarily to subsidence, with loss of mangroves, sediment input depletion, and SLR as being exacerbating factors (Bidorn, 2016, PhD Thesis, Florida State University). The objective of this project is (1) to build a mathematical model of delta retreat / formation, in which SLR and land subsidence are prescribed background forcings and validate it via the Chao Phraya data-set; (2) conduct a sensitivity study using different scenarios of SLR and subsidence to explore how much upstream sediment input (natural flooding or dredging from dams) and mangrove replanting can mitigate these effects; (3) using the dependencies and behaviours observed in this study, infer behaviours that may be seen as generic to (tropical) delta morphodynamics, and which will therefore be valuable to assess long-term sustainability of these regions. In year 1 the student will conduct a literature search on sediment transport processes (3 months), followed by (about 4 months) learning and running the existing code (Dodd et al, 2008, Coast Eng, 55), including verification tests. The existing model will thereafter be augmented by the inclusion of vegetation (initially by altering the bed friction factor, although other approaches will be considered), by including fluvial sediment input (building on the work of Dodd et al, 2008), and by extending the sediment description to cohesive sediments (by altering thresholds of mobilisation and settling (Pritchard and Hogg, 2003, J. Geophys. Res., 108). The student will then-15 months into the project--build a discretized representation of the Chao Phraya delta for use in the model. This will be aided by an 8-week visit to Chulalongkorn University in Bangkok so as to become familiar with the site (Dr Sriariyawat will accompany the student on site visits to the delta, to conduct update surveys, and to take sediment cores), as well as to become familiar with available validation data sets (2 months). Thereafter validation tests will be run (3 months). Likely scenarios of SLR / subsidence will then be identified, with reference to the aforementioned local data, as well as global forecasts. Underpinned by these background conditions, the sensitivities to sediment input and mangrove extent will be explored via multiple model runs, and the variable space populated so as to note dependencies and, in particular, infer nonlinear feedbacks. During this time, and with the knowledge of deltas already acquired, the student will also assess other tropical deltas (e.g. Yellow, Yangtze, Nile, Irawaddy, Mekong), so as to build a picture of the degree to which the Chao Phraya test case is generic. This will lead into general conclusions, the student write-up, including journal publications