Multi-Sensor Airborne Remote Sensing for Calibrating Hydrodynamic and Sediment Transport Models in Coastal Louisiana Wetlands (Atchafalaya–Terrebonne)

IF 6.3 1区 地球科学 Q2 ENVIRONMENTAL SCIENCES
Ali Reza Payandeh, Marc Simard, Cathleen E. Jones, Alexandra Christensen, Daniel Jensen, Michael Denbina, Talib Oliver-Cabrera
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Abstract

This study integrates high resolution remote sensing data from NASA's Delta-X mission with a process based hydrodynamic and sediment transport model to improve predictions of water levels and suspended sediment dynamics in the Mississippi River Delta, in coastal Louisiana, USA, focusing on Atchafalaya and Terrebonne basins. A two dimensional Delft3D Flexible Mesh model was implemented using spatially variable bottom friction maps derived from optical imagery (AVIRIS-NG and Sentinel-2) to represent vegetation heterogeneity. Hydrodynamic calibration leveraged airborne interferometric radar measurements (Airborne Surface Water and Ocean Topography (AirSWOT) and Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR)) of water surface elevations and water level changes, while validation used in situ tide gauge records from spring and fall 2021. Model comparison with AirSWOT measurements in channels showed that spatially explicit roughness parameterizations substantially improved performance. Results were notably better for the spring acquisitions (root mean square error = 0.09 m; R2 = 0.82), likely due to higher wind speeds and steeper water surface slopes that increased surface roughness and improved radar retrieval performance. UAVSAR provided additional spatial constraints on transient water level changes across wetlands at ∼30-min intervals, further informing roughness calibration. Model deviation from UAVSAR were typically within ±$\pm $4 cm, although performance degraded in forested and densely vegetated areas due to reduced radar coherence. Validation with in situ tide gauges confirmed model performance for tidal and subtidal variability. Sediment transport calibration using AVIRIS-NG total suspended solids allowed refinement of settling velocity and critical shear stress. Overall, the integration of remote sensing data into model calibration and parameterization led to measurable improvements in hydrodynamic and sediment predictions.
路易斯安那滨海湿地水动力与输沙模式的多传感器机载遥感定标
本研究将NASA Delta- x任务的高分辨率遥感数据与基于过程的水动力和泥沙输送模型相结合,以改进对美国路易斯安那州沿海密西西比河三角洲水位和悬浮泥沙动力学的预测,重点是Atchafalaya和Terrebonne盆地。利用基于光学影像(AVIRIS-NG和Sentinel-2)的空间可变底部摩擦图实现二维Delft3D柔性网格模型,以表示植被异质性。水动力校准利用机载干涉雷达测量(机载地表水和海洋地形(AirSWOT)和无人驾驶飞行器合成孔径雷达(UAVSAR))的水面高度和水位变化,同时使用2021年春季和秋季的原位潮汐计记录进行验证。模型与通道中的AirSWOT测量结果的比较表明,空间显式粗糙度参数化大大提高了性能。春季采集的结果明显更好(均方根误差= 0.09 m; R2 = 0.82),这可能是由于更高的风速和更陡峭的水面斜坡增加了表面粗糙度,提高了雷达检索性能。UAVSAR为间隔约30分钟的湿地瞬态水位变化提供了额外的空间约束,进一步为粗糙度校准提供了信息。尽管由于雷达相干性降低,在森林和茂密植被地区的性能会下降,但模型与UAVSAR的偏差通常在±$\pm $4 cm以内。现场验潮仪的验证证实了模型对潮汐和潮下变化的性能。使用AVIRIS-NG总悬浮固体进行泥沙输移校准,可以细化沉降速度和临界剪应力。总体而言,将遥感数据整合到模式校准和参数化中导致了水动力和沉积物预测的可测量改进。
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来源期刊
Water Resources Research
Water Resources Research 环境科学-湖沼学
CiteScore
8.80
自引率
13.00%
发文量
599
审稿时长
3.5 months
期刊介绍: Water Resources Research (WRR) is an interdisciplinary journal that focuses on hydrology and water resources. It publishes original research in the natural and social sciences of water. It emphasizes the role of water in the Earth system, including physical, chemical, biological, and ecological processes in water resources research and management, including social, policy, and public health implications. It encompasses observational, experimental, theoretical, analytical, numerical, and data-driven approaches that advance the science of water and its management. Submissions are evaluated for their novelty, accuracy, significance, and broader implications of the findings.
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