Remote sensing of the river Rhine plume

The data content of remote sensing (RS) images of sea surface temperature (SST) and normalized water-leaving radiance (nLw), for the year 1998, with respect to the River Rhine plume, is investigated. Questions that this study tries to answer are: is it possible to identify the plume from the available RS images, and under which conditions is this possible? How much information on the plumes behaviour can be derived from these images? Does or can this information contribute to our general knowledge of the plume? The images provide a spatial resolution of I km2 and a temporal resolution of I or 2 images per day per sensor for nLw and SST, respectively (in the case of a cloudless atmosphere). In the presence of clouds, no signal is detected for the area of surface water underneath the clouds. Two hypotheses are set up to explain how the RS images can be used to trace the plume. In the hypotheses links are established between salinity gradients that delimit the plume and SST and nLw respectively. The results are based on these hypotheses. From the available images, 9 SST images in spring provide detailed information on the stratified plume and allow for derivation of indirect information on sub-surface processes. In winter the temperature gradients as visible on SST imagery seem to indicate the broad plume patterns. From the nLw images it was not possible to identify the boundaries of the plume. However it is expected that the nLw images are an excellent source for monitoring suspended particulate matter (SPM) in the North Sea. The general conclusion of this study is that the RS data used in this project provide a valuable source of information, with respect to the Dutch coastal zone, in addition to the currently available measurement techniques and computer models. The SST imagery turns out to be particularly useful for tracing stratification, whereas nLw imagery seems to be an excellent source for monitoring SPM in the North Sea. For detailed monitoring of the DCZ and the plume, increased spatial and temporal resolutions are required.

本研究针对1998年莱茵河羽状流区域的海表温度（SST）与归一化离水辐亮度（nLw）遥感（RS）影像数据展开探究。本研究旨在解答如下问题：能否借助现有遥感影像识别该羽状流？其可被识别的前提条件是什么？从这类影像中可获取多少有关羽状流运动特征的信息？此类信息能否助力我们深化对该羽状流的整体认知？该类影像的空间分辨率为1平方千米；针对nLw与SST数据，各对应传感器在无云大气条件下每日可分别获取1幅与2幅影像，若存在云层，则云层下方的地表水区域无有效信号。本研究提出两项假设，以阐释利用遥感影像追踪该羽状流的可行路径：两项假设分别将界定羽状流的盐度梯度与SST、nLw建立关联，本研究的全部结果均基于该两项假设推导得出。在所获取的影像中，春季的9幅SST影像详细呈现了层化羽状流的分布特征，可间接反演次表层过程的相关信息；冬季SST影像中呈现的温度梯度，则可用于勾勒该羽状流的大范围分布格局。通过nLw影像无法识别该羽状流的边界，但nLw影像可作为北海海域悬浮颗粒物（SPM）监测的优质数据源。本研究的总体结论为：相较于当前已有的测量技术与数值模型，本项目所用的遥感数据可为荷兰沿海区域（Dutch Coastal Zone, DCZ）提供极具价值的信息支撑。其中，SST影像在追踪羽状流层化特征方面表现尤为优异，而nLw影像则是北海海域SPM监测的理想数据源。若要实现对荷兰沿海区域与该羽状流的精细化监测，仍需进一步提升影像的空间与时间分辨率。