Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari (Italy), via Orabona 4, 70125 Bari, Italy.
CoNISMa, National Interuniversity Consortium of Marine Sciences, Piazzale Flaminio 9, 00196 Roma, Italy.
Sensors (Basel). 2019 Mar 30;19(7):1552. doi: 10.3390/s19071552.
The present work aims at illustrating how the joint use of monitoring data and numerical models can be beneficial in understanding coastal processes. In the first part, we show and discuss an annual dataset provided by a monitoring system installed in a vulnerable coastal basin located in Southern Italy, subjected to human and industrial pressures. The collected data have been processed and analysed to detect the temporal evolution of the most representative parameters of the inspected site and have been compared with recordings from previous years to investigate recursive trends. In the second part, to demonstrate to what extent such type of monitoring actions is necessary and useful, the same data have been used to calibrate and run a 3D hydrodynamic model. After this, a reliable circulation pattern in the basin has been reproduced. Successively, an oil pollution transport model has been added to the hydrodynamic model, with the aim to present the response of the basin to some hypothetical cases of oil spills, caused by a ship failure. It is evident that the profitable prediction of the hydrodynamic processes and the transport and dispersion of contaminants strictly depends on the quality and reliability of the input data as well as on the calibration made.
本工作旨在说明监测数据和数值模型的联合使用如何有助于理解海岸过程。在第一部分中，我们展示和讨论了一个由安装在意大利南部一个脆弱的沿海盆地的监测系统提供的年度数据集，该盆地受到人类和工业压力的影响。所收集的数据经过处理和分析，以检测检查点最具代表性的参数的时间演变，并与前几年的记录进行比较，以研究递归趋势。在第二部分，为了说明此类监测行动的必要性和有用性，相同的数据被用于校准和运行一个 3D 水动力模型。之后，盆地内可靠的环流模式得到了重现。随后，将一个溢油传输模型添加到水动力模型中，目的是展示盆地对一些假设的溢油事件的响应，这些事件是由船舶故障引起的。显然，水动力过程以及污染物的传输和扩散的有利预测严格取决于输入数据的质量和可靠性以及所做的校准。
