基于光谱分析的原位海洋水质参数监测数据

应用于海水水质监测领域，在舟山长峙岛揽月湖附近海域，基于光谱分析原位水质参数传感器，每间隔1分钟实时采集一次海水样品的光谱数据，每次采集256个光谱值，通过算法模型准确获取海水浊度、化学需氧量两项重要的水质参数。能够提升海洋环境监测效率，降低监测成本，不仅有助于科学管理海洋水质状况，为海洋生态建设和海洋资源开发提供重要保障，还可以及时发现和处理污染源，确保海洋资源的有效利用和可持续开发，并进一步为政府和相关机构制定科学的海洋管理政策提供依据‌。在舟山长峙岛揽月湖附近海域进行样本采集，根据采集到的海水水体256个光谱值计算浊度、化学需氧量的算法分为以下三步：第一步，利用比尔—朗伯定律将256个光谱值转换为吸光度数据；第二步，进行归一计算，并分析浊度、化学需氧量量参数对多参数混合样本在不同波长处的贡献值，划分浊度、化学需氧量的特征波段；第三步，基于偏最小二乘算法得到的计算模型，基于仪器采集到的多个光谱值计算得到浊度、化学需氧量两项水质参数值。

This dataset is applied in the field of seawater quality monitoring. It was collected in the sea area near Lanyue Lake, Changzhi Island, Zhoushan. Using in-situ water quality parameter sensors based on spectral analysis, spectral data of seawater samples were collected in real time at 1-minute intervals, with 256 spectral values acquired per collection. Through algorithmic models, two critical water quality parameters, seawater turbidity and chemical oxygen demand (COD), can be accurately obtained.

This dataset can improve the efficiency of marine environmental monitoring and reduce monitoring costs. It not only facilitates the scientific management of marine water quality, providing important support for marine ecological construction and marine resource development, but also enables timely detection and handling of pollution sources, ensuring the effective utilization and sustainable development of marine resources. Furthermore, it provides a basis for governments and relevant institutions to formulate scientific marine management policies.

The algorithm for calculating turbidity and chemical oxygen demand from the 256 spectral values of collected seawater samples, which was developed in the sea area near Lanyue Lake, Changzhi Island, Zhoushan, consists of three steps:
1. Convert the 256 spectral values into absorbance data using the Beer-Lambert Law;
2. Perform normalization calculations, analyze the contribution values of turbidity and chemical oxygen demand parameters to multi-parameter mixed samples at different wavelengths, and identify the characteristic bands of turbidity and chemical oxygen demand;
3. Establish a calculation model based on the partial least squares (PLS) algorithm, and calculate the values of the two water quality parameters, turbidity and chemical oxygen demand, from multiple spectral values collected by the instrument.