Hydrological Monitoring of Rivers and Reservoirs Using Innovative Image Processing and Satellite-based Approaches

The combination of in-situ measuring systems and non-intrusive optical technologies can highly improve the monitoring of water quantity and water quality in rivers and reservoirs. This paper presents two applications about innovative camera-based and satellite-based approaches to estimate flow velocity, water level, discharge, turbidity and chlorophyll concentration. The river site of the first case study presented is equipped with a DischargeKeeper, a camera-based discharge measuring system for a continuous measurement of water level, velocity and discharge in real time, and with a Multi-Parameter System MPS for water quality measurement. The MPS measures water temperature, turbidity, oxygen concentration, oxygen saturation, electric conductivity and total suspended solids TSS. The MPS probe is connected to a data logger with data transmission module to deliver measured data in real time. The DK offers. The DK consists of a video camera, an infrared beamer for illumination, a central unit for data processing, a modem for data transfer and a power supply. In operational use the camera takes video sequences of around 5s in predefined intervals, usually ranging from a few minutes to several hours. To determine the surface flow velocity of the river a processing technique called Surface Structure Image Velocimetry (SSIV) is applied. The transmitted proof images with time stamp are very helpful for the optical verification of the measurement especially during flood events.  Furthermore, the camera used can be installed at almost any position with respect to the flow, regardless of the presence of a bridge, as far as the flow is in the view of the camera with a good resolution.

Optical satellite sensors, which is the second case study of this paper, provide the opportunity to determine water constituents for whole water bodies. It is possible to derive optically active substances, which leads to good assessment of chlorophyll concentration as a proxy for algal blooms, of the water turbidity, coloured dissolved organic matter and suspended sediment. If the concentration of algae is high enough (appr. > 10 µg/l), also the occurrence of cyanobacteria can be detected. For deriving these parameters, atmospheric correction and in-water retrieval are most important processing steps. The products derived from satellite data can be aligned with the in-situ measurements acquired within DIWA which provides a complementary view on a water body. In our case we aim in combining high temporal, but punctual in-situ data with the spatial information derived from satellite data. They both contribute to the warning system for exceptional high algal blooms or occurrence of cyanobacteria. In case of river systems, the detection of a bloom that occurs upstream can already help to prepare for measures further downstream. Besides the added value that satellite data provide, limits come with reduced data availability due to cloud coverage and limits in spatial resolution for very small water bodies or very narrow river systems.

Both case studies presented showed a very good applicability of image processing technologies for measuring various hydrological and water quality parameters.