Monitoring water quality in Lake Atitlan, Guatemala using Earth Observations

Abstract:

Frequent and spatially continuous water quality monitoring is either unattainable or challenging for developing nations if only standard methods are used. Such standard methods rely on in situ water sampling, which is expensive, time-consuming and point specific. Through the Regional Visualization and Monitoring System (SERVIR), Lake Atitlan’s water quality was first monitored in 2009 using Earth observation satellites. Lake Atitlan is a source of drinking water for the towns located nearby and a major touristic attraction for the country. Several multispectral sensors were used to monitor the largest algal bloom known to date for the lake, which covered 40% of the lake’s 137 square kilometer surface. Red and Near-Infrared bands were used to isolate superficial algae from clean water. Local authorities, media, universities and local communities, broadly used the information provided by SERVIR for this event. It allowed estimating the real extent of the algal bloom and prompted immediate response for the government to address the event. However, algal blooms have been very rare in this lake. The lake is considered oligotrophic given its relatively high transparency levels that can reach 15 m in the dry season. To continue the support provided by SERVIR in the algal bloom event, an algorithm to monitor chlorophyll a (Chl a) concentration under normal conditions was developed with the support of local institutions. Hyperspectral data from Hyperion on board EO-1 and in situ water quality observations were used to develop a semi-empirical algorithm for the lake. A blue to green band ratio successfully modeled Chl a concentration in Lake Atitlan with a relative error of 33%. This presentation will explain the process involved from providing an emergency response to developing a tailored tool for monitoring water quality in Lake Atitlan, Guatemala.