Water ways and aquatic ecosystems are increasingly under threat from contamination world-wide due to influence from both anthropogenic and naturogenic sources. The ability to monitor and sense levels of key contaminants within environmental waters is a critical step towards reversing this trend and improving water quality. This necessitates the need for reliable methods of monitoring water quality on a global scale with the potential for high spatial and temporal resolution. The research described in this thesis is focused on the development of autonomous analytical devices for monitoring of environmental water quality with the ability to contribute and scale into future sensing networks. The goal of this work has been to develop and validate chemical sensors which are capable of sensing reliably and robustly. By integrating optimised reagent-based detection methods into simple and reliable optical detection systems this goal can be achieved. Through this strategy an adaptable benchtop sensing platform has been developed and optimised which can detect several colorimetric chemical methods using a modular LED and photodiode detector integrated with a fluidic chip. This work was further developed into an autonomous based platform capable of delivering environmental samples as well as calibration standards to the detector for reliable autonomous environmental sensing. This system has been shown to provide a base platform that can be used for the detection of several key analytes remotely and autonomously. The platform’s analytical performance was successfully tested both in the Lab and in field deployments.