High-frequency water quality monitoring systems provide valuable measurements for
predicting the trend of water quality, warning of abnormal activities or operating hydrological …

Recent developments in smart mining technology have enabled the production, collection,
and sharing of a large amount of data in real time. Therefore, research employing machine …

It is challenging to develop an extensive water mains renewal program or risk management
action plan if there is incomplete, partial or missing water network data. For small and …

Digital agriculture increasingly relies on the availability and accuracy of measurement data
collected from various sensors. Of this data, water quality attracts great attention due to its …

In the current era of “information everywhere”, extracting knowledge from a great amount of
data is increasingly acknowledged as a promising channel for providing relevant insights to …

Accurately assessing and managing risks associated with inorganic pollutants in
groundwater is imperative. Historic water quality databases are often sparse due to rationale …

Indicators of ecological condition status of water bodies associated with field measurements
are often subject to data gaps. This obstacle can often lead to abandonment of assessment …

Missing data is a common problem for data clustering quality. Most real-life datasets have
missing data, which in turn has some effect on clustering tasks. This chapter investigates the …

The Schumann resonance is an electromagnetic phenomenon, a product of lightning activity
inside the earth-ionosphere cavity. Five years of Schumann resonance records are analyzed …

Acid rock drainage (ARD) is a major pollution problem globally that has adversely impacted
the environment. Identification and quantification of uncertainties are integral parts of ARD …