Towards digitalization of water supply systems for sustainable smart city development—Water 4.0
Urban water supply systems are complex and dynamic in nature, and as a result, can be
considered complex to manage owing to enhanced urbanization levels, climate change …
considered complex to manage owing to enhanced urbanization levels, climate change …
Industry 4.0 as a strategy to contribute to the water supply universalization in developing countries
DA Senna, VR Moreira, MCS Amaral… - Journal of …, 2023 - Elsevier
Access to safe water is still a challenge. Millions of people worldwide, mainly in rural and
remote regions, still do not have access to safe drinking water. Point-of-use and …
remote regions, still do not have access to safe drinking water. Point-of-use and …
A comparison of ensemble and deep learning algorithms to model groundwater levels in a data-scarce aquifer of Southern Africa
Machine learning and deep learning have demonstrated usefulness in modelling various
groundwater phenomena. However, these techniques require large amounts of data to …
groundwater phenomena. However, these techniques require large amounts of data to …
An autoregressive machine learning approach to forecast high-resolution groundwater-level anomalies in the Ramotswa/North West/Gauteng dolomite aquifers of …
A novel approach using machine learning algorithms is used to predict high-resolution
groundwater-level changes, both current and in the future. The Southern African …
groundwater-level changes, both current and in the future. The Southern African …
Sand dams for sustainable water management: Challenges and future opportunities
Sand dams are impermeable water harvesting structures built to collect and store water
within the volume of sediments transported by ephemeral rivers. The artificial sandy aquifer …
within the volume of sediments transported by ephemeral rivers. The artificial sandy aquifer …
Forecasting multiple groundwater time series with local and Global Deep Learning Networks
Time series data from environmental monitoring stations are often analysed with machine
learning methods on an individual basis, however recent advances in the machine learning …
learning methods on an individual basis, however recent advances in the machine learning …
Where should hydrology go? An early-career perspective on the next IAHS Scientific Decade: 2023–2032
TC van Hateren, HJ Jongen… - Hydrological …, 2023 - Taylor & Francis
This paper shares an early-career perspective on potential themes for the upcoming
International Association of Hydrological Sciences (IAHS) Scientific Decade (SD). This …
International Association of Hydrological Sciences (IAHS) Scientific Decade (SD). This …
[HTML][HTML] Downscaling and validating GLDAS groundwater storage anomalies by integrating precipitation for recharge and actual evapotranspiration for discharge
C Viviers, M van der Laan, Z Gaffoor… - Journal of Hydrology …, 2024 - Elsevier
Abstract Study region The Steenkoppies Catchment is located approximately 75 km
southwest from Pretoria, South Africa (RSA). Study focus This study tested a framework for …
southwest from Pretoria, South Africa (RSA). Study focus This study tested a framework for …
A transformative framework reshaping sustainable drought risk management through advanced early warning systems
TE Masupha, ME Moeletsi, M Tsubo - Iscience, 2024 - cell.com
In light of the increasing vulnerability to drought occurrences and the heightened impact of
drought-related disasters on numerous communities, it is imperative for drought-sensitive …
drought-related disasters on numerous communities, it is imperative for drought-sensitive …
The Potential of Big Data and Machine Learning for Ground Water Quality Assessment and Prediction
Water, a priceless gift from nature, acts as Earth's matrix, medium, and life-sustaining
substance. While the planet is predominantly covered by water, only 3% is available as …
substance. While the planet is predominantly covered by water, only 3% is available as …