An evaluation of time series forecasting models on water consumption data: A case study of Greece
This work tackles water resource management for urban and industrial planners in Greece, but it is incremental as it applies existing methods to new data.
The paper evaluated several well-known forecasting algorithms on real-world water consumption time series data from Greece to address the imbalance between water supply and demand, finding key insights about each algorithm's performance.
In recent years, the increased urbanization and industrialization has led to a rising water demand and resources, thus increasing the gap between demand and supply. Proper water distribution and forecasting of water consumption are key factors in mitigating the imbalance of supply and demand by improving operations, planning and management of water resources. To this end, in this paper, several well-known forecasting algorithms are evaluated over time series, water consumption data from Greece, a country with diverse socio-economic and urbanization issues. The forecasting algorithms are evaluated on a real-world dataset provided by the Water Supply and Sewerage Company of Greece revealing key insights about each algorithm and its use.