According to UN data, water and climate-related events have accounted for half of the human and economic damage caused by disasters over the last fifty years. Figures show that, during this period, weather, climate and water hazards accounted for 45% of recorded deaths (1.3 million people) and 74% of global economic losses. World Meteorological Organization studies have also put droughts, storms and floods at the top of the most devastating catastrophes list.
It is therefore essential to reduce the adverse consequences of these phenomena, especially since their frequency and intensity are increasing due to climate change combined with other factors. These adverse effects include damage to public health, property, the environment, cultural heritage, the economy and infrastructures.
Technology can help in the fight against climate change by pre-empting and forecasting these phenomena. According to the Global Commission on Adaptation, early warning systems offer a 10-fold plus return on investment. As a result, in 2023 and beyond, utilities and river basin water authorities are set to increase their investments in these types of systems. The Global Commission, a non-profit, non-governmental body founded in 2018, estimates that storm and heatwave damage can be mitigated by up to 30% if predicted 24 hours in advance.
In short, early warning systems stand to play a key role in risk management through the forecasting of overflows and floods. Their deployment, together with the implementation of monitoring and management solutions for sanitation systems, will reduce the consequences of these floods through the advanced analysis and integration of existing data.
Sanitary Sewer Overflows
Sanitary Sewer Overflows (SSOs) occur when untreated water is dumped into the environment causing issues such as water eutrophication, the increase of pathogens, and the contamination of groundwater, seas and oceans. They also lead to heavy administrative fines for utilities.
Most SSOs occur during rainfall events, when the sanitation system is unable to decant and treat all the water it collects. In a context where all climate change models are forecasting more extreme and more unpredictable rainfall episodes, it is essential to have an early warning system that takes into account real-time monitoring of system assets to predict these events, and thus pre-empt decision-making and shorten the response time to react to potential issues.
In addition to SSOs during rain events, these overflows also increase in dry weather every year in cities, mainly due to clogging, excess infiltration and/or broken sewers. They increase for dietary reasons (fast food and fatty foods are discharged into sewers), wipes being flushed down the toilet, and aging assets. Therefore, system monitoring to detect sedimentation, infiltration and blockages in sewer systems is the first step to prevent this phenomenon.
Utilities will continue to rely on digital platforms that integrate and analyze the data sent by sewer level and quality sensors, together with information on the state of the WWTP’s sewers, pumping stations and relief points.
One of the main outcomes will be to design risk-based preventive maintenance plans for each asset, rather than scheduled cleaning operations. These plans will deliver the ideal cleaning programs, based on historical and real-time information from integrated data and systems (previous SSOs, most recent preventive and reactive work orders, GIS, etc.), and the application of statistical models based on risk analysis.
Digital platforms will also be an essential tool to assess the risk of overflows based on detecting sensor anomalies (sewers, assets and manholes), as well as to calculate the location and the minimum number of sensors needed to prevent SSOs using AI algorithms.
Early warning systems will increasingly be relied upon to pre-empt urban flooding during rainy periods, thanks to the monitoring of key points in urban drainage and sewer networks, and the integration of information from weather forecasting.
Over the next few years, more extensive deployment of sensors in sewers will provide greater amounts of real-time data, which will undoubtedly enhance the rollout of these systems. In addition, early warning will go hand in hand with flood prevention recommendations, based on the state of the sanitation and urban drainage networks, and on rainfall forecasts. For example, this technology will make it easier to concentrate preventive sewer cleaning work where it is actually needed.
River and rain-related floods
According to the World Bank, floods and droughts have been among the most devastating consequences of the climate crisis over the past two decades, affecting three billion people and causing economic losses averaging more than US$200 billion annually. Climate change, together with economic development, population growth and rapid urbanization of high-risk areas, are exacerbating flood risk around the world. This phenomenon is caused by river overflows, rainfall, snowmelt, flash floods and/or tidal surges above normal levels.
In this context, early flood warning systems are crucial. In Europe alone, it is estimated that this technology has the potential to reduce damage costs by 25%, saving an estimated €30 billion over the next 20 years.
Early warning systems are based on real-time observational data and weather forecasts which, in conjunction with integrated hydrological and hydraulic simulation models, can anticipate potential flooding even in places that have high variations. These systems, which use historical and real-time data, trigger alarms when the thresholds of different variables are exceeded, thus providing hydrological warnings. In short, they reduce the damage caused by this phenomenon through pre-emption and prevention.
Idrica’s Water Technology Trends 2023 report provides a comprehensive list of trends for the industry, including this article on how Pre-emption and prevention can help responding to extreme events.