A learning-based approach towards the data-driven predictive control of combined wastewater networks - An experimental study

Smart control in water systems aims to reduce the cost of infrastructure expansion by better utilizing the available capacity through real-time control. The recent availability of sensors and advanced data processing is expected to transform the view of water system operators, increasing the need for deploying a new generation of data-driven control solutions. To that end, this paper proposes a data-driven control framework for combined wastewater and stormwater networks. We propose to learn the effect of wet- and dry-weather flows through the variation of water levels by deploying a number of level sensors in the network. To tackle the challenges associated with combining hydraulic and hydrologic modelling, we adopt a Gaussian process-based predictive control tool to capture the dynamic effect of rain and wastewater inflows, while applying domain knowledge to preserve the balance of water volumes. To show the practical feasibility of the approach, we test the control performance on a laboratory setup, inspired by the topology of a real-world wastewater network. We compare our method to a rule-based controller currently used by the water utility operating the proposed network. Overall, the controller learns the wastewater load and the temporal dynamics of the network, and therefore significantly outperforms the baseline controller, especially during high-intensity rain periods. Finally, we discuss the benefits and drawbacks of the approach for practical real-time control implementations.Peer ReviewedPostprint (published version

Is it possible to develop a green management strategy applied to water systems in isolated cities? An optimized case study in the Bahamas

[EN] The inclusion of new strategies is crucial to achieve the different targets of the sustainable development goals for the guarantee of supply in the different cities and reduction the consumption of non-renewable resources. The development of these strategies implies the improvement of the sustainability indicators and green rating systems of the city. This research proposes a decarbonisation strategy, which includes different optimization procedures based on a self-calibration process according to recorded flow values over time. These stages are integrated into one tool to define the best making decision in the management of the supply system, analysing whether self -consumption of energy is feasible. It was applied on the Bahamas. The application of the strategy enabled the decrease of the annual consumption of energy equal to 32%. The self-consumption could represent 30% of the consumed energy of the pump station. The making decision to define the best operation strategy, establishing a Levelized Cost of Energy around 0.12 euro/kWh when the feasibility of using photovoltaic systems combined with micro hydropower was done. It implies the reduction of 40% of the tCO2 emission, getting a cost of carbon abatement values around 400 euro/tCO2 for different discount rates and scenarios.Fundings Grant PID2020-114781RA-I00 funded by MCIN/AEI/10.13039/501100011033.Mercedes García, ÁV.; Sánchez-Romero, F.; López Jiménez, PA.; Pérez-Sánchez, M. (2022). Is it possible to develop a green management strategy applied to water systems in isolated cities? An optimized case study in the Bahamas. Sustainable Cities and Society. 85:1-15. https://doi.org/10.1016/j.scs.2022.1040931158

Implementation of an IoT Based Radar Sensor Network for Wastewater Management

Critical wastewater events such as sewer main blockages or overflows are often not detected until after the fact. These events can be costly, from both an environmental impact and monetary standpoint. A standalone, portable radar device allowing non-invasive benchmarking of sewer pumping station (SPS) pumps is presented. Further, by configuring and deploying a complete Low Power Wide Area Network (LPWAN), Shoalhaven Water (SW) now has the opportunity to create Internet of Things (IoT)-capable devices that offer freedom from the reliance on mobile network providers, whilst avoiding congestion on the existing Supervisory Control and Data Acquisition (SCADA) telemetry backbone. This network infrastructure allows for devices capable of real-time monitoring to alert of any system failures, providing an effective tool to proactively capture the current state of the sewer network between the much larger SPSs. This paper presents novel solutions to improve the current wastewater network management procedures employed by SW. This paper also offers a complete review of wastewater monitoring networks and is one of the first to offer robust testing of Long Range Wide Area Network (LoRaWAN) network capabilities in Australia. The paper also provides a comprehensive summary of the LoRa protocol and all its functions. It was found that a LPWAN, utilising the LoRaWAN protocol and deployed appropriately within a geographic area, can attain maximum transmission distances of 20 km within an urban environment and up to 35 km line of sight

Application of multi-scale assessment and modelling of landfill leachate migration: implications for risk-based contaminated land assessment, landfill remediation, and groundwater protection

There are a large number of unlined and historical landfill sites across Britain, contaminating groundwater and soil resources as well as posing a threat to human health and local communities. There is an essential requirement for robust methodology when carrying out risk-based site investigations prior to risk assessment and remediation of landfill sites. This research has focused upon the methods used during site investigations for two reasons. Firstly, the site investigation is often conducted using field instruments and methods that do not account for the heterogeneous conditions found at landfill sites. Interpreting geophysical conditions between sampled points is a common practise. Given the complex and heterogeneous conditions at landfill sites, such methodology introduces uncertainty into data sets. Secondly, risk estimation models that simulate groundwater flow and contaminant transport require extensive field information. The data used during model construction will significantly impact contaminant transport simulations. Modelling guidelines also need further development, ensuring that sound modelling practises are adhered toduring model construction.To address these concerns, four research objectives were identified: (1) Two new multi-spatial field assessment methods (remote sensing and ground penetrating radar), previously applied in other fields of science, were tested on landfill sites; (2) Kriging was used as a tool to improve landfill-sampling strategies; (3 & 4) Groundwater flow and contaminant transport models were used to evaluate whether different scales of field data and modelling practises influenced modelling assumptions and simulation.The utility of novel field- and airborne-based remote sensing methodologies in identifying the location and intensity of vegetation stress caused by leachate migration and inferring pathways of near surface contamination using patterns of vegetation stress was proven. The results from the kriging investigations demonstrated that additional insight into field conditions could be resolved to identify locations of additional sampling points, and provide information about variability in hydrological data sets. The Ground Penetrating Radar investigations provided three types of valuable near-surface information that could assist in determining landfill risks: buried landfill features, leachate plume locations and local hydrogeological conditions. These combined methods provided detailed synoptic geophysical and contaminant information that would otherwise be difficult to determine. Their application and acceptance as site assessment methods (used under certain landfill conditions) could increase the accuracy of assessing risks posed by landfill leachate.These applications also demonstrated that the most effective site assessments are achieved when integrated with other field data such as soil, vegetation, and groundwater quantity measurements, contaminant concentrations and aerial photographs, providing comprehensive information needed for risk estimation modelling.The modelling analyses found that close attention must be paid to site-specific and model-specific characteristics, as well as modelling practises. These factors influenced model results. By using additional data to infer model parameters, it was evident that the amount of data available will influence the way in which risk will be perceived. The more data that was available during model construction, the higher the risk prediction. This was the case for some seventy- percent of the models.By improving the accuracy of site investigation methodology, and by adhering to robust assessment and modelling practices, a higher level of quality assurance can be achieved in the risk assessment and remediation of contaminating landfill sites. If the improvements and recommendations presented in this research are considered, uncertainties inherent in the site investigation could be reduced, therefore enhancing the accuracy of landfill risk assessment and remedial decisions

NASA Tech Briefs Index, 1976

Abstracts of new technology derived from the research and development activities of the National Aeronautics and Space Administration are presented. Emphasis is placed on information considered likely to be transferrable across industrial, regional, or disciplinary lines. Subject matter covered includes: electronic components and circuits; electronic systems; physical sciences; materials; life sciences; mechanics; machinery; fabrication technology; and mathematics and information sciences

Ground water and surface water under stress

Presented at Ground water and surface water under stress: competition, interaction, solutions: a USCID water management conference on October 25-28, 2006 in Boise, Idaho.Includes bibliographical references.The A&B Irrigation District in south-central Idaho supplies water to irrigate over 76,000 acres. The district's 14,660-acre Unit A is supplied with water from the Snake River. Unit B is comprised of 62,140 acres of land irrigated by pumping groundwater from the Eastern Snake Plain Aquifer (ESPA) using 177 deep wells. Pumping depths range from 200 to 350 feet. Water from Unit B wells is distributed to irrigated lands via a system of short, unlined lateral canals averaging about 3/4-mile in length with capacities of 2 to 12 cfs. During the period from 1975 to 2005, the average level of the ESPA under the A&B Irrigation District dropped 25 ft and as much as 40 ft in some locations. This has forced the district to deepen some existing wells and drill several new wells. To help mitigate the declining aquifer, the district and its farmers have implemented a variety of irrigation system and management improvements. Improvements have involved a concerted effort by the district, landowners, and local and federal resource agencies. The district has installed variable speed drives on some supply wells, installed a SCADA system to remotely monitor and control well pumps, and piped portions of the open distribution laterals. This has permitted farmers to connect farm pressure pumps directly to supply well outlets. Farmers have helped by converting many of their surface irrigation application systems to sprinklers, moving farm deliveries to central locations to reduce conveyance losses, and installing systems to reclaim irrigation spills and return flows

Ground water and surface water under stress

Presented at Ground water and surface water under stress: competition, interaction, solutions: a USCID water management conference on October 25-28, 2006 in Boise, Idaho.Includes bibliographical references.The METRIC evapotranspiration (ET) estimation model was applied using MODIS (Moderate Resolution Imaging Spectroradiometer) satellite images in New Mexico to evaluate the applicability of MODIS images to ET estimation and water resources management. With the coarse resolution of MODIS (approximately 1km thermal resolution), MODIS was not found to be suitable for field-scale applications. In project and regional scale applications, MODIS has potential to contribute to ET estimation and water resources management. MODIS based ET maps for New Mexico were compared with Landsat based results for 12 dates. Average ET calculations using MODIS and Landsat applications were similar, indicating that MODIS images can be useful as an ET estimation tool in project and regional scale applications