Unauthorized Water Research Articles

Socio-hydrological modelling for incorporating human behaviour into storage–yield analysis

ABSTRACTA socio-hydrological model that simulates, couples and co-evolves reservoir operation and human behaviour to assess the impact of unauthorized water abstractions on reservoir performance is developed. The model relates hydrological state, well-being, user compliance and management competence and is applied to two reservoirs. To generalize the modelling, well-being, user compliance and management competence are normalized (0 to 1) and modelled using logistic functions. When compliance is below the set threshold, unauthorized water abstraction occurs; the magnitude depends on water allocation, user compliance and management competence. In the absence of real data, eight hypothetical scenarios are applied. The expected dependence of well-being on the hydrological state and that of well-being, virtues and management competence on user risk perception and user compliance was realized as initially hypothesized. The variation of the effect of human factors on storage and yield was found to be more pronounced during low hydrological states (drought). The modelling is considered applicable for assessing the likely impact of humans on real reservoir performance.

Detection of unauthorized consumption in water supply systems: A case study using logistic regression

This study proposes characterizing unauthorized water consumption and fitting multiple logistic regression models for detecting illegal connections. The research used monthly water consumption data from 42,131 single-family homes in Joinville, southern Brazil. The obtained models achieved accuracies ranging from 83% to 100% for detecting three types of fraud (unauthorized reconnection of a disconnected water service line, bypass, and direct connection). The results showed previous minor violations, tampering with water meters and stands, and non-compliance of meter installation with utility standards are related to illegal connections.

High Fidelity Digital Twin-Based Anomaly Detection and Localization for Smart Water Grid Operation Management

Smart Water Grid (SWG) plays a critical role in sustaining cities economic and social development, but challenges remain in fully realizing the benefits of SWG. While Digital twin (DT) has been discussed in some literature for possible SWG applications, there has been limited, or no technical framework developed to facilitate SWG operation and management. In this paper, a generic framework is developed for constructing SWG high fidelity Digital Twin (DT) by integrating digital thread with various digital models for visualization, data-driven analysis, physics-based simulations, and decision-making support. Both the physics-based models and data-driven models are trained/retrained and calibrated/re-calibrated respectively by using the data collected with the sensors installed throughout a SWG. The information derived from the SWG DT can be diagnostic, predictive, and prescriptive to significantly augment users’ intelligence for improving SWG operation and management. One important application of digital twin augmented intelligence is illustrated to timely detect and localize anomaly events, which may include, but not be limited to, pipe bursts and unauthorized water usages. The solution is tested on the selected areas in Singapore to construct the ever-green DT by calibrating and recalibrating the models for near real-time SWG operation management. The case study was conducted for three supply zones with the total pipeline length of more than 1000 km and 40 weeks of monitoring data, collected by 89 pressure monitoring stations and 8 flow meters at inlets and boundary. More than 3300 data-driven models are trained for optimizing the model performance to achieve accuracy of greater than 80% F1 score for detecting anomaly events, which are subsequently localized within 400 m with 2–3 days lead time.

A stand-alone remote sensing approach based on the use of the optical trapezoid model for detecting the irrigated areas

Under the current water scarcity scenario, the promotion of water saving strategies is essential for improving the sustainability of the irrigated agriculture. In particular, high resolution irrigated area maps are required for better understanding water uses and supporting water management authorities. The main purpose of this study was to provide a stand-alone remote sensing (RS) methodology for mapping irrigated areas. Specifically, an unsupervised classification approach on Normalized Difference Vegetation Index (NDVI) data was coupled with the OPtical TRApezoid Model (OPTRAM) for detecting actual irrigated areas without the use of any reference data. The proposed methodology was firstly applied and validated at the Marchfeld Cropland region (Austria) during the irrigation season 2021, showing a good agreement with an overall accuracy of 70%. Secondly, it was applied at the irrigation district Quota 102,50 (Italy) for the irrigation seasons 2019–2020. The results of the latter were instead compared with the data declared by the Reclamation Consortium, finding an overestimation of irrigated areas of 21%. In conclusion, this study suggests an easy-to-use approach, eventually independent of reference data such as agricultural statistical surveys or records and replicable under different agricultural settings in continental or Mediterranean climates to support stakeholders for regular estimation of irrigated areas in different growing years or detecting eventual unauthorized water uses. However, some uncertainties should be considered, needing further analyses for improving the accuracy of the proposed approach.

Groundwater Exploitation and Illegal Behaviors in a Differential Game

This paper studies groundwater management through a leader–follower differential game between a water agency and farmers. The access to the common pool is not free and farmers have to pay a water tax to withdraw. To save this cost, we assume that farmers may not declare all the water pumped and face the risk of being sanctioned. The water agency, on the other hand, knows that unauthorized water extraction may occur and chooses the water tax that maximizes only the legal social welfare. The value of the farmers’ evasion share is unknown ex-ante by the water agency. The game is solved using feedback Nash solution. To understand how the water agency may counter illegal behaviors, we perform numerical simulations based on the Western La Mancha (Spain) aquifer data. It emerges that the optimal path of the water table is always above the minimum level, although it is sensitive to the level of the ecosystem costs. Moreover, increasing the administrative sanction reduces the unauthorized water extraction and raises the social welfare.

Data-driven and model-based framework for smart water grid anomaly detection and localization

Abstract With increasing adoption of advanced meter infrastructure, smart sensors together with SCADA (Supervisory Control and Data Acquisition) systems, it is imperative to develop novel data analytics and couple the results with hydraulic modeling to improve the quality and efficiency of water services. One important task is to timely detect and localize anomaly events, which may include, but not be limited to, pipe bursts and unauthorized water usages. In this paper, a comprehensive solution framework has been developed for anomaly detection and localization by formulating and integrating data-driven analytics with hydraulic model calibration. Data analysis for anomaly detection proceeds in multiple steps including the following: (1) data pre-processing to eliminate and correct erroneous data records, (2) outlier detection by statistical process control methods and deep machine learning, and (3) system anomaly classification by correlation analysis of multiple sensor events. Classified system anomaly events are subsequently localized via hydraulic model calibration. The integrated solution framework is developed as a user-friendly and effective software tool, tested, and validated on the selected target areas in Singapore.

Modelling and assessing the impact of illegal water abstractions by upstream farmers on reservoir performance

This study proposes a reservoir yield analysis that incorporates the realities of upstream illegal human activities relating to water abstraction. The study assesses the impact of such unlawful human activities on reservoir storage and yields quantitatively. A reservoir operation water balance model was simulated and coupled with upstream irrigation users’ propensity to unauthorized water abstraction and set to co-evolve for the entire simulation period. The model was developed using four-state drivers (hydrological state, users’ compliance, management competence and reservoir performance). The impact of human behaviour (users’ and management) was assessed using 9 plausible human behaviour scenarios. The model was applied to a system of 5 reservoirs using the 90-year historical hydrologic dataset. The trajectories of the storage, yield-demand and storage-yield ratios were analyzed under different human behaviour scenarios. Both storage and yield were found to substantially decrease as users’ compliance and management competence deteriorated for the same reservoir hydrological state. Depending on the scenario, the annual yield (%) was observed to reduce from 100 to 80 or 50 or even 30 of the annual demand due to changing behaviour. Also, most of the years in which the yield differs significantly from one scenario to the other are years with shallow storage due to drought. A yield difference of about 23% was recorded between the scenarios without and with the highest unauthorized abstractions. The study, therefore, revealed how human behaviour can significantly affect reservoir storage and yield performances. This highlighted the need to be incorporating the impact of unlawful human activities into yield analysis models to quantitatively assess the impact of human behaviour on reservoir performance.

Time Series Data Decomposition-Based Anomaly Detection and Evaluation Framework for Operational Management of Smart Water Grid

With the increasing adoption of advanced meter infrastructure (AMI), smarter sensors, and temporary and/or permanent data loggers, it is imperative to leverage data analytics methods with hydraulic modeling to improve the quality and efficiency of water service. One important task is to timely detect and evaluate anomaly events so that corresponding actions can be taken to prevent and mitigate the impact of possible water service disruption, which may be caused by the anomaly incidents including but not limited to pipe bursts and unauthorized water usages. In this paper, a comprehensive analysis framework is developed for anomaly event detection and evaluation by developing an integrated solution, which is implemented in multiple components including: (1) data-preprocess or cleansing to eliminate and correct error data records; (2) decomposition of time series data to ensure data stationarity; (3) outlier detection by statistical process control methods with stationary time series; (4) classification of system anomaly events by either correlation analysis of high-flow events with low-pressure events or high-flow outliers with low-pressure outliers; and (5) quantitative evaluation of the system anomaly events with field reported leak incidents. The solution framework has been applied to the water supply zone that is permanent monitored with the flow meter at the inlet and 12 pressure stations throughout the zone with more than 8,000 pipes. Analysis has been conducted with one-year monitoring data and 106 historical leak records, which are employed to validate 526 detected anomaly events. Among them, a 75% true positive rate has been achieved and 90% of 106 field events have been successfully detected with a lead time of more than 24 h. The results obtained indicate that the developed solution method is effective at facilitating the operational management of a smart water grid by maximizing the return of investment in continuously monitoring water distribution networks.

Reduction in Non-Revenue Water in Water Distribution System

Water is the world’s most critical natural resource. Rapid population growth and economic development have led to higher demand for water worldwide whereas on the supply side, natural sources of water have become less reliable. This demand-supply imbalance in the water sector calls for more innovative water management practices and suitable technologies. Utilities cannot afford the water loss because of poor operation and maintenance of water distribution infrastructure facilities. The terms theft, smuggling and leakages are most common sources of generation of Non- revenue water (NRW). Newspaper articles around the world, particularly in countries experiencing intense drought and water shortages, are highlighting water theft as a growing problem. Analysis of various city development plans in India shows that water leakages, theft and unauthorized water connections gives rise to a high level of unaccounted water. A recent study on Water Governance (2013) reveals that unaccounted water in Delhi amounts to around 50% of the total water pumped into the system, whereas it is 35-40% in Hyderabad and Bengaluru. The World Bank in its report, ‘The Challenge of Reducing Non-Revenue Water in Developing Countries’, reveals that 48 million cubic meters of drinkable water escape daily from official supply networks, which is enough to provide water for 200 million people. The same report on India had clearly highlighted that 40-60% of water in Mumbai is lost through illegal diversion. In This paper we have made an attempt to analyze the current methods, their drawbacks and we have provided solution in the form of software-based approach (using Bentley Watergems) which is more relevant as compared to the current field method.

RiMARS: An automated river morphodynamics analysis method based on remote sensing multispectral datasets

Assessment and monitoring of river morphology own an important role in river engineering; since, changes in river morphology including erosion and sedimentation affect river cross-sections and flow processes. An approach for River Morphodynamics Analysis based on Remote Sensing (RiMARS) was developed and tested on the case of Mollasadra dam construction on the Kor River, Iran. Landsat multispectral images obtained from the open USGS dataset are used to extract river morphology dynamics by the Modified Normalized Difference Water Index (MNDWI). RiMARS comes with a river extraction module which is independent of threshold segmentation methods to produce binary-level images. In addition, RiMARS is equipped with developed indices for assessing the morphological alterations. Five characteristics of river morphology (spatiotemporal Sinuosity Index (SI), Absolute Centerline Migration (ACM), Rate of Centerline Migration (RCM), River Linear Pattern (RLP), and Meander Migration Index (MMI)), are applied to quantify river morphology changes. The results indicated that the Kor River centerline underwent average annual migration of 40 cm to the southwest during 1993–2003 (pre-construction impact), 20 cm to the northeast during 2003–2011, and 40 cm to the south-west during 2011–2017 (post-construction impact). Spatially, as the Kor River runs towards the Doroudzan dam, changes in river morphology have increased from upstream to downstream; particularly evident where the river flows in a plain instead of the valley. Based on SI values, there was a 5% change in the straight sinuosity class in the pre-construction period, but an 18% decrease in the straight class during the post-construction period. Here we demonstrate the application of RiMARS in assessing the impact of dam construction on morphometric processes in Kor River, but it can be used to assess other riverine changes, including tracking the unauthorized water consumption using diverted canals. RiMARS can be applied on multispectral images.

АНАЛИЗ ЯДЕРНОЙ БЕЗОПАСНОСТИ ПРИ ОБРАЩЕНИИ С ТОПЛИВОМ РЕАКТОРА МБИР

The main results of neutron and physical calculations for the unirradiated and fulfilled fuel storages of the MBIR reactor, transport processing equipment and radiation protective cameras are adduced in this work. The analysis was made in full accordance with requirements of the state normative documents for nuclear safety of research nuclear facilities. The results of effective neutron reproduction coefficient calculations received with use of the MCU-RFFI/A program were used for the analysis. According to the results of neutron and physical calculations, the NSM mass, enrichment, a step and geometry of placement of products in a binding reactor facility rooms restrictions were set, norms of loading at which nuclear safety at the unirradiated and fulfilled storage of MBIR reactor fuel, transport and technological operations are provided both in regular conditions, and in the considered emergencies were defined. The dependence of effective coefficient of neutron reproduction changes at unauthorized water ingress into points of "dry" storage and the equipment from water density was calculated, the maximum values were defined. The extreme values of effective neutron reproduction coefficient at violation of placement geometry of the nuclear sharing materials owing to external influences and human errors were also defined. The quantity and geometry restrictions of products arrangement with the nuclear sharing materials for all radiation protective cameras on the basis of settlement researches were set.

Quantifying the unauthorized lake water withdrawals and their impacts on the water budget of eutrophic lake Dianchi, China

Water withdrawn from lakes is one of pathways to support economic development in China. Yet lake water withdrawals, especially through unauthorized behaviors, have not been accurately quantified. Here we proposed a coupled simulation-optimization model to determine the unauthorized water withdrawals from Lake Dianchi (the sixth largest freshwater lake in China) and assessed their impacts on lake hydrology. Together the results of systematic observations, on-site surveys, and local statistics reveal that lake water withdrawals played a non-negligible role in lake water budget, accounting for 19.6% of total outputs from the lake over the period 1999–2011. Most water withdrawal events occurred from April to October when toxic blooms of cyanobacteria happened. Lake water withdrawals reshuffled water budget components of the lake itself, leading to a substantial decrease in lake outflows and water levels and an increase of highly-polluted return flows, which might further intensify local lake eutrophication and downstream water scarcity. In the light of the importance for sustainable water management, we suggest that a new and expanding monitoring network across China’s lakes to understand the process of lake water withdrawals would be beneficial to meet water demands without compromising lake ecosystems.

Creating Accountability with Interstate Cooperation

While lacking coercive power to compel enforcement, interstate compacts create accountability through multiple sources and layers connecting enforcement behavior to oversight. Using logistic regression, we test a model of accountability and enforcement of unauthorized water usage on the Klamath River. Findings indicate unauthorized water usage is far more likely to be reported and enforced on the Klamath River than on neighboring rivers in the same counties. Conclusions indicate the increased institutional layers of interstate compacts lead to more accountability and stringent enforcement and reporting of unauthorized water use.

A multi-agent architecture for diagnosing simultaneous faults along water canals

Water is intensively used in mankind activities, in particular in agriculture. Water is commonly conveyed for agriculture purposes through water canal networks which are large-scale spatially distributed systems crossing extensive regions. In the presence of leaks, unauthorized water withdrawals, water depth sensor faults or gate faults, the quality of service can be severely compromised. A system able to diagnose which type of fault is present at a given time is of vital importance to access the current state of the water canal and proceed to restore its nominal condition. This paper proposes a multi-agent architecture to simultaneously detect, isolate and estimate lateral outflows (e.g., leaks or water withdrawals) and hardware faults (e.g., a gate obstruction or a downstream water depth sensor fault) in water canal networks. First, the main canal network is broken down into several subsystems composed of a single canal pool with the corresponding gate. Then, an agent is assigned to each subsystem aiming at its fault diagnosis. The approach is based on the generation and evaluation of residuals obtained from the comparison of model-based output signals with real data. Application to an experimental water canal bears out the proposed architecture as a valuable tool for monitoring and supervising general water canals.

Unauthorized groundwater use: institutional, social and ethical considerations

In many areas of the world, particularly in arid regions or in areas experiencing population growth, there is increased competition over scarce water resources. This is likely to increase in the future due to continued population growth, urban expansion and the challenge of the impact of climate change on water resource availability. In this context, groundwater is likely to play a pivotal role in facing water scarcity. When different users share a common-pool resource, basic rules are usually established to manage access to the resource and ensure balance between demand and supply. Water authorities worldwide are increasingly paying added attention towards regulating the use of groundwater because of its strategic value, e.g. in times of drought or as a natural reserve. In the case of groundwater, although regulatory measures exist, they are often difficult to enforce. This paper explores the situation with a discussion of two aspects: first (and in line with this special issue on water ethics), an examination of the fundamental individual values that underpin behavior in relation to water use, and second, an investigation of the typologies of unauthorized water use, its main potential impacts, potential root causes and reflections on imperfect institutions and social norms.

New Fault Isolation Architecture for Irrigation Canals

Irrigation is one of the most consuming water resources in human activity. As water conveyance systems are commonly spatially distributed and crossing large regions it is important to guarantee their best efficiency. A fault diagnosis architecture is an important tool to increase efficiency in water conveyance systems. In the presence of leaks, unauthorized water extractions or water level sensor faults, the service level can be severely compromised. Recent literature deal with these situations as a unique fault of water extraction type. Isolating correctly each fault is important to access the real current state of the irrigation canals and proceed in accordance to restore its nominal conditions. This paper proposes a fault diagnosis architecture to distinguish common faults in water canals, considering either unexpected water extractions, gate faults and downstream water level sensor errors. The architecture is based on geometric and hydraulic parameters and therefore can be extended to existent irrigation canals. The proposed fault isolation architecture is an important tool to support maintenance services and be extended to fault tolerant controllers.