Hydraulic State Research Articles

A Digital Twin of a Water Distribution System by Using Graph Convolutional Networks for Pump Speed-Based State Estimation

Water distribution system monitoring is currently carried out using advanced real-time control technologies to achieve a higher operational efficiency. Data analysis techniques can be implemented for condition estimation, which are crucial tools for managing, developing, and operating water networks using the monitored flow rate and pressure data at some network pipes and nodes. This work proposes a state estimation methodology that enables one to infer the hydraulic state of the operating speed of pumping systems from these pressure and flow measurements. The presented approach suggests using graph convolutional neural network theory linked to hydraulic models for generating a digital twin of the water system. It is validated on two benchmark hydraulic networks: the Patios-Villa del Rosario, Colombia, and the C-Town networks. The results show that the proposed model effectively predicts the state estimation in the two hydraulic networks used. The results of the evaluation metrics indicate low values of mean squared error and mean absolute error and high values of the coefficient of determination, reflecting high predictive ability and that the prediction results adequately represent the real data.

Act of phosphorus on cell hydraulic state, K+ use efficiency and induction of positive correlations between yield and vegetative traits in chickpea

ABSTRACT Salinity is one of the most severe factors that can affect agricultural productivity worldwide particularly in the arid and semi-arid agro-ecological zones. Chickpea seedlings were grown in the field and subjected to different NaCl concentrations (0, 50 and 150 mM) and P application (90 kg ha–1). The experimental design was based on a completely randomised design with three replications. Salinity has disturbed the physiological and ionic state of cells by increasing stomatal resistance and significantly decreased growth and yield parameters (−66%). Under salinity, plant growth traits presented a negative correlation with yield components. P application had positive effect on growth parameters and physiological responses of the plants. Our results suggest that the tolerance of chickpea at (NaCl × P) combination is closely associated with ionic homeostasis and physiological activities of the plants. Phosphorus application allowed salinity tolerance by increasing leaf hydraulic statute, improvement of KUE and consequently enhanced grain yield of chickpea. (P × salinity) combination induced a positive correlation between vegetative traits and yield parameters like unstressed treatment. These results suggest that the use of suitable amounts of phosphorus fertiliser (i. e. 90 kg ha–1) to saline soil is a beneficial starter for plant development, yield components and rehabilitation of degraded soils.

Analysis and Improvement of the Q-iteration Method

The q-iteration method is simple, efficient and robust in determining the concentration distribution in an isotope separation cascade with a known hydraulic state. The expression of the quantity q and the value of the relaxation factor of the q-iteration method have a significant influence on the convergence rate of iteration. Through analyzing the convergence of the q-iteration method, an improved method for updating q is proposed, and the value range of the relaxation factor is obtained. Numerical analysis shows that the improved method can significantly speed up the convergence. By selecting an appropriate value of the relaxation factor, the convergence can be further improved.

Improvement of Flood Extent Representation With Remote Sensing Data and Data Assimilation

Flood simulation and forecast capability have been greatly improved thanks to advances in data assimilation. Such an approach combines in-situ gauge measurements with numerical hydrodynamic models to correct the hydraulic states and reduce the uncertainties in the model parameters. However, these methods depend strongly on the availability and quality of observations, thus necessitating other data sources to improve the flood simulation and forecast performances. Using Sentinel-1 images, a flood extent mapping method was carried out by applying a Random Forest algorithm trained on past flood events using manually delineated flood maps. The study area concerns a 50-km reach of the Garonne Marmandaise catchment. Two recent flood events are simulated in analysis and forecast modes, with a +24h lead time. This study demonstrates the merits of using SAR-derived flood extent maps to validate and improve the forecast results based on hydrodynamic numerical models with Telemac2D-EnKF. Quantitative 1D and 2D metrics were computed to assess water level time-series and flood extents between the simulations and observations. It was shown that the free run experiment without DA under-estimates flooding. On the other hand, the validation of DA results with respect to independent SAR-derived flood extent allows to diagnose a model-observation bias that leads to over-flooding. Once this bias is taken into account, DA provides a sequential correction of area-based friction coefficients and inflow discharge, yielding a better flood extent representation. This study paves the way towards a reliable solution for flood forecasting over poorly gauged catchments, thanks to available remote sensing datasets.

Potential Performance of Hydraulic State Estimation in Water Distribution Networks

Hydraulic State Estimation (HSE) is a suitable tool to gain real-time understanding of water supply systems. This technique enables to estimate the most likely hydraulic behavior in the network, as well as its associated uncertainty, from available measurements. HSE has been successfully applied to trunk mains, but additional work is required to implement it on Water Distribution Networks (WDNs). The reason for this is that WDNs generally have less real-time information than trunk mains. The new telemetry devices that can be installed at water service connections provide an opportunity to gain distributed information that could be used to monitor WDNs using HSE. However, these technologies often provide records with different time intervals (i.e. sampling rates), which should be leveled to the same time resolution for HSE application. This poses a challenge: combining information associated with different temporal scales, especially when there are larger time intervals than the monitoring time resolution, which requires considering additional uncertainty due to temporal disaggregation. The aim of this paper is twofold. First, to propose a methodology that enables to systematically level records with different time intervals to a same time resolution. This makes the application of HSE to WDNs affordable and enables to consistently evaluate the associated uncertainty. Second, to analyze the potential of HSE in WDNs using a case study. This paper thus presents a systematic framework to assess HSE at different resolution levels and highlights the importance of increasing the information available within the distribution level to reduce uncertainty.

UNORGANIZED AIR RELEASES WITH RADIOACTIVE AEROSOLS FROM THE NEW SAFE CONFINIMENT OF CHNPP INTO THE ENVIRONMENT

The New Safe Confinement (NSC) of the Chernobyl NPP, which isolates the destroyed reactor and the “Shelter Object” from the environment, is not airtight, so the problem is the lack of information on the flow of unorganized air with radioactive aerosols outside the NSC. This work presents computational model of the hydraulic state of the NSC, which allows to determine these flow rates through the leaks in the shells and building structures under the walls of the NSC. In addition to the developed model, the NSC hydraulic state model, created by neural network technology, was tested, which showed similar results and much higher computational performance, which allows its use for analysis and prediction of NSC`s hydraulic state in real time.

The coupled effect of soil and atmospheric constraints on the vulnerability and water use of two desert riparian ecosystems

Plant response to soil and atmospheric water stresses is the dominant control of Dryland ecosystem functions, affecting water resources, ecosystem stability and biodiversity. The link between water stresses and plant water status is regulated by plant hydraulics, of which the corresponding impact on plant water use and the susceptibility of Dryland ecosystems remains under-explored. We used a plant hydraulic model to describe hydraulic states and water flux of two species (Populus euphratica and Tamarix ramosissima) in desert riparian ecosystems. We optimized hydraulic parameters and tested the model using observed physiological states and ecosystem water flux. The optimized model was used to evaluate plant hydraulic sensitivity, tree mortality risk, and evapotranspiration under a wide range of water stress scenarios. The model captures the observed leaf water potential, sap-flow and ecosystem evapotranspiration. Our scenario analysis demonstrates that hydraulic sensitivities generally reduce as the water stresses intensify. The results highlight a strong coupled impact of the co-occurrence of soil and atmospheric water stresses on restricting ecosystem water flux and intensifying mortality risk. The assessment of multiple aspects of eco-physiological functions and the stress scenario analysis of desert riparian ecosystems will contribute to a better prediction of ecosystem functions and facilitate resource management under future climate.

Development and verification of coupled hydro-mechanical analysis for rainfall-induced shallow landslides

To improve the performance of rainfall-based shallow landslide warning systems, a coupled hydro-mechanical analysis framework that integrates mechanical slope analysis and hydraulic infiltration is proposed. The limit equilibrium approach for infinite slopes of unsaturated soil is coupled with 1D infiltration analysis to evaluate the transient stability of the soil mass. A hybrid testing process that combines the calculations of stress and hydraulic boundaries near the sliding surface and an element testing system capable of simulating both the stress and hydraulic states on the element boundaries was developed to verify the coupled hydro-mechanical theory. The element-level modeling reveals that the proposed coupled hydro-mechanical analysis is adequate to predict the sliding depth and time of shallow landslides. Furthermore, a time-dependent warning framework based on subsurface moisture content measurements is proposed as an alternative to rainfall-based approaches for early warning of shallow landslides.

Tackling random fields non-linearities with unsupervised clustering of polynomial chaos expansion in latent space: application to global sensitivity analysis of river flooding

A surrogate model is developed to accurately approximate a two-dimensional hydrodynamics numerical solver in order to conduct a reduced-cost variance-based global sensitivity analysis of the hydraulic state. The impact of uncertainties in river bottom friction and boundary conditions on the simulated water depth is analyzed for quasi-unsteady flows. An autoencoder technique adapted to non-linear variable dimension reduction is used to reduce the multi-dimensional model output so that the formulation of the surrogate remains computationally parsimonious. In addition, following the divide-and-conquer principle, a mixture of local polynomial chaos expansions is proposed to deal with non-linearity in the hydraulic state with respect to uncertain inputs. Machine learning techniques are used to automatically partition the input space into clusters that are not affected by non-linearities and support accurate surrogates. This combined strategy is applied to a reach of the Garonne River where river and floodplains dynamics are simulated by the numerical solver Telemac-2D. The merits of this strategy are highlighted when the flood front reaches regions where the topography features a strong gradient and where, consequently, strong non-linearities occur between the water depth and friction as well as hydrologic input forcing. By applying this strategy, the Q_2 metric improves by 90% compared to a classical polynomial chaos expansion surrogate, resulting in a much more reliable sensitivity analysis. This is particularly important in floodplain areas where human and economic activities are at stake.

Simulation Design and Optimization of UV-LED Water Purification System Based on Fluid Dynamics and Radiometry

In this paper, we established the flow field and radiation intensity distribution models of water purification equipment based on computational fluid dynamics (CFD) technology and radiometric principles. From geometric shape to hydraulic state and radiation intensity distribution, we fully simulated the real scene of the Ultraviolet LED (UV-LED) water purification system, and provided the reliable data for the UV-LED in the water purification field. Compared with mercury lamp, UV-LEDs have a more flexible layout to produce a variety of radiation intensity distributions. UV dose (the product of radiation intensity over time) is an important indicator. We used a discrete phase model (DPM) to track the path of microbial particles, and found that the residence time of microorganisms in different parts of the model was different. By optimizing the UV-LED layout, the radiation intensity was increased in the sites where the microbes resided longer. The results show that we can improve the efficiency of the water purification equipment by simply adjusting the UV-LED layout without increasing the power, and make the UV dose achieves the national standard.

Pipedream: An interactive digital twin model for natural and urban drainage systems

Faced with persistent flooding and water quality challenges, water managers are now seeking to build digital twins of surface water systems that combine sensor data with online models to better understand and control system dynamics. Towards this goal, this study presents pipedream—an end-to-end simulation engine for real-time modeling and state estimation in natural/urban drainage networks. The engine combines (i) a new hydraulic solver based on the one-dimensional Saint-Venant equations and (ii) a Kalman filtering scheme that efficiently updates hydraulic states based on observed data. Using sensor data from a real-world watershed, we find that the simulation engine is effective at both interpolating hydraulic states and forecasting future states based on current measurements. By providing a complete, real-time view of system hydraulics, our software will enable rapid detection of flooding, improved characterization of maintenance and remediation needs, and robust real-time control for both small-scale (stormwater) and large-scale (river/reservoir) networks.

Civilizing the Past: Egyptian Irrigation in the Colonial Imagination

Abstract Reviews of the historiography of irrigation regularly single out Karl August Wittfogel’s “hydraulic hypothesis” as a uniquely deleterious contribution to the study of ancient water management. His errors notwithstanding, this article argues that the ideological misshaping of Western scholarship on irrigation instead emerged from Egypt’s long colonial experience. First articulated in the Napoleonic Description de l’Égypte, the theory of a centralized, ancient Egyptian “hydraulic state” was crafted to justify French attempts to reshape Egypt’s irrigated landscape. British hydraulic engineers later received and refined this narrative during the British colonial period. Their popularizing discourse retrojected the technocratic character of modern irrigation into antiquity, defining the Egyptian “irrigation system” as a static and unchanging fusion of hydraulic expertise and state power. Widely disseminated in specialist and popular fora, this tendentious argument had become received wisdom by the beginning of the twentieth century and subtly shaped early Egyptological descriptions of irrigation in antiquity.

Water Well Hydrographs: An Underutilized Resource for Characterizing Subsurface Conditions.

Many of the world's major aquifers are under severe stress as a result of intensive pumping to support irrigated agriculture and provide drinking water supplies for millions. The question of what the future holds for these aquifers is one of global importance. Without better information about subsurface conditions, it will be difficult to reliably assess an aquifer's response to management actions and climatic stresses. One important but underutilized source of information is the data from monitoring well networks that provide near-continuous records of water levels through time. Most organizations running these networks are, by necessity, primarily focused on network maintenance. The result is that relatively little attention is given to interpretation of the acquired hydrographs. However, embedded in those hydrographs is valuable information about subsurface conditions and aquifer responses to natural and anthropogenic stresses. We demonstrate the range of insights that can be gleaned from such hydrographs using data from the High Plains aquifer index well network of the Kansas Geological Survey. We show how information about an aquifer's hydraulic state and lateral extent, the nature of recharge, the hydraulic connection to the aquifer and nearby pumping wells, and the expected response to conservation-based pumping reductions can be extracted from these hydrographs. The value of this information is dependent on accurate water-level measurements; errors in those measurements can make it difficult to fully exploit the insights that water-well hydrographs can provide. We therefore conclude by presenting measures that can help reduce the potential for such errors.

A novel sensor measuring local voidage profile inside a fluidised bed reactor

Liquid-solid fluidisation is frequently encountered in drinking water treatment processes, often to obtain a large liquid-solid interfacial surface area. A large surface area is crucial for optimal seeded crystallisation in full-scale softening reactors. Due to crystallisation, particles grow and migrate to a lower zone in the reactor which leads to a stratified bed. Larger particles adversely affect the surface area. To maintain optimal process conditions in the fluidised beds, information is needed about the distribution of particle size, local voidage and available surface area, over the reactor height.In this work, a sensor is developed to obtain the hydraulic state gradient, based on Archimedes’ principle. A cylindrical heavy object is submerged in the fluidised bed and lowered gradually while its weight is measured at various heights using a sensitive force measuring device.Based on accurate fluidisation experiments with calcite grains, the voidage is determined and a straightforward empirical model is developed to estimate the particle size as a function of superficial fluid velocity, kinematic viscosity, suspension density, voidage and particle density. The surface area and specific space velocity can be estimated accordingly, which represent key performance indicators regarding the hydraulic state of the fluidised bed reactor. The prediction error for voidage is 5 ± 2 % and for particle size 9 ± 4 %.The newly developed soft sensor is a more time-effective method for obtaining the hydraulic state in full-scale liquid-solid fluidised bed reactors.

Calculating Chlorine Concentration Bounds in Water Distribution Networks: A Backtracking Uncertainty Bounding Approach

AbstractThe estimation of chlorine concentration in water distribution networks is a challenging task due to hydraulic and water‐quality parameter uncertainties. In this work, we propose a methodology for calculating chlorine concentration bounds at node locations of water distribution networks which is suitable for sensor fault and contamination detection purposes. The proposed Backtracking Uncertainty Bounding Algorithm (BUBA) considers known bounds on hydraulic states and water‐quality model parameters to calculate the chlorine concentration bounds. The validity of the calculated bounds is demonstrated using a large number of Monte Carlo simulations on benchmark networks. Moreover, the proposed methodology can be used in conjunction with a real‐time parameter estimation algorithm, as it allows the use of time‐varying bulk reaction coefficients. A parameter estimation algorithm is designed and implemented to approximate the unknown bulk reaction coefficient of water at the sources of the WDN, which are typically water tanks filled with water originating from different sources. The BUBA then uses these time‐varying parameters to improve the chlorine concentration bounds, as demonstrated in a case study with real data from a water transport network.

Analytical and numerical investigations on the one-dimensional permanent deformations of granular materials under repeated deviatoric loading

This work proposes a theoretical framework for the permanent deformation calculation of unsaturated granular materials. The approach is based on the separation of the Soil Water Retention Curve (SWRC) into three linear phases. This representation makes unique the wetting and drying paths with a newly defined normalized suction s/s*. The same unique curves of permanent deformations with the normalized suction value are then developed. The proposed approach is initially applied to reproduce the experimental permanent deformation of two granular materials with different water contents on the wetting and drying paths. The effect of the deviatoric stress on the permanent deformations is also considered in the multi-stage loading tests. The good correspondence between the predicted and experimental results confirms the good capacity of the proposed approach. Finally, the proposed approach is injected in a finite difference code to model the tests performed on the two aforementioned granular materials. The numerical simulations show that both modeling concepts with variable and non-variable suction profile predict well the experimental results of the single-stage and multi-stage tests. The maximum deflection of a typical pavement is also estimated at the different hydraulic states, giving more credits to the proposed approach. • This work proposes a theoretical framework for permanent deformation of granular materials. • The Soil Water Retention Curve (SWRC) is divided into three linear phases." can be eliminated from the highlights. • The same unique curves of permanent deformations with the normalized suction are developed. • A good correspondence between the estimated and experimental values is obtained. • The proposed approach is also injected in a finite difference code. • The numerical simulations are performed on a full scale test of a typical pavement structure.

Decision of The Hydraulic State of Rivers within Growth Cities using GIS: Al-Hneidiyah River as Example

Generally, the rivers in both the natural and lined form use the open-section system to carry water, either for distribution or conveyance purposes. With time and depreciation effect, this system needs to be changed or modified to become more indirectly suitable with cities' growth, especially with the transformation of land use from agricultural to residential. The present paper aims to reach a proper decision to select the best hydraulic section for a part of Al-Hneidiyah river in Karbala city by determining the remain agricultural lands within the study area, for the distance between stations (0+000) and (4+000), to choose between keeping up the currently open section or change, (modify), it to a closed conduit. For this study, the cadastral maps were used as a reference to determine the agricultural areas served by the river during its route within the study area, and geographic information system to monitor the change like these areas represented by a gradual transformation from agricultural to residential purpose, by using of satellite images for four different years, 2002, 2007, 2013, and 2016. The results of this study showed a significant recession in the agricultural areas on both sides of the chosen length of river route by a percentage of 13.45%, which leads to an urgent need to change or modify the flow system from opened to closed and use it only for conveyance purposes to protect the water quality and water shares. The geographic information system is a good and helpful technique for evaluation and makes water-related subjects decisions by giving a clear vision of the studied problem.

Real-Time Monitoring for Hydraulic States Based on Convolutional Bidirectional LSTM with Attention Mechanism.

By monitoring a hydraulic system using artificial intelligence, we can detect anomalous data in a manufacturing workshop. In addition, by analyzing the anomalous data, we can diagnose faults and prevent failures. However, artificial intelligence, especially deep learning, needs to learn much data, and it is often difficult to get enough data at the real manufacturing site. In this paper, we apply augmentation to increase the amount of data. In addition, we propose real-time monitoring based on a deep-learning model that uses convergence of a convolutional neural network (CNN), a bidirectional long short-term memory network (BiLSTM), and an attention mechanism. CNN extracts features from input data, and BiLSTM learns feature information. The learned information is then fed to the sigmoid classifier to find out if it is normal or abnormal. Experimental results show that the proposed model works better than other deep-learning models, such as CNN or long short-term memory (LSTM).

Conceptual Hydraulic Conductivity Model for Unsaturated Soils at Low Degree of Saturation and Its Application to the Study of Capillary Barrier Systems

Accurate modeling and prediction of the variation of the hydraulic conductivity of unsaturated soils at a very low degree of saturation has important implications in various engineering problems. Physical processes underlying the hydraulic behavior of unsaturated soils (retention behavior and variation of hydraulic conductivity) are first explained, and then a consistent set of new definitions for key transition hydraulic states is proposed. This lays the foundation for the presentation of a new predictive hydraulic conductivity model, accurate for the full range of degree of saturation and applicable to relatively coarse-grained soils (i.e., gravels, sands, and silts). The hydraulic conductivity is divided into two components—a bulk water component and a liquid film component—each of which varies with the degree of saturation or suction. The model is then validated against experimental data. Finally, the new hydraulic conductivity model is applied to the numerical study of the hydraulic behavior of capillary barrier systems (CBSs). The new model is able to predict the behavior of CBSs better than conventional models, and the numerical modeling highlights the role of liquid film flow, which is often neglected.

Shakedown Analysis of Unsaturated Soils Considering the Variation of Hydraulic States

Long-term stability evaluation of unsaturated earth structures has always been one of the most important issues in geotechnical engineering. Most available methods are appropriate for calculating the maximum loads that the structures can resist when the hydraulic state is fixed, and the external loads are monotonically increased. In practical engineering, however, the hydraulic condition is ever changing, and so are the matric suction and the shearing strength of unsaturated soils. In this situation, the obtained minimized collapse loads can no longer be used as reference for the design criterion, which may greatly overestimate the stability of the structures. Classical shakedown analysis is a more appropriate method, which can only consider the variation of the loads but not the variation of hydraulic states. This paper presents a novel formulation for shakedown analysis of unsaturated soils considering both the variation of external loads and the variation of the shearing strength caused by drying–wetting cycles. By using the suction stress-based effective stress of unsaturated soils, the three-phased mixture is dealt with as a single-phased material. The suction-stress equivalent forces are established, and the variation of the hydraulic state is dealt with as the variation of equivalent forces. Numerical formulations are then developed by the combination of the finite-element method and the second-order cone programming. Some shakedown problems are solved, and the effect of hydraulic state variation on the shakedown limits of foundations, pavements, and slopes is studied in detail. It is shown that the neglection of moisture content variation would greatly overestimate the safety of earth structures, and the produced errors become more significant with the increase of the suction-stress increment and the decrease of the shearing strength. The shakedown limit reaches the smallest when both external loads and suction stress are varying. When the variation of equivalent forces is complicated, the loading domain can be approximated by a polyhedron using a uniform distribution of sampling points, and the shakedown factor of safety converges to the true value with the increase of the number of sampling points. Shakedown analysis is necessary in engineering designs when several wetting and drying cycles happen.