Review of Water Network Analysis and Validation of SCALER Hydraulic Simulator

The article intends to present the validation stage of a software to model and simulate hydraulic networks for water distribution, the SCALER, through its application to a real system, with many branches, with a model previously developed and verified using the EPANET software. SCALER was developed in 2020 and 2021 and, until then, had only been applied to networks with a relatively small number of branches. After discussing topics related to hydraulic modeling of distribution networks, techniques and applications, a brief review of the fundamentals of SCALER is carried out, passing on to its application to the case at hand, which is the Vila Joaniza community, in the municipality of Rio de Janeiro. Data from image, scheme and table are used to assist in the description of the local situation and respective distribution network, with the objective of assessing whether the nodal pressures obtained by SCALER are sufficiently similar to those obtained by EPANET, in order to ensure the proper functioning of the software. After this step, and the calculations have been made by the program, an operation screen, the generated graph of the local situation and a table with the comparison of absolute and percentage deviations between the nodal pressures resulting from the SCALER and those obtained with the EPANET are inserted, confirming that the deviation values are quite small, which validates SCALER as a software also applicable to networks with many branches.

Analyzing the Application of X-Band Radar for Improving Rainfall Observation and Flood Forecasting in Yeongdong, South Korea

The mountainous Yeongdong region of South Korea contains mountains over 1 km. Owing to this topographic blockage, the region has a low-density rain-gauge network, and there is a low-altitude (~1.5 km) observation gap with the nearest large S-band radar. The Korean government installed an X-band dual-polarization radar in 2019 to improve rainfall observations and to prevent hydrological disasters in the Yeongdong region. The present study analyzed rainfall estimates using the newly installed X-band radar to evaluate its hydrological applicability. The rainfall was estimated using a distributed specific differential phase-based technique for a high-resolution 75 m grid. Comparison of the rainfall estimates of the X-band radar and the existing rainfall information showed that the X-band radar was less likely to underestimate rainfall compared to the S-band radar. The accuracy was particularly high within a 10 km observation radius. To evaluate the hydrological applicability of X-band radar rainfall estimates, this study developed a rain-based flood forecasting method—the flow nomograph—for the Samcheok-osib stream, which is vulnerable to heavy rain and resultant floods. This graph represents the flood risk level determined by hydrological–hydraulic modeling with various rainfall scenarios. Rainfall information (X-band radar, S-band radar, ground rain gauge) was applied as input to the flow nomograph to predict the flood level of the stream. Only the X-band radar could accurately predict the actual high-risk increase in the water level for all studied rainfall events.

Simulation-optimization framework in urban flood management for historic and climate change scenarios

A simulation-optimization framework is established by integrating Hydrologic Engineering Center Hydraulic Modeling System (HEC-HMS) for computation of runoff, siting tool EPA System for Urban Storm-water Treatment and Analysis INtegration (EPA-SUSTAIN) for placement of Best Management Practices (BMPs), and Binary Linear Integer Programming (BLIP) for runoff reduction. The framework is applied to an urban catchment, namely Greater Hyderabad Municipal Corporation (GHMC). The rainfall-runoff analysis was conducted for extreme rainfalls for historic (2016) and future events in 2050 and 2064 under Representative Concentration Pathways (RCPs) 6.0 and 8.5. The simulation-optimization approach in the historic scenario yielded 495,607 BMPs occupying 76.99 km2 resulting in runoff reduction of 21.54 mm (198.76–177.22 mm). Achieved runoff reduction is 38.72 (428.35–389.63 mm) and 55.03 (602.65–547.62 mm), respectively, for RCPs 6.0 and 8.5, which could meet the water demands of GHMC for 10.33 and 11.53 days. Impacts of 10 different BMP configurations of varying costs (10–70%) and pollutant load reductions (0–3%) on runoff reduction are accomplished as part of sensitivity analysis.

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

With increasing adoption of advanced meter infrastructure, smart sensors together with SCADA 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.

Shallow Water Equations in Hydraulics: Modeling, Numerics and Applications

This Special Issue aimed to provide a forum for the latest advances in hydraulic modeling based on the use of non-linear shallow water equations (NSWEs) and closely related models, as well for their novel applications in practical engineering. NSWEs play a critical role in the modeling and simulation of free surface flows in rivers and coastal areas and can predict tides, storm surge levels and coastline changes from hurricanes and ocean currents. NSWEs also arise in atmospheric flows, debris flows, internal flows and certain hydraulic structures such as open channels and reservoirs. Due to the important scientific value of NSWEs, research on effective and accurate numerical methods for their solutions has attracted great attention in the past two decades. Therefore, in this Special issue, original contributions in the following areas, though not exclusively, have been considered: new conceptual models and applications; flood inundation and routing; open channel flows; irrigation and drainage modeling; numerical simulation in hydraulics; novel numerical methods for shallow water equations and extended models; case studies; and high-performance computing.

Spatio-temporally Varying Manning Roughness in Rivers and Streams: A calibration approach using in-situ water level and UAS altimetry

Hydraulic roughness (expressed in terms of e.g. Manning's roughness coefficient) is an important input to hydraulic and hydrodynamic simulation models. One way to estimate roughness parameters is by hydraulic inversion, using observed water surface elevation (WSE) collected from gauging stations, satellite platforms or UAS (Unmanned Aerial System) −based altimeters. Specifically, UAS altimetry provides close to instantaneous observations of longitudinal profiles and seasonal variations of WSE for various river types, which are useful for calibrating roughness parameters. However, it is computationally expensive to run high−resolution hydrodynamic models for long simulation periods (e.g. multiple years), and thus global optimization of spatially and temporally distributed parameter sets for such models, e.g., spatio−temporally varying river roughness, is still challenging.This study presented an efficient calibration approach for hydraulic models, using a simplified steady-state hydraulic solver, UAS altimetry datasets, and in-situ observations. The calibration approach minimized the weighted sum of a misfit term, spatial smoothness penalty, and a sinusoidal a priori temporal variation constraint. The approach was first demonstrated for several synthetic calibration experiments and the results indicated that the global search algorithm accurately recovered the Manning–Strickler coefficients M for short river reaches in different seasons, and M varied significantly in time (due to the seasonal growth cycle of the aquatic vegetation) and space (due to, e.g. spatially variable vegetation density). Subsequently, the calibration approach was demonstrated for a real WSE dataset collected at a Danish test site, i.e., Vejle Å. Results indicated that spatio-temporal variation in M was required to accurately fit in-situ and UAS altimetry WSE observations. This study illustrated how UAS altimetry and hydraulic modeling can be combined to achieve improved understanding and better parameterization of small and medium-sized rivers, where conveyance is controlled by vegetation growth and other spatio-temporally variable factors.

Hydraulic optimization of the physical parameters of a drinking water distribution system

Drinking-water distribution systems are generally designed with methodologies based on trial-and-error tests, which generate feasible results. However, these trials are not the most economical and reliable solution since they do not consider the optimization of the network. For the present work, the hydraulic model of the drinking water distribution network of San José de Cúcuta, Colombia, was optimized by applying the concept of resilience rate and minimum cost. The development of the work consisted of the hydraulic modeling of the physical components of the network in EPANET software, as well as the application of calculations of the connectivity coefficient and the unitary power of each section. With the data obtained from the modeling and calculations, the physical parameters were optimized, and the cost-benefit ratio was estimated. It was found that the current drinking water distribution system does not have a power surplus to overcome a system failure. The optimization increased the total energy surplus of the network (261%) and the resilience rate (585%). Also, the connectivity coefficient was improved with an average value of 0.95. The hydraulic optimization methodology applied resulted in a network resilient to system failures.

Analysis of human physical vulnerability using static equilibrium techniques of a Hazard flood for the determination of unsafe areas in the city of Catacaos – Piura, Peru

Heavy rains and El Niño phenomenon are recurring natural phenomena at a national level. These can cause floods due to the overflowing of rivers, which, when close to cities, can cause both human and material losses. The district of Catacaos, located in the city of Piura, was the one with the highest number of injuries due to the flood caused by El Niño phenomenon in 2017. This phenomenon causes a large amounts of rainfalls due to the presence of abnormally warm waters along the northern coast of Peru [1]. It is for this reason that the need arose to carry out an analysis of the physical vulnerability due to instability of people through static equilibrium, in said district, in order to present maps of unsafe areas in the face of this phenomenon. In this investigation, flood hazard maps are generated simulating the one presented in 2017, using 2D hydraulic modeling. For the generation of vulnerability curves, the instability analysis is performed by moment and drag force. Finally, maps with unsafe areas are made using ArcGis software. Where the results obtained indicate that 29.37% of the city was flooded. Likewise, the vulnerability maps generated show us that women and men over 18 years of age in the city of Catacaos would be vulnerable to dragging and overturning in the face of floods in 16.54% and 13.21%, respectively, of the total studied area. This information will be useful for the development of future evacuation plans during floods, carried out by national entities.