Flow hydraulics and sediment transport influence the overall stability and sustainability of rivers. This work reports the flow hydraulics and water quality parameters of Damercherla and Wadapally, the two gauging stations on the Musi River, Hyderabad, India. The trend analysis of the flow rate of these two gauging stations was carried out using the Mann-Kendall test (MKT) and a revised innovative trend analysis (RITA) by considering parameters such as flow rate, total alkalinity, total hardness, electrical conductivity, chlorine, potassium, sulphate, and pH for the period of 1987–2018. Data was segregated to develop a monthly time series for each parameter. Apart from conductivity and hardness, the average value of all other water quality parameters at these two gauging sites were within the permissible limit of the Bureau of Indian Standards (BIS). The average conductivity value was 882 and 560 µS cm-1, respectively, at the Damercherla and Wadapally gauging stations. The hardness of water at Damercherla and Wadapally was noted to be 239 and 156 mg L-1, respectively, which was greater than the permissible limit of BIS, whereas the average value of alkalinity at Damercherla and Wadapally was 193 and 128 mg L-1, respectively. RITA shows an insignificant discharge trend at Damercherla and a significant discharge trend at Wadapally. Similar trend results were observed for the MKT, too. The rate of decline of discharge is around 33 m3/s at Wadapally during the month of August. The changes observed in discharge at the studied sites on the Musi River may be due to unplanned urbanization and climate change, apart from other contributing factors.
This study investigates the hydrodynamics and sediment transport processes around an isolated submerged non-uniform flexible vegetation (FV) element in an open-channel flow using FLOW-3D HYDRO. The observed reconfigured FV shape is represented using a hybrid solid–porous configuration with a height-varying frontal area and porosity. Numerical simulations incorporate the RNG k–ε turbulence model, the saturated Forchheimer porous-media formulation, and Nielsen’s bedload transport formulation, and are validated against laboratory measurements of velocity profiles and bed elevation changes. Results show that FV induces a distinct three-layer flow structure, with a velocity deficit within the canopy and an accelerated shear layer at the canopy–water interface. Flow vectors reveal wake formation and coherent vortices that promote sediment mobilization, while turbulent kinetic energy (TKE) peaks above the canopy due to shear-layer instabilities. A C-shaped scour hole develops at the FV base, followed by downstream deposition, consistent with experimental observations. Although computational fluid dynamics (CFD) slightly underpredicts the maximum scour and deposition magnitudes, it effectively reproduces the centerline bed-elevation trends (R2 = 0.92) and key morphodynamic patterns with satisfactory agreement. The proposed robust and computationally efficient CFD framework demonstrates the capability of reproducing complex flow–vegetation–sediment interactions in vegetated channel systems and is applicable to river restoration, sediment management, and ecohydraulic design.
Sewer infrastructure is essential to urban functionality but vulnerable to blockages that compromise hydraulic performance and increase maintenance costs. Traditional sewer asset management focuses on structural deterioration, neglecting operational problems such as wipe buildup, a growing source of blockage due to poor disintegration. This research develops a novel algorithm that simulates the formation, growth, and effect of wipe-caused blockages, enhancing urban drainage models by accounting for their hydraulic implications. Capacity loss in sewers due to wipe accumulation was quantified and shown to increase with greater population densities. Results showed the need to adopt structural and operational factors in sewer management. By addressing wipe-caused blockages, this research gives insights into the deterioration of sewer performance that requires better mitigation measures. An improved blockage modeling strategy can be used to enhance asset management, maintain sewer functionality, and provide sustainable urban drainage systems.
An equilibrium stream is characterized as one where channel dimensions and slope have been adjusted over a duration, enabling the conveyance of incoming sediment and water with minimal erosion or deposition. The time taken by the flow to attain this equilibrium state is referred to as equilibrium time. Studies have been conducted on cohesive channel bed for critical shear stress expression and further extended for bed load transport rate; however, studies were not found on equilibrium time expression on erosion for cohesive channel bed. The present study fills the gap for the computation of equilibrium time for cohesive mixture of clay–silt–sand. A laboratory-based investigation was conducted to analyse the factors influencing the time it takes for equilibrium to be reached in a cohesive channel bed made of mixture of clay, silt, and sand in which clay content varied from 10% to 50%. The study indicated a decreasing trend in effective shear stress with an increase in clay content. An increase in clay content in the channel bed led to a lengthening of the equilibrium time. A relationship was established to compute the dimensionless equilibrium time for the cohesive clay–silt–sand mixture. Impressively, a strong correlation (R2 = 0.97) emerged between the computed values and the actual observed data in this study. The developed model estimates the dimensionless equilibrium time in cohesive clay–silt–sand mixtures, emphasizing the dominant influence of clay content on erosion dynamics and bed stabilization.
Erosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the effects of construction buildings such as dikes, jetties, and dams. This paper attempts to summarize the characteristics of these natural phenomena and the parameters affecting them, in addition to the solutions to control the estuarine morphological changes. Knowing the amount of water flow in the estuary system is important and considered the main reason for erosion, deposition, bank shifting, and sediment transport due to high velocities. Using concrete blocks to control the erosion and deposition processes was a suggestion to be applied as an effective solution under different conditions.
Recent best management practices established for reducing urban flooding include rain gardens. However, despite their increasing use, rain gardens often lack standardized, data-driven design specifications, particularly concerning infiltration behaviour. In order to forecast the infiltration features of the rain garden, the current work uses conventional and machine learning approaches. In order to conduct research on perennial flower species, a series of small rain gardens were constructed within the hydraulics laboratory at NIT Kurukshetra in Haryana, India. The study involved the utilization of three conventional models (the Philips model, Multi-linear Regression, and the Kostiakov model), as well as two soft computing approaches (M5P tree and Gaussian Process (GP)) to predict the infiltration rate of the rain gardens. The M5P tree model exhibited superior performance compared to other models in the study. The Correlation Coefficient (CC), root mean square error (RMSE), and Nash-Sutcliffe efficiency (NSE) values for the training data set are 0.960, 0.526 cm/hr, and 0.858, respectively, and for validation, data set values are obtained as CC = 0.941, RMSE = 0.667 cm/hr, and NSE = 0.87. The results of this study will be helpful for accurately calculating the infiltration rate of rain gardens.
This paper, and the associated keynote presentation at ICWMM 2025, review several topics that show how stormwater monitoring has been critical in the development of stormwater quality models. The first example is a timeline of how street cleaning was originally conceived as a stormwater quality control and how subsequent focused monitoring enabled a more accurate representation of its benefits. The next example illustrates scaling issues in monitoring and how data have been used to verify appropriate extrapolations of the information. Finally, a short summary of emerging contaminants of current interest illustrates the need for expanded monitoring to understand these little understood stormwater constituents and how they can be modeled to predict their sources, transport, controls, and fates. Many other topics relating to monitoring and modeling exist obviously, but these examples, mostly from the author’s publications, illustrate the range of some of these issues needing further monitoring and model development. The examples shown are only a small portion of the data collected during the referenced studies, and the full reports should be consulted for further information.
Urban stormwater management is essential for limiting flooding, protecting ecosystems and ensuring infrastructure durability. However, the long-term effectiveness of these systems depends heavily on an appropriate maintenance strategy. This paper develops a preventive maintenance plan based on a systemic approach, aimed at enhancing the sustainability and performance of stormwater management infrastructures, particularly bioretention basins. The approach adopted breaks down each infrastructure into critical sub-components, assesses their performance according to specific criteria, and then recommends maintenance actions based on observed results. A case study of four basins in Montr & eacute;al revealed performance levels ranging from 83.21% to 85.23%, indicating the need for regular inspections, continuous monitoring, and a medium priority for intervention. The results support the effectiveness of the systemic method for prioritizing interventions and anticipating deterioration, ensuring optimal and sustainable infrastructure management. This research proposes a structuring framework, offering municipal managers a decision-making tool tailored to address the growing challenges posed by urbanization and climate change. It demonstrates the practical effectiveness of the systemic approach in an operational urban stormwater context.
Flood hazard mapping is essential for reducing flood risks by identifying vulnerable areas and guiding response strategies. However, obtaining high-resolution topographic data over large areas can be costly, and reducing this expense while maintaining accuracy is crucial for effective 2D hydraulic mapping. The limited availability of topographic data in river areas makes it difficult to delineate flood inundation. This research aims to investigate the best model for extending high-resolution Digital Elevation Model (DEM) data as input for flood hazard mapping. To enhance DEM resolution, the best model was selected by comparing Root Mean Square Error (RMSE) values from various interpolation methods, namely nearest neighbour interpolation (NNI), bicubic, and bilinear in spatial analysis. The model was then validated using 40 data points. Subsequently, the best model was used to generate a DEM for a larger scale as input for 2D modeling with HEC-RAS. The flood inundation model was validated twice: first, based on water level measurements at the Automatic Water Level Recorder (AWLR) Rowotamtu, and second, based on field observations of extreme flood events. The model results show that the best interpolation method for obtaining a high-resolution DEM is bilinear. The first flood data validation produces an RMSE value of 0.113, while the second is slightly higher at 0.316. Both indicate good model accuracy, and the flood inundation maps generated can be used demonstrate flood hazards.
It is difficult to accurately predict the water levels of an open-channel water transfer project with pumping stations due to various uncertainties. To solve this problem, this paper proposes a new water level prediction model based on K Nearest Neighbor Algorithm-Ensemble Kalman Filter (KNN-ENKF). A hydrodynamic model is used to construct the water regime database, and the KNN is used to search for the data that best matches the current water regime state, which is taken as the initial value of the model to ensure the prediction accuracy in the initial stage. Then, ENKF is used to real-time correct the water regime state and reduce error accumulation. A case study is conducted with the Songzhuang-Bushang section of the Jiaodong Water Transfer Project, China. It is found that the KNN-ENKF model can significantly improve the water level prediction accuracy with an average error of less than 0.04 m.
Anthropogenic discharges into coastal waters introduce fecal pathogens that threaten both aquaculture sustainability and human health. In shrimp farming, workers are frequently exposed to contaminated estuarine water, underscoring the importance of evaluating occupational health risks. This study assessed fecal contamination in estuarine water used for shrimp aquaculture in San Blas, Nayarit, Mexico, and estimated the probability of gastrointestinal infection (GI) of shrimp farm workers across dry and rainy seasons under two exposure scenarios: immersion (INM) and hand-to-mouth contact (HMC). Escherichia coli (EC) and Enterococcus (ENT) were used as microbial indicators in a quantitative microbial risk assessment model. A total of 56.7% and 96.7% of samples (n = 30) exceeded recommended limits for EC (1.00 & times;10 & sup3; CFU/100 mL) and ENT (35 CFU/100 mL), respectively. Microbial loads did not differ significantly among sites (p > 0.05) but showed seasonal variation (p < 0.05). The highest GI risk was associated with INM exposure, particularly in the dry season for EC (1.65 & times;10(-)& sup1;) and in both seasons for ENT (5.47 & times;10(-)& sup1; to 5.96 & times;10(-)& sup1;). HMC exposure presented lower but notable risks, ranging from 1.89 & times;10(-)(4) to 6.78 & times;10(-)(5) for EC, and from 3.85 & times;10(-)& sup2; to 7.59 & times;10(-)& sup2; for ENT. Seasonal dynamics of contamination pose significant occupational health risks for shrimp farm workers and highlight the need to reinforce water quality management and safer aquaculture practices.
Water scarcity is a critical challenge in Jordan, intensified by its arid climate, limited water resources, and growing demand across different sectors. The Um Naa'am watershed, located in a water-stressed area, requires sustainable solutions to enhance water availability and address climate change. This study aims to assess the suitability of Green Water Harvesting (GWH) interventions-including contour ridges, runoff strips, and marabs-in the Um Naa'am watershed using Geographic Information Systems (GIS) technology. GWH has shown promise in supplementing water resources, increasing soil moisture, improving vegetation cover, boosting crop productivity, and enhancing groundwater recharge. Spatial analysis, data reclassification, and multi-criteria evaluation were used in ArcGIS, taking into consideration topography and soil characteristics to analyze the suitability for GWH. In the present study, it was found that 42.46% of the watershed is suitable for runoff strips, 29.30% for contour ridges, and 1.64% for Marabs. The results may indicate that techniques for GWH can effectively act at deeper levels regarding water scarcity management, increasing resilience for more sustainable agriculture in this region. The integration of GWH and GIS thus provides a data-driven approach toward solving water-related problems, which is very important in terms of food security and sustainable development in semi-arid regions.
This study investigates the spatio-temporal variation of stable isotopes (delta & sup1;O-8, delta & sup2;H), deuterium excess (d-excess) in rainwater and surface water in the Mekong Delta, Vietnam to identify hydrological processes and freshwater-seawater interaction. The delta & sup1;O-8 and delta & sup2;H of the rainwater samples from five sites experienced seasonal change, with an average delta & sup1;O-8 and delta & sup2;H of -5.35 parts per thousand and -35.74 parts per thousand, respectively. D-excess ranged from -13.25 parts per thousand to 26.09 parts per thousand with an average of 7.07 parts per thousand, suggesting mixing of moisture sources and post-depositional evaporation. Surface waters were generally enriched (-4.23 parts per thousand for delta & sup1;O-8; -30.16 parts per thousand for delta & sup2;H), with inland river waters the most depleted (-6.17 parts per thousand for delta & sup1;O-8) and coastal waters the most enriched (-1.60 parts per thousand to -1.87 parts per thousand for delta & sup1;O-8), due to effects of tides and evaporation. Isotopic concentrations became more positive closer to the coast, and significant and positive relationships were observed between chloride and delta & sup2;H (r = 0.74) and delta & sup1;O-8 (r = 0.60; p < 0.001). Rainwater presented the highest d-excess values, indicating a greater evaporative influence on surface waters. These observations suggest that the isotope-salinity relation may support to understand the influences of the mixing of water sources, seasonal recharge, and saltwater intrusion. The results also indicate that stable isotopes could be recommended as reliable hydrological indicators in some deltaic regions subjected to clearly distinct climatic and anthropogenic influences for analyzing hydrological processes and providing insights into water management.
Water scarcity is a critical global issue, specifically in regions with complex water dependency dynamics. This study analyzes the efficiency of two models, the Bankruptcy Theory and the Nash Bargaining Solution (NBS), for equitable water distribution in Anbar Province, Iraq, from 2019 to 2040. The research compares these models under varying water availability conditions to address water distribution across agricultural, industrial, and domestic sectors. The Bankruptcy model allocated a uniform water supply across the sectors, whereas the NBS prioritized agriculture's domain demand. Overtime, both models showed a declining trend in fulfillment rates for all sectors due to an increasing water shortage. The study employed the Mean Absolute Error (MAE) and Reliability Index (RI) to determine stability, with values of 0.037 and 0.076 for the Bankruptcy model, and 0.035 and 0.073 for NBS, respectively, highlighting a slightly higher reliability for the NBS. This research signifies the necessity for strategic management that integrates forecasting and stakeholder participation to execute balanced and sustainable water distribution.
Urban flooding presents a critical challenge worldwide, driven by rapid urbanization, inadequate drainage systems, and climate change. In developed countries, aging infrastructure and increasing precipitation intensities worsen flood risks. In contrast, developing nations struggle with uncontrolled urban sprawl, poor stormwater and waste management, and limited financial resources for flood mitigation. Pakistan's major cities, including Peshawar, frequently experience urban flooding, resulting in infrastructure damage, economic loss, and disrupted livelihoods. This study explores the role of Green Infrastructure (GI) in enhancing urban flood resilience in Peshawar, using Khamosh Colony as a case study which faces frequent flooding due to poor drainage, and encroachments. Climate projections (2015-2100) were analyzed for two Shared Socioeconomic Pathways (SSPs) using the best-performing Global Climate Models (GCMs), revealing a significant increase of 10-40% in precipitation for smaller return periods (2-10 years) and up to 61.66% and 81.35% increases for 200-year events under SSP2-4.5 and SSP5-8.5, respectively, consistent with severe flooding observed in 2022. Using SWMM, standalone and combined GI strategies were assessed for their flood mitigation potential under 2-and 5-year return period rainfall events, including future climate scenarios. Economic feasibility was evaluated using 2024 market rates while community preferences were assessed through surveys conducted in Peshawar via Kobo Toolbox. Among the options, permeable pavement (standalone) and permeable pavement with bioretention (combined) emerged as the most effective and preferred solutions. A novel aspect of this study is the integration of 1D hydrodynamic modeling with 3D visualization in SWMM and GIS, providing stakeholders with an intuitive understanding of pre-and post-GI flood scenarios. This enhances public awareness, facilitates participatory decision-making, and supports investment prioritization. By addressing the lack of integrated flood modeling and decision-support tools in Pakistan, this research fills a key gap and offers a replicable framework for evidence-based, climate-adaptive, and community-inclusive urban planning to build flood-resilient cities.
Flood risk assessment in ungauged watersheds remains a challenge due to limited flow data. This study investigates peak discharge and flood risk in the ungauged Wupa River Basin, Nigeria, using Manning's equation, the Kinematic Wave Parameter (KWP) model, and the Natural Resources Conservation Service-Curve Number (NRCS-CN) method. The thorough analysis provides valuable insights into peak discharge dynamics, underscoring the significance of accurate hydrological modeling and watershed characterization. Results indicate that Manning's equation and KWP produce similar peak discharge estimates (e.g., 155.71 m3/s and 155.98 m3/s for September 2022), whereas the NRCS-CN method yields significantly higher values (376.80 m3/s for the same month) due to its sensitivity to soil and land use characteristics. The study also addresses the potential inadequacy of the NRCS-CN method for forested areas in West Africa. These findings provide critical insights for flood management and infrastructure planning in ungauged basins across West Africa.
Allegheny County Sanitary Authority, based in Pittsburgh, Pennsylvania, is implementing its Clean Water Plan to manage sewage overflows in compliance with a Federal Consent Decree. ALCOSAN and CDM Smith developed receiving water quality models to support alternative analysis and facility sizing. The technical approach involved statistical calibration for flow and bacteria utilizing an 11,000+ node PCSWMM model. The tributaries were simulated using SWMM and the main rivers using EPA's Environmental Fluid Dynamics Code. Covering 280 miles (451 kms), the model simulates hydrology, river hydraulics, bacteria loading, and temperature-dependent decay. A literature review identified prior studies describing model calibration assessment methods and calibration statistics for flow and nutrients with limited information available for bacteria. ALCOSAN and CDM Smith developed bacteria calibration methods and metrics to objectively assess model calibration suitability for intended purposes. Calibration results for bacteria show a strong fit to observed data, with the root mean square error (RMSE) of the log transformed counts of fecal coliform of between 0.51 and 0.95 and for E. coli of 0.57 and 0.83. Since the model simulated bacteria counts were within 1 log of the observed data, the model is suitable for the purpose of forecasting attainment with water quality standards over a typical year.
The demand for designated sites to receive sludge waste from marine and coastal dredging projects is rising in Vietnam. Coastal areas are particularly promising for such purposes. Evaluating the dispersion of submerged sludge in the marine environment is crucial for assessing potential impacts on adjacent ecological zones that require protection. Tidal currents in the proposed discharge area are a significant factor influencing sludge propagation. The results indicate that varying average tidal currents affect horizontal propagation and result in different changes in bottom topography. Simulations demonstrate that underwater mud could dissolve to a great distance from the discharge site when discharged at an average rate of 100,000 m3/month. The study utilized the Telemac3D numerical model, which addressed the problem of sludge dispersion through diffusion and convection and incorporated the TOMOWAC module to solve the issue of wave propagation along the coast. The TELEMAC-3D numerical model is used to solve the problem of sediment dispersion through combined diffusion and advection processes, which has been integrated with the TOMOWAC wave propagation model, which simulates wave dynamics in coastal zones. The combined approach is applied to investigate the impact of mean tidal currents on the dispersal of dredged sediment, considering different discharge timing scenarios.
Lake Edku is one of the northern Nile Delta lakes in Egypt. It suffers from a high level of eutrophication. Lake Edku suffers from pollution from a variety of sources, including municipal and agricultural waste. This study presents a simulated model for a hydrology system that provides a challenge in predicting hydraulic residence time or how water contaminants circulate over the time. Hydraulic residence time is realized as a measure of how rapidly water quality will be affected by changes in pollutant loadings. A hydrological model was created to predict the hydraulic residence time for Edku Lake using a modular three-dimensional finite-difference groundwater flow model called "MODFLOW". The model revealed that the accurate hydraulic residence time for Lake Edku is 14, 25, 20, and 10 days for autumn, winter, spring, and summer correspondingly, with a 17.25-day yearly average. However, this study presents many challenges in understanding how hydraulic residence time is determined by considering the interaction between surface water and subsurface water. Lake hydraulic residence time calculations are considered a useful water quality management tool in preparing the proceedings and solution scenarios that in turn will contribute to lake restoration efforts.
An effective urban drainage system is the primary key to overcoming the risk of flooding due to high rainfall intensity. Tempe District, Wajo Regency, South Sulawesi, is one of the areas facing severe problems in its drainage system. The flooding in this area is caused by the inability of conventional drainage systems to handle high surface water runoff, especially during periods of intense rain. This research introduces a new approach to sustainable drainage systems by applying the infiltration well technique. The analysis was carried out by considering the infiltration well parameters, such as a depth of 3 m, a radius of 0.6 m, and a soil permeability of 5 x 10-5 m/s. This infiltration well was implemented in the upstream subcatchment area of the Sengkang City primary channel. The results of the analysis show that the use of infiltration wells can produce a significant positive impact in reducing flood risk. In a five-year return period, the flood volume can be reduced by 12.15 x 103 m3; in a 10-year return period, the volume reduction reaches 13.16 x 103 m3. Although the effectiveness of infiltration wells is limited to 9% and 6% for each return period, this approach significantly contributes to minimizing the impact of flooding in affected areas. Hopefully, these findings can contribute to planning and managing urban water systems, especially in areas vulnerable to flood risk.
