Lateral Inflow Research Articles

On Steady Two-dimensional Free-surface Flows with Spatially-varied Discharges

Abstract In an open-channel, the transition of a flow from a subcritical to a supercritical state may occur as a result of a lateral inflow or outflow that produces a streamwise discharge variation. Apparently, such a transition cannot be modeled accurately by a conventional hydrostatic pressure approach. In this study, a depth-averaged model that accounts for the effects of a spatially-varied discharge and a non-hydrostatic pressure distribution was developed and applied to simulate the transcritical flow in a lateral-spillway channel and the subcritical flow in a main channel fitted with side weirs. The model results for the axial free-surface profile and variation of discharge in the main channel were compared with the results of a shallow-flow model and experimental data, thereby resulting in a closer match to the measurements than the shallow-flow model. Overall, the investigation results confirmed the efficiency and validity of the non-hydrostatic depth-averaged model in simulating the mean flow characteristics of the subcritical and transcritical free-surface flows with spatially increasing or decreasing discharges, thus demonstrating its potential to be used as a numerical tool in engineering practice.

Effect of Different Conduit-Network Recharge Ways on Karst Spring Simulation

AbstractTwo recharge ways, point inflow and lateral inflow, exist on the conduit network in karst aquifers. Point inflow is commonly included in pipe-flow models, but lateral inflow along the condu...

Numerical study of transport pathways of 137Cs from forests to freshwater fish living in mountain streams in Fukushima, Japan

The accident at the Fukushima Dai-ichi Nuclear Power Plant in 2011 released a large quantity of radiocesium into the surrounding environment. Radiocesium concentrations in some freshwater fish caught in rivers in Fukushima Prefecture in October 2018 were still higher than the Japanese limit of 100 Bq kg−1 for general foodstuffs. To assess the uptake of 137Cs by freshwater fish living in mountain streams in Fukushima Prefecture, we developed a compartment model for the migration of 137Cs on the catchment scale from forests to river water. We modelled a generic forest catchment with Fukushima-like parameters to ascertain the importance of three export pathways of 137Cs from forests to river water for the uptake of 137Cs by freshwater fish. The pathways were direct litter fall into rivers, lateral inflow from the forest litter layer, and lateral transfer from the underlying forest soil. Simulation cases modelling only a single export pathway did not reproduce the actual trend of 137Cs concentrations in river water and freshwater fish in Fukushima Prefecture. Simulations allowing a combined effect of the three pathways reproduced the trends well. In the latter simulations, the decreasing trend of 137Cs in river water and freshwater fish was due to a combination of the decreasing trend in the forest leaves/needles and litter compartments, and the increasing trend in soil. The modelled 137Cs concentrations within the forest compartments were predicted to reach an equilibrium state at around ten years after the fallout due to the equilibration of 137Cs cycling in forests. The model suggests that long term 137Cs concentrations in freshwater fish in mountain streams will be controlled by the transfer of 137Cs to river water from forest organic soils.

A River Temperature Model to Assist Managers in Identifying Thermal Pollution Causes and Solutions

Thermal pollution of rivers degrades water quality and ecosystem health, and cities can protect rivers by decreasing warmer impervious surface stormwater inflows and increasing cooler subsurface inflows and shading from riparian vegetation. This study develops the mechanistic i-Tree Cool River Model and tests if it can be used to identify likely causes and mitigation of thermal pollution. The model represents the impacts of external loads including solar radiation in the absence of riparian shade, multiple lateral storm sewer inflows, tributaries draining reservoirs, groundwater flow, and hyporheic exchange flow in dry weather steady flows and wet weather unsteady flows. The i-Tree Cool River Model estimates the shading effects of the riparian vegetation and other features as a function of heights and distances as well as solar geometry. The model was tested along 1500 m of a New York mountain river with a riparian forest and urban areas during 30 h with two summer storm events in 2007. The simulations were sensitive to the inflows of storm sewers, subsurface inflows, as well as riparian shading, and upstream boundary temperature inflows for steady and unsteady conditions. The model simulated hourly river temperature with an R2 of 0.98; when shading was removed from the simulation the R2 decreased 0.88, indicating the importance of riparian shading in river thermal modeling. When stormwater inflows were removed from the simulation, the R2 decreased from 0.98 to 0.92, and when subsurface inflows were removed, the R2 decreased to 0.94. The simulation of thermal loading is important to manage against pollution of rivers.

Aerodynamic characteristics of flapping wings under steady lateral inflow

This experimental study investigates the effect of a uniform lateral inflow on the aerodynamic characteristics of flapping wings. Seven designated sideward ratios in the hovering condition and in the presence of a contralateral wing and a body were taken into account as variables in order to secure a better understanding of wing–wing and/or wing–body interactions under the lateral inflow. Our results from the single-wing cases clarified that an inflow running from the wingroot strengthened the leading-edge vortex, thereby augmenting the aerodynamic force/moment. The inflow running in the opposite direction drastically bent the leading-edge vortex to the trailing edge, but the cycle-averaged aerodynamic force/moment was barely changed. This led to substantial imbalances in the force/moment on the two wings. The roll moment on a centre of gravity and the static margin suggested flight instability in the lateral direction, similar to previous studies. We found that the wing–wing interaction was not completely negligible overall under a lateral inflow. A massive downwash induced by the wing on the windward side nearly neutralized the aerodynamic force/moment augmentations on the other wing with lower effective angles of attack. The wing–wing interaction also gave rise to a low-lift high-drag situation during the pitching-up wing rotation, resulting in greater side force derivatives than the theory of flapping counterforce. Further calculations of the roll moment and the static margin with the centre of gravity showed that the wing–wing interaction can improve static stability in the lateral direction. This mainly stemmed from both the attenuation of the lift augmentation and the elimination of the positive roll moment of the flapping-wing system.

A bivariable coupling model for river channel routing developed from the flow continuity equation and its application

In this study, a bivariable coupling model for river channel routing is presented. The proposed model is developed from the Priessmann 4-point implicit differential scheme with a weight coefficient of river flow continuity equation. It is based on the transformation of two different expression forms of river channel storage equation. Furthermore, we consider the impact of lateral inflow along the study river channel from another perspective. In this paper we deduct lateral inflow from the lower section instead of adding lateral inflow to the upper section. In order to be representative of geographical range, river channel characteristics, flood magnitude, hydraulic characteristics and time, the proposed model is tested in 38 river channels of 6 river systems in China by using observed data during flood season. The rationality of model structure and the validity of model simulation are examined comprehensively. Comparison between the proposed model and Muskingum model shows that the proposed model can improve the simulation accuracy. The results show that the simulation accuracy and stability of the bivariable coupling model is much better than that of the Muskingum model.

Multiparameter daily time-series analysis to groundwater recharge assessment in a caldera aquifer: Roccamonfina Volcano, Italy

The definition of hydrogeological conceptual models sometimes suffers on uncertainties depending on the available dataset. The availability and the elaboration of long-term hydrogeological dataset allow ensuring a better definition of the aquifer dynamics and features. One of the main features, which can benefice on long-term datasets, is the recharge quantification. According to the literature, several methods exist to calculate the recharge and to get a deeper insight in recharge mode assessment. Most of them allow the quantification of infiltrating water by means of meteo-climatic data and land use information. In this research, a combined approach on hydrogeological time-series is proposed. The Cross-Correlation among the rainfall and the piezometric levels was applied to point out the response time of each aquifer layer. In addition, the Water Table Fluctuation method was used to indirectly quantify the recharge.The study area is the Roccamonfina Volcano caldera (Italy), where lateral inflows are absent, and the almost total natural groundwater discharge occurs in the Savone delle Ferriere stream. Here, a monitoring scheme of the major hydrogeological features was implemented. The local rainfall, the groundwater levels in 2 wells tapping the different aquifer layers, and the river stage of the Savone delle Ferriere stream were measured daily during the 2016–2017 period. The analyses defined different recharge modes for each aquifer layer. The aquifer recharge rates, calculated with different approaches, are comparable to each other and in line with the mean groundwater discharge through the Savone delle Ferriere streambed springs.

Estimation of reservoir inflow with significant lateral inflow by using the adjoint equation method

Reservoir inflow estimation is important in flood control operation. Reservoir inflow includes three components, namely, upstream, tributary, and lateral inflow. However, the lateral inflow, which has a significant contribution to reservoir inflow during flood seasons, is difficult to estimate in regions where precipitation or meteorological data are lacking. A reverse model based on the adjoint equation method (AEM) was proposed to improve the estimated accuracy of reservoir inflow without using rainfall data. The model inverted the lateral inflow on the basis of observed hydraulic characteristic data, such as water levels and discharges. The AEM, which is considered an optimization method, determines the optimal lateral inflow by minimizing misfits between the observed and simulated data. The capability of the AEM was verified by two synthetic examples with varied boundary conditions. After running the forward model to solve one-dimensional Saint-Venant equations, the resulting water level hydrographs were used as known observations for the inversion. The practical applicability was tested by reproducing a historical flood event of the Three Gorges Reservoir by using water level data and outflow hydrograph. Results demonstrated that the AEM could successfully invert lateral and reservoir inflows by using observed data and has practical applicability in complicated reservoirs.

Integration of SWAT and QUAL2K for water quality modeling in a data scarce basin of Cau River basin in Vietnam

Water quality modeling in a river basin often faces the problem of having a large number of parameters yet limited available data. The important inputs to the water quality model are pollution concentrations and discharge from river tributaries, lateral inflows and related pollution load from different sources along the river. In general, such an extensive data set is rarely available, especially for data scarce basins. This makes water quality modeling more challenging. However, integration of models may be able to fill this data gap. Selection of models should be made based on the data that is available for the river basin. For the case of Cau River basin, the SWAT and QUAL2K models were selected. The outputs of SWAT model for lateral inflows and discharges of ungauged tributaries, and the observed pollutant concentrations data and estimated pollution loads of sub-watersheds were used as inputs to the water quality model QUAL2K. The resulting QUAL2K model was calibrated and validated using recent water quality data for two periods in 2014. Four model performance ratings PBIAS, NSE, RSR and R2 were used to evaluate the model results. PBIAS index was chosen for water quality model evaluation because it more adequately accounted for the large uncertainty inherent in water quality data. In term of PBIAS, the calibration and validation results for Cau River water quality model were in the “very good” performance range with ǀPBIASǀ<15%. The obtained results could be used to support water quality management and control in the Cau River basin.

Flood Inundation Mapping of the Sparsely Gauged Large-Scale Brahmaputra Basin Using Remote Sensing Products

Sustainable water management is one of the important priorities set out in the Sustainable Development Goals (SDGs) of the United Nations, which calls for efficient use of natural resources. Efficient water management nowadays depends a lot upon simulation models. However, the availability of limited hydro-meteorological data together with limited data sharing practices prohibits simulation modelling and consequently efficient flood risk management of sparsely gauged basins. Advances in remote sensing has significantly contributed to carrying out hydrological studies in ungauged or sparsely gauged basins. In particular, the global datasets of remote sensing observations (e.g., rainfall, evaporation, temperature, land use, terrain, etc.) allow to develop hydrological and hydraulic models of sparsely gauged catchments. In this research, we have considered large scale hydrological and hydraulic modelling, using freely available global datasets, of the sparsely gauged trans-boundary Brahmaputra basin, which has an enormous potential in terms of agriculture, hydropower, water supplies and other utilities. A semi-distributed conceptual hydrological model was developed using HEC-HMS (Hydrologic Modelling System from Hydrologic Engineering Centre). Rainfall estimates from Tropical Rainfall Measuring Mission (TRMM) was compared with limited gauge data and used in the simulation. The Nash Sutcliffe coefficient of the model with the uncorrected rainfall data in calibration and validation were 0.75 and 0.61 respectively whereas the similar values with the corrected rainfall data were 0.81 and 0.74. The output of the hydrological model was used as a boundary condition and lateral inflow to the hydraulic model. Modelling results obtained using uncorrected and corrected remotely sensed products of rainfall were compared with the discharge values at the basin outlet (Bahadurabad) and with altimetry data from Jason-2 satellite. The simulated flood inundation maps of the lower part of the Brahmaputra basin showed reasonably good match in terms of the probability of detection, success ratio and critical success index. Overall, this study demonstrated that reliable and robust results can be obtained in both hydrological and hydraulic modelling using remote sensing data as the only input to large scale and sparsely gauged basins.

One-dimensional coupled modeling of bed evolution and bank erosion processes in the Middle Yangtze River

After the operation of the Three Gorges Project, the Middle Yangtze River has continuously suffered from channel degradation, along with significant bank erosion processes in local subreaches, especially in the Jingjiang Reach, which may cause serious problems to channel stability, flood control management and navigation safety. In this study, a one-dimensional coupled morphodynamic model for bed evolution and bank erosion processes was proposed, including three modules for hydro- and sediment dynamics, groundwater flow and bank erosion, with the mode of plannar failure in the Upper Jingjiang Reach (UJR) and the mode of cantilever failure in the Lower Jingjiang reach (LJR) being considered. The proposed model was applied respectively to simulate the fluvial processes in the Jingjiang Reach in 2005, 2007 and 2010, in order to conduct a detailed process of model calibration and validation. These calculated results show that: (1) The proposed model accurately reproduced the flow and sediment transport processes, with the root mean squared errors of daily averaged discharge and suspended sediment concentration far less than the corresponding mean values. Besides, the model also predicted the major occurrence regions of serious bank erosion processes; (2) bank failure was mainly controlled by fluvial erosion in the Jingjiang Reach, with more than 50% of cantilever failure events in the LJR occurring during the flood period; and (3) the groundwater level variation was delayed, as compared with the river stage change, which could also obviously influence bank erosion processes in the UJR. Furthermore, multiple test runs were conducted to investigate the influences of the variations in outlet river stage and bank soil properties on the processes of bank erosion. These results from test runs indicate that: (1) If the outlet river stage was increased due to a higher lateral inflow from the Dongting Lake, the bank retreat width in the Jingjiang Reach would be decreased, resulting from the reduced longitudinal water surface slope and mean velocity in section; (2) the calculated bank retreat width at a section was most sensitive to an reduction in critical shear stress of bank soil, especially in the LJR. However, the calculated bank retreat width in the UJR was also sentitive to the change in bank soil cohesion, but it did not monototically decrease with an increase in soil cohesion. This is because the varitation in soil cohesion can lead to changes in the number, timing and individual failed block volumes of bank failure events. As the failure number keeps unchanged, an increase in soil cohesion would lead to a delayed occurrence of bank failure event and thus a larger failed block volume, which finally results in a larger total retreat width.

Simplified two-dimensional modelling to constrain the deep groundwater contribution in a complex mineral water mixing area, Riardo Plain, southern Italy

Complex hydrogeological systems require detailed knowledge of aquifer dynamics to ensure appropriate and sustainable management of the groundwater resource. The Riardo Plain aquifer, southern Italy, is a strategic resource for conjunctive uses; nevertheless, the conceptual model still suffers some uncertainties due to the presence of a deep lateral inflow through the carbonate basement. Therefore, the realisation of a 3D numerical model at catchment scale needs preliminary tests to constrain the possible additional inflow rate, which is at the moment only estimated through the results of the groundwater budget calculation. A 2D section of the mixing area was modelled using FEFLOW in order to test the hypothesis of a combined recharge. Seven versions of the same model were calibrated over an increasing number of adjustable parameters according to their sensitivity. The most efficient model version was identified according to the calculated information criteria and the sum of squared-weighted residuals. In the second phase of the work, nine model scenarios characterised by different deep inflow rates were calibrated and validated according to the same procedure of the first model, in order to identify the range of possible acceptable solutions. The most likely deep inflow rate is 34 ± 4% of the total recharge, corresponding to an estimated deep inflow of 415 ± 50 L/s in the Riardo Plain aquifer through the carbonate basement. This methodological approach will be the basis of following numerical 3D numerical models of the Riardo Plain and can be a valuable tool in conceptualising similar mineral water areas.

Features of the groundwater formation of the main aquifers of St.Petersburg and suburbs on the data of chemical and isotope composition

The main aquifers used for water supply in St. Petersburg and the Leningrad region contain waters, TDS and chemical composition of which vary considerably with the distance from modern recharge areas, as well as depending on the composition of the host rocks. The waters of the Quaternary, Devonian, Ordovician and Cambrian-Ordovician and Vendian aquifers were sampled and analyzed. With low mineralization, a bicarbonate calcium-magnesium composition predominates in waters of low TDS, while with its increase over 400-600 mg/dm3, chlorides dominate in the anion composition, and sodium – in cation composition. In some cases, low-mineralized water contains significant amounts of iron and can be considered as mineral medicinal waters. A regional feature is the local excess (sometimes significant) of the activity of natural radionuclides over the intervention levels. To identify the formation conditions, data on the isotopic composition (deuterium and oxygen content-18) of groundwater were used. The greatest variety of isotopic compositions is observed in the waters of the Vendian aquifer. On the Karelian Isthmus, it contains modern water (which is also indicated by tritium). When moving to the South, in the direction of increasing TDS, the isotopic composition of water in the Vendian aquifer gets lighter, up to the appearance of waters with obvious signs of cryogenic metamorphosis. Light isotopic compositions are explained by the formation of groundwater in the cold climatic period, which ended in this area at least 12 thousand years ago. Changes in the isotopic composition and chemistry of the waters of the Vendian aquifer are simultaneous with an increase in their age at a distance from the recharge area. Hence, in natural conditions, there is no areal recharge of the aquifer outside the area of its outcome to the land surface or under the permeable Quaternary deposits. In terms of water management, this means that its resources in the area, where TDS exceeds 0.7–1.0 g/dm3 should be calculated only as lateral inflow.

Uncertainty estimation in hydrodynamic modeling using Bayesian techniques

ABSTRACT Uncertainty estimation analysis has emerged as a fundamental study to understand the effects of errors inherent to hydrodynamic modeling processes, of aleatory and epistemic nature, due to input data such as discharge, topography and bathymetry, to the structure and parameterization of the mathematical models used and to their necessary boundary and initial conditions. The study reported in this paper sought to apply a Bayesian-based methodology, associated with thousands of Markov Chain Monte Carlo simulations, in order to identify and quantify the uncertainty related to the Manning’s n roughness coefficient in a 1D hydrodynamic model and the total uncertainty involved in the prediction of hydrographs and water surface elevation profiles resulting from flood routing through a reach located in the upper São Francisco river, between the Abaeté river outlet and the town of Pirapora. The results show that the Bayesian scheme allowed an adequate posterior identification of the parametric uncertainties and of those associated to other sources of errors, with important changes in the prior probability distributions. In addition, the residuals analysis corroborates the applicability of the method to the analysis of uncertainties in hydrodynamic modeling through the use of a more flexible likelihood function than the classical one based on the hypotheses of normality, homoscedasticity and uncorrelated residuals. Future work includes the sensitivity evaluation of the posterior distributions to the addition of lateral inflows, especially concerning the residuals serial correlation, as well as the adoption of other variables to update the prior uncertainties, and the validation of the methodology through the use of the posterior distributions to estimate the total uncertainty involved in the prediction of floods other than the ones used in the inference process.

High-spatial-resolution streamflow estimation at ungauged river sites or gauged sites with missing data using the National Hydrography Dataset (NHD) and U.S. Geological Survey (USGS) streamflow data

The need for a method of estimating streamflow with both high-quality and high spatial resolution, particularly for ungauged sites, is critical under current circumstances: intensifying competition over water resources and limited streamgages. A source of accurate and timely computations of streamflow, particularly at high spatial resolutions, has been the National Hydrograph Dataset (NHD), a comprehensive geographic information system (GIS) dataset of vector-based surface water features such as streams, lakes, and streamgages in fine detail. Utilizing the NHD with streamflow data from the U.S. Geological Survey and usage records of local water utilities, this paper proposes a simple streamflow estimation method that computes streamflow at any point on river reaches of the NHD with valid hydrograph data and tests the method in a local 613 square mile watershed. The method assumes that linearly connecting the timings of peak or bottom-base flows from upstream to downstream hydrographs leads to retracing upstream lateral inflows that have eventually arrived at a user-selected site between the upstream and downstream gauge stations of the hydrographs at any given time in a common period of record between the two hydrographs. Subsequently, the lateral inflows are added up to become the streamflow for a given site at a given time. NHD river networks and ArcGIS tools identify the locations of lateral inflows and the necessary parameters of the method. This paper assesses the results of the method by comparing them to measured streamflows through recommended evaluation statistics and visual inspection. The method has yielded promising results, including values of the Nash-Sutcliffe efficiency within 0.83 and 0.99 for daily streamflow estimates over seven years. It also credibly reconstructs missing daily streamflow over a considerable number of years.

Real-time flood forecasting downstream river confluences using a Bayesian approach

Accurate forecast stages at river sections is of paramount importance to properly address Flood Forecasting and Warning Systems (FFWSs) operating in real-time. The forecast values can be provided by flood wave routing models to be implemented when gauged sections are operative along the channel. Different models have been proposed in the literature and the forecast can be approached by neglecting or involving the contribution of lateral inflows. Among the latter, recently STAFOM-RCM (STAge FOrecasting Model-Rating Curve Model) has been proposed assuming a lateral contribution uniformly distributed along the reach. Therefore, the model application is not suitable for future stage prediction at hydrometric sections located just downstream river confluences. To overcome this issue, we propose a methodology that exploits the probabilistic forecast estimated at a gauged site on a tributary through a Bayesian approach and the probabilistic relationship between the stages recorded here and the ones at a downstream site located along the main channel, where the forecasted stage estimate is of interest.The Paglia River basin, in central Italy, is selected as case study. The results indicate that the procedure can be useful to address real-time hydraulic risk management even at river sections located downstream important confluences, provided that gauged sites are operative along the tributary.

Variance based sensitivity analysis of 1D and 2D hydraulic models: An experimental urban flood case

This paper explores spatial sensitivities of 1D and 2D shallow water (SW) models of branched urban flood flows, based on an experimental data-set and a variance decomposition method for various combination of uncertainty sources. General sensitivity patterns of SW model for subcritical flows show that: simulated water height variance is explained upstream by inflow discharge and roughness whereas downstream it is fully explained by downstream water height, influence of lateral inflows propagates in both directions. High sensitivities to roughness can be local in space thus identifying the strongest hydraulic controls for orienting calibration efforts is needed. 2D sensitivities show: the filtering effect of branched network topography on inflow, the zone of influence of boundary conditions, the role of large streets as global flow pattern separators, the difference in roughness sensitivity patterns with 1D. This sensitivity analysis of SW models could be a base for studying flow path and uncertainty propagation.

A variable parameter bidirectional stage routing model for tidal rivers with lateral inflow

Water stage variations are complicated in tidal rivers due to the combination of upstream flood and downstream tide. This study proposed a bidirectional stage routing model (BSR) for tidal rivers by considering the stage hydrograph as the overlay of bidirectional propagation of upstream flood wave and downstream tidal wave. The basic stage routing equations derived from the storage equation and water balance equation are used to calculate the upstream flood wave routing and the downstream tidal wave propagation, respectively. The lateral inflow can be directly specified as an additive term in the basic equation of BSR model or indirectly estimated by a lateral flow rate reflecting the proportion of lateral inflow to the upstream water. Parts of the model parameters are time-variable to account for the effect of water surface slope on water stage. The model inputs include stage hydrographs at the upstream and downstream boundaries. The channel geometric characteristics data are not required when the average channel width is estimated as a parameter. The case study results in the tidal reaches of the Caoe River and Qiantang River in China demonstrate that the BSR model performs well in water stage simulation. With relatively simple structure, modest data requirement and stable performance, the physically-based BSR model has the potential for water stage routing in tidal rivers when channel geometry data are not available.

DETERMINATION OF DOWNSTREAM FLOOD FLOW CONSIDERING INPUTS FROM DIFFERENT UPSTREAM RIVERS USING ANN

For estimating and forecasting of flood event, researchers and engineers mostly use the Muskingum flood routing method which is widely used throughout the world. The application of two parameter based Muskingum model is valid only for single inflow flood routing without any lateral inflow into the routing reach. However, normally a river is fed by a number of branch channels or rivulets at various upstream points. So, the single inflow-outflow Muskingum model cannot be applied in such situation. To overcome this problem, artificial Neural Network (ANN) has been applied in a river system considering inflow from various upstream rivers with a common outflow section. A simple static ANN model have been developed using concurrent discharge data. The model is applied in Mississippi River network starting from St. Louis, Montana to downstream section at Thebes, Illinois. In this reach, from St. Louis to Thebes, in the Mississippi river, a total of six lateral inflows confluence to the main river at different locations. Using ANN model, considering water discharge as input from all the upstream sections, water discharge at the most downstream section, Thebes is computed. Statistical performance analysis of the estimated data shows that ANN can be efficiently used for estimation of flood flow considering multiple inflows.

Delineating multiple salinization processes in a coastal plain aquifer, northern China: hydrochemical and isotopic evidence

Abstract. Groundwater is an important water resource for agricultural irrigation and urban and industrial utilization in the coastal regions of northern China. In the past 5 decades, coastal groundwater salinization in the Yang–Dai river plain has become increasingly serious under the influence of anthropogenic activities and climatic change. It is pivotal for the scientific management of coastal water resources to accurately understand groundwater salinization processes and their causative factors. Hydrochemical (major ion and trace element) and stable isotopic (δ18O and δ2H) analysis of different water bodies (surface water, groundwater, geothermal water and seawater) were conducted to improve understanding of groundwater salinization processes in the plain's Quaternary aquifer. Saltwater intrusion due to intensive groundwater pumping is a major process, either by vertical infiltration along riverbeds which convey saline surface water inland, and/or direct subsurface lateral inflow. Trends in salinity with depth indicate that the former may be more important than previously assumed. The proportion of seawater in groundwater is estimated to have reached up to 13 % in shallow groundwater of a local well field. End-member mixing calculations also indicate that the geothermal water with high total dissolved solids (up to 10.6 g L−1) with depleted stable isotope compositions and elevated strontium concentrations (&gt; 10 mg L−1) also mixes locally with water in the overlying Quaternary aquifers. This is particularly evident in samples with elevated Sr ∕ Cl ratios (&gt; 0.005 mass ratio). Deterioration of groundwater quality by salinization is also clearly exacerbated by anthropogenic pollution. Nitrate contamination via intrusion of heavily polluted marine water is evident locally (e.g., in the Zaoyuan well field); however, more widespread nitrate contamination due to other local sources such as fertilizers and/or domestic wastewater is evident on the basis of NO3 ∕ Cl ratios. This study provides an example of how multiple geochemical indicators can delineate different salinization processes and guide future water management practices in a densely populated water-stressed coastal region.