Nutrient,heavy metal and organic pollutant composition of suspended and bed sediments in the Rhone River

The environmental quality of the Rhone River (Switzerland-France) has been assessed with a geochemical survey of the pollutants bound to suspended sediments. Ten samples were collected between Lake Geneva and the Mediterranean Sea in Nobember 1989 by continuous flow centrifugation and analysed for grain size distribution, carbonate, organic C, N, forms of particulate P, trace metals, and organic compounds (chlorobenzenes, organochlorine pesticides, PCBs, and PAHs). Four bed sediment samples were also studied for comparative purposes. The suspended solids provide lower variance by parameter than the bed sediments and are clearly most suitable for synoptic monitoring.The Upper Rhone River carries a glacial derived sediment with a low nutrient content, the stretch from Geneva to Lyon provides a sediment dominated by carbonate, and in the Lower Rhone the organic matter and phosphorus are relatively increased, mainly due to wastewater effluents and to an industrial P source. High concentrations of metals and organic micropollutants downstream of Lyon indicate a multiple contamination in the Lower Rhone, whereas more specific inputs are located downstream of Geneva and Arles.The comparison with data from other polluted major systems, the Rhine, the Niagara and the Detroit rivers, shows on overall similarity confirming that the Rhone quality is degraded downstream of Lyon. The levels of particular concern are for Hg, DDT metabolites which reveal a recent release in the basin, PCBs with a likely high chlorine content, and PAHs.The statistical evaluation of the compositional variables indicates a limited number of well defined associations, suggesting that the contamination of the suspended sediments results from the combination of numerous and intermittent point and diffuse sources in the Rhone River basin.     

Attributes and uncertainty of dissolved zinc data from a mined catchment

This study evaluated the attributes and uncertainty of non‐point source pollution data derived from synoptic surveys in a catchment affected by inactive metal mines in order to help to identify and select appropriate methods for data analysis/reporting and information use. Dissolved zinc data from the Upper Animas River Basin, Colorado, USA, were the focus of the study. Zinc was evaluated because concentrations were highest relative to national water quality criteria for brown trout, and zinc had the greatest frequency of criteria exceedances compared with other metals. Data attributes evaluated included measurement and model error, sample size, non‐normality, seasonality and uncertainty. The average measurement errors for discharges, concentrations and loadings were 0·15, 0·1 and 0·18, respectively. The 90 and 95% coefficients of confidence intervals for mean concentrations based on a sample size of four were 0·48 and 0·65, respectively, and ranged between 0·15 and 0·23 for sample sizes greater than 40. Aggregation of data from multiple stations decreased the confidence intervals significantly, but additional aggregation of all data increased them as a result of increasing spatial variability. Unit area loading data were approximately log‐normal. Concentration data were right‐skewed but not log‐normal. Differences in median concentrations were appreciable between snowmelt and both storm flow and baseflow, but not between storm flow and baseflow. Differences in unit area loadings between all flow events were large. It was determined that the average concentration and unit area loading values should be estimated for each flow event because of significant seasonality. Time weighted values generally should be computed if annual information is required. The confidence in average concentrations and unit area loadings is dependent on the computation method used. Both concentrations and loadings can be significantly underestimated on an annual basis when using data from synoptic surveys if the first flush of contaminants during the initial snowmelt runoff period is not sampled. The ambient standard for dissolved zinc for all events was estimated as 1600 μg l⁻¹ using the 85th percentile of observed concentration data, with a 90% confidence interval width of 200 μg l⁻¹. Copyright © 1999 John Wiley & Sons, Ltd.     

Uncertainty in hydrograph separations based on geochemical mixing models

A detailed uncertainty analysis of three-component mixing models based on the Haute–Mentue watershed (Switzerland) is presented. Two types of uncertainty are distinguished: the ‘model uncertainty’, which is affected by model assumptions, and the ‘statistical uncertainty’, which is due to temporal and spatial variability of chemical tracer concentrations of components. The statistical uncertainty is studied using a Monte Carlo procedure. The model uncertainty is investigated by the comparison of four different mixing models all based on the same tracers but considering for each component alternative hypotheses about their concentration and their spatio-temporal variability. This analysis indicates that despite the uncertainty, the flow sources, which generate the stream flow are clearly identified at the catchments scale by the application of the mixing model. However, the precision and the coherence of hydrograph separations can be improved by taking into account any available information about the temporal and spatial variability of component chemical concentrations.     

Input data measurement-induced uncertainty in watershed modelling

Abstract

This study presents a new methodology for estimation of input data measurement-induced uncertainty in simulated dissolved oxygen (DO) and nitrate-nitrogen (NO₃-N) concentrations using the Hydrological Simulation Program–FORTRAN (HSPF) model and data from the Amite River, USA. Simulation results show that: (1) a multiplying factor of 1.3 can be used to describe the maximum error in temperature measurements; similarly, a multiplying factor of 1.9 was estimated to accommodate the maximum of ±5% error in rainfall measurements; (2) the uncertainty in simulated DO concentration due to positive temperature measurement errors can be described with a normal distribution, N(0.062, 0.567); (3) the uncertainty in simulated NO₃-N concentration due to rainfall measurement errors follows a generalized extreme value distribution; and (4) the probability density functions can be utilized to determine the measurement-induced uncertainty in simulated DO and NO₃-N concentrations according to the risk level acceptable in water quality management.

Editor D. Koutsoyiannis

Citation Patil, A. and Deng, Z.-Q., 2012. Input data measurement-induced uncertainty in watershed modelling. Hydrological Sciences Journal, 57 (1), 118–133.     

Measuring and modeling vertical gradients in suspended sediments in the Solimões/Amazon River

Accurately measuring sediment flux in large rivers remains a challenge due to the spatial and temporal cross‐sectional variability of suspended sediment concentrations in conjunction with sampling procedures that fail to accurately quantify these differences. This study presents a field campaign methodology that can be used to improve the measurement of suspended sediment concentrations in the Amazon River or similarly large rivers. The turbidity signal and Rouse model are together used in this study to define the spatial distribution of suspended sediment concentrations in a river cross‐section, taking into account the different size fractions of the sediment. With this methodology, suspended sediment fluxes corresponding to each sediment class are defined with less uncertainty than with manual samples. This paper presents an application of this methodology during a field campaign at different gauging stations along a 3,000‐km stretch of the Solimões/Amazon River during low water and flood periods. Vertical concentration profiles and Rouse model applications for distinctive sediment sizes are explored to determine concentration gradients throughout a cross‐section of the river. The results show that coupling both turbidity technology and the Rouse model may improve our understanding of the spatial distribution of different sediments fractions sizes in the Solimões/Amazon River. These data are very useful in defining a pertinent monitoring strategy for suspended sediment concentrations in the challenging context of large rivers.     

The integrated effects of climate and hydrologic uncertainty on future flood risk assessments

This work examines future flood risk within the context of integrated climate and hydrologic modelling uncertainty. The research questions investigated are (1) whether hydrologic uncertainties are a significant source of uncertainty relative to other sources such as climate variability and change and (2) whether a statistical characterization of uncertainty from a lumped, conceptual hydrologic model is sufficient to account for hydrologic uncertainties in the modelling process. To investigate these questions, an ensemble of climate simulations are propagated through hydrologic models and then through a reservoir simulation model to delimit the range of flood protection under a wide array of climate conditions. Uncertainty in mean climate changes and internal climate variability are framed using a risk‐based methodology and are explored using a stochastic weather generator. To account for hydrologic uncertainty, two hydrologic models are considered, a conceptual, lumped parameter model and a distributed, physically based model. In the conceptual model, parameter and residual error uncertainties are quantified and propagated through the analysis using a Bayesian modelling framework. The approach is demonstrated in a case study for the Coralville Dam on the Iowa River, where recent, intense flooding has raised questions about potential impacts of climate change on flood protection adequacy. Results indicate that the uncertainty surrounding future flood risk from hydrologic modelling and internal climate variability can be of the same order of magnitude as climate change. Furthermore, statistical uncertainty in the conceptual hydrological model can capture the primary structural differences that emerge in flood damage estimates between the two hydrologic models. Copyright © 2014 John Wiley & Sons, Ltd.     

A Method to Assess Analytical Uncertainties Over Large Concentration Ranges With Reference to Volatile Organics in Water

The uncertainty associated with a volatile organic concentration measurement is a function of variability and bias introduced at the various levels of sample handling: collection, storage, and analysis. During the past decade, sampling materials and the development and/or improvement of sampling protocols have been the subject of considerable research activity. As a result, in cases of samples properly handled, the analytical variability can be the dominant source of uncertainty in a given concentration value. Here analytical variability refers to any error that might arise during analysis, including the detector response error and any sample handling errors common to both standards and samples. This can be a particular concern for field analyses by gas chromatography (GC), Well-established statistical methods are available to estimate analytical uncertainty from linear calibration curves, but these methods are poorly suited for the analysis of volatile organics because organic samples frequently require instrument calibration (usually GC) over several orders of magnitude in concentration. If a single linear calibration curve is used to determine sample concentrations and uncertainties, then unrealistically large uncertainties may be assigned to low concentration samples. However, the methods can be adopted for extended concentration range calibration curves by breaking the overall calibration line down into smaller sub-calibration lines that span smaller ranges. These can then be examined and used selectively to determine concentrations with more appropriate uncertainties attached. The method of multiple callbration line analysis described here is suitable for programming with any high level computer language. It can be used to calculate meaningful analytical uncertainty values for any substance analyzed over a wide range in concentrations (i.e., an order of magnitude or more).     

Impacts of climate variability on water quality with best management practices in sub‐tropical climate of USA

Efficiency of non‐point source pollution control methods may be altered in future climate. This study investigated climate change impacts on sediment and nutrient transport, and efficiency of best management practices (BMPs), in the Upper Pearl River Watershed (UPRW) in Mississippi. The Soil and Water Assessment Tool was applied to the UPRW using observed flow, sediment and nutrient data. Water quality samples were collected at three US geological survey gauging stations. The model was successfully calibrated and validated for daily time steps (Nash Sutcliffe efficiency and coefficient of determination – R² up to 0.7) using manual and automatic (sequential uncertainty fitting version 2) methods from February 2010 to May 2011. Future weather scenarios were simulated using the LARS‐WG model, a stochastic weather generator, with Community Climate System Model, global climate model, which was developed by the National Center for Atmospheric Research in the USA. On the basis of the Special Report on Emissions Scenarios A1B, A2 and B1 of the Intergovernmental Panel on Climate Change, climate change scenarios were simulated for the mid (2046–2065) and late (2080–2099) century. Effectiveness of four BMPs (Riparian buffer, stream fencing, sub‐surface manure applications and vegetative filter strips) on reducing sediment and nutrient were evaluated in current and future climate conditions. Results show that sediment, nitrogen and phosphorus loadings will be increased up to a maximum of 26.3%, 7.3% and 14.3%, respectively, in future climate conditions. Furthermore, the effectiveness of BMPs on sediment removal will be reduced in future climate conditions, and the efficiency of nitrogen removal will be increased, whereas phosphorus removal efficiency will remain unchanged. Copyright © 2013 John Wiley & Sons, Ltd.     

Occurrence and distribution of organochlorine residues in surface sediments of the Candarli Gulf (Eastern Aegean)

The residual levels of organochlorine pesticides (OCPs) and polychlorinated biphenyls (PCBs) were determined in surface sediments collected from Candarli Gulf. Total concentrations of OCPs and PCBs in sediments ranged from 10.2 to 57.3 and 2.8 to 205 ng g⁻¹ dwt, respectively. DDTs in sediments were derived from the aged and weathered agricultural soils in 61% of the sampling stations while 39% of the sites originated from the recent DDT inputs. Their concentrations appeared to be relatively low by global standards and only sediments receiving the impact from the Bakircay River and petrochemical industry approached the sediment quality guidelines for PCBs and DDTs. Based on ERL/ERM guidelines, DDT and PCBs posed ecological risk to the bottom-dwelling consumers.     

Evaluation of longitudinal and transverse dispersivities/distance ratios for tracer test in a radially convergent flow field with scale-dependent dispersion

This study presents a novel mathematical model for analysis of non-axisymmetrical solute transport in a radially convergent flow field with scale-dependent dispersion. A two-dimensional, scale-dependent advection–dispersion equation in cylindrical coordinates is derived based on assuming that the longitudinal and transverse dispersivities increase linearly with the distance of the solute transported from its injected source. The Laplace transform finite difference technique is applied to solve the two-dimensional, scale-dependent advection–dispersion equation with variable-dependent coefficients. Concentration contours for different times, breakthrough curves of average concentration over concentric circles with a fixed radial distance, and breakthrough curves of concentration at a fixed observation point obtained using the scale-dependent dispersivity model are compared with those from the constant dispersivity model. The salient features of scale-dependent dispersion are illustrated during the non-axisymmetrical transport from the injection well into extraction well in a convergent flow field. Numerical tests show that the scale-dependent dispersivity model predicts smaller spreading than the constant-dispersivity model near the source. The results also show that the constant dispersivity model can produce breakthrough curves of averaged concentration over concentric circles with the same shape as those from the proposed scale-dependent dispersivity model at observation point near the extraction well. Far from the extracting well, the two models predict concentration contours with significantly different shapes. The breakthrough curves at observation point near the injection well from constant dispersivity model always produce lesser overall transverse dispersion than those from scale-dependent dispersivity model. Erroneous dimensionless transverse/longitudinal dispersivity ratio may result from parametric techniques which assume a constant dispersivity if the dispersion process is characterized by a distance-dependent dispersivity relationship. A curve-fitting method with an example is proposed to evaluate longitudinal and transverse scale-proportional factors of a field with scale-dependent dispersion.     

Distribution of uranium isotopes in the main channel of Yellow river (Huanghe), China

Uranium isotopes were measured in waters and suspended particulate matters (SPM) of the main channel of Yellow River, China that were sampled during four field trips between August 2005 and July 2006. The results show that the concentration of dissolved U (2.04–7.83 μg/l) and the activity ratio of ²³⁴U/²³⁸U (1.36–1.67) are much higher than the average U concentrations and activity ratios of global major rivers. Mass balance calculations using the results of simulated experiments and measurement data show that the section of the Yellow River between Lanzhou and Sanmenxia has its dissolved U derived from two sources: suspended sediments (68%) and groundwater/runoff from loess deposits (32%). Both sources are related to the heavy erosion of the Chinese Loess Plateau.     

Trace organic contamination in the Americas: An overview of the US National Status & Trends and the International ‘Mussel Watch’ programmes

The National Status & Trends (NS&T, 1986–1993) and the International Mussel Watch (IMW, 1991–1992) programmes provide a good coverage of a broad range of environmental conditions along the North, Central and South American coasts. Total concentrations of DDTs, chlordane-related compounds, PCBs and PAHs present fairly homogeneous distributions along the northern Gulf of Mexico coast, with very few sites showing extremely high or low concentrations. In contrast, a larger variability in the geographical distribution of some of these organic contaminants was observed for IMW sites. For example, high concentrations of DDT and its metabolites, DDD and DDE, were generally found in tropical and subtropical areas as compared to more temperate zones of South America. ‘Industrial’ contaminants, such as PCBs and PAHs, have similar distributions with the highest concentrations encountered generally along the southern South Atlantic coast. An overall comparison of the concentrations of these organic contaminants measured at NS&T and IMW sites indicates that contamination is significantly higher along the northern coast of the Gulf of Mexico.     

Effect of land‐use changes on nonpoint source pollution in the Xizhi River watershed,Guangdong, China

The Annualized Agricultural Non‐point Source (AnnAGNPS) pollution model has been widely used to assess and predict runoff, soil erosion, sediment and nutrient loading with a geographic information system. This article presents a case study of the effect of land‐use changes on nonpoint source (NPS) pollution using the AnnAGNPS model in the Xizhi River watershed, eastern Pearl River Delta of Guangdong province, China. The land‐use changes in the Xizhi River watershed between 1998 and 2003 were examined using the multitemporal remote sensing data. The runoff, soil erosion, sediment transport and nutrient loading 1998 and 2003 were assessed using AnnAGNPS. The effects of land‐use changes on NPS were studied by comparing the simulation results of each year. Our results showed that (i) the NPS loadings increased when forest and grass land converted into paddy, orchard and farmland land, and population size and gross domestic product size as well as the usage amounts of fertilizer and pesticide in the entire watershed were firmly correlated with the NPS loadings; (ii) the land‐use change during fast urbanization in particular when other land types were converted into the development land and buildup land led to increasing of NPS pollution; and (iii) urban land expansion showed more important effects on total organic carbon (TOC) loading compared with nitrogen and phosphorus loadings. Copyright © 2012 John Wiley & Sons, Ltd.     

Modelling of hydrodynamics and cohesive sediment transport in Tanshui River estuarine system,Taiwan

A laterally averaged two-dimensional numerical model is used to simulate hydrodynamics and cohesive sediment transport in the Tanshui River estuarine system. The model handles tributaries as well as the main stem of the estuarine system. Observed time series of salinity data and tidally averaged salinity distributions have been compared with model results to calibrate the turbulent diffusion coefficients. The overall model verification is achieved with comparisons of residual currents and salinity distribution. The model reproduces the prototype water surface elevation, currents and salinity distributions. Comparisons of the suspended cohesive sediment concentrations calculated by the numerical model and the field data at various stations show good agreement. The validated model is applied to investigate the tidally averaged salinity distributions, residual circulation and suspended sediment concentration under low flow conditions in the Tanshui River estuarine system. The model results show that the limit of salt intrusion in the mainstem estuary is located at Hsin-Hai bridge in Tahan Stream, 26 km from the River mouth under Q75 flow. The null point is located at the head of salt intrusion, using 1 ppt isohaline as an indicator. The tidally averaged sediment concentration distribution exhibits a local maximum around the null point.     

Using geostatistical simulation to disaggregate air quality model results for individual exposure estimation on GPS tracks

In this work, we address the mismatch in spatio-temporal resolution between individual, point-location based exposure and grid cell based air quality model predictions by disaggregating the grid model results. Variability of PM₁₀ point measurements was modelled within each grid cell by the exponential variogram, using point support concentration measurements. Variogram parameters were estimated over the study area globally using constant estimates, and locally by multiple regression models using traffic, weather and land use data. Model predictions of spatio-temporal variability were used for geostatistical unconditional simulation, estimating the deviation of point values from grid cell averages on GPS tracks. The distribution of deviations can be used as an estimate of uncertainty for individual exposure. Results showed a relevant impact of the disaggregation uncertainties compared to other uncertainty sources, dependent of the model used for spatio-temporal variability. Depending on individual behaviour and variability of the pollutant, these uncertainties average out again over time.     

Connectivity of the Apalachicola River flow variability and the physical and bio-optical oceanic properties of the northern West Florida Shelf

Maps of satellite-derived estimates of monthly averaged chlorophyll a concentration over the northern West Florida Shelf show interannual variations concentrated near the coastline, but also extending offshore over the shelf in a tongue-like pattern from the Apalachicola River during the late winter and early spring. These anomalies are significantly correlated with interannual variability in the flow rate of the Apalachicola River, which is linked to the precipitation anomalies over the watershed, over a region extending 150–200 km offshore out to roughly the 100 m isobath. This study examines the variability of the Apalachicola River and its impacts on the variability of water properties over the northern West Florida Shelf. A series of numerical model experiments show that episodic wind-driven offshore transport of the Apalachicola River plume is a likely physical mechanism for connecting the variability of the river discharge with oceanic variability over the middle and outer shelf.     

Broadband ground motion simulation using a hybrid approach of the May 21, 2021 M7.4 earthquake in Maduo,Qinghai, China

In this study, the broadband ground motions of the 2021 M7.4 Maduo earthquake were simulated to overcome the scarcity of ground motion recordings and the low resolution of macroseismic intensity map in sparsely populated high-altitude regions. The simulation was conducted with a hybrid methodology, combining a stochastic high-frequency simulation with a low-frequency ground motion simulation, from the regional 1-D velocity structure model and the Wang WM et al.(2022) source rupture model,respect...     

Evaluating spatio-temporal representations in daily rainfall sequences from three stochastic multi-site weather generation approaches

Many hydrological and agricultural studies require simulations of weather variables reflecting observed spatial and temporal dependence at multiple point locations. This paper assesses three multi-site daily rainfall generators for their ability to model different spatio-temporal rainfall attributes over the study area. The approaches considered consist of a multi-site modified Markov model (MMM), a reordering method for reconstructing space–time variability, and a nonparametric k-nearest neighbour (KNN) model. Our results indicate that all the approaches reproduce adequately the observed spatio-temporal pattern of the multi-site daily rainfall. However, different techniques used to signify longer time scale observed temporal and spatial dependences in the simulated sequences, reproduce these characteristics with varying successes. While each approach comes with its own advantages and disadvantages, the MMM has an overall advantage in offering a mechanism for modelling varying orders of serial dependence at each point location, while still maintaining the observed spatial dependence with sufficient accuracy. The reordering method is simple and intuitive and produces good results. However, it is primarily driven by the reshuffling of the simulated values across realisations and therefore may not be suited in applications where data length is limited or in situations where the simulation process is governed by exogenous conditioning variables. For example, in downscaling studies where KNN and MMM can be used with confidence.