Assesment of the response of a shallow macrotidal estuary to changes in hydrological and wastewater inputs through numerical modelling

The aim of this study was to investigate the response to short-term changes in river freshwater discharges and in nutrients loadings (mainly from the treatment of urban wastewater), of the shallow macrotidal Urdaibai estuary (north of Spain), by using numerical tools. A two-dimensional hydrodynamic model and a water quality model were applied to the estuary, in order to better use it as a prediction tool in the study of the effects of variations in hydrodynamic conditions and in waste water inputs. The model was calibrated and verified using data measured under different hydrological conditions (spring and summer). A model calibration was carried out with field data measured during the summer, while the model validation was conducted for spring conditions. The calibration process allowed the model parameter definition, while the model validation permitted the verification of the calibrated parameters under different environmental conditions. The model results were in reasonable agreement with field measurements, in both the calibration and the validation phases. The model showed a significant decrease in phytoplankton concentration with river input increase. A study on the effects of nutrient input reduction from the Gernika Waste Water Treatment Plant (WWTP) was conducted. It showed a decrease in phytoplankton concentration with decreasing levels of nutrient discharge. This reduction was more pronounced in conjunction with the highest river discharge. In that case, a 50% decrease for the elimination of the WWTP discharge was observed.     

Assessing and simulating the major pathway and hydrogeochemical transport of arsenic in the Beitou–Guandu area,Taiwan

This study involved assessing and simulating the probable major pathways (surface and subsurface flow) and hydrogeochemical transport of arsenic (As) in the Beitou–Guandu area, Taiwan. A one-dimensional (1-D) generic, reactive, chemical transport model (PHREEQC) was adopted. The calibrated model showed that As transported to the downstream Guandu plain and Tan Shui river mouth accounted for 50.7 and approximately 100 % of the As in the subsurface flow pathway, respectively, suggesting that subsurface flow constituted a major As pathway. The highest As water concentration occurred near the Beitou geothermal valley because of the low pH and high redox potential in both the surface and subsurface pathways. However, As may be scavenged by aqueous Fe(II) in a reducing environment. The As concentrations in the downstream Guandu plain and Guandu wetland decreased as the simulated time increased, resulting in the adsorption of As on the surface of Fe oxydroxides and limiting the mobility of As in the surface flow pathway. The major retardation mechanism of As mobility in the subsurface flow pathway of the Guandu plain and Guandu wetland was governed by the adsorption reactions of iron-oxide and iron-sulfide minerals. The 1-D transport model was applied to predict the evolution of As in the subsurface flow pathway from 2013 to 2020. The results indicated that the As concentrations in all cells gradually increased. The geochemical redox reactions of As in the subsurface pathway subsequently led to the oxidization of As-bearing sulfides, causing As concentrations to rise substantially in the hillside area.

     

Changes in nutrient ratios and phytoplankton community structure caused by hydropower development in the Maotiao River,China

Reservoirs created for hydropower production have become an important feature impacting a river. Understanding the effects of river impoundment on the downstream environment is critical to decision-making for water resource protection. The changes caused by impoundment are changes in water quality and the resulting effect on the phytoplankton community structure. The impacts caused by a series of reservoirs along a river are still not well understood. In this study, we conducted an investigation of five reservoirs along the Maotiao River, China. We found that a series of impoundments plays a role in decreasing the phytoplankton biomass in downstream reservoirs. Within the studied area, nitrogen is not a limiting factor for phytoplankton growth. The ratio of silicon to phosphorus (Si:P) can become a major factor in the regulation of phytoplankton community structure. The Si:P ratio increased from upstream to downstream reservoirs, causing a concurrent increase in the percentage of Bacillariophyta, particularly during the winter. In addition, our results indicate that the creation of dams eliminates Si limitation downstream.     

Artificial neural network modeling of the river water quality—A case study

The paper describes the training, validation and application of artificial neural network (ANN) models for computing the dissolved oxygen (DO) and biochemical oxygen demand (BOD) levels in the Gomti river (India). Two ANN models were identified, validated and tested for the computation of DO and BOD concentrations in the Gomti river water. Both the models employed eleven input water quality variables measured in river water over a period of 10 years each month at eight different sites. The performance of the ANN models was assessed through the coefficient of determination (R²) (square of the correlation coefficient), root mean square error (RMSE) and bias computed from the measured and model computed values of the dependent variables. Goodness of the model fit to the data was also evaluated through the relationship between the residuals and model computed values of DO and BOD. The model computed values of DO and BOD by both the ANN models were in close agreement with their respective measured values in the river water. Relative importance and contribution of the input variables to the model output was evaluated through the partitioning approach. The identified ANN models can be used as tools for the computation of water quality parameters.     

An interval dynamic multimedia fugacity (IDMF) model for environmental fate of PAHs and their source apportionment in a typical oilfield,China

An interval dynamic multimedia fugacity (IDMF) model with a new validation criterion of interval average logarithmic residual error (IALRE) was developed in this study. The environmental fate of polycyclic aromatic hydrocarbons (PAHs) and their source apportionment in a typical oilfield of China were simulated from 1985 to 2010. The PAH concentrations predicted by the model were in agreement with the measured concentrations, which were indicated by the IALREs calculated at 0.41, 0.63, 0.52, and 0.58 for air, water, soil, and sediment, respectively. The multimedia concentrations of Σ16 PAHs were 29.55, 39.22, 31.98, and 26.69 times greater in 2010 than those in 1985, and were higher than any other year modelled. Additionally, 87.82% of PAHs remained in the soil in 2010. PAH source emission into the soil was the major modelled source, whereas PAH degradation in the air was the major modelled loss pathway; the dominant transfer process between the adjacent compartments was atmospheric deposition from air to soil. It was demonstrated that high-temperature combustion was the major source of PAHs in the air and soil, whereas biomass and coal combustion were attributed to water and sediment compartments. The IDMF model was effective in the dynamic source apportionment of PAHs.     

A simulation model of management alternatives in a freshwater fishery

A model for investigating management alternatives on the Pyramid Lake-Truckee River system of Nevada and California is presented. Cutthroat trout, Cui-ui, Tahoe Sucker and Tui Chub are modeled with special emphasis on river spawning by trout. Management decision variables include hatchery input, water flow control, and diversion screening. Preliminary results indicate that some hatchery input will be needed to support the trout even with the best river management.     

Development of a coupled reservoir operation and water diversion model: Balancing human and environmental flow requirements

Maintaining a natural flow regime helps preserve the health of riverine ecosystems. Conventional studies on reservoir operations have focused mainly on identifying optimal operational schemes for satisfying human water demands. To systematically reflect the ecological effects of both natural and human-induced hydrologic alterations, water diversions downstream of the reservoirs should be considered as well. This research focused on a coupled reservoir operation and water diversion (CROWD) model, created through the integration of a reservoir operation model and a water diversion model. The proposed model considers both human and environmental flow requirements, and represents a compromise that balances ecological protection (preservation of the natural flow regime of a river) and human needs (reduced water shortages). In the reservoir operation model, the reservoir space is divided into three zones and different operating rules are developed for directing reservoir operation when water levels are in different zones; in the water diversion model, different water users are assigned different supply priorities with the instream flows no more than the minimum environmental flows having the highest priority; and the two models are coupled by the water mass balance between the two hydraulic facilities. The non-dominated-sorting genetic algorithm II (NSGA-II) was used to determine the parameters of the developed CROWD model and the model was applied to support the joint operational management of the Tanghe Reservoir and the Liaoyang Diversion in the Tang river basin, China. The resulting reservoir operation and water diversion schemes indicate that the CROWD model is useful for optimizing the operation of reservoirs and water diversion schemes. Moreover, it helps to analyze tradeoffs between human and environmental water needs, resulting in solutions that reduce the risk of water shortages and minimize ecological integrity disturbances.     

River water quality management model using genetic algorithm

Conventional mathematical programming methods, such as linear programming, non linear programming, dynamic programming and integer programming have been used to solve the cost optimization problem for regional wastewater treatment systems. In this study, a river water quality management model was developed through the integration of a genetic algorithm (GA). This model was applied to a river system contaminated by three determined discharge sources to achieve the water quality goals and wastewater treatment cost optimization in the river basin. The genetic algorithm solution, described the treatment plant efficiency, such that the cost of wastewater treatment for the entire river basin is minimized while the water quality constraints in each reach are satisfied. This study showed that genetic algorithm can be applied for river water quality modeling studies as an alternative to the present methods.     

A simulation framework for water allocation to meet the environmental requirements of urban rivers: model development and a case study for the Liming River in Daqing City,China

In this paper, we describe the development of a simulation framework for allocating water from different sources to meet the environmental flows of an urban river. The model permits the development of a rational balance in the utilization of storm water, reclaimed water from wastewater treatment plants, and freshwater from reservoirs with consideration of the limited capacities of different water resources. It is designed to permit the full utilization of unconventional water sources for the restoration of river water quality by increasing river flow and improving water quality. To demonstrate practical use of the model, a case study is presented in which the model was used to simulate the environmental water allocation for the Liming River in Daqing City, China, based on the three water sources mentioned above. The results demonstrate that the model provides an effective approach for helping managers allocate water to satisfy the river’s environmental water requirements.     

Integrating wetlands and riparian zones in river basin modelling

Wetlands, and in particular riparian wetlands, represent an interface between the catchment area and the aquatic environment. They control the exchange of water and related chemical fluxes from the upper catchment area to surface waters like streams and lakes. Their influence on water and nutrient balances has been investigated mainly at the patch scale. In this study an attempt was made (a) to integrate riparian zones and wetlands into eco-hydrological river basin modelling, and (b) to quantify the impacts of riparian wetland processes on water and nutrient fluxes in a meso-scale catchment located in the northeastern German lowland. The investigation was performed by analysing hydro-chemical field data and applying the eco-hydrological model SWIM (Soil and Water Integrated Model), which was extended to reproduce the relevant water and nutrient flows and retention processes at the catchment scale in general, and in riparian zones and wetlands in particular. The main extensions introduced in the model were: (1) implementation of daily groundwater table dynamics at the hydrotope level, (2) implementation of water and nutrient uptake by plants from groundwater in riparian zones and wetlands, and (3) assessment of nutrient retention in groundwater and interflow. The simulation results indicate that wetlands, though they represent relatively small parts of the total catchment area, may have a significant impact on the overall water and nutrient balances of the catchment. The uncertainty of the simulation results is considerably high, with the main sources of uncertainty being the model parameters representing the geo-hydrology and the input data for land use management.     

Uncertainty analysis of a pharmacokinetic modeling for inorganic arsenic

This paper presents an uncertainty and sensitivity analysis of a pharmacokinetic modeling of inorganic arsenic deposition in rodents for a short‐term exposure. Efforts to develop the pharmacokinetic model are directed towards predicting the kinetic behavior of inorganic arsenic in the body, including tissue and blood concentrations, and especially, the urinary excretion of arsenic and its methylated metabolites. However, the use of the model raises an important question when fixed values of model parameters are used: how is the uncertainty in the model prediction based on the collective uncertainties in the model inputs? This study focuses on an “epistemic”; uncertainty in order to handle this problem. In this case, the uncertainty refers to an input that has a single value which cannot be known with precision due to a lack of knowledge about items or its measurement. The combination of the pharmacokinetic model and the uncertainty analysis would help understand the uncertainties in risk assessment associated with inorganic arsenic.     

Estimating the critical phosphorus loading of shallow lakes with the ecosystem model PCLake: Sensitivity, calibration and uncertainty

There is a vast body of knowledge that eutrophication of lakes may cause algal blooms. Among lakes, shallow lakes are peculiar systems in that they typically can be in one of two contrasting (equilibrium) states that are self-stabilizing: a ‘clear’ state with submerged macrophytes or a ‘turbid’ state dominated by phytoplankton. Eutrophication may cause a switch from the clear to the turbid state, if the P loading exceeds a critical value. The ecological processes governing this switch are covered by the ecosystem model PCLake, a dynamic model of nutrient cycling and the biota in shallow lakes. Here we present an extensive analysis of the model, using a three-step procedure. (1) A sensitivity analysis revealed the key parameters for the model output. (2) These parameters were calibrated on the combined data on total phosphorus, chlorophyll-a, macrophytes cover and Secchi depth in over 40 lakes. This was done by a Bayesian procedure, giving a weight to each parameter setting based on its likelihood. (3) These weights were used for an uncertainty analysis, applied to the switchpoints (critical phosphorus loading levels) calculated by the model. The model was most sensitive to changes in water depth, P and N loading, retention time and lake size as external input factors, and to zooplankton growth rate, settling rates and maximum growth rates of phytoplankton and macrophytes as process parameters. The results for the ‘best run’ showed an acceptable agreement between model and data and classified nearly all lakes to which the model was applied correctly as either ‘clear’ (macrophyte-dominated) or ‘turbid’ (phytoplankton-dominated). The critical loading levels for a standard lake showed about a factor two uncertainty due to the variation in the posterior parameter distribution. This study calculates in one coherent analysis uncertainties in critical phosphorus loading, a parameter that is of great importance to water quality managers.     

Scenario analysis of water pollution control in the typical peri-urban river using a coupled hydrodynamic-water quality model

The water quality pollution and ecological deterioration in peri-urban rivers are usually serious under rapid urbanization and economic growth. In the study, a typical peri-urban river, Nansha River, was selected as a case study to discuss the scheme of peri-urban river rehabilitation. Located in the north part of the Beijing central region, the Nansha River watershed has been designated as an ecologically friendly garden-style area with high-tech industry parks and upscale residential zones. However, the Nansha River is currently seriously contaminated by urban and rural pollutants from both nonpoint sources (NPS) and point sources (PS). In this study, the pollutant loads from point sources and nonpoint sources in the Nansha River watershed were first assessed. A coupled model, derived from the Environmental Fluid Dynamics Code and Water Quality Analysis Simulation Program, was developed to simulate the hydrodynamics and water quality in the Nansha River. According to the characteristics of the typical peri-urban river, three different PS and NPS control scenarios were designed and examined by modeling analyses. Based on the results of the scenario analysis, a river rehabilitation scheme was recommended for implementation.     

Phosphorus flow analysis of the socioeconomic ecosystem of Shucheng County, China

Human activities disturb the long-term phosphorus (P) cycle in nature, whereby the resulting intensive release of P contributes to the eutrophication of surface water. Hence, a detailed understanding of P flow as it relates to socioeconomic systems is essential for effective nutrient management. This study develops a substance-flow-analysis model for P metabolism for the socioeconomic ecosystem of Shucheng County in Anhui Province in central China as a case study. We estimate P flow using data from questionnaires, face-to-face interviews, published literature, and official statistical databases. Our results show that P flow in Shucheng's current socioeconomic system is linear and openly metabolic. The total P input into Shucheng in 2008 reached 12 748 Mg, mainly as P ores and crops. In all, 43.83% of the total P input was exported, and 30.44% was discharged into surface water. More-balanced nutrient management and options for improving nutrient use efficiency are discussed. The quantifiable, science-based methods used in this study may be applied to neighboring regions of central China for sustainable development and water management.     

Impact of time series data on calibration and prediction uncertainty for a deterministic hydrogeochemical model

Model calibration is fundamental in applications of deterministic process-based models. Uncertainty in model predictions depends much on the input data and observations available for model calibration. Here we explored how model predictions (forecasts) and their uncertainties vary with the length of time series data used in calibration. As an example we used the hydrogeochemical model MAGIC and data from Birkenes, a small catchment in southern Norway, to simulate future water chemistry under a scenario of reduced acid deposition. A Bayesian approach with a Markov Chain Monte Carlo (MCMC) technique was used to calibrate the model to different lengths of observed data (4–29 years) and to estimate the prediction uncertainty each calibration. The results show that the difference between modelled and observed water chemistry (calibration goodness of fit) in general decreases with increasing length of the time series used in calibration. However, there are considerable differences for different time series of the same length. The results also show that the uncertainties in predicted future acid neutralizing capacity were lowest (i.e. the distribution peak narrowest) when using the longest time series for calibration. As for calibration success, there were considerable differences between the future distributions (prediction uncertainty) for the different calibrations.     

Defining and modelling the coastal zone affected by the Po river (Italy)

One of the most important sources of pollution in coastal zones (CZ) is certainly that one produced by human activities in the associated river basin. Understanding the linkage between water quality in CZ and river catchments is important in order to better assess CZ processes and to evaluate different management options aimed at improving the coastal ecosystem state. CZ water quality targets as identified by the Water Framework Directive (EC 2000/60) require an accurate study of the effects of pollutant loads coming from river discharge.In order to evaluate the impacts of human activities in river catchments on the associated coastal zone, a sound definition for this geographic area is needed. Many definitions for this area have been proposed in different contexts. The definition is generally built upon a particular goal, and is henceforth highly variable according to the different purposes. In this paper a general methodology allowing to discern those areas of the sea that are directly influenced by fluvial discharge is presented. The methodology is based on the variation pattern of sea water characteristics, and provides a numerical evaluation of this influence. In particular an analysis based on salinity as tracer, results in a sound definition of this area. The methodology has been applied on the case study of the Po river. Due to the significant nutrient loads discharged by the river, the CZ associated with Po is affected by severe eutrophication phenomena that have important consequences on the ecosystem and on the socio-economy of the area.In order to study the impacts of nutrients loads carried by the river, a water quality model (WASP6) has been implemented. The model simulates the seasonal variability of nutrient concentrations, phytoplankton biomass and dissolved oxygen. Using the CZ model is possible to compare the effects of variations of nutrient loads on the biochemical (short term) and ecological (long term) quality of the coastal environment. This is accomplished by feeding nutrients loads forecasted for different scenarios by the catchment model (MONERIS) as forcing functions to the CZ model. This way the effect of the different catchment management scenarios are propagated to the CZ model, and the trophic conditions of the coastal ecosystem evaluated using TRIX.This study has been developed in the context of the European project EUROCAT.     

Simulation of water quality in a flood detention area using models of different spatial discretization

Detention areas provide a means to lower peak discharges in rivers by temporarily storing excess water. In the case of extreme flood events, the storage effect reduces the risk of dike failures or extensive inundations for downstream reaches and near the site of abstraction. Due to the large amount of organic matter contained in the river water and the inundation of terrestrial vegetation in the detention area, a deterioration of water quality may occur. In particular, decay processes can cause a severe depletion of dissolved oxygen (DO) in the temporary water body. In this paper, we studied the potential of a water quality model to simulate the DO dynamics in a large but shallow detention area to be built at the Elbe River (Germany). Our focus was on examining the impact of spatial discretization on the model’s performance and usability. Therefore, we used a zero-dimensional (0D) and a two-dimensional (2D) modeling approach in parallel. The two approaches solely differ in their spatial discretization, while conversion processes, parameters, and boundary conditions were kept identical. The dynamics of DO simulated by the two models are similar in the initial flooding period but diverge when the system starts to drain. The deviation can be attributed to the different spatial discretization of the two models, leading to different estimates of flow velocities and water depths. Only the 2D model can account for the impact of spatial variability on the evolution of state variables. However, its application requires high efforts for pre- and post-processing and significantly longer computation times. The 2D model is, therefore, not suitable for investigating various flood scenarios or for analyzing the impact of parameter uncertainty. For practical applications, we recommend to firstly set up a fast-running model of reduced spatial discretization, e.g. a 0D model. Using this tool, the reliability of the simulation results should be checked by analyzing the parameter uncertainty of the water quality model. A particular focus may be on those parameters that are spatially variable and, therefore, believed to be better represented in a 2D approach. The benefit from the application of the more costly 2D model should be assessed, based on the analyses carried out with the 0D model. A 2D model appears to be preferable only if the simulated detention area has a complex topography, flow velocities are highly variable in space, and the parameters of the water quality model are well known.     

From meso- to macro-scale dynamic water quality modelling for the assessment of land use change scenarios

The implementation of the European Water Framework Directive requires reliable tools to predict the water quality situations in streams caused by planned land use changes at the scale of large regional river basins. This paper presents the results of modelling the in-stream nitrogen load and concentration within the macro-scale basin of the Saale river (24,167 km²) using a semi-distributed process-based ecohydrological dynamic model SWIM (Soil and Water Integrated Model). The simulated load and concentration at the last gauge of the basin show that SWIM is capable to provide a satisfactory result for a large basin. The uncertainty analysis indicates the importance of realistic input data for agricultural management, and that the calibration of parameters can compensate the uncertainty in the input data to a certain extent. A hypothesis about the distributed nutrient retention parameters for macro-scale basins was tested aimed in improvement of the simulation results at the intermediate gauges and the outlet. To verify the hypothesis, the retention parameters were firstly proved to have a reasonable representation of the denitrification conditions in six meso-scale catchments. The area of the Saale region was classified depending on denitrification conditions in soil and groundwater into three classes (poor, neutral and good), and the distributed parameters were applied. However, the hypothesis about the usefulness of distributed retention parameters for macro-scale basins was not confirmed. Since the agricultural management is different in the sub-regions of the Saale basin, land use change scenarios were evaluated for two meso-scale subbasins of the Saale. The scenario results show that the optimal agricultural land use and management are essential for the reduction in nutrient load and improvement of water quality to meet the objectives of the European Water Framework Directive and in view of the regional development plans for future.     

胡杨年轮记录的塔里木河下游54年来区域水环境历史变迁

通过胡杨（Populus euphratica Oliv．）树木年轮宽度的分析,建立了塔里木河下游大西海子（A）、阿克墩（B）、亚合甫马汗（c）、英苏（D）、阿布达勒（E）、喀尔达依（F）、吐格买莱（G）、阿拉干（H）、依干不及麻（I）和考干（J）10个采样区过去54a来的STD、RES和ARS年表,并借助RES年表,采用年代际变化分析和突变检验,反演了塔里木河下游54a年来区域水环境状况变迁时空格局。结果表明：①下游10个样区54a来区域水环境状况具有多样性和复杂性,并不完全表现为距离下游上段（大西海子水库）越近其水环境状况就越好,区域水环境状况总体变异程度由低到高排序为A、G、C、H、E、D、I、B、F、J,也反映了下游10个样区生态退化程度的差异;②下游54a来区域水环境状况最好时期出现在20世纪60年代和21世纪初,大部分区域最差时期主要集中在20世纪90年代,是下游地区长达30a断流水环境变干累积效应的体现;③下游10个样区区域水环境变化具有明显的突变时间,突变出现时间相对水文事件年代具有滞后性。胡杨年轮记录的塔里木河下游54a来区域水环境时空变迁格局对下游生态退化的历史认识具有重要意义。