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This paper examines and ranks restoration alternatives for improving fish habitat by evaluating tradeoffs between fish production and restoration costs. Optimization modelling is used to maximize out‐migrating coho salmon (Oncorhynchus kisutch) from a natal stream and is applied as a case study in California’s Shasta River. Restoration activities that alter flow and water temperature conditions are the decision variables in the model and include relocating a major diversion, increasing riparian shading, increasing instream flow, restoring a cool‐water spring and removing a dam. A budget constraint limits total restoration expenditures. This approach combines simple fish population modelling with flow and water quality modelling to explore management strategies and aid decision making. Previous fish habitat optimization research typically uses single restoration strategies, usually by altering reservoir releases or modifying outlet structures. Our method enlarges the solution space to more accurately represent extensive and integrated solutions to fish habitat problems. Results indicate that restoration alternatives can be prioritized by fish habitat improvement and restoration cost. For the Shasta River case study, considerable habitat restoration investments were required before fish productivity increased substantially. This exercise illustrates the potential of ecological optimization for highlighting promising restoration approaches and dismissing poor alternatives. Copyright © 2011 John Wiley & Sons, Ltd.

This study on water quality modelling in Sungai Juru, Penang was undertaken as one of the most polluted rivers in Malaysia and is literally known as the 'dying river'. The research objectives are to assess the parameters that govern the amount of pollutants in the river and to identify appropriate measures to improve the river water quality. The main pollution sources are pig waste, discharge from agro-based industries, dumping of municipal and industrial waste. Due to its relatively flat bed gradient, Sungai Juru experienced tidal effect up to a distance of 13 km from the estuary. As a result, pollutants in the river are hardly discharged into the sea. This research on Dissolved Oxygen (DO) parameter has been carried out to develop a rehabilitation solution for Sungai Juru by using the numerical hydrodynamic modeling technique simulated by I-D Infoworks R.S software. The modeling involved two phases namely, development of a flow model followed by a water quality model. After the model has been successfully calibrated, the pollutant behaviour under various scenarios can be investigated. The hydraulic study of Sungai Juru revealed that the velocity at STJ02 ranging from -0.1 to +0.12 m sec-1 during high and low tide, respectively. Based on this velocity, traveling time from S TJ02 (Sungai Juru) to STJ01 (Sungai Rambai) (3.5 km) is approximately between 9-10 h. The duration provides ample time for photosynthesis to occur resulting high DO ranging from 4-10 mg at STJ01. The information is useful to determine pollution characteristics in Sungai Juru particularly related to tidal impacts. It is hoped that the modeling technique developed can be applied in other rivers in Malaysia which are subjected to tidal influences.

The temporal-spatial resolution of input data-induced uncertainty in a watershed-based water quality model, Hydrologic Simulation Program-FORTRAN (HSPF), is investigated in this study. The temporal resolution-induced uncertainty is described using the coefficient of variation (CV). The CV is found to decrease with decreasing temporal resolution and follow a log-normal relation with time interval for temperature data while it exhibits a power-law relation for rainfall data. The temporal-scale uncertainties in the temperature and rainfall data follow a general extreme value distribution and a Weibull distribution, respectively. The Nash-Sutcliffe coefficient (NSC) is employed to represent the spatial resolution induced uncertainty. The spatial resolution uncertainty in the dissolved oxygen and nitrate-nitrogen concentrations simulated using HSPF is observed to follow a general extreme value distribution and a log-normal distribution, respectively. The probability density functions (PDF) provide new insights into the effect of temporal-scale and spatial resolution of input data on uncertainties involved in watershed modelling and total maximum daily load calculations. This study exhibits non-symmetric distributions of uncertainty in water quality modelling, which simplify weather and water quality monitoring and reducing the cost involved in flow and water quality monitoring. Copyright © 2011 John Wiley & Sons, Ltd.

A modelling approach is presented that determines the most cost-effective set of reduction measures to reach an in-stream concentration target. The framework is based on the coupling of two models: the hydrological water quality model SWAT and an economic optimization model (Environmental Costing Model, ECM). SWAT is used to determine the relationship between the modelled in-stream concentration at the river basin outlet and the associated emission reduction. The ECM is used to set up marginal abatement cost curves for nutrients and oxygen demanding substances. Results for nitrogen are presented for the Grote Nete river basin in Belgium for the year 2006. Results show that the good status for total nitrogen can be reached in the study area. The most cost-effective measures are more productive dairy cattle, implementing basic measures as defined in the WFD, winter cover crops, improved efficiency of WWTP, enhanced fodder efficiency for pigs, further treatment of industrial waste water and tuned fertilization. (C) 2010 Elsevier Ltd. All rights reserved.

This paper extends previous work comparing the response of water quality models under uncertainty. A new model, the River Water Quality Model no. 1 (RWQM1), is compared to the previous work of two commonly used water quality models. Additionally, the effect of conceptual model scaling within a single modelling framework, as allowed by RWQM1, is explored under uncertainty. Model predictions are examined using against real-world data for the Potomac River with a Generalized Likelihood Uncertainty Estimation used to assess model response surfaces to uncertainty. Generally, it was found that there are tangible model characteristics that are closely tied to model complexity and thresholds for these characteristics were discussed. The novel work has yielded an illustrative example but also a conceptually scaleable water quality modelling tool, alongside defined metrics to assess when scaling is required under uncertainty. The resulting framework holds substantial, unique, promise for a new generation of modelling tools that are capable of addressing classically intractable problems.

Laguna de Bay is the second largest inland waterbody in South-east Asia. Considering its large size, its competing and conflicting water resource users, and increasing threats to its ecological integrity, coherent and participative relationship between and among its stakeholders is crucial for its sustainable management. This study discusses the foundation and framework, and the research results, of an ongoing joint monitoring and research collaboration between an academic institution and a government agency directed to the Laguna de Bay environment. Spatial and temporal monitoring of climatic, hydrodynamic and water quality lake variables were carried out collaboratively through field surveys and laboratory analyses. The lake’s temporal and spatial dynamics under changing atmospheric conditions were investigated through field monitoring efforts, coupled with three-dimensional hydrodynamic and water quality modelling. Contrary to common perception, these study results indicated significant vertical and diurnal variations in lake variables, in spite of a shallow average water depth of 2.5 m. Intense atmospheric heating (≈800 W m−2), accentuated by the lake’s high turbidity (16–32 FTU), generated density differences along the vertical axis and caused stratification. Higher biological activity, with significantly correlated pH, dissolved oxygen and chlorophyll-a variations during the dry season, is strongly related to the stable solar irradiance, reduced lake water volume and inflow of nutrient-rich seawater from Manila Bay and Metro Manila sewage. The observed bottom hypoxic conditions (2–4 mg L−1), concurrent with the absence of thermal overturn, are suggestive of the importance of diel wind-induced mixing and attest to the eutrophic condition of the lake. Numerical modelling analysis indicated that lake water quality was significantly affected by aquaculture operations and polluted seawater intrusions. Scenario simulations on bathymetric evolution demonstrated morphological changes that contributed to the eutrophic vulnerability of Laguna de Bay, in addition to anthropogenic-based stressors. Given the natural inclination of tropical lakes to eutrophic conditions, actions across boundary, resource and responsibility sharing, and expansion of intellectual horizon through partnership, are vital for the rational and systematic resolution of lake water resource allocations and ecological preservation.

Summary River water quality models can be valuable tools for the assessment and management of receiving water body quality. However, such water quality models require accurate model calibration in order to specify model parameters. Reliable model calibration requires an extensive array of water quality data that are generally rare and resource-intensive, both economically and in terms of human resources, to collect. In the case of small rivers, such data are scarce due to the fact that these rivers are generally considered too insignificant, from a practical and economic viewpoint, to justify the investment of such considerable time and resources. As a consequence, the literature contains very few studies on the water quality modelling for small rivers, and such studies as have been published are fairly limited in scope. In this paper, a simplified river water quality model is presented. The model is an extension of the Streeter–Phelps model and takes into account the physico-chemical and biological processes most relevant to modelling the quality of receiving water bodies (i.e., degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production). The model has been applied to an Italian case study, the Oreto river (IT), which has been the object of an Italian research project aimed at assessing the river’s water quality. For this reason, several monitoring campaigns have been previously carried out in order to collect water quantity and quality data on this river system. In particular, twelve river cross sections were monitored, and both flow and water quality data were collected for each cross section. The results of the calibrated model show satisfactory agreement with the measured data and results reveal important differences between the parameters used to model small rivers as compared to those for large rivers. Additionally, these results appear related to the different roles played by physical–chemical–biological processes in small rivers as compared to larger systems.

River are one of vital water resources for human and ecosystem, and it is important to monitored and controlled the river water quality. Malacca watershed is located at the centred of Malacca state, and one of the important attraction places for tourism and urbanization activity. The tremendous activity at Malacca river has led to water pollution issues and of river water quality. There are several cases of fish kills incident reported at the estuarine Malacca River. The objectives of present work are to assess water quality status of the Malacca river based on Water Quality Index (WQI) analysis and to investigate the trend of Chemical Oxygen Demand (COD) along the Malacca river from 2003 until 2012. Statistical analysis was done by using Pearson Correlation Coefficient Analysis based on water quality data collected from August 2014 until October 2014 at Malacca River. As a results, from the WQI analysis at four different times of sampling, Malacca River was classified into Class III, which is polluted river. The correlation analysis shows the strong correlation between PO43- and TP; PO43- and NH3+ ; TN and NH3+; COD and TSS; and COD and DO; at probability value, p equals to 0.01. As a conclusion, present work is crucial for water quality assessment to develop the suitable watershed management in order to sustain the river water quality. This study can be used for future study in developing water quality modelling and total maximum daily load (TMDL) approach.

Nowadays, the development and urbanization have increase the pollutant loads in the river environment. As one of the important water resource, river has been threatened by the increasing of pollutant loads in the river body. The water quality modelling is an important tool to simulate water quality analysis and river management by addition of pollutant loads. The needs of effective watershed management are crucial to ensure the river is well managing and regulated. In Malaysia, Malacca River has become one of the most popular place for tourism activities. Present work has developed water quality modelling by using InfoWork River Simulation version 10.5, to simulate the water quality condition by doing pollution reduction analysis. The modelling framework is developed to simulate the load reduction for Chemical Oxygen Demand (COD) as the pollutant controlled at the selected area. The simulation shows that, based on four scenarios created, Scenario 3 are selected as the best condition to achieved Class II water quality standard. As a conclusion, the development of water quality modelling by using InfoWork (RS) can improve the water quality condition at Malacca River by using pollution loading reduction analysis and suggested for future watershed management such as Total Maximum Daily Load (TMDL) implementation plan.

Istanbul, being one of the highly populated metropolitan areas of the world, has been facing water scarcity since the past decade. Water transfer from Melen Watershed was considered as the most feasible option to supply water to Istanbul due to its high water potential and relatively less degraded water quality. This study consists of two parts. In the first part, water quality data covering 26 parameters from 5 monitoring stations were analyzed and assessed due to the requirements of the "Quality Required of Surface Water Intended for the Abstraction of Drinking Water" regulation. In the second part, a one-dimensional stream water quality model with simple water quality kinetics was developed. It formed a basic design for more advanced water quality models for the watershed. The reason for assessing the water quality data and developing a model was to provide information for decision making on preliminary actions to prevent any further deterioration of existing water quality. According to the water quality assessment at the water abstraction point, Melen River has relatively poor water quality with regard to NH(4)(+), BOD(5), faecal streptococcus, manganese and phenol parameters, and is unsuitable for drinking water abstraction in terms of COD, PO(4)(3-), total coliform, total suspended solids, mercury and total chromium parameters. The results derived from the model were found to be consistent with the water quality assessment. It also showed that relatively high inorganic nitrogen and phosphorus concentrations along the streams are related to diffuse nutrient loads that should be managed together with municipal and industrial wastewaters.

An "all pipes" hydraulic model of a drinking water distribution system was constructed with two types of demand allocations. One is constructed with the conventional top-down approach, i.e. a demand multiplier pattern from the booster station is allocated to all demand nodes with a correction factor to account for the average water demand on that node. The other is constructed with a bottom-up approach of demand allocation, i.e., each individual home is represented by one demand node with its own stochastic water demand pattern. This was done for a drinking water distribution system of approximately 10 km of mains and serving ca. 1000 homes. The system was tested in a real life situation. The stochastic water demand patterns were constructed with the end-use model SIMDEUM on a per second basis and per individual home. Before applying the demand patterns in a network model, some temporal aggregation was done. The flow entering the test area was measured and a tracer test with sodium chloride was performed to determine travel times. The two models were validated on the total sum of demands and on travel times. The study showed that the bottom-up approach leads to realistic water demand patterns and travel times, without the need for any flow measurements or calibration. In the periphery of the drinking water distribution system it is not possible to calibrate models on pressure, because head losses are too low. The study shows that in the periphery it is also difficult to calibrate on water quality (e.g. with tracer measurements), as a consequence of the high variability between days. The stochastic approach of hydraulic modelling gives insight into the variability of travel times as an added feature beyond the conventional way of modelling.

This study investigates the efficiency of Bayesian network (BN) and also artificial neural network models for predicting water quality parameters in Honolulu, Pacific Ocean. Monthly forecasting of three important characteristics of water body including water temperature, salinity and dissolved oxygen have been taken under consideration. Two separate strategies were applied in which the first strategy was related to prediction of the water quality parameters based on previous time series of the same variable. In the second strategy, an attempt was made to forecast DO using different affecting parameters such as temperature, salinity, previous time series of DO, and amount of chlorophyll. The efficiency of the models were assessed by using error measures. Results revealed that the BN models are superior over the ANN models in case of temperature and DO forecasting. Also, it was found that the first strategy is more efficient than the second strategy for predicting DO concentration. The best BN models for temperature, salinity and DO were achieved when time series of the same parameter up to 3, 2, and 3 previous months applied as input variables respectively. Overall, it can be concluded that BN and ANN models can be successfully applied for water quality modelling and forecasting in coastal waters. Moreover, the current study demonstrated that the BN models have a great ability dealing with time series including incomplete or missing data.

Water quality modelling is of crucial importance for the assessment of physical, chemical, and biological changes in water bodies. Mathematical approaches to water modelling have become more prevalent over recent years. Different model types ranging from detailed physical models to simplified conceptual models are available. Actually, a possible middle ground between detailed and simplified models may be parsimonious models that represent the simplest approach that fits the application. The appropriate modelling approach depends on the research goal as well as on data available for correct model application. When there is inadequate data, it is mandatory to focus on a simple river water quality model rather than detailed ones. The study presents a parsimonious river water quality model to evaluate the propagation of pollutants in natural rivers. The model is made up of two sub-models: a quantity one and a quality one. The model employs a river schematisation that considers different stretches according to the geometric characteristics and to the gradient of the river bed. Each stretch is represented with a conceptual model of a series of linear channels and reservoirs. The channels determine the delay in the pollution wave and the reservoirs cause its dispersion. To assess the river water quality, the model employs four state variables: DO, BOD, NH4, and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project in which quantity and quality data were gathered. A sensitivity analysis of the model output to the model input or parameters was done based on the Generalised Likelihood Uncertainty Estimation methodology. The results demonstrate the suitability of such a model as a tool for river water quality management.

Surfing is becoming an important asset for local development, despite engaging water quality concerns is often limited to bathing season - thus, a tool for decision support is required to yearly forecast the water quality, in order to minimise health risks and support water management decisions. The QUAL2E model was used on a watershed, in Peniche, a coastal city in Portugal. This study area was chosen due to complaints related to the water quality by the local surfing community. Results returned a total coliform concentration of 1,500 MPN/100 mL, with pig farming effluents being the major contamination source. These results constitute evidence that surfing here may represent a health risk - as winter months are more favourable to wave sports. Therefore, it would be of the uttermost importance to improve monitoring and mitigate the potential health risk. This should include a more profound analysis of the contribution of diffuse sources and to extend the current bathing season monitoring scheme during winter times.

A numerical catchment-scale model capable of simulating diffuse water pollution is necessary in sustainable environmental management for better implementation of the EU Water Framework Directive. This paper provides critical reviews of most popular and free models for diffuse water modelling, with detailed sources and application potential. Based upon these reviews, further work of selecting and testing the HSPF model was carried out, with a case study in the Upper Bann Catchment, Northern Ireland. The calibrated and validated HSPF model can well represent the characteristics of surface water quantity and quality. Climate change scenario evaluation in 5 years showed that when the annual mean temperature increase 3°C the mean yearly total runoff volume will decrease by 11.1% and the mean daily river flow 11.4%. If 20% crop and pasture land is converted into forest land in the study area, the mean river concentration of nitrate, nitrite, NH4 and PO4 in 5 years will decrease by 19.4%, 33.3%, 31.3% and 31.3% respectively. When applying filter strip method in 80% crop and pasture land in the area, the reduction of the mean concentration of nitrate, nitrite, NH4 and PO4 in 5 years will be 15.3%, 33.3%, 31.3%, and 5.6% respectively. This study shows that HSPF is a suitable model in handling diffuse source water pollution, which can be introduced into the Programme of Measures in the River Basin Management Plans for better implementation of the EU WFD.

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 km 2 ) 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.

In recent years, there has been growing recognition of the importance of riparian buffers between agricultural fields and waterbodies. Riparian buffers play an important role in mitigating the impacts of land use activities on water quality and aquatic ecosystems. However, evaluating the effectiveness of riparian buffer systems on a watershed scale is complex, and watershed models have limited capabilities for simulating riparian buffer processes. Thus, the overall objective of this paper is to develop an understanding of riparian buffer processes towards water quality modelling/monitoring and nonpoint source pollution assessment. The paper provides a thorough review of relevant literature on the performance of vegetative buffers on sediment reduction. It was found that although sediment trapping capacities are site- and vegetation-specific, and many factors influence the sediment trapping efficiency, the width of a buffer is important in filtering agricultural runoff and wider buffers tended to trap more sediment. Sediment trapping efficiency is also affected by slope, but the overall relationship is not consistent among studies. Overall, sediment trapping efficiency did not vary by vegetation type and grass buffers and forest buffers have roughly the same sediment trapping efficiency. This analysis can be used as the basis for planning future studies on watershed scale simulation of riparian buffer systems, design of effective riparian buffers for nonpoint source pollution control or water quality restoration and design of riparian buffer monitoring programs in watersheds. Published in 2009 by John Wiley & Sons, Ltd.

The water quality improvement plan for the Tha Chin river basin in central Thailand has been studied by using integrated land-use and water quality modelling. There has been little research on water quality planning in this basin due to the complex and intensive data requirements and also due to modelling difficulties. This research attempts to apply the integrated land-use and water quality modelling to the Tha Chin river basin. Loading reduction scenarios were applied to find out the appropriate loading reduction target and hence the improved water quality in the main stream.

Complying with proposed Water Framework Directive (WFD) water quality standards for ‘good ecological status’ in England and Wales potentially requires a range of Programmes of Measures (PoMs) to control point and diffuse sources of pollution. There is an urgent need to define the benefits and costs of a range of potential PoMs. Water quality modelling can be used to understand where the greatest impact in a catchment can be achieved through ‘end of pipe’ and diffuse source reductions. This information can be used to guide cost-effective investment by private water companies and those with responsibilities for agricultural, industrial and urban diffuse inputs. In the UK, river water quality modelling with the Environment Agency SIMCAT model is regarded as the best current approach to support decision making for river water quality management and planning. The paper describes how a SIMCAT model has been used to conduct a trial WFD integrated catchment planning study for the River Ribble catchment in the North West of England. The model has been used to assess over 80 catchment planning scenarios. The results are being used support a national assessment of the cost-effectiveness of proposed PoMs.

Rivers in hilly region are generally swift fast moving, steep and varying slopes, shallow depth and narrow as compared to rivers in plain regions. They are typically characterized by the presence of water falls of small to medium height, the algal growth attached to river bed stones, and small deeper pools formed in the course of river, which affect the rate kinetics of river. Thus, in these rivers significant re-aeration is caused by frequent falls and turbulence created by bed-stones; algal growth on bed-stones causes large diurnal DO variations; pools formed in the river course act as oxidation ponds which remove significant BOD and formation of thick biological slime layer on the stones and rocks at the bed in the more polluted stretches. The widely used 1-dimensional river water quality models such as QUAL2e and STREAM do not explicitly simulate these processes with the result that these models become less useful for modelling such rivers. Application of a simple 1-D water quality model was ...

A simple and robust Lagrangian particle scheme is proposed to solve the advective-diffusion transport problem. The scheme is based on relative diffusion concepts and simulates diffusion by regulating particle separation. This new approach generates a deterministic result and requires far less number of particles than the random walk method. For the advection process, particles are simply moved according to their velocity. The general scheme is mass conservative and is free from numerical diffusion. It can be applied to a wide variety of advective-diffusion problems, but is particularly suited for ecological and water quality modelling when definition of particle attributes (e.g., cell status for modelling algal blooms or red tides) is a necessity. The basic derivation, numerical stability and practical implementation of the NEighborhood Separation Technique (NEST) are presented. The accuracy of the method is demonstrated through a series of test cases which embrace realistic features of coastal environmental transport problems. Two field application examples on the tidal flushing of a fish farm and the dynamics of vertically migrating marine algae are also presented.

Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.

Understanding of riverine and estuarine mixing processes remains limited, and predictions are highly sensitive to specific features of natural systems. One reason for this is the very complex variations of hydrodynamic and physio-chemical properties with the tidal phase. This study presents the results of two field works during which a range of flow and chemical parameters were recorded simultaneously at several locations along a small sub-tropical estuary. The studies were conducted in contrasting (wet and dry) conditions. Field measurements indicated that the hydrodynamics and water conductivity were dominated by tidal forcing and, to a lesser extent, by freshwater inputs. There were generally significantly greater differences between longitudinal sites than between vertical depths, although some marked differences were observed between the upper and lower estuarine zones. The comparative results between wet and dry field studies illustrated some marked stratification in wet weather along the whole of the estuary, implying that the surface samples were not representative of the average water column properties. Overall, the complexity of the hydrodynamics and water quality has some impact on water quality modelling of the system.

Water quality modelling in the meso-scale Rhin catchment in the German federal state Brandenburg was done (1) to answer some specific questions concerning identification of point and diffuse sources of nutrient pollution in the catchment, (2) to assess the influences of possible climate and land use changes on water quantity and quality and (3) to evaluate potential measures to be done in order to achieve a “good ecological status” of the river and its lakes as required by the Water Framework Directive (WFD). The Rhin catchment is a typical highly regulated lowland river basin in Northern Germany. The regulations complicate water quantity and quality modelling in the catchment. The research was done by using the eco-hydrological model SWIM (Soil and Water Integrated Model), which simulates water and nutrient fluxes in soil and vegetation, as well as transport of water and nutrients to and within the river network. The modelling period was from 1981 until 2005. After calibrating the hydrological processes at different gauges within the basin with satisfactory results, water quality (nitrogen and phosphorus) modelling was done taking into account the emissions of different point sources (sewage treatment plants, etc.) and identifying the amount of diffuse pollution caused mainly by agriculture. For suggesting some feasible measures to improve water quality and to reduce diffuse pollution considering possible climate and land use changes, different reasonable scenarios were applied in consultation with the Environmental Agency of Brandenburg (LUA). The study revealed that the amount of water discharge has significant influence on the concentration of nutrients in the river network, and that nitrogen pollution, caused mainly by diffuse sources, could be notably reduced by application of agricultural measures, whereas the pollution by phosphorus could be diminished most effectively by the reduction of point source emissions.

Recent trends in the management of water supply have increased the need for modelling techniques that can provide reliable, efficient, and accurate representation of the complex, non-linear dynamics of water quality within water distribution systems. Statistical models based on artificial neural networks (ANNs) have been found to be highly suited to this application, and offer distinct advantages over more conventional modelling techniques. However, many practitioners utilise somewhat heuristic or ad hoc methods for input variable selection (IVS) during ANN development. This paper describes the application of a newly proposed non-linear IVS algorithm to the development of ANN models to forecast water quality within two water distribution systems. The intention is to reduce the need for arbitrary judgement and extensive trial-and-error during model development. The algorithm utilises the concept of partial mutual information (PMI) to select inputs based on the analysis of relationship strength between inputs and outputs, and between redundant inputs. In comparison with an existing approach, the ANN models developed using the IVS algorithm are found to provide optimal prediction with significantly greater parsimony. Furthermore, the results obtained from the IVS procedure are useful for developing additional insight into the important relationships that exist between water distribution system variables.

Today, there is a growing interest in network water quality modelling. The water quality issues of interest relate to both dissolved and particulate substances. For dissolved substances the main interest is in residual chlorine and (microbiological) contaminant propagation; for particulate substances it is in sediment leading to discolouration. There is a strong influence of flows and velocities on transport, mixing, production and decay of these substances in the network. This imposes a different approach to demand modelling which is reviewed in this article. For the large diameter lines that comprise the transport portion of a typical municipal pipe system, a skeletonised network model with a top-down approach of demand pattern allocation, a hydraulic time step of 1 h, and a pure advection-reaction water quality model will usually suffice. For the smaller diameter lines that comprise the distribution portion of a municipal pipe system, an all-pipes network model with a bottom-up approach of demand pattern allocation, a hydraulic time step of 1 min or less, and a water quality model that considers dispersion and transients may be needed. Demand models that provide stochastic residential demands per individual home and on a one-second time scale are available. A stochastic demands based network water quality model needs to be developed and validated with field measurements. Such a model will be probabilistic in nature and will offer a new perspective for assessing water quality in the drinking water distribution system.

This study intends to provide the necessary basic data needed for predicting the water quality and examining changes in water quality on the basis of the hydrological changes: an outflow or the character of a flow by investigating the interaction of the parameters through the estimation of optimal parameters need for predicting the water quality of the dam basin and the sensitivity among those estimated parameters. Im-Ha Dam in the upstream area of the Nakdong River was selected for analysis, and the water quality survey data necessary for parameter estimation was based on the monthly water quality data (water temperature, BOD, T-N and T-P) between December 1, November 31, 2006. K1C(the saturated growth rate of plant plankton), K1RC (endogenous respiratory quotient of plankton), KDC(deoxidized ratio), K71C(minealized ratio of dissolved organic phosphorus), K83C(mineralized ratio of dissolved organic nitrogen) have been considered as the factors of the water quality performed in this water quality simulation, that is, the most effective parameters on BOD, T-N and T-P. In the result of the analysis of the sensitivity, KDC(deoxidized ratio) was the most sensitively reacted parameter on BOD and it was K71C(mineralized ratio of dissolved organic phosphorus) and K83C(mineralized ratio of dissolved organic nitrogen) on T-N and T-P. It is considered that it will be possible to apply the most optimal parameter to an analysis of the water quality simulation at Im-Ha Ho basin in the goal year by examining the interaction of the parameters through the parameters sampling which are able to applicable to prediction of the water quality and the analysis of the its sensitivity, in the future, also the analysis on the basis of the hydrological conditions: an outflow or the character of a flow will be needed.

The quality of drinking water generally deteriorates when it is delivered through a distribution system due to the decay of disinfectant, which subsequently allows the re-growth of microorganisms in the distribution system in addition to the formation of trihalomethane (THM). Therefore, a model which describes the changes that occur in the water quality in the distribution system is needed to determine whether to enhance the treatment processes or to improve the distribution system so that microbiological criteria are met. In this paper the chlorine decay kinetics and THM formation in treated water is modeled considering the reaction of chlorine with fast and slow reacting organic and nitrogenous compounds which are present in that water. The treated water was also passed through three types of resins to fractionate very hydrophobic acids (VHA), slightly hydrophobic acids (SHA), hydrophilic charged (CHA) and hydrophilic neutral (NEU) compounds which are present in the water. Chlorine decay tests were conducted on the effluents emerging from the resins to evaluate the chlorine demand and THM formation potential of those organic fractions. The model shows that the CHA presented in the waters has a very high THM formation potential (around 62% of the THM produced). VHA, NEU and CHA contributed to chlorine demand in the water.

Water quality modelling in small rivers is often considered unworthy from a practical and economic viewpoint. This paper shows instead that a simple model structure can be set up to describe the stationary water quality in small river basins in terms of carbon and nitrogen compounds, when the use of complex models is unfeasible. In short rivers point and nonpoint sources play a key role in shaping the model response, being as important as the self-purification dynamics. Further, the varying river characteristics, in terms of morphology, hydraulics and vegetation, require the introduction of variable parameters, thus complicating the originally simple model structure. To determine the identifiability of the resulting model an identifiability assessment was carried out, based on sensitivity analysis and optimal experiment design criteria. The identifiable subset was determined by ranking the parameters in terms of sensitivity and computing the associated Fisher Information Matrices. It was found that the inclusion of the nonpoint sources as piecewise constant parameters affected the identifiability to a considerable extent. However, the combined parameter-sources calibration was made possible by the use of a robust estimation algorithm, which also provided estimation confidence limits. The calibrated model responses are in good agreement with the data and can be used as scenario generators in a general strategy to conserve or improve the water quality.

A recently developed approach to divide phytoplankton into functional groups was implemented in the biogeochemical lake model BELAMO and tested by comparing model results with data from three lakes of different trophic state. The groups are distinguished by different values of specific growth rate (kgro,ALG), half-saturation light intensity of primary production (KI,ALG), edibility (kgro,ZOO), sedimentation velocity ( v sed ), and half-saturation concentration with respect to phosphate uptake (KP,ALG). After calibration, the occurrence pattern of the functional groups in the three lakes can qualitatively be represented by the model. However, some quantitative and systematic differences between model results and data remain. Furthermore, the division of total phytoplankton into functional groups makes these groups very sensitive to changes in kinetic model parameters. There is a very high sensitivity of each group not only to the parameters characterizing this group, but due to very strong interactions, also to the parameters determining the dynamics of the other groups. In contrast, the sensitivity of total phytoplankton to parameter changes remains at a similar level as in the aggregated model. The resulting high sensitivity of the composition of the phytoplankton community on model parameters indicates a poor predictability of the occurrence of functional groups in these lakes. Strong phosphorus limitation during the summer could be the cause for the better predictability of total phytoplankton concentrations in both, the aggregated and the functional group phytoplankton models.

The following paper presents a computer-based learning strategy to assist in introducing and teaching water quality modelling to undergraduate civil engineering students. As part of the learning strategy, an interactive computer-based instructional (CBI) aid was specifically developed to assist students to set up, run and analyse the output from a commercially available water quality model (WQMAP) for a hypothetical raw sewage spill. The CBI aid comprised a Hypertext Markup Language (HTML) module with helpful text and still graphics, and links to on-screen recorded motion movie clips showing on-screen actions and voice narrations during the instructors absence. An anonymous class questionnaire to assess the students' perceptions of the developed approach found that most students felt they were able to complete the project with minimum supervision, and have acquired a basic understanding of water quality modelling as a result of the activity. Additionally, almost all of the students found the CBI aid helpful and easy to follow.

We present an independent assessment of the health and water sustainability of the East River (Dongjiang) in South China, which is the source of nearly 80% of Hong Kong's water supply. Field measurements show that the water quality in the upper and middle reaches is generally good and well exceeds the drinking quality standard, with high bio-diversity. The streamflow of the East River Basin is satisfactorily simulated using both the distributed MIKE-SHE model and the lumped HSPF model. With an average streamflow of 760 m3/s, the River is able to satisfy the current water demand. Using the HSPF model, the water quality is found to have deteriorated in recent years. In addition to water supply, the River also supports a variety of needs such as hydro-power generation, waste assimilation, navigation, habitat for aquatic life, and expulsion of sea water intrusion. Using the projected need of 150 m3/s for water supply, the instream flow requirement based on hydrological and water quality simulation is estimated to be 467 m3/s in 2010. This suggests that the water sustainability of the East River requires alternative strategies, which may include integrated water resources management, provision of better wastewater treatment, and water and soil conservation.

The objective of this study is analysis of Andong-Dam lake water quality with water quality model. Model parameters of the WASP applied to Lake Andong-Dam were estimated. The methodology is based on grouping water quality constituents and relevant parameters and successively estimating parameters by a trial-and-error procedure. Water qualify system for modeling consisted of BOD, DO, T-N, T-P. The results of water quality modelling using WASP. T-N was maximum affected by K71C(Organic nitrogen mineralization rate) parameter. T-P was maximum affected by K83C(Dissolved organic phosphorus mineralization) parameter, and It did not show a difference almost from the parameter of others and it omitted. BOD was maximum affected by Temperature parameter, it was visible of the reaction due to the KDC(Deoxygenation rate) in afterwords, and it did not show a difference from the parameter of others and it omitted. DO was maximum affect by Temperature parameter, and It did not show a difference almost from the parameter of others and it omitted. The parameter which it presumes from the this study uses a water quality modeling and Actual value and the result with which it compares, error rate the parameter presumption which is appropriate with 1% interior and exterior is investigated, It will reach and it uses and it will be able to apply to the suitable parameter in water quality modelling of the objective area which can be feeded by it becomes.

This paper describes the utility of QUAL2E as a modelling package in the evaluation of a water quality improvement programme. In this study, QUAL2E was applied to determine the pollution loads in the river Yamuna during its course through the national capital territory of Delhi, India. The study aimed at examining the influence of different scenarios on river water quality. Four different pollution scenarios were analysed besides the 'business as usual' situation. The study revealed that it was necessary to treat the discharge from drains to the river Yamuna and diversion of a substantial load to the Agra canal for further treatment was also essential. It was also established through this study that maintaining a flow rate of more than 10 m(3)/s in the river could also help preserve the river's water quality. To clearly display the model outcomes and demarcate polluted zones in the river stretch, model results were interfaced with a Geographical Information System (GIS) to produce cartographic outputs. In addition, uncertainty analysis in the form of first-order error analysis and Monte Carlo analysis was performed, to realise the effect of each model parameter on DO and BOD predictions. The uncertainty analysis gave satisfactory results on simulated data.

Summary In a national effort, since 1972, the Swiss Government started the “National Long-term Monitoring of Swiss Rivers” (NADUF) program aimed at evaluating the chemical and physical states of major rivers leaving Swiss political boundaries. The established monitoring network of 19 sampling stations included locations on all major rivers of Switzerland. This study complements the monitoring program and aims to model one of the program’s catchments – Thur River basin (area 1700 km 2 ), which is located in the north-east of Switzerland and is a direct tributary to the Rhine. The program SWAT (Soil and Water Assessment Tool) was used to simulate all related processes affecting water quantity, sediment, and nutrient loads in the catchment. The main objectives were to test the performance of SWAT and the feasibility of using this model as a simulator of flow and transport processes at a watershed scale. Model calibration and uncertainty analysis were performed with SUFI-2 (Sequential Uncertainty FItting Ver. 2), which was interfaced with SWAT using the generic iSWAT program. Two measures were used to assess the goodness of calibration: (1) the percentage of data bracketed by the 95% prediction uncertainty calculated at the 2.5 and 97.5 percentiles of the cumulative distribution of the simulated variables, and (2) the d-factor , which is the ratio of the average distance between the above percentiles and the standard deviation of the corresponding measured variable. These statistics showed excellent results for discharge and nitrate and quite good results for sediment and total phosphorous. We concluded that: in watersheds similar to Thur – with good data quality and availability and relatively small model uncertainty – it is feasible to use SWAT as a flow and transport simulator. This is a precursor for watershed management studies.

A water quality model (MERES) is applied in the multi-purpose reservoir of Plastiras in Greece. The model was calibrated with limited field data using the standard trial and error procedure; next, it was applied for four scenarios of reservoir operation, which correspond to four values of minimum water levels (MWL). Model results were combined with landscape aesthetics to establish a “safe” MWL in the reservoir. MWL was proposed to be +784 m, a value that ensures a very good water quality by retaining the reservoir in the status of “a little beyond oligotrophic” and a very good quality of landscape with an acceptable area of dead zones; it also ensures an annual release of 127.5 hm3 of water within a reliability level of 90%. This quantity can be considered as acceptable from the water supply point of view.

Additive models are widely used to provide very flexible and effective descriptions of regression data where assumptions of linear relationships are too restrictive. However, these models usually assume independent errors and there are many applications where the data are correlated. This is often true in environmental settings and an application to water quality modelling in the River Clyde is described. Methods of fitting and analysing an additive model in this setting are discussed. An approach which fits an additive model in the usual way but incorporates the correlated error structure into the assessment of components is described. The methods are applied to the Clyde data to identify the factors which affect water quality, as well as spatial and temporal trends. Interaction terms, which allow the effects of explanatory variables to change smoothly with position down the river, are also explored. Particular emphasis is placed on approximate F tests to identify the most suitable models and the presence and nature of particular covariate effects. Copyright © 2007 John Wiley & Sons, Ltd.

Water quality investigations were undertaken in the Dionosoyiet wetland (Lake Victoria basin, Kenya) from June 2004 to April 2005 for nutrients and suspended solids. Hydrology and Water Quality modelling were performed based on the CRC FE POND model. The model was adapted to incorporate a rainfall runoff module based on the isochronal histogram technique and a partially stochastic prediction of water quality (TSS, TN and TP) based on incoming flow rates. Using the data gathered from June 2004 to April 2005 for calibration and earlier climatic data, modelling was performed to cover an 11 year period, from January 1994 to December 2004, and indicated that the wetland removed 43% TSS, 41% TP and 20% TN with average areal removal rates of 21.3 TSS, 0.038 TP and 1.03 TN (kg ha −1 day −1 ). The findings show that, in addition to being a central community activity feature of the town, the wetland performs significant functions of water quality improvement. The preservation of this wetland and other similar wetlands is important in ensuring sustainable utilisation of water resources in the Lake Victoria Basin.

Artificial neural networks (ANNs) have been applied successfully in various fields. However, ANN models depend on large sets of historical data, and are of limited use when only vague and uncertain information is available, which leads to difficulties in defining the model architecture and a low reliability of results. A conceptual fuzzy neural network (CFNN) is proposed and applied in a water quality model to simulate the Barra Bonita reservoir system, located in the southeast region of Brazil. The CFNN model consists of a rationally-defined architecture based on accumulated expert knowledge about variables and processes included in the model. A genetic algorithm is used as the training method for finding the parameters of fuzzy inference and the connection weights. The proposed model may handle the uncertainties related to the system itself, model parameterization, complexity of concepts involved and scarcity and inaccuracy of data. The CFNN showed greater robustness and reliability when dealing with systems for which data are considered to be vague, uncertain or incomplete. The CFNN model structure is easier to understand and to define than other ANN-based models. Moreover, it can help to understand the basic behaviour of the system as a whole, being a successful example of cooperation between human and machine. Copyright © 2006 John Wiley & Sons, Ltd.

Managing combined sewage systems in large cities discharging to coastal waters, often bearing recreational activities, remains a challenge. Studying the impacts of such discharges requires the development of specific models. Hydrodynamic and water quality modelling of coastal waters employs numerical methods and algorithms, leading to the design of complex models which require expert use. The use of such models as decision support tools to simulate discharge impacts and define adequate corrective measures could represent a key part in meeting this challenge. In this paper, the authors describe the work undertaken to develop an operational decision support system (ODSS) methodology aiming to enable wastewater utilities' non-expert staff to carry out user-friendly scenario analysis based on computational fluid dynamics simulations. This article depicts the application and validation of the ODSS to the combined sewage system and the Tagus estuary of the city of Lisbon in Portugal. The ODSS was used for simulating the effects in the receiving coastal waters of a discharge caused by a scheduled maintenance operation in the sewage infrastructure. Results show that the use of such ODSS by non-expert staff increases their decision capabilities and knowledge of the wastewater utility's contribution to reducing negative impacts of sewage discharges on the receiving water bodies.

Cryptosporidium is a protozoan parasite that can cause diarrhoea. Human faeces are an important source of Cryptosporidium in surface waters. We present a model to study the impact of sanitation, urbanization and population growth on human emissions of Cryptosporidium to surface waters. We build on a global model by Hofstra et al (2013 Sci. Total Environ. 442 10–9) and zoom into Bangladesh and India as illustrative case studies. The model is most sensitive to changes in oocyst excretion and infection rate, and to assumptions on the share of faeces reaching the surface water for different sanitation types. We find urban centres to be hotspots of human Cryptosporidium emissions. We estimate that 53% (Bangladesh) and 91% (India) of total emissions come from urban areas. 50% of oocysts come from only 8% (Bangladesh) and 3% (India) of the country area. In the future, population growth and urbanization may further deteriorate water quality in Bangladesh and India, despite improved sanitation. Under our 'business as usual' ('sanitation improvements') scenario, oocyst emissions will increase by a factor 2.0 (1.2) for India and 2.9 (1.1) for Bangladesh between 2010 and 2050. Population growth, urbanization and sanitation development are important processes to consider for large scale water quality modelling.

As the recognition of the concept ‘Sustainable Development’ is increasing throughout the world, understanding the adverse impact of water quality parameters is highly important for the protection and improvement of aquatic environments from the impact of pollution. Therefore, the measurement of water quality parameters is required to protect and improve aquatic environments from the impact of pollution. The estimation of water quality parameters from direct field measurement is costly, time-consuming and sometimes impossible. Therefore, mathematical approaches of water quality models have become prevalent in recent years for the purpose of watershed management strategies. However, water quality model parameters vary not only spatially (i.e. catchment to catchment), but also temporally (i.e. differ among different rainfall events). Because depending upon the catchment characteristics such as soil permeability and initial pollutant loads, the impact of the actual land-use and management changes. There exists a wide range of water quality models to be used in managing water quantity and quality with respect to a variety of environmental impacts. This chapter presents a rigorous literature review regarding available catchment water quality modelling techniques developed in recent years. The goal is to identify the most effective water quality modelling technique which will help in the analysis, improvement and update of best management practices (BMPs). The selected modelling technique will help watershed management authorities to enable them implement economically viable and effective management and mitigation strategies to protect aquatic environments from the impact of pollution.

Waste load allocations in the United States have traditionally been based on historic data. Total Maximum Daily Load (TMDL) policies and stormwater permits are often based on steady-state low flow analysis without considering unsteady flow and pollutant conditions prevalent during stormwater events. Questions surrounding remedial investments for conditions that don’t exist during low flow events have been raised. Furthermore, the frequency of violations under various pollutant removal scenarios has been hard to determine. The Spokane River TMDL used a 2001 low flow event as the basis for planning multi-million dollar investments in wastewater treatment systems and stormwater plans. This study modified the original CE-QUAL-W2 model to simulate hydrology and water quality over a 1999–2009 period with attention to flow, phosphorus, nitrogen, dissolved oxygen, and river temperature. By calibrating and applying the model for an extended period, we were able to better predict nutrient dynamics under varying flow conditions and facilitate investigation regarding permissible nutrient levels. Model results indicate that hydrologic conditions outside the low flow period may be cause for concern. Violation of water quality standards occurred outside the 2001 time frame with both phosphorus and nitrate concentrations being much higher in years with higher flows. We were able to successfully demonstrate that additional information concerning stormwater inputs and nutrient cycling would permit better decisions in the future.

[ES] Este trabajo presenta un trabajo integrado de modelización de los impactos por oxígeno disuelto y amonio producidos por los DSU del sistema de saneamiento de Lugo sobre el río Miño. La modelización de la red de saneamiento se ha realizado con el programa SWMM. Para la modelización del impacto sobre el río Miño se ha empleado el programa Iber. Los impactos por los DSU se han evaluado empleando estándares de emisión (frecuencia y volumen de los DSU), y los estándares de calidad ambiental recogidos en el Urban Pollution Management. Los principales resultados del estudio indican que el tramo de río estudiado no es adecuado para la vida de salmónidos en términos de oxígeno disuelto, aunque las restricciones por amonio se cumplen para todo el tramo analizado., [EN] This study presents an integrated modelling approach to estimate dissolved oxygen and ammonia impacts of CSO of the city of Lugo sewer network in the Miño river. Sewer network modelling was performed with the SWMM software package, while Iber 2D shallow water code was used for river quality modelling. CSO impacts were evaluated by means of Emission Standards (CSO spill frequency/volume), and the Environmental Quality Standards presented in the Urban Pollution Manual were applied to evaluate the receiving water quality. The main results show that the studied river reach is not suitable for salmonid fishery in terms of dissolved oxygen concentrations, whereas total ammonia limitations are verified throughout the reach., Este trabajo ha sido desarrollado con ayuda de la Confederación Hidrográfica Miño-Sil y PROYFE. Daniel Torres colaboró en el desarrollo de la campaña de caracterización de DSU. Por último, los autores quieren agradecer los comentarios de José Piñeiro, Fran Aguirre y Juan Vidal.

This paper reviews the accomplished research on water quality modelling with the use of Geographical Information Systems (GIS) and remotely sensed data. Basic definitions, theory and classifications of hydrological models usually used in the field of hydrological water quality modelling are highlighted. Examples of research in field of hydrology that benefited from modern technologies of GIS and remote sensing are discussed. Integration of hydrological models with topographic information known as digital elevation model (DEM) is investigated. Conclusions and possible research areas are also suggested.

Water quality modelling in small rivers is often considered unworthy from a practical and economic point of view. This work shows that a simple model structure can be set up to describe the stationary water quality in small river basins in terms of carbon and nitrogen compounds, when it is unfeasible to use complex models. The one-dimensional model include principle factors such as chemical and biological oxidation, concentration of nutrients. Natural process of self-purification for small river in sharp continental climate of Central Siberia is inhibited by low temperatures, rapid currents and poor development of plankton cenosis. So, a determination of model parameters demands carrying out of special experiments with water samples. The results of numerical modelling are verified by data from the environmental monitoring of some rivers in the basin of Central Enisey.

Water quality modelling deals with multidisciplinary questions ranging from fundamental to applied. Addressing this broad range of questions requires multiple analysis techniques and therefore multiple frameworks. Through the recently developed database approach to modelling (DATM), it has become possible to run a model in multiple software frameworks without much overhead. Here we apply DATM to the ecosystem model for ditches. PCDitch and its twin model for shallow lakes PCLake. Using DATM, we run these models in six frameworks (ACSL, DELWAQ, DUFLOW, GRIND for MATLAB, OSIRIS and R), and report on the possible model analyses with tools provided by each framework. We conclude that the dynamic link between frameworks and models resulting from DATM has the following main advantages: it allows one to use the framework one is familiar with for most model analyses and eases switching between frameworks for complementary model analyses, including the switch between a 0-D and 1-D to 3-D setting. Moreover, the strength of each framework – including runtime performance – can now be easily exploited. We envision that a community-based further development of the concept can contribute to the future development of water quality modelling, not only by addressing multidisciplinary questions but also by facilitating the exchange of models and process formulations within the community of water quality modellers.

The aim of the research presented in this manuscript is to model the outflow discharge and nutrient load at the outlet of small scale, mainly agricultural catchments. There to two approaches for the simulation of the transport of water and the transport and transformation of nitrogen in the stream were tested and compared. Both approaches use the DRAINMOD and the DRAINMOD-N models to simulate the hydrology and the nitrogen balance of the land phase at the scale of a field/field block/sub-catchment. Both models are used to generate the drain outflow and the nitrate concentration of the drainage water of the field unit considered. The contribution of the field units to the nutrient load of the river are calculated by multiplying the simulated flow weighted N concentrations with drain outflows. In a first approach, called the lumped approach, the water discharge and the nutrient load of field blocks are routed through the river using an exponential model. In this model the nitrate contribution of an individual field block to the nitrate load in the river outlet is calculated assuming first order nutrient decay/attenuation during the transport of the drainage water from the field outlet to the river outlet. The arrival at the outlet section of the nitrate plumes of the field blocks are phased in time based on the velocity profile in the river. The second approach, herein called the complex approach is using the hydraulic river modeling code MIKE 11. This model is using a complex process ADR (advective-dispersive-reactive) equation to calculate the chemical changes in the river water. The comparative analysis between both routing approaches reveals that the lumped approach is able to predict sufficiently accurate nutrient load at the catchment outlet. The complex approach has the advantage of giving a more accurate estimate of the nutrient load at the catchment outlet, resulting in a more precise modeling of the transport and transformation of the nutrient load in streams.

There are four ecologically important river catchments that contain candidate Special Areas of Conservation (cSACs) under the Habitats Directive in the Lake District National Park located in the North of England. These are the rivers Ehen, Kent, Derwent and Eden. For each cSAC, there are defined ecological criteria that include water quality targets to protect the designated species. Stretches of the riverine cSACs in each catchment are failing to meet these and other water quality targets. The Environment Agency commissioned a study of each catchment to provide the underpinning scientific knowledge to allow it to deliver its statutory obligations under the Habitats Directive. SIMCAT river water quality models were produced and used to predict the water quality impacts resulting from a number of water quality planning scenarios aimed at achieving full compliance with the Habitats Directive and other national and EEC water quality targets. The results indicated that further controls on effluent discharges will allow the majority of targets to be met but other sources of pollution will also need to be controlled. The outcome of the study also recognised that water quality improvements alone will not necessarily produce the required improvement to the ecological interest features in each cSAC.