Hydrological Water Quality Model Research Articles

Control of urban river water pollution is studied based on SMS

With the rapid development of economy and society, environmental pressure is increasing and environmental problems are emerging. The pollution of urban water environment is particularly serious. A large number of river channels are cut off and landfilled, land plants are destroyed and hardened, and domestic and production sewage is directly discharged into river channels, resulting in serious damage to the ecological environment of urban water bodies. In the perspective of ecological environment protection, urban polluted rivers have become the focus of water pollution control. In order to improve the ecological environment of urban water body and ensure the sustainable development of social economy, it is of great significance to study the control of urban river water pollution. In this paper, the methods of data collection, numerical simulation and theoretical analysis are used to study the water pollution control of urban inland rivers. Firstly, the current situation of urban water pollution is understood through data access, and then the hydrological water quality model is established based on RMA2 and RMA4 models in SMS. The main parameters of the model were determined by the method of sensitivity analysis. The results show that RMA2 model with Peclet number of 20 and roughness of 0.045, RMA4 model with diffusion coefficient of 1 and NH 3 -N degradation coefficient of 0.16 d −1 can simulate pollutant diffusion well. This paper uses the water quality model to simulate the water environment of urban inland rivers. The research results show that the water quality model can calculate the water environment capacity and pollutant capacity, so as to obtain the amount of water pollutants to be reduced, and realize the effective control of urban river water pollution. • This paper uses data collection, numerical simulation and theoretical analysis to study the prevention and control of water pollution in urban inland rivers. • This article first understands the current situation of urban water pollution through data access, and then establishes a hydrological and water quality model based on the RMA2 and RMA4 models in the SMS. • In this paper, through the calculation of the water quality model, the urban mainstream water environmental capacity is obtained, and the environmental capacity is allocated to the tributaries.

Spatial validation of a semi-distributed hydrological nutrient transport model

Semi-distributed hydrological and water quality models are increasingly used as innovative and scientific-based management tools. However, their application is usually restricted to the gauging stations where they are originally calibrated, limiting their spatial capability. In this study, the semi-distributed hydrological water quality model HYPE (HYdrological Predictions for the Environment) was tested spatially to represent nitrate-N (NO3--N) and total phosphorus (TP) concentrations and loads of the nested and heterogeneous Selke catchment (463 km2) in central Germany. First, an automatic calibration procedure and uncertainty analysis were conducted using the DiffeRential Evolution Adaptive Metropolis (DREAM) tool to simulate discharge, NO3--N and TP concentrations. A multi-site and multi-objective calibration approach was applied using three main gauging stations, covering the most important hydro-meteorological and physiographical characteristics of the whole catchment. Second, the model’s capability was tested to represent further internal stations, which were not initially considered for calibration. Results showed that discharge was well represented by the model at all three main stations during both calibration (1994–1998) and validation (1999–2014) periods with lowest Nash-Sutcliffe Efficiency (NSE) of 0.71 and maximum Percentage BIAS (PBIAS) of 18.0%. The model was able to reproduce the seasonal dynamics of NO3--N and TP concentrations with low predictive uncertainty at the three main stations, reflected by PBIAS values in the ranges from −16.1% to 6.4% and from −20.0% to 11.5% for NO3--N and TP load simulations, respectively. At internal stations, the model could represent reasonably well the seasonal variation of nutrient concentrations with PBIAS values in the ranges from −9.0% to 14.2% for NO3--N and from −25.3% to 34.3% for TP concentration simulations. Overall, results suggested that the spatial validation of a nutrient transport model can be better ensured when a multi-site and multi-objective calibration approach using archetypical gauging stations is implemented. Further, results revealed that the delineation of sub-catchments should put more focus on hydro-meteorological conditions than on land-use features.

Modelling the effect of different agricultural practices on stream nitrogen load in central Germany

Understanding the response of nitrogen fluxes to changes in land use and agricultural practices is crucial for improving the instream water quality prediction. In central Germany, the expansion of bioenergy crops during the last decade led to an increase in fertiliser application rates. The purpose of this study is to investigate the effect of agricultural management changes on the stream nitrogen load of a drinking water reservoir catchment (Weida, 99.5 km2) using a hydrological water quality model. The semi-distributed hydrological water quality model—the HYdrological Predictions for the Environment (HYPE)—was calibrated and validated successfully for discharge and nitrate-N concentrations during the period 1997–2003 (the lowest discharge Nash-Sutcliffe efficiency (NSE) was 0.78). Subsequently, stream nitrogen load of six different land use scenarios and their associated agricultural practice changes were compared to the baseline simulations of the period 2006–2009. Some of these scenarios were designed considering the increased cultivation of bioenergy crops. Results revealed that an increase in mineral fertiliser by 20 % for all crops augmented an increase of monthly stream nitrogen loads in the range of 2–6 % compared to the baseline simulations. Also, it was found that stream nitrogen load increased in scenarios where all or some crop areas were converted to maize and rape, which are the established bioenergy crops in Germany. The increase of nitrogen load resulting from these scenarios differed in terms of magnitude and their temporal patterns, reflecting the importance of timing, the amount of fertiliser applications, and harvesting periods. However, results showed that nitrogen load was reduced in situations when only organic farming or summer barley was used and when rape and maize cropping areas were converted to winter wheat. In this intensively used agricultural catchment, the simulated stream nitrate-N loads quickly responded to fertiliser application changes (increase/decrease). This rapid response could be explained by short residence time of the interflow and baseflow runoff components because of the hardrock geological properties of the catchment.

Multi-site identification of a distributed hydrological nitrogen model using Bayesian uncertainty analysis

Summary For capturing spatial variations of runoff and nutrient fluxes attributed to catchment heterogeneity, multi-site hydrological water quality monitoring strategies are increasingly put into practice. This study aimed to investigate the impacts of spatially distributed streamflow and streamwater Inorganic Nitrogen (IN) concentration observations on the identification of a continuous time, spatially semi-distributed and process-based hydrological water quality model HYPE (HYdrological Predictions for the Environment). A Bayesian inference based approach DREAM(ZS) (DiffeRential Evolution Adaptive Metrololis algorithm) was combined with HYPE to implement model optimisation and uncertainty analysis on streamflow and streamwater IN concentration simulations at a nested meso scale catchment in central Germany. To this end, a 10-year period (1994–1999 for calibration and 1999–2004 for validation) was utilised. We compared the parameters’ posterior distributions, modelling performance using the best estimated parameter set and 95% prediction confidence intervals at catchment outlet for the calibration period that were derived from single-site calibration (SSC) and multi-site calibration (MSC) modes. For SSC, streamflow and streamwater IN concentration observations at only the catchment outlet were used. While, for MSC, streamflow and streamwater IN concentration observations from both catchment outlet and two internal sites were considered. Results showed that the uncertainty intervals of hydrological water quality parameters’ posterior distributions estimated from MSC, were narrower than those obtained from SSC. In addition, it was found that the MSC outperformed SSC on streamwater IN concentration simulations at internal sites for both calibration and validation periods, while the influence on streamflow modelling performance was small. This can be explained by the “nested” nature of the catchment and high correlation between discharge observations from different sites. Results revealed, also, that 95% prediction confidence intervals of streamflow and streamwater IN concentration estimated from MSC were more credible compared with those estimated from SSC, which are reflected by narrower confidence intervals and higher percentage of observations bracketed in the estimated unit confidence intervals. The outcomes of this study pointed out the importance of spatially distributed hydrological water quality observations for improving model parameter identification and provided guidelines for choice of adequate calibration strategy and design of hydrological water quality monitoring campaign.

Application of the SWAT model to assess the impact of changes in agricultural management practices on water quality

An excessive use of nitrogen in agricultural regions leads to nitrate pollution of surface and groundwater systems. The Alegria River watershed (Basque Country, northern Spain) is an agricultural area dominated by a Quaternary shallow aquifer that has suffered nitrate-related problems since the 1990s. Our objective was to use the SWAT hydrological water quality model for long-term backward simulation (1990–2011) considering main changes in management practices to determine their impact on water quality. Hydrology, crop yield, nitrogen losses and soil nitrogen budgets were simulated satisfactorily. Nitrogen budgets indicated that annual N inputs exceed outputs (which consider main N loss pathways), resulting in mean N surpluses of 114 and 65 kg ha-1 year-1 in the periods 1990–1999 and 2000–2011, respectively. In the long-term, trends in N surplus generally follow those of fertilization input, which directly affect groundwater nitrate concentration. The characteristics of the aquifer and non-point source pollution have enabled us to properly simulate the historical trends in N concentration in the Vitoria-Gasteiz aquifer.Editor Z.W. Kundzewicz; Guest editor V. Krysanova

Potential effects of climate change and eutrophication on a large subtropical shallow lake

In many aquatic ecosystems, increased nutrient loading has caused eutrophication, which is reflected in the trophic structure of the ecosystem. In Lake Mangueira, a large shallow subtropical lake in Brazil, nutrient loading has also increased, but it is still unclear what the effects of this increase will be and how this relates to climate change. To evaluate the effects of increased nutrient loadings in such large lake one would need to integrate hydrological and ecological processes into one model, an approach that has rarely been used before. Here, we apply different versions of a complex 3D ecological model, called IPH-TRIM3D-PCLake, which describes the integrated hydrodynamic, water-quality, and biological processes in the lake. First, the nutrient loadings from the watershed were estimated using a separate hydrological water quality model of the watershed based on field data. Second, we calibrated the 3D ecological model for a 6-year monitoring period in the lake using a simplified non-spatial version of the model. Finally, the calibrated ecological model was applied to evaluate the spatial explicit effects of different scenarios of land use, water pumping for irrigation, and climate change. On short term (1.5 year), the system seemed to be rather resilient, probably because of the lake size related to its high inertia. Our simulations indicated warming can increase water transparency in Lake Mangueira which may be related to two factors: (a) the current meso-oligotrophic state of the lake which may easily lead to nutrient limitation; and (b) submerged macrophytes grow during the whole season. The combined effect of climate change and increased nutrient loading, less strong than increased nutrient loading alone. The model can only be used for qualitative predictions of the effect of management scenarios, such as maintenance of water levels in the dry season, and water-pumping rules for irrigation in order to maintain the ecosystem structure and functions in the future under additional stress caused by increased use or climate change.

Coupling a hydrological water quality model and an economic optimization model to set up a cost-effective emission reduction scenario for nitrogen

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.