HS2.3.1

Intensive agricultural land use have introduced vast quantities of nutrients such as reactive nitrogen (N) to soils and subsequently to groundwater and surface waters. High nitrate concentrations are still a pressing issue for drinking water safety and aquatic ecosystem health e.g. in Europe, although fertilizer inputs have been significantly lowered in the last decades. This is partly due to a slow response of riverine nitrate concentrations to changes in nitrogen inputs attributed to N legacies in catchments. N can be stored organically bound as a biogeochemical legacy in soils or can be slowly transported as nitrate in groundwater forming a hydrologic legacy. Legacy can thus lead to a net retention of N in catchments and to substantial time lags in the response to input changes. Here, we systematically explore legacy effects over a wide range of catchment in the Western European countries France and Germany. We are making use of long observational time series of nitrate concentration in 238 catchments covering 40% of the total area of France and Germany. We apply a Weighted Regression on Time, Discharge, and Season (WRTDS) to derive continuous daily flow-normalized concentrations and loads. The temporal pattern of concentration and loads at the catchment outlet is compared to the N input time series evolving from agricultural N surplus, atmospheric deposition and biological fixation. We found that on long-term catchments retain on average 72% of the N input. Time lags between input and output were successfully explained by a lognormal transport time distribution. The modes of these distributions were found to be rather short with a median mode of 5.4 years across all catchments. Based on this data-driven assessment only the fate of N in the catchments is hard to assess as denitrification in soil and groundwater can lead to similar observations as the storage of N in legacies. Focusing on the mobile part of N that is exported by catchments, we estimate that a substantial amount of N is still stored in the subsurface that will be released in the coming years. We therefore analyzed how catchment nitrate export will evolve under the scenario of a total cut down, reduced or constant future N inputs. We report the expected timescale of reaction to implemented measures to help tackling this pressing water quality problem.

How to cite: Musolff, A., Ehrhardt, S., Dupas, R., Kumar, R., Ebeling, P., and Fleckenstein, J. H.: Assessing Nitrogen Legacies in Western Europe, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14526, https://doi.org/10.5194/egusphere-egu21-14526, 2021.

The use of fertilizers and pesticides in agriculture activity is a worldwide extended practice since decades for improving crops performance, which can cause, however, with excessive dosage rates, aquifers’ pollution and water quality problems, like the study case hereby presented of Mar Menor sea-lake waterbody and “Campo de Cartagena” aquifer, in the southern coast of Spain.

Due the agricultural practices, the Campo de Cartagena aquifer presents in this moment high values of nitrate, around 150 mgNO₃ / l, appearing also these high values of nitrogen in soil in this area. This situation produces a great contribution of nitrogen to the Mar Menor lake, by two mainly processes, firstly, continuously through groundwater returns to the waterbody’s surface and secondly, through the precipitation events when a large amount of nitrogen is washed from soil by the rainfall. Finally, the large amount of nitrogen incomes to the Mar Menor sea lake contributes to deteriorate the status of this waterbody and also promotes the eutrophication processes that have been taking place during last years.

A large watershed scale nitrates’ transport simulation model, Patrical Model (Perez-Martín et al., 2016), is used to estimate the measures to recovery the “Campo de Cartagena” aquifer. The model establishes, mathematically, the relationship between nitrogen application, nitrogen surplus (excess), and nitrate concentration in groundwater and surface waterbodies.

Model results show that it is necessary to reduce around 80% of the current nitrogen surplus in the “Campo de Cartagena” aquifer to recovery the good status in the aquifer. This reduction of nitrogen surplus can be obtained by reducing the fertilizers dosage and consequently the nitrates contribution, with a maximum dose of nitrogen applied by farmers of 170 kgN /ha. Applying this measure could reduce significantly the nitrogen retained in soil in 1-2 years, so the nitrogen contribution during rainfall events also could be reduced significantly. Nitrogen levels in groundwater will gradually decrease in the following years, reaching values around 50 mgNO₃ / l in 7-9 years after the application of these measures.

How to cite: Gómez Martínez, G., Pérez-Martín, M. Á., and Estrela Segrelles, C. E.: “Application of Hydrological Simulation models to solve pollution impacts in the water management decision-making processes. Measures for the recovery of Mar Menor sea lake and “Campo de Cartagena” aquifer (Spain)”, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1605, https://doi.org/10.5194/egusphere-egu21-1605, 2021.

Acidic deposition derived from human activities causes negative effects on nutrient cycling in forest ecosystems.  However, nutrient cycling of forest ecosystems is expected to recover because the emission of pollutants is generally decreasing in recent years.  However, the extent of recovery would be differed between forest ecosystems in different climatic conditions.  The study investigated changes of stream water chemistry of forest ecosystems in Shimanto River Basin in southwestern Japan.  The 92 samples of stream water were collected from forested watersheds in summer of 1999 and 2020 and chemistry of the samples was compared.  The mean pH value of the stream water in 2020 (7.60) was higher than that in 1999 (7.29).  The mean concentration of potassium ion increased by 2.1% whereas that of sodium, calcium, and magnesium ions decreased by 2.5%, 10.3%, and 8.6%, respectively.  The mean concentration of chloride, nitrate and sulfate ions decreased by 24.8%, 9.4% and 22.5%, respectively whereas that of bicarbonate increased by 0.7%. 　The relationship between mean annual temperature and the ratio of ion concentration in 2020 to that in 1999 was analyzed.  The ratio of calcium and manganese concentration was lower at warmer sites.  The ratio of sulfate concentration was lower at warmer sites whereas the ratio of chloride concentration was not related with mean annual temperature.  The results suggest that the runoff of sulfate and chloride from forest ecosystems in the Shimanto River Basin have decreased presumably due to the reduced input of these elements and that the residence time of sulfur in forest ecosystems is shorter in warmer sites as indicated by the greater reduction of sulfate concentration.

How to cite: Inagaki, Y., Inagaki, M., Shichi, K., Yoshinaga, S., Yamada, T., Miura, S., Shinomiya, Y., and Fujii, K.: Spatial variation of stream water chemistry in the Shimanto River Basin in southwestern Japan: A comparison of results in 1999 and 2020, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-9149, https://doi.org/10.5194/egusphere-egu21-9149, 2021.

The prediction of water quality is an efficient way for managing water resources and protecting ecosystems by providing an early warning against water quality deterioration. So far, the classical approach is to predict water quality by the utilization of complex process-based water quality models. However, these models are not easy to set up and require comprehensive input data. The local characteristics, detailed process understandings and eventually data from land users such as farmers are needed, to build up a valid model structure. Such constraints can end up in wrong scientific conclusions ranging from false alarms to unpredicted environmental pollution in practical water monitoring application. Long short-term memory (LSTM) algorithms are known to be able to overcome some of the typical constraints in hydrological model applications. However, their performance in water quality prediction has rarely been explored. In this study, we investigate the ability of a LSTM model to predict the complex, nonlinear behavior of water quality parameters in the Schwingbach Environmental Observatory (SEO), Germany.  We predict weekly nitrogen-nitrate concentrations, weekly stable isotopes of water concentrations (δ¹⁸O) and daily water temperature in six stream‑ and six groundwater sources with different landuse and hillslope conditions. We use meteorological forcing data and catchment attributes as input variables. To ensure an efficient model performance, we employ a Bayesian optimization approach to optimize the hyperparameters of the LSTM. The model performance is evaluated by the Root Mean Squared Error (RMSE). Our LSTM is robust in capturing the dynamics of the water quality parameters over time. The RMSE for the LSTM performance ranges from 0.27 to 3.38 mg/l, from 0.069 to 0.27 ‰ and from 1.3 to 2.1 °C for nitrogen‑nitrate, δ¹⁸O and water temperature, respectively. We compare the RMSE with statistical parameters of data. Results confirm that the LSTM is a promising tool for early risk assessment of water quality, particularly in view that only a minimal set of catchment information is needed to gain robust results.

How to cite: Sahraei, A., Breuer, L., Kraft, P., and Houska, T.: Deep learning for water quality prediction: the application of LSTM model to predict water quality in catchment scale, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8756, https://doi.org/10.5194/egusphere-egu21-8756, 2021.

Abstract

Freshwater ecosystems provide many benefits to a variety of species but, unfortunately, human-caused environmental issues are undermining their ability to provide key functions and services. Changes in climate and land use, for instance, impact the habitat suitability for freshwater organisms by affecting water quantity and quality. Nutrients, pesticides, heavy metals and other contaminants which are released to the environment as a result of anthropogenic activities have the potential to degrade the environment and damage freshwater communities. Hence, the present research activity aims to investigate aquatic ecosystem responses to environmental deterioration using a case study of Clariano River, Spain. The Soil and Water Assessment Tool (SWAT) is used as an eco-hydrological tool to model discharge, sediment and nutrients, and to predict the biological status in Clariano River under different scenarios. As the diversity and presence of species represent the quality of ecosystem, this study focuses on macroinvertebrates as biological indicators of stream health. The SUFI-2 algorithm in the SWAT-CUP program is used for the calibration, validation, sensitivity and uncertainty analysis of the SWAT model. The results from the calibrated model are then coupled to regression equations between measured nutrient concentrations and values of several macrobenthic metrics in six sampling sites along the Clariano River. The coupling of these regression equations with concentrations simulated with SWAT for different scenarios allows to improve the understanding of the relations between environmental changes in watersheds, nutrient concentrations, and the biologic status of stream water.

Keywords: water quality, macroinvertebrates, environmental degradation, eco-hydrological modelling, Clariano River

How to cite: Vagheei, H., Vezza, P., Palau-Salvador, G., and Boano, F.: Predicting Responses of Chemical and Biological Water Quality to Human-induced Environmental Changes: The Case Study of Clariano River, Spain, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4215, https://doi.org/10.5194/egusphere-egu21-4215, 2021.

Northern Ireland has been somewhat overlooked in terms of water quality modelling in the past. Many of its catchments have consistently failed to meet Water Framework Directive targets especially due to high levels of dissolved nutrients and poor ecological status. A catchment based modelling study to address this issue has not been undertaken here previously and the approach described here uses two water quality models to achieve this aim. The objectives of the modelling were firstly to identify the total load reductions (in terms of Phosphorus (P)) required to reduce in-stream loadings sufficiently for concentrations of soluble reactive P (SRP) to be reduced to achieve the WFD “Good” status levels, and secondly to split these loadings into diffuse and point components. The third objective was to identify the most likely flow pathways for the transport of the diffuse component of P to the watercourses particularly for the agricultural (mostly intensive grassland farming) land use which dominates in almost all NI catchments.

The first model applied is the Source Load Apportionment Model (SLAM) developed by the Irish EPA. This model provides a large-scale assessment of the point and diffuse load components across catchments where multiple pressures are occurring. The second model us the Catchment Runoff Flux Assessment Tool (CRAFT) which is able to back-calculate nutrient loads associated with three major flow pathways. SLAM is a static model which uses averaged loadings from diffuse agriculture and non-agricultural land uses, and point sources (where information can be obtained from various sources) to calculate N and P exports. For P, the agricultural diffuse load component uses an enhanced version of the export coefficient approach based on combining the sources of P from applied nutrients (slurry and fertiliser) and soil P. A modelling tool allows the user to evaluate load reduction scenarios where one or several components of P (both point and diffuse) are adjusted downwards to achieve the catchment’s required load reduction. The CRAFT model works on a dynamic (daily) modelling scale and has simulated sub-catchments where the SLAM model has identified the need for significant load reductions. It identifies the different reductions (P export) that are required for each flow pathway, which will then inform on the type of additional measures (e.g. sediment traps, riparian buffer strips and wetlands) that may also be required.

The initial aim of this study is to complete a pilot application to the trans-border (UK and ROI) Blackwater catchment (1360 km²). Through a review of alternative modelling options for the whole area of NI, an assessment of whether this approach is suitable for application to the entire territory can be made.

How to cite: Adams, R. and Doody, D.: Reducing Nutrient Loads in Northern Irish Catchments: A Modelling Approach Based on Load Apportionment and Flow Pathway Identification, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15216, https://doi.org/10.5194/egusphere-egu21-15216, 2021.

The third largest European river Dnipro covers 48% of Ukraine’s territory. An analysis of the main anthropogenic pressures in the Dnipro Basin was first performed according to the requirements of EU WFD.

Surface water pollution by organic substances and nutrients is principally attributed with point sources, among which the municipal wastewaters play the dominant role. The main load by organic substances and nutrients is caused by the wastewater discharges of big cities with Population Equivalent >100 000; 89% of such cities are located within the sub-basins of Middle Dnipro and Lower Dnipro. 

Point sources form 33% of nitrogen and 61% of phosphorus loads in the Dnipro Basin. Diffuse sources related to agricultural production cause incoming of 29% of nitrogen and 36% of phosphorus. Phosphorus is transported to the water bodies mainly with erosion particles. 

Natural conditions in the River Basin are one of the reasons of nitrogen load significant share (33%). Humus compounds and nitrogen compounds enter into water bodies due to the high bogginess of the Dnipro Basin upper part, especially the Prypiaty Basin. This leads to winter and summer anoxia in the rivers and upper reservoirs and creates prerequisites for eutrophication of the Dnipro cascade reservoirs. Rivers of the Prypiaty sub-basin, Upper Dnipro, and Desna sub-basins are extremely vulnerable to anthropogenic pollution by nutrients and organic substances that generates the increased background of organic compounds and nitrogen in the Dnipro reservoirs cascade. 

The load of the Dnipro Basin surface water by hazardous substances (especially synthetic) still remains insufficiently studied. Currently, information is only available regarding load by heavy metals included to the list of priority substances and some other ones. Water pollution by metals is noted mostly in the Lower Dnipro sub-basin where the most of the metallurgical enterprises are located. 

The high application of pesticides (> 3 kg/ha) in 4 administrative Rayons leads to the appearance of risk conditions for pollution of xenobiotics in 50 surface water bodies (SWBs). 

The Dnipro reservoirs cascade serves as a powerful geochemical barrier causing heavy metals and pesticides deposition in bottom sediments. The highest pollution by metals is noted in the sediments of the Dnipro reservoirs that receive the metallurgy enterprises wastewaters. Probability of significant secondary remobilization is foremost noted for Cadmium. Organochloride pesticides content in the bottom sediments is 2 to 5 times lower than maximal allowable concentration in soil. 

Water abstraction volume is around 22% of the annual flow of 95% probability. The natural flow of the Dnipro is regulated by 6 large reservoirs. Besides, there are 1072 dams and other cross-sectional artificial installations. Natural morphology changes are observed in a large number of rivers within the Dnipro Basin. 

It was found that 56% of the Dnipro Basin SWBs are at risk of failing the “good” ecological status.

Hydromorphological alterations cause the main anthropogenic pressure in the Dnipro Basin (concerning 45% of the SWBs). Risks from diffuse sources and point sources are observed in 23% and 5% of SWBs, respectively.

How to cite: Osadcha, N., Nabyvanets, Y., Osadchyi, V., Ukhan, O., Osypov, V., Luzovitska, Y., Klebanov, D., and Biletska, S.: Pressures and impact analysis in the Dnipro river basin within Ukraine, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6493, https://doi.org/10.5194/egusphere-egu21-6493, 2021.

The Moskva River catchment is a complex system consisting of a network of rivers affected by a wide variety of land- and water-use factors that create unique spatial and temporal patterns of their water quality. Major sources of anthropogenic impact on the Moskva River and its tributaries include multiple flow regulation structures on streams, direct pollution from municipal sewage and industrial wastewaters of Moscow megacity and smaller towns, runoff generated in agricultural areas and within multiple landfills located on the watershed, and many more. Only a short upstream section of the Moskva River remains relatively unchanged in terms of water runoff and geochemistry.

In 2019, we began a pioneering study focusing on collecting detailed field data on geochemistry of water, suspended matter and bottom sediments of the Moskva River and its major tributaries, including concentrations of nutrients, potentially toxic elements (PTEs), polyaromatic hydrocarbons and total petroleum hydrocarbons (TPH). The main purpose of this project is to obtain a holistic picture of material fluxes within the river system combined with an inventory of natural and anthropogenic factors controlling them.

Our results indicate gradual increase of total dissolved solids, and content of nutrients and some PTEs (i.e., Cu) in water along the course of Moskva River. It can be linked to non-point pollution, as well as drastic changes occurring downstream Moscow and other urban areas caused by direct pollution. Massive increase of chloride, sulfate, sodium, mineral phosphorus, nitrogen, Mo and Sr concentrations in water is observed downstream outlets of Moscow wastewater treatment plants, which is characteristic of insufficiently treated urban sewage. Concentrations of nutrients and PTEs only slightly decrease downstream the city, remaining at levels often exceeding environmental guidelines up to the river’s mouth, whereas increased concentrations of other pollutants, such as TPH, are more closely limited to urban areas and fade more quickly with distance from the source.

Nutrient pollution of the Moskva River, as well as concentrations of some PTEs (i.e., Sb, Pb), steadily increased during summer low-flow period, when low dilution capacity limits biochemical self-purification. On the other hand, Mn, Co and Zn reached maximum concentrations during the spring flood due to their accumulation in city road dust and subsequent concentrated inflow with snowmelt runoff.

The Moskva River tributaries that flow within close proximity to the metropolitan area were revealed to have significantly higher pollution levels than the Moskva River itself, indicating stronger anthropogenic stress.

Balance calculations performed on our database showed that during the flood the Mozhaysk Reservoir – the single large reservoir on the Moskva River – retains huge volumes of major elements and PTE, at times even greater than their subsequent input from urban areas downstream from the dam. It proves crucial role of the reservoir’s retention capacity in the Moskva River’s geochemical balance formation.

Authors acknowledge Russian Geographical Society (project 28/2019-I), Russian Science Foundation (project 19-77-30004) and Russian Foundation for Basic Research (project 19-05-50109) for financial support.

How to cite: Shinkareva, G., Erina, O., Tereshina, M., Sokolov, D., and Lychagin, M.: Anthropogenic impact on behavior of nutrients and potentially toxic elements in the Moskva River water, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12864, https://doi.org/10.5194/egusphere-egu21-12864, 2021.

The ecohydrological models AnnAGNPS and ZIN-AgriTra are compared regarding their performance in a small watershed. Both models are presently applied for the transport simulation of plant protection products (PPP) from an agricultural area to a small stream to quantify the impact of reduction measures as part of a comprehensive study.

The spatial discretization of AnnAGNPS is based on hydrologic response units with homogeneous characteristics (land use, slope and soil type). For the continuous simulations daily time steps are used, only soil moisture is simulated using hourly time steps. The underlying equations are physically based, mostly simple calculation methods are used.
ZIN-AgriTra operates on grid cells, which allows a more accurate representation of the flow paths. The model is physically based, e. g. for the unsaturated soil zone the Richards equation is used. This requires detailed soil properties for its parameterization and leads to small computational time steps (minutes to hours) to fulfil the mass balance requirements. The detailed spatial and temporal scales, as well as the complex equations, result in a long computation time in comparison to AnnAGNPS.  
AnnAGNPS and ZIN-AgriTra are compared regarding their accuracy in the water balance and the mass balance simulation. For the mass balance different constituents as e. g. sediment, phosphorus and selected pesticides are simulated.

The study area is located in southern Lower Saxony, Germany. The catchment area has a size of 5 km². The investigated stream (Lahbach) flows along agriculturally cultivated land. The relatively high slopes and the fine soil texture lead to a high fraction of generated discharge (as surface runoff, erosion and rapid interflow) from precipitation events. In the ongoing study the catchment was intensively monitored regarding meteorological and hydrological data. In addition, an event-based monitoring campaign was performed to quantify the reaction of the Lahbach during precipitation events, particularly the change in constituent concentrations. Due to the close cooperation with a local farmer, management measures are known very precisely.

The different temporal resolution of the input data and the time step of output parameters lead to differences in the agreement between measured and simulated time series among the two models. Overall, ZIN-AgriTra led to a more accurate reproduction of the rainfall-runoff events.

How to cite: Schwenkel, J., Zeunert, S., Le, H., Müller-Thomy, H., Schöniger, M., and Meon, G.: Comparison of the ecohydrological models AnnAGNPS and ZIN-AgriTra for a small agricultural catchment, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12233, https://doi.org/10.5194/egusphere-egu21-12233, 2021.

Application of Sentinel-2A/B satellites to retrieve turbidity in the Guadalquivir estuary (Southern Spain)

Due to climate change, contamination, and diverse anthropogenic effects, water quality monitoring is intensifying its importance nowadays. Remote sensing techniques are becoming an important tool, in parallel with fieldwork, for supporting the cost-effective accomplishment of water quality mapping and management. In the recent years, Sentinel-2A/B twin satellites of the European Commission Earth Observation Copernicus programme emerged as a promising way to monitor complex coastal waters with higher spatial, spectral and temporal resolution. However, atmospheric and sunglint correction for the Sentinel-2 data over the coastal and inland waters is one of the major challenges in terms of accurate water quality retrieval. This study aimed at evaluating the ACOLITE atmospheric correction processor in order to develop a regional turbidity model for the Guadalquivir estuary (southern Spain) and its adjacent coastal region using Sentinel-2 imagery at a 10 m spatial resolution. Two settings for the atmospheric correction algorithm within the ACOLITE software were applied: the standard dark spectrum fitting (DSF) and the DSF with an additional option for sunglint correction. Turbidity field data were collected for calibration/validation purposes from the monthly Guadalquivir Estuary-LTER programme by Andalusian Institute of Agricultural and Fisheries Research and Training (IFAPA) using a YSI-EXO2 multiparametric sonde for the period 2017-2020 at 2 fixed stations (Bonanza and Tarfia) sampling 4 different water masses along the estuary salinity gradient. Several regional models were evaluated using the red band (665 nm) and the red-edge bands (i.e. 704, 740, 783 nm) of the Sentinel-2 satellites. The results revealed that DSF with glint correction performs better than without glint correction, especially for this region where sunglint is a major concern during summer, affecting most of the satellite scenes. This study demonstrates the invaluable potential of the Sentinel-2A/B mission to monitor complex coastal waters even though they were not designed for aquatic remote sensing applications. This improved knowledge will be a helpful guideline and tool for the coastal managers, policy-makers, stakeholders and the scientific community for ensuring sustainable ecosystem-based coastal resource management under a global climate change scenario.

How to cite: Chowdhury, M., Vilas, C., VanBergeijk, S., Navarro, G., Laiz, I., and Caballero, I.: Application of Sentinel-2A/B satellites to retrieve turbidity in the Guadalquivir estuary (Southern Spain), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15445, https://doi.org/10.5194/egusphere-egu21-15445, 2021.

High-resolution water quality data obtained with in situ sensors and analysers coupled to flow discharge records can reveal critical information on hydrochemical and biogeochemical functioning of aquatic ecosystems. In this study we explore a rich high-resolution hydrochemical dataset to synthesise the impact of hydrological flushing and biogeochemical cycling on water quality in a 3^rd order groundwater-fed stream draining an agricultural catchment dominated by grassland.Our results show that despite large storm to storm diversity in hydrochemical responses, storm event magnitude and timing have a critical role in controlling the type of mobilisation, flushing and cycling behaviour. These results can be used to evaluate pollution risks in streams and their effects on freshwater quality.

How to cite: Bieroza, M. and Heathwaite, A. L.: The interplay between hydrological flushing and biogeochemical cycling in a 3rd order stream, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8314, https://doi.org/10.5194/egusphere-egu21-8314, 2021.

Current understanding is fragmented of the environmental, economic, and social processes involved in water quality issues. The fragmentation is particularly evident for coastal water quality, impacted both by local land catchment and larger-scale marine pressures and impacts. Research and policy so far has primarily addressed coastal water quality issues from either a land-based or a sea-based perspective, which does not support integrated management of the coupled land-coast-sea systems affecting coastal waters. For example, mitigation measures for improving the severe Baltic Sea eutrophication have mostly focused on land-based drivers, and not yet managed to sufficiently improve coastal or marine water quality. The strong human dimension involved in these water quality issues also highlights a need for participatory approaches to facilitate knowledge integration and drive synergistic strategic planning for sustainable management of coastal water quality. Considering the Swedish water management district of Northern Baltic Proper, including its main Norrström drainage basin and surrounding coastal catchment areas and waters, this study has used a participatory approach to evaluate various land-sea water quality interactions and associated management measures. A causal loop diagram has been co-created with different stakeholder groups, following a problem-oriented system thinking approach. This has been further used in fuzzy-cognitive scenario analysis to assess integrated land-coast-sea system behavior under changing human pressures and hydro-climatic conditions. Results show that synergy of several catchment measures is needed to improve coastal water quality locally, while cross-system/sector cooperation is also needed among all contributing national catchments to mitigate coastal eutrophication at the scale of the whole Baltic Sea. Furthermore, large-scale hydro-climatic changes and long-lived nutrient legacy sources also need to be accounted for in water quality management strategies and measures. System dynamics modelling, based on co-created causal loop diagrams and fuzzy-cognitive scenario analysis like those developed in this study, can support further quantification and analysis of the impacts of various mitigation strategies and measures on regional water quality problems and their possible sustainable solutions.

How to cite: Seifollahi-Aghmiuni, S., Kalantari, Z., and Destouni, G.: Use of co-created causal loop diagrams and fuzzy-cognitive scenario analysis for water quality management, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5210, https://doi.org/10.5194/egusphere-egu21-5210, 2021.

The recognition of natural environment current functioning is possible throughout the determination of the energy and material balance (mainly water and dissolved substances) in various catchments. Dissolved matter circulation in the river catchment reflects natural hydrometeorological and hydrochemical processes as well as anthropogenic activity, which appears primarily as the supply of pollutants.

The research was conducted in 4 hydrological years (2016-2019) within the borders of a small urban catchment in the northern part of the city of Poznań (Poland), the main watercourse of which is the Różany Stream (Różany Strumień). The natural environment of the Różany Stream catchment is characterized by significant transformations due to human activity. The most important environmental problems include threats related to the pollution of surface waters and groundwater as a result of processes related to the functioning of an urban catchment.

The main aim of this work is to present the magnitude of pollution supply into the catchment and to determine the temporal variability of matter circulation in a small urban catchment in years with different pluvial conditions and therefore quantitatively changing atmospheric supply reaching the geoecosystem.

The magnitude of pollution supply to the catchment was determined on the basis of systematic, comprehensive measurements of the natural environment. The measurement system and the field research methodology refer to the methodological concept of the system functioning, as well as the assumptions of the European International Cooperative Programme on Integrated Monitoring of Air Pollution Effects on Ecosystems (ICP IM) and Integrated Monitoring of the Natural Environment in Poland (ZMSP) programs.

This work presents the results of measurements of several components of the natural environment, initially including meteorological conditions (mainly precipitation and air temperature). The next elements of the research concerned air pollution with sulphur dioxide and nitrogen dioxide as well as the chemical composition of precipitation, which is considered as an entry into the geoecosystem. Moreover, there are also presented the results of the physicochemical properties of surface waters (including levels, flows and chemical composition) and groundwater.

The quantitative and qualitative characteristics of the atmospheric supply to the geoecosystem, the water cycle in the catchment and the water runoff confirm the assumptions that the dissolved matter circulation is one of the most important indicators of changes in the natural environment in the moderate morphoclimatic zone.

How to cite: Major, M., Chudzińska, M., Majewski, M., and Stefaniak, M.: The magnitude of pollution supply in small urban catchment (Różany Stream) in Poznan, Poland, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2977, https://doi.org/10.5194/egusphere-egu21-2977, 2021.

Efficient management of drinking water quality is critical for the water supply, so effective monitoring of supply and storage systems is a priority. This project aims to predict the presence of Taste and Odour (T&O) compounds in drinking water reservoirs, using molecular analyses and smart in-situ monitoring systems. The most common T&O compounds, Geosmin and 2-MIB, are secondary metabolites that can be produced in waterbodies by cyanobacteria and actinomycetes and impact drinking water taste and odour. Although there is no evidence of related health risks, they can be perceived by humans at very low concentrations (5-10 ng/L) and the treatment process to remove them from drinking water is costly. Early assessment of T&O risk is crucial, but currently requires time-consuming and costly sampling as well as laboratory analysis which prevents real-time monitoring and a timely management response.

Cyanobacterial species responsible for T&O production can be monitored with eDNA techniques and potentially provide an early warning of T&O episodes. Moreover, detection of the genes that are responsible for T&O production within the DNA of the freshwater community can help to speed up analysis. We show that qPCR methods can target the Geosmin synthase gene (geoA) and that this correlates significantly with Geosmin concentrations >15 ng/L. Alternatively, in-situ sensors that can be deployed remotely and transmit data, can provide real-time monitoring for early warning and potentially predictive capacity. Commercially available sensors do not currently exist for T&O compounds, but they do for many other water quality parameters. We consider the analytes that could be effective for T&O warning systems, using a Welsh reservoir as an exemplar case. Assessment of nutrient dynamics suggests N and P ratios are critical, hence we evaluate the sensors that are available for these compounds and associated environmental controls on their behaviour. We present recommendations for the design of an in-situ monitoring programme and introduce the planned tests that will evaluate it.

How to cite: Elfferich, I., Bagshaw, E., Perkins, R., Kille, P., Straiton, S., von Benzon, E., and Hooper, A. S.: In-situ techniques for monitoring drinking water quality, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12109, https://doi.org/10.5194/egusphere-egu21-12109, 2021.

Estimation of dissolved organic carbon (DOC) runoff load in forested watershed is important for the assessment of the global carbon cycle as well as for the control of regional water environments. A few process-based models have been proposed to estimate the DOC load to water environments, which assume DOC source in topsoil and transport processes to the river, however, these models exhibited difficulties with the availability of input data and applicability to short time-scale rainfall-runoff processes in the Asian monsoon area. This study presents a new process-based model that consists of two separate systems for determining DOC load enforced by DOC Source Area (DSA) concept. For the runoff system, a semi-distributed hydrological modelling unit (‘modified-TOPMODEL’) was installed, by which surface and subsurface water flows, representing for DSA, were sequentially simulated. For the soil system, a wet-dry cycle was successfully simulated by an advection-diffusion and dissolution formulation as well as seasonal temperature effect. The model is first evaluated upstream (98ha) and downstream (1798ha) in the Mizugaki Watershed, Yamanashi, Japan and then applied for a Miuchi (203ha) watershed, Aichi, Japan during 2014 to 2018. The results of cumulative DOC load at baseflow and stormflow periods that the model performed well between the simulations and observations for both study sites. Considering the stormflow periods, from 25.2% to 32.0%, and 31.1% of high flows contributed to 50% of the total DOC load at Mizugaki and Miuchi watershed, respectively. Overall, the proposed model successfully simulated DOC load under different geochemical and hydrological condition by capturing the DSA variability.

How to cite: Ebata, K., Ichikawa, Y., Ishidaira, H., Matsumoto, Y., and Nishida, K.: Application of Dissolved Organic Carbon Runoff Model Considering Soil Infiltration and River Runoff Processes in Multiple Forested Watersheds, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-6986, https://doi.org/10.5194/egusphere-egu21-6986, 2021.

The Usumacinta River is the most extensive tropical fluvial system in North America and the principal river in Mexico and the tenth of North America. Diverse and growing anthropogenic activities (land-use change, agriculture, and urban development) modify water quality. However, to separate natural (e.g., geology) from anthropic factors responsible for this system characteristics, we looked to evaluate geological environment’s influence on the river’s water quality.

Water and sediment samples were collected along the mainstem and principal tributaries in the rainy and the dry seasons (2017-2018). We analyzed the major ionic composition in water and metals in sediments. We applied inverse and evaporation models (PHREEQC code) to reveal the physicochemical reactions taking place in the river.

The inverse models in the middle basin in both seasons showed the influence of ion-exchange between Ca and K, dissolution of dolomite, and precipitation of kaolinite and calcite, whereas in the lower basin in the rainy season suggested the chemical composition is controlled by ion-exchange among Ca, Na and K, dissolution of dolomite, halite, plagioclase, and feldspar and precipitation of calcite, gypsum, and kaolinite. In addition, the evaporation models in the dry season in the lower basin demonstrate the dominant process taking place is the precipitation of calcite, dolomite, gypsum, halite, and kaolinite.

We found that Cr and Ni are the most abundant metals in the sediments along the river. The geological environment in the basin suggests that the volcanic rocks with felsic minerals could be the source of Ni, whereas sedimentary rocks such as shales and clays could be the source of Cr.

The use of geochemical models in river systems is of great relevance to understanding the presence of major ions concentrations in water and their seasonal and spatial variations, as well the physicochemical processes (i.e., ion-exchange, dissolution, precipitation, redox reactions, and so on) that allow associating or discard the presence of metals.

How to cite: Olea-Olea, S., Alcocer, J., and Oseguera, L. A.: Physicochemical processes in the main river of Mexico using geochemical models, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14358, https://doi.org/10.5194/egusphere-egu21-14358, 2021.