HS2.3.6
Orals: Fri, 28 Apr | Room 2.15
Long-term climate change and increased frequency and intensity of hydroclimatic extremes (e.g. droughts, heatwaves, floods) pose serious challenges for water management, not only in terms of water quantity, but also for securing suitable water quality for human use and ecosystems. Recent droughts, heatwaves and floods have been illustrative in showing major challenges due to exceeded water quality thresholds for sectoral use (e.g. inlet stops for drinking water production, irrigation). However, compared to water quantity, a limited number of studies have focused on water quality impacts, which are prevalent in many river basins of the world.
This presentation provides a synthesis of the potential impacts of climate change and extremes (droughts, heatwaves and floods) on global river water quality considering various water quality constituents relevant for different sectoral uses and ecosystems. This synthesis is based on: 1) an extensive literature review of local, regional to global river water quality studies; 2) statistical analyses of water quality monitoring data in various river basins over the last 40 years; and 3) global river water quality projections generated by process-based global water quality models forced with bias-corrected climate change scenarios. Comparison of results over various river basins show overall consistent responses for some general water quality constituents (e.g. water temperature, dissolved oxygen, salinity) due to the predominance of generic mechanisms (e.g. lower dissolved oxygen solubility under warming). However, mixed responses are overall found for nutrients, pathogens and pharmaceuticals due to different counterbalancing mechanisms. In addition, water quality responses vary due to differences in constituent forms (e.g. dissolved vs. particulate nutrient forms) and persistence in surface waters (e.g. for pharmaceuticals). Furthermore, geographic, environmental and socio-economic (e.g. pollution management and infrastructure) conditions conspire, showing substantial impacts on the magnitude of water quality responses under climatic change and extreme events.
How to cite: van Vliet, M. T. H.: River water quality under climate change and extremes: a synthesis of impacts for river basins globally (Invited), EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2361, https://doi.org/10.5194/egusphere-egu23-2361, 2023.
The European Union has adopted an ambitious long-term, zero pollution vision for 2050 aiming for EU’s “air, water and soil pollution to be reduced to levels no longer considered harmful to health and natural ecosystems …” [1]. However, the extent to which such a goal can be realistically realized for legacy contaminants like nitrogen (N) is not yet properly understood. Herein, we provide a comprehensive assessment of nitrogen retention and export across the European landscapes to receiving waterbodies using a suite of climate, hydrology, and future socioeconomic scenarios. We establish a chain of hydroclimate and nitrogen export scenarios, comprising climate simulations from global climate models (CMIP) under different emission pathways (RCPs) and shared socioeconomic pathways (SSPs) to force a coupled hydrology and water quality model (mHM-N [2]) that characterizes the N retention and export dynamics over the period 1971-2070. SSPs consider balancing options for agricultural land management and technical innovations, taking into account future food, economic growth, and environmental demands; and provide N input trajectories from both diffuse (agricultural) and point (wastewater) sources. Our analysis shows a higher degree of improvement with substantially lower N levels in all European surface water bodies by the 2050s, compared to current levels (2010s). Eastern European rivers may benefit from technological improvements by reducing point source inputs, while in the Western European region, lower N levels can be noticed due to a reduction in diffuse N inputs. Despite these improvements, there are areas of concern where some European water bodies may still suffer from N levels exceeding critical thresholds (e.g., 2-3 mg N/l) in 2050. This may be related to continued N exports that slowly deplete legacy storages (e.g., soil and groundwater). Overall, this requires more proactive measures, particularly aiming at reducing N inputs while harvesting/utilizing and attenuating the built-up storage, to achieve the zero-pollution goal.
References
[1] https://environment.ec.europa.eu/strategy/zero-pollution-action-plan_en
[2] https://doi.org/10.1029/2008WR007327; https://doi.org/10.1029/2022GL100278
How to cite: Kumar, R., V. Nguyen, T., J. Sarrazin, F., Ebeling, P., Schmidt, C., Beusen, A., Bouwman, L., H. Fleckenstein, J., Attinger, S., and Musolff, A.: Towards realizing the EU 2050 Zero Pollution Vision for Nitrogen Export, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-12024, https://doi.org/10.5194/egusphere-egu23-12024, 2023.
Deforestation is currently a widespread phenomenon and a growing environmental
concern in the era of rapid climate change. In temperate regions, it is challenging to
quantify the impacts of deforestation on the catchment dynamics and downstream
aquatic ecosystems such as reservoirs and disentangle these from direct climate
change impacts, let alone project future changes to inform management. Here, we
tackled this issue by investigating a unique catchment-reservoir system with two
reservoirs in distinct trophic states (meso- and eutrophic), both of which drain into the
largest drinking water reservoir in Germany. Due to the prolonged droughts in 2015-
2018, the catchment of the mesotrophic reservoir lost an unprecedented area of forest
(exponential increase since 2015 and ca. 17.1% loss in 2020 alone). We coupled
catchment nutrient exports (HYPE) and reservoir ecosystem dynamics (GOTM-WET)
models using a process-based modelling approach. The coupled model was validated
with datasets spanning periods of rapid deforestation, which makes our future
projections highly robust. Results show that in a short-term time scale (by 2035),
increasing nutrient flux from the catchment due to vast deforestation (80% loss) can
turn the mesotrophic reservoir into a eutrophic state as its counterpart. Our results
emphasize the more prominent impacts of deforestation than the direct impact of
climate warming in impairment of water quality and ecological services to downstream
aquatic ecosystems. Therefore, we propose to evaluate the impact of climate change
on temperate reservoirs by incorporating a time scale-dependent context, highlighting
the indirect impact of deforestation in the short-term scale. In the long-term scale (e.g.
to 2100), a guiding hypothesis for future research may be that indirect effects (e.g., as
mediated by catchment dynamics) are as important as the direct effects of climate
warming on aquatic ecosystems.
How to cite: Rode, M., Kong, X., Ghaffa, S., Determann, M., Friese, K., Jomaa, S., Mi, C., Shatwell, T., and Rinke, K.: Reservoir water quality deterioration due to deforestation emphasizes the indirect effects of global change, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-5239, https://doi.org/10.5194/egusphere-egu23-5239, 2023.
Both discharge (Q) and stream temperature (Tw) are the key factors affecting water quality and the suitability of instream habitats, which are expected to experience substantial evolutions due to climate change. However, the absence of continuous and long-term data of Tw at a large scale limits our understanding of the spatio-temporal variations of Tw and their control factors, like riparian vegetation, strahler order, hydroclimate.
The present study used a physically-based thermal model (T-NET), coupled with a semi-distributed hydrological model (EROS) using SAFRAN meteorological reanalysis data provided of Météo-France to reconstruct past daily Q and Tw over the 1963-2019 period for 52 000 hydrographic reaches of the Loire basin (100 000 km²), France. Three regionalized climate projections under several future emissions scenarios (available on the DRIAS portal: www.drias-climat.fr) were used to project future daily time series of these variables over the 2005-2100 period.
The results over the 1963-2019 period showed that the increase of the Tw was higher than those air temperature (Ta) in spring, summer and autumn for the majority of the reaches of the basin. Indeed, Tw increased for almost all reaches and all seasons (average = +0.38°C/decade) with the largest increase in the spring (Mar-May) (range=+0.11 to +0.76°C per decade) and in summer (Jun-Aug) (+0.08 to +1.02°C per decade). Highest spring and summer increases were generally found in the south of the basin (Massif Central and Limousin plateau) and in higher Strahler order where a larger increase in Ta (up to 0.67 °C/decade) and a larger decrease in Q (up to -16%/decade) occurred jointly.
Depending on climate models, scenarios and seasons,future projections showed changes in seasonal flow and water temperature. Seasonal median flow over the basin would be between -40% and +35% for the middle of the 21st century (2040-2079) compared to the 1990-2019 period. For the end of the century (2070-2099), flow change would be between -53% and +73%. A clear increase in future Tw was also found with seasonal median increases of +0.7 to +2.7°C in the middle (2040-2079) and of +0.8°C to +5.0°C, at the end of the century (2070-2099).
These climate-induced changes in Q and Tw could help us to explain shifts in the phenology and geographical distribution of cold-water species. Moreover, they highlight that we should take vital actions for both adaptation and mitigation strategies. In this regard, we found that some of these climate change-induced impacts on Tw can be mitigated through the restoration and maintenance of riparian shading specially in small streams.
How to cite: Moatar, F., Seyedhashemi, H., Vidal, J.-P., Diamond, J., Thiery, D., Hendrickx, F., and Maire, A.: Evolution of discharge and stream temperature from past to future in a large European River basin, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7683, https://doi.org/10.5194/egusphere-egu23-7683, 2023.
Precipitation is one of the essential driving factors of natural processes influencing the structure and functioning of river catchment ecosystems. Changes in precipitation conditions have a significant impact on surface runoff and consequently the intensity of sediment transport, and its deposition especially in mountain catchments exposed to frequent rainfalls and prone to erosion. Therefore, insightful information about future precipitation regional projections seems to be crucial for ecosystem services management, including dammed reservoirs and fresh water resources.
In general, precipitation is projected to change its annual structure over Central Europe in relation to enhanced atmospheric moisture, moisture convergence and extratropical cyclone activity. Although new generations of climate models focus on improved simulation of water cycle, precipitation projections still become a challenge as key processes driving precipitation changes at local and hemispheric scale remain significantly sensitive to model resolution.
The aim of the study is to indicate the differences between particular precipitation projections for the exemplary Carpathian mountains catchment (Raba River, Poland) and their further evaluation towards the impact of the chosen climate model on the environmental modelling results (sediment load variability). The outcomes of High Resolution Model Intercomparison Project (HighResMIP) - CMIP6 and higher-resolution regional data for Europe from the Coordinated Regional Climate Downscaling Experiment (EURO-CORDEX) will be taken into account. Absolute and relative changes in annual precipitation structure will be examined for the whole period of 2026-2100 with short-term (2026-2050) and long-term (2051-2100) perspectives.
The research conducted so far revealed that both sediment yields from the exemplary catchment and the sediment loads from the studied river could be greatly altered due to the predicted changes in precipitation and temperature. Since such changes can have a pronounced impact on vital ecological processes ongoing in the catchment the utmost attention should be paid to assessment of differences between climate change scenarios applied in such studies.
How to cite: Wypych, A., Wilk, P., Szalińska, E., and Orlińska-Woźniak, P.: Precipitation driven river catchment changes - how the climate models determine the results (the example from Polish Carpathians), EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-14799, https://doi.org/10.5194/egusphere-egu23-14799, 2023.
This presentation reports on the results of simulating 17 regulatory SIMCAT water quality models for England based on using the CEH Future Flows dataset. The de-biased uplifts were generated across 140 flow gauges comparing 2060-2080 with 2000-2020 for 11 ensembles, and kriged across the country to capture the gradients and apply river reach-specific uplifts in headwater and along-reach flows (for mean and 95 percentile exceedance flows). The resulting uplifts were applied using a recently developed UKWIR workbook and the statistical water quality models were simulated for a range of sanitary and chemical determinands (BOD, ammonia, dissolved oxygen, total and soluble phosphorus, nitrate, PFOS, cadmium and cypermethrin) to assess the potential change to Sewage Treatment Work permits.
Failure of target EQS and 10% deterioration of quality are analysed, computing the necessary adjustment to water quality permits to meet the water quality standards in the future. Ensemble uplifts representative of upper, lower and mid flows were used (focussing on the low flows) and their predicted annual average reduction. The sensitivity of the results to travel time, seasonality and temperature are investigated, and outputs are compared with recent process-based modelling using the EA HYPE model of England.
How to cite: Hankin, B., Heaney, T., Eccleston, P., Simmons, P., Garratt, A., and Wang, C.: Stress testing the impacts of climate change on water quality permitting across England, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6793, https://doi.org/10.5194/egusphere-egu23-6793, 2023.
Human activities greatly impact surface water quality due to the emission of various pollutants associated with different water use sectors (e.g. irrigation, livestock, domestic, energy and manufacturing)1,2. In-stream concentrations are also strongly dependent on the dilution capacity of receiving waters, which is related to both the hydrological regime and surface water abstractions. Pollutant emissions, hydrological regimes and surface water abstractions are all projected to change into the future as a result of both (uncertain) climate change and socio-economic developments. Yet, quantitative projections of future surface water quality are sparse, particularly at the global scale.
In this work, we apply a new high-resolution global surface water quality model (DynQual)3 to project water temperature (Tw) and total dissolved solids (TDS), biological oxygen demand (BOD) and fecal coliform (FC) concentrations for the time period 2005-2100, considering multiple scenarios that combine Representative Concentration Pathways (RCPs) with Shared-Socioeconomic Pathways (SSPs). Input from five general circulation models (GCMs) is used to force PCR-GLOBWB2, the hydrological model coupled to DynQual, to account for the large range of uncertainties inherent in the climatological projections.
The mechanisms that drive patterns in future surface water quality are a complex balance between changes in pollutant emissions, the dilution capacity of streams and in-stream decay processes, which are strongly driven by water temperature, under global change. Patterns of both water quality improvement and deterioration exist, which vary greatly across world regions. Reductions in pollutant emissions across most of Western Europe, North America and East Asia drive trends towards surface water quality improvements, irrespective of climate and socio-economic scenario. Conversely, developing countries are more sensitive to (uncertain) climate and socio-economic changes, with surface water quality typically improving under SSP1-RCP2.6, a mixed response under SSP5-RCP8.5 and strong degradation under SSP3-RCP7.0. Changes to the hydrological cycle are particularly important for surface water quality in the Amazon basin, with substantial reductions in discharge projected under SSP3-RCP7.0 and SSP5-RCP8.5. These changes result in reduced dilution capacities of rivers and thus higher in-stream concentrations, for instance of TDS.
Surface water quality deterioration occurs across Sub-Saharan Africa under all scenarios, albeit to different magnitudes, which substantially increases the number of people that are exposed to poor water quality. Under SSP3-RCP7.0, the “worst-case” scenario for all constituents considered in our study, 4.2 billion people will be exposed to surface water with unsafe levels of organic (BOD) pollution by 2100. With 1.5 billion (36%) of these people located in Sub-Saharan Africa, compared to 290 million (11%) in the historical reference period, we conclude that Sub-Saharan Africa will become the new hotspot of water quality issues.
References
1. Jones, E. R. et al. Current wastewater treatment targets are insufficient to protect surface water quality. Communications Earth & Environment 3, 221, doi:10.1038/s43247-022-00554-y (2022).
2. van Vliet, M. T. H. et al. Global water scarcity including surface water quality and expansions of clean water technologies. Environmental Research Letters 16, 024020, doi:10.1088/1748-9326/abbfc3 (2021).
3. Jones, E. R. et al. DynQual v1.0: A high-resolution global surface water quality model. Geosci. Model Dev. Discuss. 2022, 1-24, doi:10.5194/gmd-2022-222 (2022).
How to cite: Jones, E. R., Bierkens, M. F. P., van Puijenbroek, P. J. T. M., and van Vliet, M. T. H.: Modelling global surface water quality under uncertain climate and socio-economic change, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1161, https://doi.org/10.5194/egusphere-egu23-1161, 2023.
Current multi-stressor pressures on water quality in agricultural catchments will be exacerbated by the more frequent occurrence of extreme weather events resulting in multi-stressor environments. Managing surface water under future climatic conditions will require adaptations and targeted mitigation strategies that consider individual catchment characteristics. Assessing the impacts of recent extreme weather events can allow for the better understanding of, and insight into, the key drivers of elevated pollutant losses and point to the possible future challenges for water quality management.
As a part of the Irish EPA funded WaterFutures project, changes in the impact of climatic drivers on nutrient losses from field to small stream scale catchments of different typologies are being investigated using long-term and high-frequency water quality datasets. The trends of daily nitrate-N, and phosphorus (TP) concentrations and loads over 11 years were interrogated in two agriculturally-dominated catchments in Ireland, and in both a permanent pasture and arable field in the southwest UK (ca. 0.38– 12 km2). The trends in nutrient losses and the significance of discharge, precipitation, potential evapotranspiration (PET), soil moisture deficit, air temperature, and soil temperature, were investigated using Mann-Kendall Trend and Generalised Additive Model, respectively.
Significant inter-seasonal trends were identified in both countries and similar fluctuations of nutrient concentrations and loads in October and November 2018 were observed following an exceptional summer drought. All study sites responded to daily rainfall exceeding 10mm, although in different ways due to the different site characteristics. The soil and air temperature in the two geographically-close Irish catchments revealed a significant upward trend from June to September. During this period, these two drivers, along with discharge and PET, were key drivers of N-losses in the well-drained and arable dominated catchment. The increasing trend of monthly average N-concentrations were significant in April and November (from 5.6 in 2009 to 8.9 nitrate-N mg L-1 in 2018, Kendall-tau= 0.424). On the other hand, a catchment dominated by poorly-drained grassland showed an increasing trend in TP concentrations during January, May, September, and October (from 0.79 in 2009 to 6.72 TP mg L-1 in 2020, Kendall-tau= 0.455). Here, changes in air temperature, precipitation, and discharge were the key drivers for P losses.
Changing weather patterns, consequent changes in nutrient concentrations and load trends, and precipitation-discharge responses can be detected using long-term water quality records and should be considered for future climate smart mitigation strategies.
How to cite: Ezzati, G., Mellander, P.-E., Pulley, S., and Collins, A.: Drivers and inter-seasonal trends of nutrient losses from contrasting agricultural river catchments in Ireland and UK, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1994, https://doi.org/10.5194/egusphere-egu23-1994, 2023.
Lake chlorophyll-a (Chl-a) is one of the important components of the lake ecosystem. The Chl-a concentration of global water has generally increased in recent decades due to climate change and intensified anthropogenic activity. However, few researches have been done on the lake Chl-a variations in remote areas with less disturbance by human activities such as the Tibet Plateau (TP). Here, we combined 95 in situ measured lake Chl-a concentration data and Landsat reflection spectrum to establish an inversion model of Chl-a concentration through the backpropagation (BP) neural network prediction method, by which the mean annual Chl-a concentration in the past 35 years (1986–2021) of 318 lakes with an area of > 10 km2 in the TP have been retrieved. Meteorological and hydrological data, measured water quality parameters and glacier change in the lake basin were used to elucidate the driving factors of the Chl-a concentration changes in the TP lakes, with the help of geographic information system (GIS) technology and by spatial statistical analysis. The results showed that the mean annual Chl-a in the 318 lakes performed overall decrease during 1986-2021, but 63%, 32% and 5% of the total number exhibited no significant change, significant decrease and significant increase, respectively. After a slight increase during 1986–1995 (0.05 μg/L/y), the mean annual lake Chl-a significantly decreased during 1995–2004 (–0.18 μg/L/y). Further, after a slight increase during 2004–2011 (0.07 μg/L/y), it decreased slightly during 2011–2021 (–0.04 μg/L/y). The mean annual lake Chl-a concentration was significantly negatively correlated with precipitation (R2 = 0.48, P < 0.01), air temperature (R2= 0.31, P < 0.01), lake surface water temperature (LSWT) (R2 = 0.51, P < 0.01), lake area (R2= 0.42, P < 0.01) and lake water volume change (R2 = 0.77, P < 0.01). The decrease in mean annual Chl-a was in consistant to the decrease in that of salinity (R2= 0.69, P < 0.01) and increase in that of transparency (R2= 0.55, P < 0.01). The Chl-a concentrations of non-glacial meltwater-fed lakes were higher than those of glacial meltwater-fed lakes, except during higher precipitation period. Our result of lake Chl-a inversion and their variation reason analyses is able to further deeply understand the climate change impacts on Chl-a changes in the TP lakes.
How to cite: Zhu, L., Pang, S., Liu, C., and Ju, J.: The decreasing Chlorophyll-a in Tibet Plateau lakes during 1986–2021 based on Landsat image inversion and their impact causes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-6888, https://doi.org/10.5194/egusphere-egu23-6888, 2023.
Posters on site: Fri, 28 Apr, 14:00–15:45 | Hall A
Groundwater quality is being deteriorated as a result of climate change, overuse, and decreased precipitation, consequently impacting both agricultural productivity and human health. Thus, to investigate the potential variations in groundwater quality for irrigation and household applications, groundwater samples were collected from 88 different sites in Sarat Al-Baha region, Saudi Arabia. The Al-Baha region is characterized by a fragile agro-ecosystem, which is extremely susceptible to climate change. The collected samples were subjected to hydrochemical analyses to determine whether groundwater was suitable for irrigation and household consumption. Results showed that concentrations of nitrate and heavy metals were within maximum permissible limits for drinking purposes in 91% of the collected samples. However, because of elevated levels of arsenic and nitrate, 8% of the collected groundwater samples were deemed to be of poor or very poor quality for drinking purposes. The estimated saturation index revealed that the majority of the minerals in the samples were under-saturated, suggesting a higher possiblity of salinity owing to the dissolution of under-saturated minerals, conseqently increasing iron, calcium, magnesium, sodium, chloride, and sulfate concentrations. No sodicity risks were anticipated, despite of medium to higher salinity hazard. More than 90% of the collected groundwater samples had unsatisfactory quality for irrigation purposes due to the presence of salts in higher amounts, which could be due to lower precipitation and higher temperature in the study area. Hence, employing suitable management strategies to maximize groundwater utilization is recommended to avoid further groundwater quality deterioration. Groundwater discharge must be ristricted, cropping patterns should be altered to boost water productivity, and grounwater quality must be monitored on regular basis.
How to cite: Alghamdi, A. G., Aly, A. A., and Ibrahim, H. M.: Potential variations in groundwater quality for household and irrigation applications as affected by climate change , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-1721, https://doi.org/10.5194/egusphere-egu23-1721, 2023.
Coastal waters receive multiple pollutants, such as nutrients, plastics, and chemicals. Rivers transport these pollutants often from rural and urban areas to seas. Many pollutants have common sources and cause multiple impacts (e.g., eutrophication and toxicity), decreasing the availability of clean water. Meanwhile, the global change adds to coastal water pollution. For example, cities are expected to expand in size and numbers, increasing future urban pollution. In addition, agriculture may intensify to satisfy the food demand for a growing global population. This intensification may, in turn, increase agricultural pollution in river export to coastal waters. In addition, climate change is expected to result in more floods and droughts. Floods may transport more pollutants from urbanised and agricultural areas to the seas. The effects of global change will likely differ among river basins depending on their characteristics.
Existing scenarios, such as the Representative Concentrative Pathways (RCPs) and Shared Socio-economic Pathways (SSPs), address global change challenges. However, these scenarios have yet to be implemented for a global multi-pollutant assessment of coastal waters. In addition, large-scale assessments of coastal water pollution are often for single pollutants, overlooking synergies and trade-offs in pollution control for multiple pollutants. Sustainable Development Goal (SDG) 14 (clean marine waterways) may be supported by considering multiple pollutants and sources, yet additional research in the field is needed.
Our study aims to better understand the influence of global change on the river export of multiple pollutants to coastal waters by source and sub-basins. To this end, we develop the MARINA-Multi (Model to Assess River Inputs of pollutaNts to the seAs) model for more than 10,000 sub-basins and for nutrients, chemicals, and plastics to estimate future pollution trends. For these pollutants, we consider point (such as sewage systems and open defecation) and diffuse (such as agriculture and improperly managed solid waste on land) sources. Finally, we consider the SGD coastal water quality targets and develop optimistic and pessimistic futures under global change.
Our model results show that, in 2010, more than 50% of the population lived in river basins where coastal waters experienced multi-pollution problems. Rivers exported considerable amounts of nutrients, chemicals, and plastics to coastal waters globally, two-thirds reaching the Atlantic and Pacific seas. Diffuse sources contributed by over 70% to nitrogen and macroplastics in global seas. Point sources contributed by 70- 90% to phosphorus and microplastics in global seas. Multi-pollution hotspots are often found in urbanised areas. Global change will alter those pollution hotspots. First, the pollution patterns are expected to shift due to climate change affecting temperature and the water cycle. Second, changes in socioeconomic drivers are expected. Our optimistic scenarios are associated with, for example, the technological progress that enhances waste collection and treatment. The MARINA-Multi model is useful for understanding the sources and spatial variability of the multiple pollutants in rivers and coastal waters under global change. Our model can support decision-makers and water managers in implementing mitigation and adaptation policies to achieve sustainable targets for the marine environment (SDG 14).
How to cite: Micella, I., Kroeze, C., and Strokal, M.: Future coastal water pollution under global change: multi-pollutant modeling, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-2336, https://doi.org/10.5194/egusphere-egu23-2336, 2023.
Nutrient pollution derived from anthropogenic activities impacts both inland and coastal waters, altering the aquatic ecosystem and resulting in serious environmental issues. As climate change is affecting most of the hydroclimatic variables across the world, a fundamental concern in river ecology is therefore to understand the degree to which the spatial patterns and variations of nutrient concentration and loading in rivers during the last decades can be associated with climate change. This study detects and attributes the impact of historical climate change on long-term changes in the flux of nutrients from diffuse pollution sources into the coastal waters of Africa. An impact attribution approach is employed by forcing a continental process-based water quality model (Soil and Water Assessment Tool – SWAT+) for Africa with a set of observational and counterfactual climate data from the impact attribution setup of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP3a). The nonparametric Mann–Kendall test is used to identify trends while long-term mean annual river nutrient simulation differences between a model setup with observational and counterfactual climate data are calculated to allow for quantification of the climate change attribution. Results show spatial differences with climate change reasonably contributing to both an increase and decrease of both riverine Total Nitrogen and Total Phosphorus to African coastal waters. However, the climate change imprint on the riverine nutrient export is starting to emerge within the 21st century years for most rivers. These findings show spatial differences in the sensitivity of impacts of climate on riverine TP and TN export to coastal waters while highlighting the most impacted rivers in Africa.
How to cite: Nkwasa, A., Chawanda, C. J., and van Griensven, A.: Attribution of climate change imprint on riverine nutrient export from diffuse pollution sources to African coastal waters, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3312, https://doi.org/10.5194/egusphere-egu23-3312, 2023.
Freshwater lakes are a major resource for human populations. To support water quality (WQ) management for lakes, both WQ monitoring and WQ modeling are essential. Conventional approaches, such as process-based models, are usually used for WQ modelling, however, these approaches require a large number of data (meteorological, topographical, hydrological, and WQ data) with high computational demands. Recently, artificial intelligence (AI) techniques are increasingly recommended in WQ modelling to tackle these challenges. In this study, the application of AI techniques for simulating/predicting water quality for large lakes using remote sensing (RS) is investigated. Specifically, the study aims to develop a robust AI model for turbidity in Lake Victoria, using the lake basin precipitation data and the sediment concentrations of the inflow rivers. To develop the AI model, the freely available remote sensing turbidity data for the lake is used as a reference data. Two models using a multi-layer perceptron neural network (MLPNN) and least square support vector regression (LSSVR) have been trained based on three different scenarios. Some performance indices such as mean absolute relative error and percent bias have been selected for model evaluation. According to the obtained results, LSSVR is more accurate than MLPNN in both training and testing phases of all scenarios. The results indicate that AI-based models are potential tools that can be adopted for WQ simulations of large lakes. Additionally, this study illustrates the potential of the use of remote sensing data to support model development, as an alternative to in-situ measurements, especially in data-scarce regions.
Keywords: Water quality, artificial intelligence, remote sensing, sediment concentration, turbidity
How to cite: Khorashadi Zadeh, F., Khorashadizadeh, S., Nkwasa, A., and van Griensven, A.: Coupling artificial intelligence techniques and remote sensing data for water quality simulation of lakes, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-3700, https://doi.org/10.5194/egusphere-egu23-3700, 2023.
The European Green Deal has the ambition to reduce nutrient losses from agricultural catchments with 50%. In the context of a changing climate, there is an increasing need to evaluate the efficacy of catchment remediation measures and reduction in fertilisation. In this study, we set-up a daily discharge and nutrient load model for two Swedish agricultural headwater catchments using Hydrological Predictions for the Environment (HYPE). The daily model was calibrated and validated using high-frequency sensor data and flow-proportional samples analysed for nutrient and sediment concentrations. Multiple catchment remediation scenarios were run under three downscaled climate models and three Representative Concentration Pathways (RCP 2.6, RCP 4.5, and RCP 8.5). The model predicted that Inorganic Nitrogen loads will decrease in the latter half of the 21st century under RCP 4.5 and RCP 8.5 driven by increased denitrification under higher temperatures. Moreover, under all RCPs, an increase in Particulate Phosphorous and sediment loads is forecasted due to increased rainfall intensity. Decreasing the amount of mineral fertilisation only resulted in decreased Inorganic Nitrogen loads, but had no effect on Total Phosphorous loads. Catchment remediation measures were most effective for reducing Total Phosphorous loads. However, large portions of agricultural catchments will need to be converted to floodplains or wetlands in order to achieve significant load reductions and offset the predicted increases under future climatic trajectories.
How to cite: Wynants, M., Hallberg, L., and Bieroza, M.: Modelling the efficacy of catchment remediation measures for reducing sediment & nutrient exports under future climate trajectories , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7260, https://doi.org/10.5194/egusphere-egu23-7260, 2023.
Excessive nutrient (nitrogen and phosphorus) loadings to freshwater lakes cause eutrophication, which is a global water quality issue. Anthropogenic activities in lake basins emit nutrients, either as point- (e.g., sewage) or diffuse sources (e.g., agricultural runoff). Their typical impacts on lake water quality include the occurrence of harmful algal blooms, hypoxia and fish kills. These impacts are likely to worsen due to climate change, population growth and economic development. The response of lakes to a change in nutrient inputs depends on their interactions with the climate, land-use, hydrology and socio-economic conditions of a lake basin. These feedback mechanisms, however, are not often included in the eutrophication assessments for lakes. In this study, we present a new causal network of the drivers-pressure-state-impact-response (DPSIR) framework using a total of 58 sub-indicators to characterize all the DPSIR elements and systematically conceptualize the complex interactions of nutrients in freshwater lake basins. The network provides a holistic perspective on nutrient dynamics of multiple indicators and their interactive effects on water quality in lake basins, which is key to improving water quality management. Furthermore, we disentangle the complex eutrophication mechanisms using drivers and pressures, that represent different sources and nutrient pathways. The study highlights coupling of lake systems in water quality modeling frameworks and assessments which is required to understand its impact on water quality from human activities in the basin. The drivers and pressures can be used as proxies to provide meaningful information on nutrient emissions and biogeochemical pathways, that can fill the gap in water quality monitoring data, especially in data scarce regions such as Asia and Africa. These indicators can be used to set realistic water quality targets, and are, therefore, beneficial in long-term policy making and sustainable water quality management.
How to cite: Suresh, K., Tang, T., T.H. van Vliet, M., F.P. Bierkens, M., Strokal, M., Sorger-Domenigg, F., and Wada, Y.: Recent advancement in water quality indicators for eutrophication in global freshwater lakes , EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7565, https://doi.org/10.5194/egusphere-egu23-7565, 2023.
Stream temperature and discharge are two fundamental triggers of key periods of the life cycle of aquatic organisms such as the migration of diadromous fish. However, the increase in stream temperature, more frequent and severe droughts, and asynchronous evolution of stream temperature and discharge due to climate change can modify the duration and frequency of favorable temperature-flow associations for the realization of species’ ecological processes.
In this study, we investigated the influence of changes in favorable temperature-flow velocity associations for the upstream migration of Atlantic salmon, Alis shad and Sea lamprey at the scale of the Loire River basin ( km²). First, we used a physically-based thermal model (T-NET), coupled with a semi-distributed hydrological model (EROS) to reconstruct continuous daily times series over the 1963-2019 period (Seyedhashemi et al., 2022). Current velocity (V) was estimated using discharge through a hydraulic geometry model (Morel et al., 2020). We identified suitable water temperature-flow velocity associations for the migration of the three studied species based on (1) the literature and (2) observed migration recorded at fish passage stations. Using the “Choc method” (Arevalo et al., 2020), we then quantified the changes in frequency of occurrence of these suitable environmental windows over the past six decades across the hydrographic network of the Loire River basin.
Our results showed that the greatest increases in stream temperature were associated with the greatest decreases in flow velocity over the past six decades. We also found that the frequency of suitable temperature-velocity associations for upstream migration of Atlantic salmon has significantly reduced, mainly in the southern part of the basin. In contrary, the frequency of suitable associations for upstream migration of the two other species has mainly increased.
These results highlighted strong disparities in the consequence of global changes on fish migratory processes among species and in space. This work provides operational results for the management of these threatened diadromous species and the prioritization of management measures in a context of climate change.
Key words: climate change, hydrological change, water temperature, temporal trends, fish migration, long-term, large scale, Loire basin
Seyedhashemi, H., Vidal, J.P., Diamond, J.S., Thiéry, D., Monteil, C., Hendrickx, F., Maire, A. and Moatar, F., 2022. Regional, multi-decadal analysis on the Loire River basin reveals that stream temperature increases faster than air temperature. Hydrology and Earth System Sciences, 26(9), pp.2583-2603.
Morel, M., Booker, D.J., Gob, F. and Lamouroux, N., 2020. Intercontinental predictions of river hydraulic geometry from catchment physical characteristics. Journal of Hydrology, 582, p.124292.
Arevalo, E., Lassalle, G., Tétard, S., Maire, A., Sauquet, E., Lambert, P., Paumier, A., Villeneuve, B. and Drouineau, H., 2020. An innovative bivariate approach to detect joint temporal trends in environmental conditions: Application to large French rivers and diadromous fish. Science of the Total Environment, 748, p.141260.
How to cite: Seyedhashemi, H., Drouineau, H., Maire, A., and Moatar, F.: Joint temporal trends in river discharge and temperature over the past 57 years in a large European basin: implications for diadromous fish, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-7598, https://doi.org/10.5194/egusphere-egu23-7598, 2023.
Nitrate pollution adversely affects water quality, making it unsafe for human consumption and contributing to increased eutrophication. Nitrate exportation in agricultural areas is inevitable; however, climate change introduces great uncertainty into an already very complex problem. Thus estimating the effects of climate change on streamflow and nitrate dynamics would significantly contribute to the management of the affected areas. This research aimed to predict the impacts of climate change on streamflow and nitrate exportation in a Mediterranean rainfed agricultural watershed using the Soil Water Assessment Tool (SWAT). The model was first evaluated for its suitability to simulate streamflow and nitrate loads under rainfed agricultural conditions in the 477 km2 Cidacos River Watershed in Navarre, Spain. The model was then used to analyze the climate change impacts on streamflow and nitrate load in the short-term (2011-2040), medium-term (2041-2070), and long-term (2071-2100) climate projections compared to a historical baseline period (1971-2000) using the RCP4.5 and RCP8.5 CO2 emission scenarios. The model evaluation showed a good model performance during calibration (2000-2011) and validation (2011-2020) for streamflow (NSE = 0.82/0.83) and nitrates load (NSE = 0.71/0.68), indicating its suitability for adoption in the watershed. The climate change projection results showed a steady decline in streamflow and nitrate load for RCP4.5 and RCP8.5 in all the projections, with the long-term projection scenario of RCP8.5 significantly affected. Autumn and winter saw the greatest seasonal declines compared to spring and summer. The decline in streamflow was attributed to the projected decrease in precipitation and increase in actual evapotranspiration due to increasing temperatures, while the nitrate load decline was consistent with the projected streamflow decline. Based on these projections, the long-term projection scenarios of RCP8.5 indicate severe situations requiring urgent policy changes and management interventions to minimize and mitigate the negative consequences. Therefore, better agricultural management practices are needed to ensure sustainable water resource utilization and efficient nitrogen fertilizer application rates in the watershed to reduce pollution.
How to cite: Oduor, B. O., Campo-Bescós, M. Á., Lana-Renault, N., and Casalí, J.: Modeling the impacts of climate change on streamflow and nitrate export in a Mediterranean agricultural watershed in Spain, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11247, https://doi.org/10.5194/egusphere-egu23-11247, 2023.
The increase of human interventions and developments is modifying the land use/land cover (LULC) of the global landscape, thus affecting the water quality of rivers and lakes severely. Lake Titicaca and Lake Nicaragua (also known as Lake Cocibolca) are the largest lakes in Latin America. Despite Bolivia and Nicaragua being countries with a vast richness of natural resources, they face unsustainable practices ranging from over-exploitation of resources to drastic LULC changes that have created environmental problems that consequently affect human well-being and health. Additionally, climate change (CC) is exacerbating these problems and causing new ones. Therefore, it is also necessary to consider the effects that it will have on water quality, either by changes in temperature or by changes in precipitation (floods or droughts) that affect river flows and sediment transport.
Environmental sustainability means securing adequate management of natural resources in all human productive and livelihood activities. Monitoring and assessing the quality of surface waters are fundamental for managing and ensuring the improvement of its state. A good understanding of the LULC change and CC dynamics is crucial to develop efficient strategy assessment, pollution management, and land use planning for the promotion of sustainable development. For these case studies, the integrated use of remote sensing products; especially considering the scarcity of data, enables a comprehensive understanding of the cause-effect relations in the water system, which assists policymakers in developing management plans for a variety of natural resource management applications.
How to cite: Baltodano Martínez, A. and van Griensven, A.: How remote sensing can identify land cover and climate change impacts on lake water quality: Lake Nicaragua and Lake Titicaca case studies., EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-11416, https://doi.org/10.5194/egusphere-egu23-11416, 2023.
The Upper White Nile basin plays a critical role in supporting essential ecosystem services and the livelihoods of millions of people in East Africa. The basin has been exposed to tremendous environmental pressures following extensive population growth, urbanisation, and land use change, all of which are compounded by the threats posed by climate change. The water-energy-food (WEF) nexus provides an integrated solution to sustainable development by minimising the trade-offs between water, energy, and food resources. We apply quantitative and qualitative methods to understand the most pressing WEF nexus challenges within the Upper White Nile basin, how these can be represented in indicators, and how existing WEF nexus modelling tools could address this. This research combines semi-structured stakeholder interviews with a Co$tingNature analysis in order to map the greatest environmental pressures within the basin and disentangle the likely drivers. The findings from these highlight the importance of declining water quality, aquatic and terrestrial ecosystem health, and fish populations as a result of deforestation, growing human population, intensifying pollution, and increasing agricultural intensity within the basin, with most stakeholders expressing concerns for the uncertain impacts from climate change. Furthermore, a review of current WEF nexus modelling tools reveals how existing tools are insufficient in addressing the most pressing environmental challenges within the basin, with a significant gap regarding the inclusion of nuanced water quality and aquatic ecosystem indicators. Subsequently, these findings are combined in order to guide the development of holistic WEF nexus indicators that have the potential to spatially model the trade-offs within the WEF nexus in the Upper White Nile basin under climate change and land use change scenarios. This work demonstrates the use of a novel decision framework for WEF nexus indicator development, which ensures that outputs are fit-for-purpose and respond to the actual needs of stakeholders and policymakers. The outputs aim to strengthen water management decisions that enhance water quality, energy production, food production, and aquatic biodiversity within the Upper White Nile basin.
How to cite: Schlemm, A., Mulligan, M., and van Griensven, A.: Including water quality in the water-energy-food nexus: An Upper White Nile case study, EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-16167, https://doi.org/10.5194/egusphere-egu23-16167, 2023.
