Climate change may alter the services ecosystems provide by changing ecosystem functioning. As ecosystems can also resist environmental perturbations, it is crucial to consider the different processes that influence resilience. “Climate proofing” can identify potential climate-related threats to ongoing delivery of ecosystem services. Dr. Katri Rankinen and colleagues have published a new study modelling the potential for increased nitrate(NO3−) concentrations in drinking water due to climate change. They analyzed catchment-scale changes in ecosystem services connected to water purification in southern Finland by combining climate change scenarios with process-based forest growth (PREBAS) and eco-hydrological (PERSiST and INCA) models. By using the aforementioned model chain, they improved traditional model calibration by including timing of forest phenology and duration of the snow-covered period from networks of cameras and satellite data. They upscaled the combined modelling results with scenarios of population growth to produce vulnerability maps. Their results show that boreal ecosystems seemed to be strongly buffered against increased NO3– leaching by a combination of increases in evapotranspiration and vegetation NO3– uptake. Societal vulnerability varied greatly between scenarios and municipalities. The most vulnerable areas were agricultural regions on permeable soil types.
Dr. Jan Deutscher and colleagues present a new study modelling streamflow decline in the Central European uplands. This study is timely as in recent decades the effects of global climate change have caused a continuous drying out of temperate landscapes. In Czech forests, this drying out has been manifested as a visible decrease in streamflow. Dr. Deutscher and colleagues address questions related to the severity of the streamflow decrease and attempt to identify its main causes. They base their analysis on daily streamflow, temperature, and precipitation data measured during five years (1/11/2014 to 31/10/2019) in a spruce-dominated temperate upland catchment located in the Czech Republic. Streamflow values were modeled in with PERSiST using precipitation and temperature values obtained from the observational E-OBS gridded dataset and calibrated against in situ measured discharge. Their modeling results show a greater than 65% decline in streamflow during the five-year study period at the Křtiny experimental catchment. This trend is most likely caused by increasing temperature. They found a strong relationship between increasing temperature and decreasing discharge during the growing seasons, which can be simplified to an increasing trend in the mean daily temperature of 0.1o C per season, effectively causing a decreasing trend in the discharge of −10% per season regardless of the increasing precipitation during the period.
Maria Holmberg and colleagues present an approach to collate spatially explicit estimated fluxes of GHGs (carbon dioxide, methane and nitrous oxide) for the main land use sectors in the landscape, and show how these fluxes can be aggregated to calculate net emissions of an entire region. They used INCA-C and PERSiST to estimate the flux of organic carbon from terrestrial ecosystems to lakes and rivers.
They developed and tested the approach in a large river basin in Finland, providing information from intensively studied eLTER research sites. To evaluate the full GHG balance, they included fluxes from natural ecosystems (lakes, rivers, and undrained mires) together with anthropogenic fluxes from agriculture and forestry. They quantified fluxes using an anthropogenic emissions model (FRES), a forest growth and carbon balance model (PREBAS), and literature values for emissions from lakes, rivers, undrained mires, peat extraction sites and cropland. Spatial data sources included CORINE land use data, soil map, lake and river shorelines, national forest inventory data, and statistical data on anthropogenic activities. Emission uncertainties were evaluated with Monte Carlo simulations. They summed the vertical fluxes of spatially explicit net emissions, disregarding the impact of lateral fluxes from terrestrial to aquatic ecosystems on the vertical fluxes.
Their model results showed that artificial surfaces were the most emission intensive land-cover class while lakes and rivers were about as emission intensive as arable land. Forests were the dominant land cover in the region (66%). The forest C sink decreased total emissions for the region by 72%. The region’s net emissions amounted to 4.37 ± 1.43 Tg CO2-eq yr-1, corresponding to a net emission intensity 0.16 Gg CO2-eq km-2 yr-1, and estimated per capita net emissions of 5.6 Mg CO2-eq yr-1. Using INCA-C and PERSiST, the amount of organic C leaching from mires, cropland, and forests to the watercourses was estimated to correspond to about 10% of the CO2 and CH4 emissions from land to air.
Although the landscape approach developed by Dr. Holmberg and colleagues opens opportunities to examine the sensitivities of important GHG fluxes to changes in land use and climate, management actions, and mitigation of anthropogenic emissions, there is still a need to extend the work to a fully integrated regional GHG budget, accounting for all lateral fluxes of C- and N-containing compounds.
Giamba Bussi and colleagues have published a new study of the effects that dams and climate change are having on sediment transport in the Mekong Delta. Credible predictions of sediment dynamics are essential for achieving the UN Sustainable Development Goals. The livelihoods of millions of people living in the world’s deltas are deeply interconnected with the sediment dynamics of these deltas. Sustainable inputs of fluvial sediments from upstream rivers are critical for ensuring the fertility of delta soils and for promoting sediment deposition that can offset rising sea levels. Yet, in many large river catchments this supply of sediment is being threatened by the planned construction of large dams. In this study, Dr. Bussi and colleagues apply the INCA hydrological and sediment model to the Mekong River catchment in South East Asia. Their aim was to assess the impact of several large dams (both existing and planned) on suspended sediment fluxes in the river. After calibrating to present day conditions, they forced the INCA model with future climate scenarios to assess the interplay of changing climate and sediment trapping caused by dam construction. Their results suggest that historical sediment flux declines have mostly been caused by dam construction and that sediment trapping will increase in the future if new, planed dams are constructed. If all dams that are currently planned for the next two decades are built, the model predicts a decline of suspended sediment flux of 50% (47–53% 90% confidence interval) compared to current levels (99 Mt/year at the delta apex), with potentially damaging consequences for local livelihoods and ecosystems.
Paul Whitehead and colleagues have published a new version of INCA. INCA-Metals, to simulate the impact of point source metal discharges (e.g., from tannery wastes or acid mine drainage) and diffuse rural runoff on riverine water quality. The model accounts for the key chemical reaction kinetic processes operating as well as sedimentation, resuspension, dilution, mixing and redistribution of pollutants in rivers downstream of discharge points. The model is dynamic and simulates the daily hydrology and behavior of eight metals, including cadmium, mercury, copper, zinc, lead, arsenic, manganese and chromium, as well as cyanide and ammonia. Like all members of the INCA family, the model is semi-distributed and can simulate catchment, tributary and instream river behavior. The apply the new model to predict impacts of the Savar tannery complex on the Dhaleshwari River system in Bangladesh on pollution levels in the river system and to evaluate a set of treatment scenarios for pollution control, particularly in the dry season. They show that the new efﬂuent treatment plant at Savar needs to signiﬁcantly improve its operation and treatment capability in order to alleviate metal pollution in the downstream Dhaleshwari River System and also protect the Meghna River System that discharges into the Bay of Bengal.
Paul Whitehead and colleagues have published a new study of microplastics in the Thames River, UK. This is an exciting paper for a number of reasons. It is one of the first realistic applications of a riverine water quality model to the problem of microplastic pollution and it is the first published paper using the INCA-Microplastics model with real data. This study also presents one of the first examples of an INCA model implemented using the open source MOBIUS framework.
Microplastic pollution of surface waters is an issue of increasing societal concern. Plastics and microplastics are ubiquitous in freshwater ecosystems. Understanding the transport and distribution of microplastics in river systems is key to assessing impacts. Modelling the main flow dynamics, mixing, sedimentation and resuspension processes is essential for an understanding of the transport processes. Professor Whitehead and colleagues applied INCA-Microplastics to the whole of the freshwater catchment of the River Thames, UK, to evaluate inputs, loads and concentrations along the river system. They calibrated the model against UK water industry measurements of microplastics in effluent discharges and sewage sludge. In their simulation, they showed significant increases in microplastic loads moving along the river system, with rising concentrations in downstream reaches and increasing deposition to the riverbed. The paper presents an assessment of potential impacts on aquatic ecosystems and a review of policy implications.
Jill Crossman and colleagues have just published a paper describing INCA-PEco, the Integrated Catchments model for Phosphorus Ecology. This new model is a major upgrade to the INCA-P model.
INCA-PEco integrates in-stream phosphorus (P), dissolved oxygen (DO), biological oxygen demand (BOD) and phytoplankton processes. The model simulates dissolved and particulate P transport and includes a new, more physically based streamflow submodel.
The team applied the new model to two eutrophied mesoscale catchments with differing climatic regime (continental vs. maritime) and phosphorus sources (point vs. diffuse). They used Generalised Sensitivity Analysis (GSA) to assess the effects of regional differences in climate, land use and P sources on parameter importance during calibration. In their analysis, they successfully reproduced in-stream total phosphorus (TP), suspended sediment, DO, BOD and chlorophyll-a (chl-a) concentrations across a range of temporal scales, land uses and climate regimes. While INCA-PEco is highly parameterized, they showed that model uncertainty, can be significantly reduced by focusing calibration and monitoring efforts on just 18 parameter, most of which are related to streamflow (i.e., base flow, Manning’s n and river depth). However, in catchments dominated by diffuse nutrient inputs, e.g., in agricultural areas, detailed data on crop growth and nutrient uptake rates are also important. The remaining parameters provide flexibility to the user, broaden model applicability, and maximize its functionality under a changing climate.
All model equations are exhaustively documented in the supplementary information.
Giamba Bussi and Paul Whitehead published a new study of the potential consequences of drought and low flows for power generation and river ecology. Power plants often use river waters for cooling purposes and can be sensitive to droughts and low flows. Water quality is also a concern, due to algal blooms and sediment loads that might clog filters.
They coupled INCA with a climate model to assess the possible impacts of droughts on river flow and water quality and the potential consequences for power plant operation, using the River Trent (UK) as a case study. Their results suggest a significant decrease in future flows and an increase in phosphorus concentrations, potentially enhancing algal production.
These findings show that power plant operators should expect more stress in the future due to reduced cooling water availability and decreasing upstream water quality. This issue might have serious consequences for energy security.
Jae-young Lee and colleagues have published a novel study of possible future trends in dissolved organic carbon (DOC) concentrations in a UK upland catchment.
Over the past several several decades, rising DOC concentrations have been seen in European lakes and rivers. A number of mechanisms have been proposed to explain these trends, including climate change and recovery from acidification. Drier summers and wetter winters are projected in the UK, and this may affect DOC levels. Lee and colleagues modelled DOC in the headwaters of the River Severn. They explored the effect of changing climate and acid deposition on surface water DOC concentrations, including the “enzymatic latch” effect in peatlands during droughts. They simulated recent (1995–2013) rising trends in DOC.
They used a novel approach to simulate possible future climate. The model was run with climatic scenarios generated using the weather@home2 climate modeling platform and EMEP sulfate deposition scenarios for 1975–2100. They showed that rising DOC trends are likely to continue in the near future (2020–2049) and stabilize in the far future (2070–2099). Seasonality will also change, with a post-drought DOC surge in autumn months.
Katri Rankinen and colleagues have published a study of the effectiveness of agri-environmental measures to reduce nitrogen (N) and phosphorus (P) loads to receiving waters in Finland.
In areas with intensive agriculture, excessive nutrient loading causes deterioration of receiving surface waters. A number of measures are used to reduce nutrient loads but there can be tradeoffs. While nitrate and particulate phosphorus load can be efficiently controlled by reducing tillage frequency and increasing vegetation cover, this often leads to increased loading of bioavailable phosphorus. In the latest phase of the EU Rural Programme, measures with the highest potential to reduce the nutrient loading to receiving waters were setting limits for fertilization of arable crops and retaining plant cover on fields with, e.g., no-till methods and uncultivated areas. Due to the latter two measures, the area of vegetation cover Finland has increased since 1995, suggesting clear effects on nutrient loading in the catchment scale as well.
In the new paper, Katri Rankinen and colleagues modeled the effectiveness of agri-environmental measures to reduce N and P loads to receiving waters. They showed that INCA-P was able to simulate both fast (immediate) and slow (non-immediate) processes that influence P loading from catchments. It was also evident that no-till methods had increased bioavailable P load to receiving waters, even though total P and total N loading were reduced.