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The soil water retention curve (SWRC) is a key soil property required for predicting basic hydrological processes. SWRC is often obtained in laboratory with non-harmonized methods. Moreover, procedures associated to each method are not standardized. This can induce a lack of reproducibility between laboratories using different methods and procedures or using the same methods with different procedures. The goal of this study was to estimate the inter/intralaboratory variability of the measurement of the wet part (from 10 to 300 hPa) of the SWRC. An interlaboratory comparison was conducted between 14 laboratories, using artificially constructed, porous and structured samples as references. The bulk densities of samples were different at the very beginning of the experiment. This resulted in a variability of retention properties between the samples, which was estimated by a linear mixed model with a "sample" random effect. Our estimate of inter/intralaboratory variability was therefore not affected by intrinsic differences between samples. The greatest portion of the differences in the measurement of SWRCs was due to interlaboratory variability. The intralaboratory variability was highly variable depending on the laboratory. Some laboratories successfully reproduced the same SWRC on the same sample, while others did not. The mean intralaboratory variability over all laboratories was smaller than the mean interlaboratory variability. A possible explanation for these results is that all laboratories used slightly different methods and procedures. We believe that this result may be of great importance regarding the quality of SWRC databases built by pooling SWRCs obtained in different laboratories. The quality of pedotransfer functions or maps that might be derived is probably hampered by this inter-/intralaboratory variability. The way forward is that measurement procedures of the SWRC need to be harmonized and standardized.

Accumulation of plastic litter in aquatic environments negatively impacts ecosystems and human livelihood. Urban areas are assumed to be the main source of plastic pollution in these environments because of high anthropogenic activity. Yet, the drivers of plastic emissions, abundance, and retention within these systems and subsequent transport to river systems are poorly understood. In this study, we demonstrate that urban water systems function as major contributors to river plastic pollution, and explore the potential driving factors contributing to the transport dynamics. Monthly visual counting of floating litter at six outlets of the Amsterdam water system results in an estimated 2.7 million items entering the closely connected IJ river annually, ranking it among the most polluting systems measured in the Netherlands and Europe. Subsequent analyses of environmental drivers (including rainfall, sunlight, wind speed, and tidal regimes) and litter flux showed very weak and insignificant correlations (r = $$-$$ - 0.19–0.16), implying additional investigation of potential drivers is required. High-frequency observations at various locations within the urban water system and advanced monitoring using novel technologies could be explored to harmonize and automate monitoring. Once litter type and abundance are well-defined with a clear origin, communication of the results with local communities and stakeholders could help co-develop solutions and stimulate behavioral change geared to reduce plastic pollution in urban environments.

Accumulation of plastic in aquatic environments negatively impacts ecosystems and human livelihood. Urban areas are assumed to the main source of plastic pollution in these environments, because of high anthropogenic activity. Yet, the drivers of plastic emissions, abundance and retention within these systems and subsequent transport to river systems is poorly understood. In this study, we demonstrate that urban water systems function as major contributors to river plastic pollution, and explore the potential driving factors contributing to the transport dynamics. Monthly visual counting of floating litter at six outlets of the Amsterdam water system results in an estimated 2.7 million items to enter the closely connected IJ river annually, ranking it among the most polluting systems measured in the Netherlands and Europe. Subsequent analyses of environmental drivers (including rainfall, sunlight, wind speed and tidal regimes) and litter flux showed no strong correlations (r = -0.19 - 0.16), implying additional investigation of potential drivers is required. High frequency observations at various locations within the urban water system and advanced monitoring using novel technologies could be explored to harmonize and automate monitoring. Once litter type and abundance are well-defined with a clear origin, communication of the results with local communities and stakeholders could help co-develop solutions and stimulate behavioural change geared to reduce plastic pollution in urban environments.

Cold regions are increasingly subjected to higher air temperatures, causing warming of permafrost and a deepening of the active layer. This activates hydrogeological groundwater flow and new groundwater pathways to emerge. Monitoring of the active layer depth occurs mainly with the use of temperature observations, but a more flexible and non-invasive method to study transient subsurface processes is with the use of Electrical Resistivity Tomography (ERT) observations. Automated time-laps ERT arrays are used to monitor the frozen ground evolution during various seasons, observing resistivity variations during freezing and thawing. Similarly, the leaching of meltwater into the ground under freezing/thawing conditions can be observed. Not only geophysical changes such as fluctuations in water content and water table, but also temperature variations affect the electrical resistivity field. In order to track the development of permafrost active-layer freeze-thaw fronts using ERT observations, it is thus essential that the effect of temperature on the resistivity is clearly defined at realistic scales representing field conditions. Our aim is to determine fluid resistivity at various stages during freezing and thawing and validate current temperature–resistivity relations for partly frozen soils.This study used a soil column (0.4 m diameter, 1 m heigh) equipped with 96 stainless steel electrodes placed at 8 horizontal rings of 12 electrodes each at various heights around the circumference of the column alongside with temperature sensors. The column was fully insulated on the sides and top except for the bottom, creating a 1D heat transfer system. The soil column was filled with quartzite sand with a D50 of 350 (μm) and organic matter content of 5 (wgt %). The experimental setup was placed within a climate chamber where the column was frozen to -4 °C and thawed to 3 °C over a 3-month period. During the freezing and thawing phase, a full 3D resistivity image was collected using the ERT at a weekly interval. Initial results show that the setup is capable of simulating permafrost freezing and thawing dynamics and ongoing work focuses on the relation between the temperature and time lapse ERT resistivity observations.

The processes controlling the transport in tidal rivers and estuaries, the interface between fluvial and marine systems, remain largely unresolved. For this reason, current estimates of riverine plastic pollution and export into the ocean remain highly uncertain. Hydrodynamics in tidal rivers and estuaries are influenced by tides and freshwater discharge. As a consequence, flow velocity direction and magnitude can change diurnally. In turn, this impacts the transport dynamics of solutes and pollutants, including plastics. Plastic transport dynamics in tidal rivers and estuaries remain understudied, yet the few available observations suggest that plastics can be retained here for long time periods, especially during periods of low net discharge. Additional factors such as riparian vegetation and riverbank characteristics, in combination with bidirectional flows and varying water levels, can lead to even higher likelihood of long-term retention.Here, we provide a first observation-based estimation of net plastic transport on daily time scales in tidal rivers. For this purpose, we developed a simple Eulerian approach using sub-hourly observations of floating plastic transport and discharge during full tidal cycles. We applied our method to the Saigon river, Vietnam, throughout six full tidal cycles in May 2022.We show that the net plastic transport is about 27-32% of the total plastic transport. We found that plastic transport and river discharge are positively and significantly correlated (Pearson's r = 0.87, R2= 0.75). The net plastic transport is higher than the net discharge (27-32% and 18%, respectively), suggesting that plastic transport is governed by other factors than water flow. Such factors include wind, plastic concentrations in the water, and entrapment of plastics downstream of the measurement site. The net plastic transport rates per tidal cycle alternate between positive (seaward) net transport and negative (landward) net transport, as a result of the diurnal inequality in the tidal cycles. We found that soft and neutrally buoyant items had considerably lower net transport rates than rigid and highly buoyant items (11-17% vs 31-39%), suggesting the retention time strongly depends on item characteristics.Our results demonstrate the crucial role of tidal dynamics and bidirectional flows in net plastic transport. We emphasize the importance of understanding fundamental transport dynamics in tidal rivers and estuaries to ultimately reduce the uncertainties of plastic emission estimates into the ocean.

Rivers transport, and store a large share of the global plastic pollution. Riverbanks are one of the river compartments where macroplastic litter is deposited and retained. Different factors influence macroplastic deposition on riverbanks. Retention related factors such as riverbank features, and supply related factors, such as hydrometeorology or land-use. Riverbank macrolitter along the Dutch Meuse has been quantified, characterized, and removed biannually since 2017. At each monitored riverbank, macroplastic and other litter items were collected along a 100 m section and classified in over 100 specific litter categories. We assume that after each monitoring round all litter is removed, and that the litter sampled in the following round has accumulated in the time between rounds. This monitoring dataset is analyzed to identify riverbanks with plastic accumulation rates continuously below or above average, and the specific characteristics of these identified riverbanks. Furthermore, correlations are investigated between macroplastic deposition and individual riverbank features and river morphology, such as types of riparian vegetation, or curvature of the river. These correlations are tested for the total amount of plastic litter, but also categories grouped by plastic characteristics such as potential source, density, size, or flexibility. This is done based on the hypothesis that plastic litter items with different characteristics are associated to different processes of plastic emission and deposition. For example, items with low or high density, or different levels of flexibility. Items with low and high densities are transported differently, because their density is lower or higher than the density of water. Items with a high level of flexibility, such as soft plastic foils, have a higher potential for entanglement in vegetation, and a lower potential for remobilization, compared to items with a low level of flexibility. The aim of this study is to identify riverbank characteristics that explain high plastic accumulation rates.

A solid understanding of the global water cycle and how land surface processes respond to both changes in climate and pressure due to water use is essential for society. Although Land Surface Models (LSM) and Global Hydrological Models (GHM) are able to simulate the spatiotemporal variability of the water balance relatively reliably, intercomparison studies have indicated considerable differences between the models. Each LSM and GHM present a unique set of equations, parameters and configurations that contribute to the spread of simulated hydrological responses to meteorological forcings. In order to improve our understanding of modeling uncertainties, we propose a variable importance assessment for 5 LSM/GHM (JULES, HTESSEL, PCR-GLOBWB, SURFEX and ORCHIDEE) from the EartH2Observe (E2O) project. The output of the models and the meteorological forcings were collected from the Water Resources Reanalysis Tier 2 of the E2O project, which consists of a global dataset with spatial resolution of 0.25ox0.25o. We used soil texture and land cover datasets that most resemble the inputs used by each LSM/GHM during the E2O project. The models’ outputs were used to estimate 6 hydrological indices for every land cell: Evaporation-Precipitation ratio; Runoff-Precipitation ratio; Surface Runoff-Total Runoff ratio; median Soil Moisture variation caused by a Rainfall event; median Surface Runoff caused by a Rainfall event; and Soil Moisture temporal autocorrelation. Then, we evaluate the input features (meteorological, land cover, and soil texture) importance to the hydrological indices of each model using machine learning. With the analysis we aim to examine a) How much the models differ and why? b) To what extent are the output differences related to the input features or/and to the models formulation? and c) How significant is each feature to the respective hydrological index?

Plastic is an emerging pollutant, and the quantities in rivers and oceans are expected to increase. Rivers are assumed to transport land-based plastic into the ocean, and the fluvial and marine transport processes have been relatively well studied to date. However, the processes controlling the transport in tidal rivers and estuaries, the interface between fluvial and marine systems, remain largely unresolved. For this reason, current estimates of riverine plastic pollution and export into the ocean remain highly uncertain. Hydrodynamics in tidal rivers and estuaries are influenced by tides and freshwater discharge. As a consequence, flow velocity direction and magnitude can change diurnally. In turn, this impacts the transport dynamics of solutes and pollutants, including plastics. Plastic transport dynamics in tidal rivers and estuaries remain understudied, yet the available observations suggest that plastics can be retained here for long time periods, especially during periods of low net discharge. Additional factors such as riparian vegetation and riverbank characteristics, in combination with bidirectional flows and varying water levels, can lead to even higher likelihood of long-term retention. Here, we provide a first observation-based estimate of net plastic transport on a daily time scale in tidal rivers. For this purpose, we developed a simple Eulerian approach using sub-hourly observations of plastic transport and discharge during full tidal cycles. We applied our method to the highly polluted Saigon river, Vietnam, throughout six full tidal cycles in May 2022. We show that the net plastic transport is about 27–32 % of the total plastic transport. We found that plastic transport and river discharge are positively and significantly correlated (Pearson's r = 0.87, R2 = 0.75). The net transport of plastic is higher than the net discharge (27–32 % and 18 %, respectively), suggesting that plastic transport is governed by other factors than water flow. Such factors include wind, varying plastic concentrations in the water, and entrapment of plastics downstream of the measurement site. The plastic net transport rates alternate between positive (seaward) net transport and negative (landward) net transport, as a result of the diurnal inequality in the tidal cycles. We found that soft and neutrally buoyant items had considerably lower net transport rates than rigid and highly buoyant items (11–17 % vs 31–39 %), suggesting the retention time strongly depends on item characteristics. Our results demonstrate the crucial role of tidal dynamics and bidirectional flows in net plastic transport. With this paper we emphasize the importance of understanding fundamental transport dynamics in tidal rivers and estuaries to ultimately reduce the uncertainties of plastic emission estimates into the ocean.

Long-term conventional tillage leads to soil compaction and formation of a plough layer, which affects soil physical properties, transport of water, and growth of crop roots toward deeper soil, resulting in soil degradation and a decline in crop productivity. Long-term sub-soiling tillage has proven to be an effective measure for remediating the plough layer and improving the structure and physical properties of the soil. In this study, we experimentally investigated the effects of long-term sub-soiling tillage in an arid region of Henan Province, China, along a deep soil (0–100 cm) profile over 8 years of sub-soiling tillage at a depth of 30 cm and compared the results against conventional tillage at a depth of 15 cm. We measured soil pore distributions of macropores (> 1 mm in diameter), mesopores (0.16–1.0 mm), and total pores (> 0.16 mm) measured by X-ray computed tomography (CT), soil total porosity (ϕ) and > 0.16 mm equivalent porosity measured by conventional methods, soil bulk density (ρs), soil organic carbon content (SOC), the proportion of macroaggregates (> 0.25 mm) (PMA), soil field moisture capacity (fc), available moisture content, and saturated hydraulic conductivity (Ksat). The results indicate that long-term sub-soiling tillage increased soil pore numbers at 0–35 cm depth (macropores, mesopores, and total pores), improved pore shape, and significantly increased porosity at 0–20 cm depth (macropores, mesopores, and total pores; p < 0.05) compared to conventional tillage. In addition, ϕ and > 0.16 mm equivalent porosity were increased by 10.4 and 87.1% at depths of 0–60 cm under sub-soiling tillage, respectively. SOC (0–55 cm depth), fc (0–45 cm depth), available moisture content (0–40 cm depth), Ksat (0–40 cm depth), and PMA (0–50 cm depth) were increased by 16.7, 14.3, 23.8, 471.5, and 98.3%, respectively, and ρs (0–60 cm depth) was reduced by 8.6%. Observed correlations between SOC, soil pore parameters, and soil physical properties suggest that soil pore parameters and soil physical properties can be improved by increasing SOC. These correlations are stronger under sub-soiling than that under conventional tillage. Therefore, sub-soiling is an effective technique for improving soil pore characteristics and physical properties while preventing soil degradation.

Water hyacinths are considered one the world’s most invasive aquatic species and are found in most tropical rivers. Hyacinths can form dense patches of several meters of length and width at the water surface and drift due to the combined action of wind and flow velocity. In rivers, hyacinth patches can function as carriers for floating macroplastic debris from rivers into the ocean. In the Saigon river, Vietnam, water hyacinths were found to accumulate a majority of the total floating macroplastic items (Schreyers et al., 2021). Despite their crucial role in macroplastic accumulation and dispersion, precise quantification of both hyacinth coverage and macroplastic concentrations in rivers are currently lacking. We present insights on the accumulation of macroplastics within hyacinth patches based on the analysis of more than 3,000 Unmanned Aerial Vehicle images collected at the Saigon river in 2021. In particular, we explore the relation between hyacinth coverage, patch abundance and floating macroplastic concentrations, and how these vary through time and space. These findings clearly illustrate the complexity of plastic transport in rivers by highlighting its spatiotemporal variability. Our insights can be used for combined clean-up efforts and reduction strategies of both hyacinths and plastic debris in the Saigon river, and support the development of future plastic monitoring strategies in other tropical river systems. ReferencesSchreyers, L., van Emmerik, T., Luan Nguyen, T., Castrop, E., Phung, N.-A., Kieu-Le, T.-C., Strady, E., Biermann, L., van der Ploeg, M. (2021). Plastic plants: Water hyacinths as driver of plastic transport in tropical rivers. Frontiers in Environmental Science 10.3389/fenvs.2021.686334

Cold-regions contain a vast pool of organic carbon in permafrost, which is currently immobilized. As the global air temperatures rise, permafrost active layer depths are increasing. The deepening of the active layer reactivates groundwater transport processes, leading to the release of solutes such as dissolved carbon to streams and the atmosphere. In order to make predictions of the rates of permafrost thaw based upon numerical modeling, we need accurate data on active layer thermal properties.Active layer thermal properties, thermal conductivity and heat capacity, are strongly coupled to geological properties such as water content, and organic matter content and are therefore highly heterogenous in natural systems. Furthermore, the effective thermal properties vary as a function of temperature through ice-content, especially across the freeze-thaw interval near 0 oC. Direct in-situ observations of active-layer thermal properties are rare because in-situ measurements involves sampling of frozen samples and analysis in a laboratory.This study uses soil column (1 m high x 0.31 m diameter) experiments to investigate the relation between soil physical properties and thermal properties. A total of nine samples were synthesized using a range of grain sizes and organic matter contents, and were fully saturated with water. The columns were insulated on the sides and top, aiming to create a fully 1D thermal system allowing only vertical heat transport. The columns are subjected to one freeze-thaw cycle, lasting about 20 weeks. Resulting temperature observations were analyzed using a numerical heat transfer model. By fitting the temperature observations to the heat transfer model, thermal properties can be inferred. Initial data shows differences in heat propagation through the soil column, indicating differences in thermal conductivity and heat capacity as a result of varying soil grain size and organic matter content. This research will help to link permafrost soil physical properties to thermal properties, and increase understanding at the dynamic freeze-thaw interval.

Current land surface models hold large uncertainties in the predictions of how key biosphere processes such as photosynthesis, respiration and transpiration will respond to the combined effects of rising atmospheric CO2, nutrient enrichment and changes in water availability. Recent developments in optimality theory provide new approaches to explicitly predict coordinated changes in leaf photosynthetic traits, specifically stomatal conductance (gs) and the maximum capacities of carboxylation (Vcmax) and electron transport (Jmax) (e.g. Prentice et al., 2014; Smith et al., 2019; Harrison et al., 2021). These novel formulations show promising results when tested with meta-analyses and global data sets. However, support from manipulative experiments that include changes in CO2-growth conditions remains scarce. Here we summarize the results from two manipulative experiments using walk-in growth chambers in which a variety of species were exposed to sub-ambient, ambient and elevated growth CO2 in combination with either a Phosphorous (P) treatment or a drought treatment, and compare the experimental results with predictions from optimality theory. The P treatment exposed plants to either severe P limitation at an N:P ratio of 45:1 or severe Nitrogen (N) limitation at an N:P ratio of 1:1, with a similar supply rate of N. The drought treatment consisted of a continuous dry-down after an initial period of unstressed establishment and growth. Results of the combined CO2-nutrient treatment showed significant effects of growth CO2 and P supply on Vcmax and Jmax, as well as the whole-plant biomass at the point of harvest. Interaction effects between growth CO2 and P supply were observed for gs, the light-saturated photosynthesis rate, leaf P content, and the N:P ratio of the leaf. Results of the combined CO2-drought experiment showed that gs, Vcmax and Jmax decreased significantly under rising CO2 treatments, whereas whole-plant biomass at the point of harvest increased significantly. When scaled with non-stressed conditions, gs and light-saturated photosynthesis declined consistently across CO2 treatments. These experimental results align with quantitative predictions of gs, Vcmax and Jmax based on optimality theory. However, additional formulations are required to predict whole-plants growth responses as well as changes in plant nutrient-stoichiometry. ReferencesHarrison SP, Cramer W, Franklin O, Prentice IC, Wang H, Brännström Å, de Boer H, Dieckmann U, Joshi J, Keenan TF, et al. 2021. Eco-evolutionary optimality as a means to improve vegetation and land-surface models. New Phytologist 231: 2125–2141.Prentice IC, Dong N, Gleason SM, Maire V, Wright IJ. 2014. Balancing the costs of carbon gain and water transport: testing a new theoretical framework for plant functional ecology. Ecology Letters 17: 82–91.Smith NG, Keenan TF, Prentice IC, Wang H, Wright IJ, Niinemets Ü, Crous KY, Domingues TF, Guerrieri R, Ishida FY, et al. 2019. Global photosynthetic capacity is optimized to the environment. Ecology Letters 22: 506–517.

The eco-evolutionary optimality principle, which states that natural selection rapidly eliminates uncompetitive combinations of traits, has proven to be a powerful source of testable hypotheses and predicting patterns in vegetation structure and composition. In this context, Prentice et al. (2014) proposed an optimality framework for plant functional ecology, which predicts relationships between parameters of photosynthetic biochemistry and stomatal conductance (gs). Leaf morphology plays an essential role herein, as shown by the conservative gs/gsmax ratio (McElwain et al., 2016) and the strong correlation between maximum photosynthesis rate and leaf hydraulic traits (Brodribb et al., 2007). The aim of this research is to determine how such leaf morphological adaptations relate to adaptations of photosynthetic traits, mainly gs/gsmax and Vcmax, over different timescales. Here we present empirical data to test predicted effects of changing CO2 concentrations on Vcmax, Ci/Ca, Jmax, gs, and leaf morphology, according to the optimality framework.The effects were tested in two genotypes of Solanum dulcamara (bittersweet) that were grown from seeds to maturity under 200, 400 and 800 ppm CO2 in walk-in growth chambers with tight control on light, temperature and humidity. The genotypes were grown from two distinct natural populations; one adapted to well-drained sandy soil (the 'dry' genotype) and one adapted to poorly-drained clayey soil (the 'wet' genotype). Measurements of photosynthetic traits were obtained with a portable photosynthesis system. Morphological and developmental leaf traits were measured on microscopy images, after plant maturation.The results show that the optimality framework is suitable to predict changes in the photosynthetic traits under changing atmospheric CO2 concentrations. With higher concentrations, the Vcmax decreased in both S. dulcamara genotypes. Also, at each CO2 growth level, the dry genotype showed a higher Huber value and a lower Vcmax than the wet genotype, indicating that the ‘dry’ genotype combines a relatively high cost of transpiration with a low cost of photosynthesis, and the ‘wet’ genotype vice versa. The down-regulation of Vcmax under high CO2 was strongest in the dry genotype, and the downregulation of gs the strongest in the wet genotype, in line with the predicted trade-off between the costs of transpiration and photosynthesis.The two leaf morphological traits with the clearest CO2 response were leaf vein density and guard cell length, which were also strongly correlated. Interestingly, stomatal density showed no CO2 response in this species, but is correlated to the guard cell length. Overall, our empirical data support the optimality responses in photosynthetic traits and gs, however, leaf morphological responses appear less consistent with the theory. More research, including experiments over a longer timescale will provide more insight in these relationships.

Recent studies show that submarine groundwater discharge (SGD) often equals or exceeds riverine inputs into marine environments. Pollution or extraction of groundwater may affect submarine groundwater discharge quality and quantity, impacting marine ecosystems. Most research focuses on relatively humid environments where large amounts of SGD can be expected and detected.However, SGD has been poorly studied on smaller (semi-)arid islands, where SGD is relatively hard to detect and quantify. We aim to shine a light on the hydrogeological link between terrestrial processes and coral reef health in the semi-arid Caribbean island Curaçao.It is hypothesized that the coral reef around the island is impacted by pollutants from tourism and agriculture. Previous hydrogeological measurements suggest the presence of groundwater fluxes towards the ocean through the karstic geology. However, quantitative data are lacking.Groundwater level and quality measurements were conducted at study locations in the various geological settings of the island. Soil infiltration measurements were performed to assess the infiltration capacity of different soil types across the island. Rainfall and groundwater level fluctuations were monitored and used to determine the hydrogeological response after rainfall events. Geophysical ERT surveys have been conducted on different geomorphological settings to assess the hydrogeology and detect preferential flow paths in the karstic geology.The field measurements will serve as input for a coupled groundwater-surface hydrology model of Curaçao in MODFLOW. The model outcomes will be used to guide field measurements in the future. These will include tracer tests, surface runoff measurements, marine Radon measurements and offshore geophysics.This study is part of the interdisciplinary SEALINK research project, comprising nine PhD projects at different Dutch universities and research institutes.

The majority of mismanaged plastic waste does not reach the oceans, and rather accumulates in terrestrial and freshwater environments. Since 2017, riverbanks along the Dutch part of the river Meuse have been monitored by volunteers in spring and fall. At each monitored riverbank macroplastic and other litter items were collected along a 100 m section and classified in over 100 specific item categories. In July 2021, the Meuse was hit by a severe flood event with an estimated return period between 100 - > 1000 years, similar to other rivers in Germany, France, Belgium, and the Netherlands. Flood conditions can highly increase plastic (re)mobilization and transport within river systems, and plastic discharge into the oceans. However, the impact of a severe flood event on plastic litter accumulation on riverbanks, to the authors knowledge, was never measured before. Within three weeks after the flood event we counted and classified macroplastic and other litter items on 25 riverbanks along the Meuse, from the Dutch-Belgian border to the river mouth. The additional sampling allows us to, for the first time, assess the impact of such a flood event on plastic accumulation on riverbanks. In this presentation we compare plastic accumulation on riverbanks after this flood event to plastic accumulation during normal conditions. We compare the amounts and types of litter, and possible litter sources. This study aims to contribute to better understand mobilization, transport, and accumulation dynamics of plastics in river systems, and the role and impact of extreme events on plastic accumulation on riverbanks.

Aquitard hydraulic properties are notoriously difficult to assess, yet accurate aquitard hydraulic conductivity estimates are critical to quantify recharge and discharge to and from semi-confined aquifer systems via hydraulic head gradients. Such flux quantification is required to evaluate the risks of aquifer exploitation by groundwater abstraction and aquifer vulnerability to surface contamination. In this study, we consider a regionally important aquitard and compare existing hydraulic conductivity estimates obtained through traditional methods to those inferred from long-term hydraulic head monitoring and thermally-derived vertical groundwater fluxes (0.04--0.25 m/y). We estimate the fluxes using numerical modeling to analyse the propagation of decadal climate signals into temperature-depth profiles and fitting the simulated and observed inflection point depths (minimum temperature). Results reveal that climate-disturbed temperature-depth profiles paired with multi-level head data can yield accurate vertical fluxes and aquitard hydraulic conductivities. This approach for characterizing groundwater systems and quantifying flows to and from sedimentary aquifers is more efficient but yields results that are comparable to conventional methods.

Longitudinal dams (LD) are novel engineering structures built parallel to the river channel that support sustainable river management. The recent replacement of groynes by longitudinal dams in low-land rivers such as the Waal has been successful in restoring the ecological river functions while simultaneously achieving its navigation, recreation, and flood-protection functions. However, the impact of the LD on the riverbanks is still unknown despite recent investigations on the flow dynamics in the side channel behind it. We fill this knowledge gap by investigating initial bank responses and quantifying changes in sediment dynamics over five years since the completion of the LD in the Waal at Wamel. We rely on available annual high-resolution LiDAR-derived DTMs, orthophotos, and in situ measurements to estimate erosion and deposition rates and their changes over the study period. A two-stage initial response is revealed with the largest bank erosion (~140 x 103 m3/yr) and deposition (~20 x 103 m3/yr) confined in the first year after installation, as the banks adjust to a new hydrogeomorphic equilibrium. This is followed by successively lower rates of surface-level changes (3 m3/yr eroded and 3 m3/yr deposited) as a response to the hydrogeomorphic dynamics in the new system. The overbank deposits from recent floods have a similar distribution with those prior to LD construction based on the DTMs. However, higher volumes of sandy deposits are found post- compared to pre-LD construction for floods of similar magnitude and duration. This increase is caused by the additional contribution of the bank sediments that have been made available through the removal of groynes. Although eroding banks may be a threat to infrastructure and navigability, they have a positive effect on restoring ecological diversity and floodplain connectivity.

Sand dunes sediments are a commonly used archive for palaeoenvironmental reconstruction, with chronologies for their accumulation rates, and migration rates, used in a large number of palaeoenvironmental reconstructions across global sand-rich drylands. A less common use of sand dunes as an archive is to explore the chemical and isotopic composition of the pore moisture stored within the sand. Sand dunes, constitute the uppermost unit above dryland aquifers, and represent part of the unsaturated (or vadose) zone in terms of hydrogeology. Chloride is a chemical tracer within the vadose zone that is commonly used to understand, and quantify rates of, recharge to the groundwater table, using a chloride mass balance (CMB) approach (e.g. Scanlon et al., 2006). In doing so, any variations in the concentration of pore-moisture chloride between discrete depths in the sand profile can also be used to provide a novel archive for tracking changes in palaeomoisture availability and land-use change (see review in Stone and Edmunds, 2016). This approach is known as a ‘hydrostratigraphy’.This presentation will explore the utility of the CMB hydrostatigraphy approach for Kalahari linear dunes above the Stampriet Basin, which is a transboundary aquifer within southern Africa. This is a region for which palaeoenvironmental proxies for rainfall are extremely scarce, owing to poor preservation of organic-rich material in this oxygen-rich environment. Three repeat field visits for sampling the dunes (2011, 2013 and 2016) were used in the research design in order to explore the repeatability of this CMB hydrostratigraphy approach at this location. In addition, a transect of dunes, including dunes close to a pan, were sampled. It was hypothesised that those dunes in close proximity to the pan would be unsuitable, owing to the possible presence of Cl-rich evaporites and capillary zone influences on the behaviour of moisture in the sand-rich sediment. The trends in these profiles will be presented, along with attempts to understand the moisture pathway behaviour in these dune sediments. ReferencesScanlon, B.R., Mukerhjee, A., Gates, J., Reedy, R., Sinha, A.K., 2010. Groundwater recharge in natural dune systems and agricultural ecosystems in the Thar Desert region, Rajasthan, India. Hydrogeology Journal 18, 959–972.Stone, A. E. C., Edmunds, W. M. (2016) Unsaturated zone hydrostratigraphies: A novel archive of past climates in dryland continental regions. Earth-Science Reviews 157, 121-144.

Land degradation reduces soil functioning and, consequently, the services that soil provides. Soil hydrological functions are critical to combat soil degradation and promote soil restoration. Soil microorganisms affect soil hydrology, but the role of soil microbiota in forming and sustaining soil is not well explored. Case studies indicate the potential of soil microorganisms as game-changers in restoring soil functions. We review the state of the art of microorganism use in land restoration technology, the groups of microorganisms with the greatest potential for soil restoration, knowledge of the effect of microorganisms on soil physical properties, and proposed strategies for the long-term restoration of degraded lands. We also emphasize the need to advance the emerging research field of biophysical landscape interactions to support soil-plant ecosystem restoration practices.

Plant transpiration accounts for about half of all terrestrial evaporation (Jasechko et al., 2013). Plants need water for many vital functions including nutrient uptake, growth, maintenance of cell turgor pressure and leaf cooling. Due to the regulation of water transport by stomata in the leaves, plants lose 97% of the water they take via their roots, to the atmosphere. They can be viewed as transpiration-powered pumps on the interface between the soil and atmosphere.Measuring plant-water dynamics is essential to gain better insight into their role in the terrestrial water cycle and plant productivity. It can be measured at different levels of integration, from the single cell micro-scale to the ecosystem macro-scale, on time scales from minutes to months. In this contribution, we give an overview of state-of-the-art techniques for transpiration measurement and highlight several promising innovations for monitoring plant-water relations. Some of the techniques we will cover include stomata imaging by microscopy, gas exchange for stomatal conductance and transpiration monitoring, thermometry for water stress detection, sap flow monitoring, hyperspectral imaging, ultrasound spectroscopy, accelerometry, scintillometry and satellite-remote sensing.Outlook: To fully assess water transport within the soil-plant-atmosphere continuum, a variety of techniques is required to monitor environmental variables in combination with biological responses at different scales. Yet this is not sufficient: to truly solve for spatial heterogeneity as well as temporal variability, dense network sampling is needed.In PLANTENNA (https://www.4tu.nl/plantenna/en/) a team of electronics, precision and microsystems engineers together with plant and environmental scientists develop and implement innovative (3D-)sensor networks that measure plant and environmental parameters at high resolution and low cost. Our main challenge for in-situ sensor autonomy (“plug and forget”) is energy: we want the sensor nodes to be hyper-efficient and rely fully on (miniaturised) energy-harvesting.REFERENCES: Jasechko, S., Sharp, Z. D., Gibson, J. J., Birks, S. J., Yi, Y., & Fawcett, P. J. (2013). Terrestrial water fluxes dominated by transpiration. Nature, 496(7445), 347-350.Plantenna: "Internet of Plants". (n.d.). https://www.4tu.nl/plantenna/en/

Permafrost has become increasingly unstable as a result of surface warming; therefore it is crucial to improve our understanding of permafrost spatiotemporal dynamics to assess the impact of active layer thickening on future hydrogeological processes. However, direct determinations of permafrost active-layer thermal properties are few, resulting in large uncertainty in forecasts of active layer thickness. To assess how to reduce the uncertainty without expanding monitoring efforts, a total of 1,728 numerical 1D models were compared using three error measures against observed active layer temperature data from the Qinghai-Tibetan Plateau. Resulting optimized parameter values varied depending on the error measure used, but agree with reported ones: bulk volumetric heat capacity is 1.82–1.94 (Formula presented.) K, bulk thermal conductivity 1.0–1.2 W/m K and porosity 0.25–0.45 (Formula presented.). The active layer thickening rate varied significantly for the three error measures, as demonstrated by a (Formula presented.) years thawing time-lag between the error measures over a 100 years modeling period.

Permafrost has become thermally instable as a result of surface warming, which has an uncertain impact on future hydrogeological conditions and the associated mobilisation of carbon and release into the atmosphere. Numerical modelling can provide insights into future permafrost spatial and temporal dynamics. However, crucial observational data of permafrost active-layer thermal properties; thermal conductivity and heat capacity are sparse, resulting in a large uncertainty in forecasts of the future development of the active layer. Therefore, our study aims to develop a methodology to numerically determine the permafrost thermal and soil properties from observations of temperature time-series in the subsurface, in order to reduce the current model uncertainty.We used an ensemble of 786 numerical 1D permafrost models fitted against observed active layer temperature data from the Qinghai-Tibetan Plateau (QTP)1 to find the optimal values for the soil thermal conductivity, heat capacity and porosity. Optimal parameter values are determined by finding the minimum RMSE, KGE and using the Russell error measure. We find optimized values for bulk volumetric heat capacity 1.3-1.85 106J/m3°C , bulk thermal conductivity 0.9-1.1 W/m°C and porosity between 0.25-0.35 (-), which are in agreement with typical ranges reported in literature for similar settings on the QTP. In a further sensitivity study, the 3 optimal parameter combinations were used to model the active layer thickness over a 100-year period with a gradual hypothetical air temperature increase of 5°C. The results indicate a substantial difference in rate of thawing and increase in depth of the active layer for these models, with a maximum time-lag of roughly 15 years in before the models reach the same active layer thawing depth. The study shows how numerical models can be applied to determine active layer thermal properties without the need for field samples, opening up new possibility for in-situ permafrost temperature observation.1. Luo, D. L., Jin, H. J., He, R. X., Wang, X. F., Muskett, R. R., Marchenko, S. S., & Romanovsky, V. E. (2018). Characteristics of water-heat exchanges and inconsistent surface temperature changes at an elevational permafrost site on the Qinghai-Tibet Plateau. Journal of Geophysical Research: Atmospheres, 123, 10,057–10,075. https://doi.org/10.1029/2018JD028298

Our recent field-based study undertaken at the Saigon river, Vietnam, shows that water hyacinths are responsible for entraining and transporting a majority of floating macroplastic litter. These invasive, free-floating water plants can form patches of several meters in length and width and tend to aggregate large amounts of plastic litter. Over the course of a six-week study, we demonstrated that 78% of the floating macroplastic observed were carried downstream accumulated within these floating plant patches.The strong seasonality of water hyacinths, coupled with the temporal variability in macroplastic flux, calls for a longer monitoring effort. To this end, a one-year monitoring campaign is currently being undertaken at the Saigon river, which will apply satellite imagery, drone, camera imagery analysis and visual counting from bridges. Combined, these methods can help to characterize the contribution of hyacinths to macroplastic transport and accumulation at different temporal (from hours/days to weeks/months) and spatial (from sample sites to the river system) scales.We evaluate the selected monitoring techniques, and present the preliminary results of this large-scale monitoring effort. We provide the first scientific overview of the contribution of water hyacinths in plastic transport relative to the total plastic transport, and its spatiotemporal variability. In addition, we assess the monitoring techniques used and provide suggestions for similar long-term monitoring strategies.

Soil erosion by gullies in Ethiopia is causing environmental and socioeconomic problems. A sound soil and water management plan requires accurately predicted gully erosion hotspot areas. Hence, this study develops a gully erosion susceptibility map (GESM) using frequency ratio (FR) and random forest (RF) algorithms. A total of 56 gullies were surveyed, and their extents were derived by digitizing Google Earth imagery. Literature review and a multicollinearity test resulted in 14 environmental variables for the final analysis. Model prediction potential was evaluated using the area under the curve (AUC) method. Results showed that the best prediction accuracy using the FR and RF models was obtained by using the top four most important gully predictor factors: drainage density, elevation, land use, and groundwater table. The notion that the groundwater table is one of the most important gully predictor factors in Ethiopia is a novel and significant quantifiable finding and is critical to the design of effective watershed management plans. Results from separate variable importance analyses showed land cover for Nitisols and drainage density for Vertisols as leading factors determining gully locations. Factors such as texture, stream power index, convergence index, slope length, and plan and profile curvatures were found to have little significance for gully formation in the studied catchment.

International audience; River plastic pollution is an environmental challenge of growing concern. However, there are still many unknowns related to the principal drivers of river plastic transport. Floating aquatic vegetation, such as water hyacinths, have been found to aggregate and carry large amounts of plastic debris in tropical river systems. Monitoring the entrapment of plastics in hyacinths is therefore crucial to answer the relevant scientific and societal questions. Longterm monitoring efforts are yet to be designed and implemented at large scale and various field measuring techniques can be applied. Here, we present a field guide on available methods that can be upscaled in space and time, to characterize macroplastic entrapment within floating vegetation. Five measurement techniques commonly used in plastic and vegetation monitoring were applied to the Saigon river, Vietnam. These included physical sampling, Unmanned Aerial Vehicle imagery, bridge imagery, visual counting, and satellite imagery. We compare these techniques based on their suitability to derive metrics of interest, their relevancy at different spatiotemporal scales and their benefits and drawbacks. This field guide can be used by practitioners and researchers to design future monitoring campaigns and to assess the suitability of each method to investigate specific aspects of macroplastic and floating vegetation interactions.

Super absorbent polymer (SAP) and organic manure (OM) may improve soil structure and change soil organic carbon (SOC) composition and agroecosystem functioning. However, the understanding of the effects of SAP and OM on SOC composition, specifically in deeper soil layers, is still not clear. The objectives of this study were to examine the effects of long-term application of SAP and OM (8 years) on changes in SOC and soil structure down to a soil depth of 100 cm. Therefore, in order to investigate the stability of soil structure and the distribution of organic carbon at different soil depths (0-10 cm, 10-20 cm,…, 90-100 cm) under long-term application of SAP, OM, and a control treatment, soil structure and soil organic carbon content were analyzed in mixed soil samples and undisturbed soil samples. The results indicated that with depth, the proportion of large aggregates (0.5-2.0 mm) decreased gradually, while the proportion of small aggregates (0.5 mm soil aggregates in the 0-30 cm and 40-60 cm soil layers (P < 0.05) and 0.25-0.5 mm in the 0-50 cm soil layer (P < 0.05), and while the OM treatment had the same effect in the 0-30 cm soil layer (P < 0.05). The total organic carbon content (TOC) and labile organic carbon content (LOC) of bulk soil increased (0-20 cm) initially with depth, and then decreased (20-70 cm) approximately. In the 0-50 cm soil layer, the TOC and LOC under SAP treatment were higher than those under OM treatment. The SAP treatment was more beneficial to the increase of the TOC and LOC of 0.5-2.0 mm and 0.25-0.5 mm aggregates in the 10-40 cm soil layer compared with the control and OM treatment (P < 0.05). The SAP treatment was also more beneficial in increasing the contribution rate of organic carbon (CROC) in> 0.5 mm aggregates in 0-40 cm soil depth, while the OM treatment was more beneficial in increasing the CROC of > 0.5 mm aggregates in 0-30 cm soil depth. The SAP treatment improved the stability of the soil structure in 0-30 cm and 40-60 cm depths, and the OM treatment had the same effect in the 0-30 cm depth. Compared with the control and OM treatments, SAP treatment has shown to be the most beneficial in improving soil structure and increasing organic carbon content.

Accurate estimates of root zone soil moisture (RZSM) at relevant spatio-temporal scales are essential for many agricultural and hydrological applications. Applications of machine learning (ML) techniques to estimate root zone soil moisture are limited compared to commonly used process-based models based on flow and transport equations in the vadose zone. However, data-driven ML techniques present unique opportunities to develop quantitative models without having assumptions on the processes operating within the system being investigated. In this study, the Random Forest (RF) ensemble learning algorithm, is tested to demonstrate the capabilities and advantages of ML for RZSM estimation. Interpolation and extrapolation of RZSM on a daily timescale was carried out using RF over a small agricultural catchment from 2016 to 2018 using in situ measurements. Results show that RF predictions have slightly higher accuracy for interpolation and similar accuracy for extrapolation in comparison with RZSM simulated from a process-based model combined with data assimilation. RF predictions for extreme wet and dry conditions were, however, less accurate. This was inferred to be due to infrequent sampling of such conditions that led to poor learning in the trained RF model and to incomplete representation of relevant subsurface processes at the study sites in the RF covariates. Since RF does not depend on parameters required to estimate subsurface water flow, it is more advantageous than a process-based model in data-poor regions where soil hydraulic parameters are incomplete or missing, especially when the primary goal is only the estimation of soil moisture states.

Root zone soil moisture (θrz) is a crucial component of the hydrological cycle and provides information for drought monitoring, irrigation scheduling, and carbon cycle modeling. During vegetation conditions, estimation of θrz thru radar has so far only focused on retrieving surface soil moisture using the soil component of the total backscatter (σsoil), which is then assimilated into physical hydrological models. The utility of the vegetation component of the total backscatter (σveg) has not been widely explored and is commonly corrected for in most soil moisture retrieval methods. However, σveg provides information about vegetation water content. Furthermore, it has been known in agronomy that pre-dawn leaf water potential is in equilibrium with that of the soil. Therefore soil water status can be inferred by examining the vegetation water status. In this study, our main goal is to determine whether changes in root zone soil moisture (Δθrz) shows corresponding changes in vegetation backscatter (Δσveg) at pre-dawn. We utilized Sentinel-1 (S1) descending pass and in situ soil moisture measurements from 2016-2018 at two soil moisture networks (Raam and Twente) in the Netherlands. We focused on corn and grass which are the most dominant crops at the sites and considered the depth-averaged θrz up to 40 cm to capture the rooting depths for both crops. Dubois’ model formulation for VV-polarization was applied to estimate the surface roughness parameter (Hrms) and σsoil during vegetated periods. Afterwards, the Water Cloud Model was used to derive σveg by subtracting σsoil from S1 backscatter (σtot). To ensure that S1 only measures vegetation water content, rainy days were excluded to remove the influence of intercepted rainfall on the backscatter. The slope of regression lines (β) fitted over plots of Δσveg against Δθrz were used investigate the dynamics over a growing season. Our main result indicates that Δσveg - Δθrz relation is influenced by crop growth stage and changes in water content in the root zone. For corn, changes in β’s over a growing season follow the trend in a crop coefficient (Kc) curve, which is a measure of crop water requirements. Grasses, which are perennial crops, show trends corresponding to the mature crop stage. The correlation between soil moisture (Δθ) at specific soil depths (5, 10, 20, and 40 cm) and Δσveg matches root growth for corn and known rooting depths for both corn and grass. Dry spells (e.g. July 2018) and a large increase in root zone water content in between two dry-day S1 overpass (e.g. from rainfall) result in a lower β, which indicates that Δσveg does not match well with Δθrz. The influence of vegetation on S1 backscatter is more pronounced for corn, which translated to a clearer Δσveg - Δθrz relation compared to grass. The sensitivity of Δσveg to Δθrz in corn means that the analysis may be applicable to other broad leaf crops or forested areas, with potential applications for monitoring periods of water stress.

Soil hydro-physical properties —such as soil water retention, (un)saturated hydraulic conductivity, shrinkage and swelling, organic matter content, texture (particle distribution), structure (soil aggregation/pore structure)and bulk density— are used in many sub(surface) modeling applications. Reliable soil-hydrophysical properties are key to proper predictions with such models, yet the harmonization and standardization of these properties has not received much attention. Lack of harmonization and standardization may lead to heterogeneity in data as a result of differences in methodologies, rather than real landscape heterogeneity. A need and scope has been identified to better harmonize, innovate, and standardize methodologies regarding measuring soil hydraulic properties that form the information base of many derived products in support of EU policy. With this identified need in mind the Soil Program on Hydro-Physics via International Engagement (SOPHIE) was initiated in 2017. Besides developing new activities that may advise future measurements, we also explore historic data and metadata and mine its relevant contents. The European Hydro-pedological Data Inventory (EU-HYDI), the largest European database on measured soil hydrophysical properties, is – to date – rather under-explored in this sense, which served as motivation for this work.From EU-HYDI we selected those records that were complete for soil texture, bulk density and organic matter, and fitted pedo-transfer functions separately for particular water retention points (at heads of 0, 2.5, 10, 100, 300, 1000, 3000, 15000 cm) and saturated hydraulic conductivity by multi-linear regression. We then subtracted the observed retention and hydraulic conductivity values from their estimated counterparts, and grouped the residuals by measurement methodologies. The results show that there can be significant differences between different methodologies and sample sizes used to obtain the water retention and hydraulic conductivity in the laboratory. The results thus show that the EU-data that may underlie large scale modelling may introduce errors in the forcing data that are attributed to a lack of harmonization and standardization in currently used measurement protocols.

Soil, the living skin of the Earth, provides ecosystem services critical for life: soil acts as a water filter and a growing medium, offers habitat for billions of organisms, and supplies most of the antibiotics. In places, it may take a hundred years to form one cm of soil, but it can be degraded only in a few years or less by a number of natural and anthropogenic factors, including climate change. Presently, one third of all land is degraded to some extent, and fertile soil is lost every year. Droughts are becoming more common, also in humid climates, and the combination of erratic weather patterns with an increased pressure on land by human activities leads to soil degradation. Soil degradation results in a loss of fertile topsoil, thereby altering the soil hydrology completely. As the consequences, soil water holding capacity decreases, hydrophobicity increases, and more runoff is observed, that leads to further soil degradation. Thus, soil hydrology is the key for a healthy functioning topsoil/soil ecosystem. We are in urgent need for novel solutions for improving soil hydraulic properties that will lead to restoration of degraded soils.In this study we investigate a possibility of restoring degraded soil using microorganisms. The hypothesis is that microorganisms can improve soil hydraulic properties such as infiltration and water retention, and reduce hydrophobicity that will facilitate further ecosystem restoration. Such strategy is based on combining the research fields of microbiology and soil physics that to date have hardly been combined. To test this hypothesis, we have inoculated sandy soil with a bacterium Bacillus mycoides and then measured its hydraulic properties using evaporation and pressure plate methods. We have also made efforts of standardizing this methodology by testing incubation time and inoculum concentrations on the hydraulic properties of the soil. Evaluation of an effect of bacteria addition on the soil water holding capacities and unsaturated water conductivity have been conducted as a comparison between inoculated soil and uninoculated (control). Results of this ongoing study will be presented here.

Cold-regions hold a pool of organic carbon that has accumulated over many thousands to millions of years and which is currently kept immobile by permafrost. However, in a warming climate, a deepening of the active layer results in the release of greenhouse gasses CO2 and CH4 into the atmosphere from this carbon pool. Additionally, due to the degradation of deeper permafost, soil hydraulic properties and associated groundwater flow paths are shifting rapidly as a result of which also organic carbon in deeper permafrost is being dissolved into groundwater, which can then reach the surface environment via groundwater flow. This provides an additional mechanism by which permafrost carbon can be mobilized in a warming climate, and one which is likely increasingly important for progressive surface warming.Although the process of carbon leaching from thawing organic rich permafrost layers into the groundwater is an increasingly important part of the carbon cycle of cold-regions, it is notoriously difficult to measure in situ or incorporate into numerical model assessments due to the highly heterogeneous properties of the permafrost, and lack of process knowledge. In particular, the crucial understanding of the influence of different soil physical properties such as soil grain size and organic matter content on permafrost thawing processes is missing, as well the precise release mechanisms of organic matter into pore waters in thawing soils.This study employs lab soil column experiments to investigate the interplay between soil physical properties and thawing dynamics of permafrost. One meter high soil columns are frozen to create controlled permafrost conditions. A range of sand grain sizes (0.1 to 0.8mm) and organic matter contents (1 to 10 wt%) representative for sedimentary permafrost are used. The column is thermally insulated on the sides and top, exposing only one face to ambient temperature in the climate chamber. In this way one-dimensional heat flow conditions are created. So far, the columns are equipped with arrays of temperature sensors. Experiments consist of a cycle of freezing and thawing. Our initial data and analysis illustrate how a fast evolving thawing front develops through the frozen soil column including the effects of latent heat at the thawing front. Numerical modeling allows to infer the soil thermal properties relevant to model the permafrost thawing process.