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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.

International audience; Recent studies suggest that water hyacinths can influence the transport of macroplastics in freshwater ecosystems at tropical latitudes. Forming large patches of several meters at the water surface, water hyacinths can entrain and aggregate large amounts of floating debris, including plastic items. Research on this topic is still novel and few studies have quantified the role of the water hyacinths in plastic transport. In this study, we present the findings of a six-week monitoring campaign, combining the use of visual observations and Unmanned Aerial Vehicle imagery in the Saigon river, Vietnam. For the first time, we provide observational evidence that the majority of macroplastic is transported by water hyacinth patches. Over the study period, these fast-growing and free-floating water plants transported 78% of the macroplastics observed. Additionally, we present insights on the spatial distribution of plastic and hyacinths across the river width, and the different characteristics of entrapped items compared with free-floating ones. With this study, we demonstrate the role of water hyacinths as a river plastic aggregator, which is crucial for improving the understanding of plastic transport, and optimizing future monitoring and collection strategies.

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.

Biochar has been lauded as a cure-all for improving water availability in soils. Yet the effect of pyrolysis temperature and feedstock type on biochar hydraulic properties and its subsequent effects on soils are not well known. We therefore systematically studied water retention, saturated hydraulic conductivity (Ksat) and hydrophobicity of 12 standard biochars (six feedstocks and two pyrolysis temperatures) developed by the UK Biochar Research Centre. The hydraulic properties were determined for pure crushed biochar, as well as for a sandy soil amended with 10 t ha−1 biochar (assessed three times over a period of 15 months). For pure biochar, the effect of feedstock-temperature treatments on the water retention curve was negligible. Rice husk at a pyrolysis temperature of 700 °C had a significantly lower saturated water content, plant available water content and Ksat than all other biochar treatments. This can be attributed to its severe hydrophobicity: while all other treatments were non-hydrophobic and rice husk at 550 °C and Miscanthus straw at 550 °C were both strongly hydrophobic, rice husk at 700 °C was severely hydrophobic. Incorporation of the biochar into a sandy soil did not significantly influence soil water retention, saturated hydraulic conductivity and hydrophobicity. There were also no significant differences between the biochar treatments. These results indicate that except for rice husk at 700 °C the different biochar feedstock types and pyrolysis temperatures yield surprisingly similar material in terms of hydraulic characteristics. Improved soil hydrology should not be a main reason to apply biochar on sandy soils, but if biochar is applied differences in hydrophobicity should be considered.

It is the core task of geoscientists to gain insight into the complex systems of nature. Yet, complexity may be perceived very differently and a plethora of models with different degrees of complexity is available. How do we, geoscientists, decide what model complexity is warranted? Does this differ among disciplines? And, how do we even define model complexity? We developed a short questionnaire to investigate the geoscientific community's views on complexity in models. The response was overwhelming, with 618 completed responses. The results show that the number of processes explicitly included and the number of interactions / feedbacks incorporated were seen as important determinants of complexity. Confidence was not per se higher in the simulations of a complex model compared to a simple one. Interestingly, neither gender, the discipline within the geosciences, nor career stage or work sector, explained the characterization of model complexity. The results of the questionnaire demonstrate that there is no general consensus on how model complexity is perceived or should be defined, and that formal definitions are not broadly or generally accepted. In an environment seeking greater collaboration and interdisciplinarity, these results indicate the need for conscious dialogue about this topic among different model users.

Elucidating segregation of precipitation in different components in forest stands is important for proper forest ecosystems management. However, there is a lack of information on important rainfall components viz. throughfall, interception and stemflow in forest watersheds particularly in developing countries. We therefore investigated the spatiotemporal variation of important component of throughfall for a forest stand in a Hyrcanian plain forest in Noor City, northern Iran. The study area contained five species of Quercus castaneifolia, Carpinus betulus, Populus caspica and Parrotia persica. The research was conducted from July 2013 to July 2014 using a systematic sampling method. Ninetysix throughfall collectors were installed in a 3.5 m × 3.5 m grid cells. The canopy covers during the growing/leaf-on (i.e., from May to November) and non-growing/leaf-off (i.e., from December to March) seasons were approximately 41% and 81%, respectively. The mean cumulative throughfall during the study period was 623±31 mm. The average throughfall (TF) as % of rainfall (TFPR) during leaf-on and leaf-off periods were calculated 56±14% and 77±10%, respectively. TF was significantly (R2 = 0.97, p = 0.00006) correlated with gross precipitation. Percent of canopy cover was not correlated with TF except when gross precipitation was

Landscape composition and land use impact the interactions between soil and vegetation. Differences in micro-behaviour, driven by the interplay of heterogeneous soil and vegetation dynamics, affect emergent characteristics across a landscape. Scaling approaches to understand the drivers of these emergent characteristics have been attempted, but the blueprint of interacting biophysical processes in landscapes is inherently messy and often still unknown. A complicating factor is single disciplinary focus in environmental sciences. Integrated knowledge is vital especially in view of future challenges posed by climate change, population growth, and soil threats. In this paper, we give examples of biophysical interactions that occur across various temporal and spatial scales and discuss how connectivity can be useful for bridging disciplines and scales to increase our understanding.

Although plastic pollution happens globally, the micro- (−1), to earthworm casts (14.8 ± 28.8 particles g−1), to chicken feces (129.8 ± 82.3 particles g−1). Chicken gizzards contained 10.2 ± 13.8 microplastic particles, while no microplastic was found in crops. An average of 45.82 ± 42.6 macroplastic particles were found per gizzard and 11 ± 15.3 macroplastic particles per crop, with 1–10 mm particles being significantly more abundant per gizzard (31.8 ± 27.27 particles) compared to the crop (1 ± 2.2 particles). The data show that micro- and macroplastic are capable of entering terrestrial food webs.

Temperature can be used to trace groundwater flows due to thermal disturbances of subsurface advection. Prior hydrogeological studies that have used temperature-depth profiles to estimate vertical groundwater fluxes have either ignored the influence of climate change by employing steady-state analytical solutions or applied transient techniques to study temperature-depth profiles recorded at only a single point in time. Transient analyses of a single profile are predicated on the accurate determination of an unknown profile at some time in the past to form the initial condition. In this study, we use both analytical solutions and a numerical model to demonstrate that boreholes with temperature-depth profiles recorded at multiple times can be analyzed to either overcome the uncertainty associated with estimating unknown initial conditions or to form an additional check for the profile fitting. We further illustrate that the common approach of assuming a linear initial temperature-depth profile can result in significant errors for groundwater flux estimates. Profiles obtained from a borehole in the Veluwe area, Netherlands in both 1978 and 2016 are analysed for an illustrative example. Since many temperature-depth profiles were collected in the late 1970s and 1980s, these previously profiled boreholes represent a significant and underexploited opportunity to obtain repeat measurements that can be used for similar analyses at other sites around the world.

Soil temperature is a very important variable in agricultural meteorology and strongly influences agricultural activities and planning (e.g. the date and depth of sowing crops, frost protection). There are many physically based studies in the literature which model soil temperature, but few are easily applicable for use in the field. Simple and precise short-term forecasting of soil temperature with minimum data requirements is the main goal of this study. The soil temperature at 0300, 0900 and 1500 GMT was forecast based only on surface air temperatures using artificial neural network (ANN) and wavelet transform artificial neural network (WANN) models. The hourly data were collected from the Mashhad synoptic station in Khorasan Razavi province in Iran between 2010 and 2013. The results of this study showed that using a wavelet transform for preprocessing improved the accuracy of soil temperature forecasting. It was also found that changing the temporal increment in forecasting time did not have a noticeable effect on errors in the WANN models. WANN models can be used as accurate tools to forecast soil temperature 1–7 days ahead at depths of 5–30 cm.

In hydrological terms raised bogs can be approximated by simple models as in the acrotelm-catotelm concept. However, raised bogs are often characterized by a pronounced surface topography, causing large changes in connectivity of contributing areas onthe bog. In this study, daily regression of measured discharges versus catchment areas is used to quantify the importance of surface topography on catchment connectivity within a raised bog. The resulting coefficient of determination shows the strengthof the relationship between the discharge and catchment area over time under different hydrological conditions. Monitoring of discharge, water table, transmissivity, and basic weather data on a raised bog (1.9 km2) in eastern central Estonia took place from May 2008 to June 2010. Contributing areas, calculated based on the outlet's discharge volume (VQ) divided by the net precipitation volume (VPnet), of the outlet containing the central pool-ridge system varied between 1 mes10− 3 m2 and 0.7 km2, suggesting significant differences in connectivity between hydrological events. Correlation between discharge and theoretical catchment size was high (R2>0.75) when the water table was closeto the surface (less than 5 cm below peat surface), and consequently transmissivities were also high (up to 1030 m2 d− 1), which lead to connectivity of local storage elements, such as pools and hollows. However, a water table below this threshold resulted in large parts of the catchment being disconnected. The importance of water table depths on catchment connectivity suggests the need to reconsider the hydrological concept of raised bogs; to incorporate these shallow flow components and better understand residence time and consequently transport of solutes, such as DOC, from patterned peatlands.

Silver nanoparticles (AgNPs) are used in a growing number of applications and products. Previous studies showed AgNPs can leach from these products to the environment. As a result of AgNPs leaching, sediment, soil and sludge-treated soils may be contaminated with AgNPs. Methods to detect, quantify and characterize AgNPs in soil are urgently needed. This study describes the development and validation of a method for the extraction, quantification and particle size determination of AgNPs in soils. The final method consists of pre-wetting the sample followed by an aqueous extraction, using sonication to re-suspend adsorbed AgNPs, and analysis of the aqueous extract with single particle ICP-MS. Validation of the method showed that the recovery of AgNPs spiked to soil was 44% for sandy soil and 42% for clayey soil. Although this recovery is relatively low, the repeatability and reproducibility values of the particle concentration were within the limits of Horwitz ratio, which makes the method suitable for its purpose. Further, the method concentration detection limit, LODc., is 5 μg kg −1 soil. The developed method can be applied in eco-toxicological and risk-assessments studies for AgNP in the soil environment.

Valley bottomland provides diverse agricultural and ecosystem benefits. Due to concentrated flow paths, they are more vulnerable to gully erosion than hillslope areas. The objective of this review was to show what caused valley bottoms gullies and to present deficiencies in existing rehabilitation measures. From the literature review, we found the following general trends: watershed characteristics determine location of valley bottom gullies, an increase in water transported from the watershed initiates the formation of gullies, the rate of change of the valley bottom gullies, once initiated, depends on the amount of rainfall and the soil and bedrock properties. Especially in humid climates, the presence of subsurface flow greatly enhances bank slippage and advancement of gully heads. Valley bottom gully reclamation measures are generally effective in arid and semi-arid areas with the limited subsurface flow and deep groundwater tables, whereas, for (sub) humid regions, similar remedial actions are not successful as they do not account for the effects of subsurface flows. To ensure effective implementation of rehabilitation measures, especially for humid regions, an integrated landscape approach that accounts for the combined subsurface and surface drainage is needed.

Environmental regulations aim to protect the environment from anthropogenic detrimental effects. To ensure their effectivity and to avoid unexpected results and budget losses, environmental regulations need careful designs grounded in observational data. Comprehensive monitoring campaigns are not always achievable in developing economies, since environmental monitoring is not always prioritized due to resource constraints. We propose to tackle the problem using an opportunistic data analysis approach as supplementary information for environmental monitoring. We applied this approach to evaluate the application of Chilean phosphorus (P) fertilization subsidy. A risk assessment for P surplus was performed using three datasets: (1) secondary data acquired from thousands of unclassified laboratory records from the private sector (n = 7957); (2) a dataset of soil available P from a budged-restricted monitoring campaign, and; (3) a conjoint dataset that comprises 1 and 2. Results indicate that while laboratory records represented the general characteristics of the study area, field monitoring data evidenced a surplus of soil P. Using the laboratory records to enrich the data acquired by field monitoring modified the reality reflected by the monitoring data alone. The use of the conjoint dataset leads to the conclusion that soils in the study area had enough available P for optimum production, and that farmers were already using external sources of P fertilizers within the current market structure. Our study constitutes an example of the use of private data to contribute to public soil monitoring programs and environmental regulation designs. The case study serves as a successful example of opportunistic data usage in environmental monitoring, as a low-cost alternative to complement field observations.

1. Climate change is a world-wide threat to biodiversity and ecosystem structure, functioning and services. To understand the underlying drivers and mechanisms, and to predict the consequences for nature and people, we urgently need better understanding of the direction and magnitude of climate change impacts across the soil–plant–atmosphere continuum. An increasing number of climate change studies are creating new opportunities for meaningful and high-quality generalizations and improved process understanding. However, significant challenges exist related to data availability and/or compatibility across studies, compromising opportunities for data re-use, synthesis and upscaling. Many of these challenges relate to a lack of an established ‘best practice’ for measuring key impacts and responses. This restrains our current understanding of complex processes and mechanisms in terrestrial ecosystems related to climate change. 2. To overcome these challenges, we collected best-practice methods emerging from major ecological research networks and experiments, as synthesized by 115 experts from across a wide range of scientific disciplines. Our handbook contains guidance on the selection of response variables for different purposes, protocols for standardized measurements of 66 such response variables and advice on data management. Specifically, we recommend a minimum subset of variables that should be collected in all climate change studies to allow data re-use and synthesis, and give guidance on additional variables critical for different types of synthesis and upscaling. The goal of this community effort is to facilitate awareness of the importance and broader application of standardized methods to promote data re-use, availability, compatibility and transparency. We envision improved research practices that will increase returns on investments in individual research projects, facilitate second-order research outputs and create opportunities for collaboration across scientific communities. Ultimately, this should significantly improve the quality and impact of the science, which is required to fulfil society's best practice, coordinated experiments, data management and documentation, ecosystem, experimental macroecology, methodology, open science, vegetation This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. © 2019 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

Climate change impacts are a serious threat to food provisioning, security and the economy. Thus, assessing agricultural suitability and yield reduction under climate change is crucial for sustainable agricultural production. In this study, we used two sub-models of the agro-ecological decision support system MicroLEIS (Terraza and Cervatana) to evaluate the impacts of climate change on land capability and yield reduction of wheat and sunflower as major rainfed crops in different Mediterranean soil types (in Andalucia, Southern Spain). The Terraza sub-model provides an experimental prediction for the bioclimate deficiency and yield reduction, while the Cervatana sub-model predicts the general land use suitability for specific agricultural uses. Sixty-two districts in Southern Spain were modeled and mapped using soil data and the A1B climate scenario (balanced scenario) for three 30-year periods ending in 2040, 2070 and 2100, respectively. Our results showed that the majority of agricultural soils were suitable for wheat production, and less for sunflowers, especially under projected climate change scenarios. Extreme impacts of climate change were observed in the soil types Typic Xerofluvents and Calcic Haploxerepts, where the land capability was reduced from Good and Moderate classes to the Marginal class. This was especially observed in sunflower crops by 2100. Yield reduction of sunflower was much higher than the reduction for wheat, especially under the projected climate periods, where the results for 2100 showed the severest effect on crop yields with about 95% of the sunflower area showing yield reductions. This high variability of the evaluation results demonstrates the importance of using soil factors, climate and crop information in conjunction in decision-making regarding the formulation of site-specific soil use and management strategies.

Silver nanoparticles (AgNPs) can enter the environment when released from products containing them. As AgNPs enter soil, they are often retained in the soil profile and/or leached to the groundwater. This research assessed the transport of AgNPs in their “particle form” through the soil profile using a series of columns. Three soil types were put into soil columns: LSH (loam with high organic matter (OM)), LSL (loam with low OM), and Sand (no OM). The results showed that AgNP transport and retention in soil as well as particle size changes are affected by soil organic matter (OM) and the cation exchange capacity (CEC) of soil. OM affected the transport and retention of AgNPs. This was evident in the LSH columns where the OM concentration was the highest and the AgNP content the lowest in the soil layers and in the effluent water. The highest transported AgNP content was detected in the Sand columns where OM was the lowest. CEC had an impact on the particle size of the AgNPs that were retained in the soil layers. This was clear in columns packed with high CEC-containing soils (LSL and LSH) where AgNP particle size decreased more substantially than in the columns packed with sand. However, the decrease in AgNP sizes in the effluent water was less than the decrease in particle size of AgNPs transported through but retained in the soil. This means that the AgNPs that reached the effluent were transported directly from the first layer through the soil macropores. This work highlights the ability to track AgNPs at low concentrations (50 μg kg−1) and monitor the changes in particle size potential as the particles leach through soil all of which increases our knowledge about AgNP transport mechanisms in porous media.

Agricultural land suitability evaluation is a good way to distinguish soil suitability in order to improve the soils by addressing major limitations. This study investigated the influence of soil factors variability on the suitability of 12 Mediterranean crops in southern Spain. To represent the variability in elevation, lithology, and soil, two latitudinal and longitudinal soil transects (TA and TB) were considered and sampled in 63 representative points at regular 4. km intervals. This research also aimed to determine how to maximize soil potential by improving limiting factors as drainage, carbonate content, salinity, and sodium saturation. Soil suitability evaluation ranged between optimum and not suitable classes along TA and TB. The decrease in the severity of soil limiting factors in the improved scenario leads to an increase in soil suitability for the 12 crops along TA and TB transects, except in segments with shallow soils and very coarse texture. Soil evaluation and spatial analyses of soil suitability for the 12 crops under current situation and improved scenario, including optimum and not suitable soils, are helpful to achieve a sustainable land management in the studied area. The improvement of soil limitation it could be as adaptation strategies for the long term of environmental changes as climate changes, this work has a real impact, which means the results valuable and easy to grasp for the decision makers.

Pollution caused by plastic debris is an urgent environmental problem. Here, we assessed the effects of microplastics in the soil surface litter on the formation and characterization of burrows built by the anecic earthworm Lumbricus terrestris in soil and quantified the amount of microplastics that was transported and deposited in L. terrestris burrows. Worms were exposed to soil surface litter treatments containing microplastics (Low Density Polyethylene) for 2 weeks at concentrations of 0%, 7%, 28%, 45% and 60%. The latter representing environmentally realistic concentrations found in hot spot soil locations. There were significantly more burrows found when soil was exposed to the surface treatment composed of 7% microplastics than in all other treatments. The highest amount of organic matter in the walls of the burrows was observed after using the treatments containing 28 and 45% microplastics. The highest microplastic bioturbation efficiency ratio (total microplastics (mg) in burrow walls/initial total surface litter microplastics (mg)) was found using the concentration of 7% microplastics, where L. terrestris introduced 73.5% of the surface microplastics into the burrow walls. The highest burrow wall microplastic content per unit weight of soil (11.8 ± 4.8 g kg-1) was found using a concentration of 60% microplastics. L. terrestris was responsible for size-selective downward transport when exposed to concentrations of 7, 28 and 45% microplastics in the surface litter, as the fraction ≤50 μm microplastics in burrow walls increased by 65% compared to this fraction in the original surface litter plastic. We conclude that the high biogenic incorporation rate of the small-fraction microplastics from surface litter into burrow walls causes a risk of leaching through preferential flow into groundwater bodies. Furthermore, this leaching may have implications for the subsequent availability of microplastics to terrestrial organisms or for the transport of plastic-associated organic contaminants in soil.

The Tropical Montane Cloud Forest (TMCF) is a hydrologically unique and highly vulnerable ecosystem to changes in land-use and climate. Assessing the impacts of these changes needs to consider soil-water dynamics. In particular, the organic layer and its functioning requires attention because its difference in water retention characteristics and root density compared to the underlying mineral soils. A higher root density and a higher water storage capacity of the organic layer compared to the mineral soils suggests that most nutrient and water uptake occurs in this layer. However, hydraulic properties of mineral soils and their impact on hydrology of TMCFs have been poorly studied. Here we provide organic layer water retention curves for TMCF soils that were measured in the laboratory. With these data we assessed the potential land-use and climate change impacts on TMCF soil moisture dynamics. From the land-use change perspective, we estimated the water storage capacity loss by slash-and-burn deforestation practices. These estimates show that the storage loss ranges from 35 to 59 mm when TMCFs are converted to pastures. This is several times higher than the estimated TMCF canopy storage capacity (2 to 5 mm). Therefore, the higher peak flow observations in deforested catchments might not only be explained by a decreasing canopy water storage but also likely due to a decreasing soil water storage. From the climate change perspective, we evaluated the effect of contrasting dry season conditions on soil moisture and transpiration using a 1-D water-flow model, and assessed the sensitivity of these hydrological variables to uncertainties in saturated hydraulic conductivity. Although transpiration was not limited by soil moisture during the mild dry season, it was affected during the severe dry season and continued to decline under expected climate change with the prolongation of dry spells. Our results show that the organic layer is a key element in TMCF's hydrological functioning and call for an increased focus on the role of organic soils when evaluating effects of land-use change.

Environmental contextMicroplastics found in soil pose several potential environmental risks. This study shows that microplastics on the soil surface can be ingested by earthworms and transported to the lower soil layers. In this way, microplastics may enter the food chain and find their way into groundwater systems, especially in cases where the water table is shallow. AbstractIn the current study, we examine how the activities of earthworms (Lumbricus terrestris) affect microplastic (MP) distribution and concentration in soil, with a focus on low density polyethylene (LDPE). We also want to determine if MPs can be flushed out with water. We used a laboratory sandy soil column (polyvinyl chloride tube) experimental set-up and tested five different treatments: (1) treatment with just soil (control) to check if the saturated conductivity (Ksat) could be impacted by MP, (2) treatment with MP, (3) treatment with MP and litter, (4) treatment with earthworms and litter as a second control for treatment 5 and (5) treatment with MPs, earthworms and litter. Each treatment consisted of eight replicates. For the treatments with MP, the concentration of MP added at the start of the experiment was 7% by weight (3.97g, polyethylene, 50% 1mm–250µm, 30% 250µm–150µm and 20%

We explored the potential of using short-term weather forecasts to increase irrigation efficiency in rice cultivation, as a potential adaptation option to future climate change. We used 5-day hypothetically perfect rainfall forecasts and 4-day real rainfall forecasts for 2007–2008 issued by the India Meteorological Department (IMD). The rainfall forecasts were incorporated into the agro-hydrological model SWAP (Soil Water Plant Atmosphere), to produce alternative irrigation schedules. The SWAP model was calibrated with data from field experiments at Kharagpur, North-East India. Rice yield simulations were performed for observed weather (1989–2009) and for a future climate with more dry spells and more intense rainfall events. The model revealed that basing the decision to irrigate rice on short-term weather forecasts could reduce average water application by 27% when 5-day perfect rainfall forecasts were used. Even though the real 4-day rainfall forecasts were not very accurate, their use also resulted in a reduction in irrigation water application. Using 5-day hypothetically perfect forecasts under future climate conditions led to a saving of 32% of irrigation water compared to water use under the current climate.

Plastic debris is widespread in the environment, but information on the effects of microplastics on terrestrial fauna is completely lacking. Here, we studied the survival and fitness of the earthworm Lumbricus terrestris (Oligochaeta, Lumbricidae) exposed to microplastics (Polyethylene

Groundwater sources supply fresh drinking water to almost half of the World’s population and are a main source of water for irrigation across world. Characterization of groundwater resources, surface-groundwater interactions and their link to the global water cycle and modern global change are important themes in hydrogeological research, whereas little attention has been given to the relation between groundwater and past climate variations. A ground-water system’s history is vital to assess its vulnerability under future and potentially adverse climatic changes. The scientific initiative Groundwater and Global Palaeoclimate Signals (G@GPS) investigates major recharge periods of large groundwater aquifers worldwide. We describe the findings for a major basin on each permanently inhabited continent and one with coastal influences in Australia. As palaeo-signals in groundwater are inherently low-resolution records, they can only be related to considerable amounts of r echarge. Long periods with substantial groundwater recharge ought to be well identifiable in terrestrial records. Correlation with regional and global climate records may give ideas of the conditions under which such large amounts of recharge were initiated.

Deep subpermafrost aquifers are highly climate-dependent, with the permafrost as an aquitard preventing groundwater recharge and discharge. A study from the high-arctic island of Spitsbergen, Svalbard, shows that during a glacial to interglacial phase, both the permafrost and the glacier regime will respond to climatic changes, and a glacier-fed groundwater flow system will vary accordingly. A full glaciation results in the melting of permafrost, and groundwater can flow through pores and fracture systems in the rocks and sediments below the temperate zones of glaciers. These groundwater flow systems will mainly be localized to fjords and valleys and form low-lying terrestrial springs when the relative sea level drops during deglaciation due to glacio-isostatic rise. During an interglaciation, permafrost develops and thickens and the groundwater recharge and discharge areas will thereby be gradually reduced to a minimum reached at the warmest part of an interglaciation. An already frozen spring system cannot reopen before the permafrost melts. Only groundwater springs related to permanently warm-based glacial ice will persist into the next glaciation. During a new glaciation, flow systems that terminated during the previous interglaciation may become revitalized if overridden by warm-based ice causing permafrost thawing.

Soil plant atmosphere continuum concepts used in vadose zone hydrology approach plants as physical entities. This approach has proven very valuable in the past decades. The need to upscale such concepts provokes the question if plant functional biology should be considered, as larger scales also imply variation in (micro)climate and soil composition. Habitat manifestation is an expression of its evolutionary history and although the spatial distribution of habitats is largely driven by current climates, a soil's water holding capacity and hence its formation over time may have played a role.Separate mechanisms involved in the soil plant atmosphere continuum are often understood and incorporated in numerical models for predictive purposes, yet interrelationships pose challenges, especially when such relationships cross traditional scientific disciplinary boundaries. In fact, the exact driver for root water uptake is itself subject of scientific debate, as there is no consensus on whether the driver for root water uptake is soil moisture content (e.g. [1]) or soil water potential (e.g. [2]). To evaluate soil water availability in relation to crop yield prognoses and the stability of natural vegetation, integrated concepts are sorely needed, especially in the perspective of climate change [3] and global water scarcity [4]. We present considerations and possible approaches for linking plant functional biology and vadose zone processes.

Several earlier studies reported that microplastics (MP) accumulated on soil surfaces could be transported into the subsoil and ingested by soil biota, such as earthworms. The present study explores how networks of earthworm burrows and MP (low‐density polyethylene, LDPE) in subsoil affect the soil hydraulic properties and saturated water flow. A repacked and saturated sandy soil column experiment was conducted in an environment‐controlled laboratory with earthworms (anecic, Lumbricus terrestris) inoculated into the soil columns to form networks of macropore. The macropore network parameters (i.e., number, length, volume, diameter, soil saturated conductivity, and tracer breakthrough curves of soil columns) have been determined. The relative arrival times of the tracer mass (i.e. T5%, T25%, and T50%) were determined in order to describe the shapes of the breakthrough curves. The results show that in some breakthrough curves for the treatments with earthworms, there are two peaks. This is an indication that water was flowing faster in the macropores than in the soil matrix. There is a significant correlation between 5% arrival time and the median burrow volume, and the correlation coefficient was .571 (at the level of p