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Drought and heat events, such as the 2018 European drought, interact with the exchange of energy between the land surface and the atmosphere, potentially affecting albedo, sensible and latent heat fluxes, as well as CO 2 exchange. Each of these quantities may aggravate or mitigate the drought, heat, their side effects on productivity, water scarcity and global warming. We used measurements of 56 eddy covariance sites across Europe to examine the response of fluxes to extreme drought prevailing most of the year 2018 and how the response differed across various ecosystem types (forests, grasslands, croplands and peatlands). Each component of the surface radiation and energy balance observed in 2018 was compared to available data per site during a reference period 2004-2017. Based on anomalies in precipitation and reference evapotranspiration, we classified 46 sites as drought affected. These received on average 9% more solar radiation and released 32% more sensible heat to the atmosphere compared to the mean of the reference period. In general, drought decreased net CO 2 uptake by 17.8%, but did not significantly change net evapotranspiration. The response of these fluxes differed characteristically between ecosystems; in particular, the general increase in the evaporative index was strongest in peatlands and weakest in croplands. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Salinity intrusion caused by land subsidence resulting from increasing groundwater abstraction, decreasing river sediment loads and increasing sea level because of climate change has caused widespread soil salinization in coastal ecosystems. Soil salinization may greatly alter nitrogen (N) cycling in coastal ecosystems. However, a comprehensive understanding of the effects of soil salinization on ecosystem N pools, cycling processes and fluxes is not available for coastal ecosystems. Therefore, we compiled data from 551 observations from 21 peer-reviewed papers and conducted a meta-analysis of experimental soil salinization effects on 19 variables related to N pools, cycling processes and fluxes in coastal ecosystems. Our results showed that the effects of soil salinization varied across different ecosystem types and salinity levels. Soil salinization increased plant N content (18%), soil NH 4 + (12%) and soil total N (210%), although it decreased soil NO 3 - (2%) and soil microbial biomass N (74%). Increasing soil salinity stimulated soil N 2 O fluxes as well as hydrological NH 4 + and NO 2 - fluxes more than threefold, although it decreased the hydrological dissolved organic nitrogen (DON) flux (59%). Soil salinization also increased the net N mineralization by 70%, although salinization effects were not observed on the net nitrification, denitrification and dissimilatory nitrate reduction to ammonium in this meta-analysis. Overall, this meta-analysis improves our understanding of the responses of ecosystem N cycling to soil salinization, identifies knowledge gaps and highlights the urgent need for studies on the effects of soil salinization on coastal agro-ecosystem and microbial N immobilization. Additional increases in knowledge are critical for designing sustainable adaptation measures to the predicted intrusion of salinity intrusion so that the productivity of coastal agro-ecosystems can be maintained or improved and the N losses and pollution of the natural environment can be minimized., (© 2016 John Wiley & Sons Ltd.)

Soil moisture is an essential climate variable of the Earth system. Understanding its spatiotemporal dynamics is essential for predicting weather patterns and climate variability, monitoring and mitigating the effects and occurrence of droughts and floods, improving irrigation in agricultural areas, and sustainably managing water resources. Here we review in depth how soils can remember information on soil moisture anomalies over time, as embedded in the concept of soil moisture memory (SMM). We explain the mechanisms underlying SMM and explore its external and internal drivers; we also discuss the impacts of SMM on different land surface processes, focusing on soil‐plant‐atmosphere coupling. We explore the spatiotemporal variability, seasonality, locality, and depth‐dependence of SMM and provide insights into both improving its characterization in land surface models and using satellite observations to quantify it. Finally, we offer guidance for further research on SMM. Plain Language Summary: Our review paper takes an in‐depth look at soil moisture memory, which is how soil records its moisture history over time and space. Analogous to human psychology, which seeks to understand how a person's/society's memory influences his/her present and future behavior, understanding soil moisture memory encourages consideration of how such memory determines present state and might determine future behavior of soils exposed to environmental disturbances. Soil moisture memory can be affected by a variety of factors, both external (e.g., weather extremes) and internal (soil's unique properties). It affects everything from the air to the way our landscapes respond to disasters like droughts, wildfires, and floods. We also studied how this phenomenon affects the balance of water and energy in our environment, the health of our plants, and even how it communicates with the atmosphere. We show how it can change depending on where you are on the planet, the time of year, and how deep you dig into the soil. We offer scientists insights into how weather and land surface models can become more accurate by accounting for soil moisture memory. Its understanding not only helps us predict and manage our environment, but also provides opportunities for exciting scientific discoveries. Key Points: Atmospheric forcings, land use and management, and soil processes and mechanisms explain how and why soil moisture memory emerges in ecosystemsNonlocality of moisture memory, its spread across different regions, and its interaction with large‐scale climate phenomena are underexploredFurther advances in land surface models and closer integration of model simulations and observations are needed to better characterize moisture memory [ABSTRACT FROM AUTHOR]

Effects of climate change on the ecosystem productivity and water fluxes have been studied in various types of experiments. However, it is still largely unknown whether and how the experimental approach itself affects the results of such studies. We employed two contrasting experimental approaches, using high-precision weighable monolithic lysimeters, over a period of 4 years to identify and compare the responses of water fluxes and aboveground biomass to climate change in permanent grassland. The first, manipulative, approach is based on controlled increases of atmospheric CO 2 concentration and surface temperature. The second, observational, approach uses data from a space-for-time substitution along a gradient of climatic conditions. The Budyko framework was used to identify if the soil ecosystem is energy limited or water limited. Elevated temperature reduced the amount of non-rainfall water, particularly during the growing season in both approaches. In energy-limited grassland ecosystems, elevated temperature increased the actual evapotranspiration and decreased aboveground biomass. As a consequence, elevated temperature led to decreasing seepage rates in energy-limited systems. Under water-limited conditions in dry periods, elevated temperature aggravated water stress and, thus, resulted in reduced actual evapotranspiration. The already small seepage rates of the drier soils remained almost unaffected under these conditions compared to soils under wetter conditions. Elevated atmospheric CO 2 reduced both actual evapotranspiration and aboveground biomass in the manipulative experiment and, therefore, led to a clear increase and change in seasonality of seepage. As expected, the aboveground biomass productivity and ecosystem efficiency indicators of the water-limited ecosystems were negatively correlated with an increase in aridity, while the trend was unclear for the energy-limited ecosystems. In both experimental approaches, the responses of soil water fluxes and biomass production mainly depend on the ecosystems' status with respect to energy or water limitation. To thoroughly understand the ecosystem response to climate change and be able to identify tipping points, experiments need to embrace sufficiently extreme boundary conditions and explore responses to individual and multiple drivers, such as temperature, CO 2 concentration, and precipitation, including non-rainfall water. In this regard, manipulative and observational climate change experiments complement one another and, thus, should be combined in the investigation of climate change effects on grassland. [ABSTRACT FROM AUTHOR]

Disentangling ecosystem evapotranspiration (ET) into evaporation (E) and transpiration (T) is of high relevance for a wide range of applications, from land surface modelling to policymaking. Identifying and analysing the determinants of the ratio of T to ET (T/ET) for various land covers and uses, especially in view of climate change with an increased frequency of extreme events (e.g. heatwaves and floods), is prerequisite for forecasting the hydroclimate of the future and tackling present issues, such as agricultural and irrigation practices. One partitioning method consists of determining the water stable isotopic compositions of ET , E , and T (δET , δE , and δE , respectively) from the water retrieved from the atmosphere, the soil, and the plant vascular tissues. The present work emphasizes the challenges this particular method faces (e.g. the spatial and temporal representativeness of the T/ET estimates, the limitations of the models used, and the sensitivities to their driving parameters) and the progress that needs to be made in light of the recent methodological developments. As our review is intended for a broader audience beyond the isotopic ecohydrological and micrometeorological communities, it also attempts to provide a thorough review of the ensemble of techniques used for determining δET , δE , and δE and solving the partitioning equation for T/ET. From the current state of research, we conclude that the most promising way forward to ET partitioning and capturing the subdaily dynamics of T/ET is by making use of non-destructive online monitoring techniques of the stable isotopic composition of soil and xylem water. Effort should continue towards the application of the eddy covariance technique for high-frequency determination of δET at the field scale as well as the concomitant determination of δET , δE , and δE at high vertical resolution with field-deployable lift systems. [ABSTRACT FROM AUTHOR]

Future crop production will be affected by climatic changes. In several regions, the projected changes in total rainfall and seasonal rainfall patterns will lead to lower soil water storage (SWS), which in turn affects crop water uptake, crop yield, water use efficiency (WUE), grain quality and groundwater recharge. Effects of climate change on those variables depend on the soil properties and were often estimated based on model simulations. The objective of this study was to investigate the response of key variables in four different soils and for two different climates in Germany with a different aridity index (AI): 1.09 for the wetter (range: 0.82 to 1.29) and 1.57 for the drier (range: 1.19 to 1.77) climate. This is done by using high-precision weighable lysimeters. According to a "space-for-time" (SFT) concept, intact soil monoliths that were moved to sites with contrasting climatic conditions have been monitored from April 2011 until December 2017. Evapotranspiration (ET) was lower for the same soil under the relatively drier climate, whereas crop yield was significantly higher, without affecting grain quality. Especially "non-productive" water losses (evapotranspiration out of the main growing period) were lower, which led to a more efficient crop water use in the drier climate. A characteristic decrease of the SWS for soils with a finer texture was observed after a longer drought period under a drier climate. The reduced SWS after the drought remained until the end of the observation period which demonstrates carry-over of drought from one growing season to another and the overall long-term effects of single drought events. In the relatively drier climate, water flow at the soil profile bottom showed a small net upward flux over the entire monitoring period as compared to downward fluxes (groundwater recharge) or drainage in the relatively wetter climate and larger recharge rates in the coarser- as compared to finer-textured soils. The large variability of recharge from year to year and the long-lasting effects of drought periods on the SWS imply that long-term monitoring of soil water balance components is necessary to obtain representative estimates. Results confirmed a more efficient crop water use under less-plant-available soil moisture conditions. Long-term effects of changing climatic conditions on the SWS and ecosystem productivity should be considered when trying to develop adaptation strategies in the agricultural sector. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is a key hydrologic state variable that is of significant importance for numerous Earth and environmental science applications that directly impact the global environment and human society. Potential applications include, but are not limited to, forecasting of weather and climate variability; prediction and monitoring of drought conditions; management and allocation of water resources; agricultural plant production and alleviation of famine; prevention of natural disasters such as wild fires, landslides, floods, and dust storms; or monitoring of ecosystem response to climate change. Because of the importance and wide‐ranging applicability of highly variable spatial and temporal SM information that links the water, energy, and carbon cycles, significant efforts and resources have been devoted in recent years to advance SM measurement and monitoring capabilities from the point to the global scales. This review encompasses recent advances and the state‐of‐the‐art of ground, proximal, and novel SM remote sensing techniques at various spatial and temporal scales and identifies critical future research needs and directions to further advance and optimize technology, analysis and retrieval methods, and the application of SM information to improve the understanding of critical zone moisture dynamics. Despite the impressive progress over the last decade, there are still many opportunities and needs to, for example, improve SM retrieval from remotely sensed optical, thermal, and microwave data and opportunities for novel applications of SM information for water resources management, sustainable environmental development, and food security. Key Points: Recent soil moisture measurement and monitoring techniques and estimation models from the point to the global scales and their limitations are presentedThe importance and application of soil moisture information for various Earth and environmental sciences disciplines such as forecasting weather and climate variability, modeling hydrological processes, and predicting and monitoring extreme events and their impacts on the environment and human society are presented [ABSTRACT FROM AUTHOR]

Leaf Area Index (LAI) is an important variable for numerous processes in various disciplines of bio- and geosciences. In situ measurements are the most accurate source of LAI among the LAI measuring methods, but the in situ measurements have the limitation of being labor intensive and site specific. For spatial-explicit applications (from regional to continental scales), satellite remote sensing is a promising source for obtaining LAI with different spatial resolutions. However, satellite-derived LAI measurements using empirical models require calibration and validation with the in situ measurements. In this study, we attempted to validate a direct LAI retrieval method from remotely sensed images (RapidEye) with in situ LAI (LAIdestr). Remote sensing LAI (LAIrapideye) were derived using different vegetation indices, namely SAVI (Soil Adjusted Vegetation Index) and NDVI (Normalized Difference Vegetation Index). Additionally, applicability of the newly available red-edge band (RE) was also analyzed through Normalized Difference Red-Edge index (NDRE) and Soil Adjusted Red-Edge index (SARE). The LAIrapideye obtained from vegetation indices with red-edge band showed better correlation with LAIdestr (r = 0.88 and Root Mean Square Devation, RMSD = 1.01 & 0.92). This study also investigated the need to apply radiometric/atmospheric correction methods to the time-series of RapidEye Level 3A data prior to LAI estimation. Analysis of the the RapidEye Level 3A data set showed that application of the radiometric/atmospheric correction did not improve correlation of the estimated LAI with in situ LAI. [ABSTRACT FROM AUTHOR]

A dynamic tension-controlled bottom boundary of lysimeters allows observing water and matter fluxes in lysimeters that are close to natural field conditions, as pressure heads at the lysimeter bottom are adjusted to measured pressure heads at the same depth in the surrounding field. However lysimeters are often transferred from their sampling location for practical reasons or to study, for example, the effect of climate change on soil functions. This transfer can be accompanied by a change aboveground but also in subsurface conditions that are used to control the bottom boundary and that may affect the soil water balance of lysimeters. This issue is also relevant for lysimeter stations which use a tension-controlled bottom boundary and are not directly installed near the site of excavation. The potential impact of different bottom boundary conditions on the water balance of lysimeters that were transferred in a climate impact experiment (SOILCan) was investigated exemplarily by a numerical study. Results showed that by using nonappropriate pressure heads, which were measured in soil profiles with a different texture and water table depth than the profile where the lysimeter was taken from, had partially large impacts on soil water fluxes, especially when the water table was located within a specific critical range. Different climate conditions between sampling and installation site were buffered by the soil and did not show a strong influence on the bottom boundary control of lysimeters when the groundwater table depth was assumed to remain constant. Considering a change in groundwater table depths due to changing climate tempered the effects of climate change on the soil water balance terms. In general, results demonstrate the importance of a proper control of the lysimeters bottom boundary conditions in studies that investigate the influence of climate change on soil functions and ecosystem variables by transferring lysimeter along climate gradients. [ABSTRACT FROM AUTHOR]

Agriculture faces several challenges including climate change and biodiversity loss while, at the same time, the demand for food, feed, biofuels, and fiber is increasing. Sustainable intensification aims to increase productivity and input-use efficiency while enhancing the resilience of agricultural systems to adverse environmental conditions through improved management and technology. Recent advances in sensing, machine learning, modeling, and robotics offer opportunities for novel smart digital technologies to enable sustainable intensification. However, developing smart digital technologies and putting them into agricultural practice, requires closing major research gaps, related in particular to (1) the utilization of multi-scale multi-sensor monitoring in space and time, (2) using artificial intelligence for linking process and data-driven methods, (3) improving decision making and intervention in plant production, and finally (4) modeling conditions and consequences of farmers acceptance. Closing these gaps requires an interdisciplinary approach. Here, we present a research agenda and steps forward to steer research efforts, highlighting research priorities, and identifying required interdisciplinary research collaboration. Following this agenda will leverage the full potential of smart digital technologies for sustainable crop production. [Display omitted] • Research gaps hinder smart digital technologies to enhance sustainable agriculture. • We present an interdisciplinary research agenda required to close these gaps. • Examples illustrate why closing these research gaps is important for sustainability. • The proposed research agenda helps steering research efforts and collaboration. [ABSTRACT FROM AUTHOR]

We used observed climate data, an ensemble of four GCM–RCM combinations (global and regional climate models) and the water balance model mGROWA to estimate present and future groundwater recharge for the intensively-used Thau lagoon catchment in southern France. In addition to a highly resolved soil map, soil moisture distributions obtained from SAR-images (Synthetic Aperture Radar) were used to derive the spatial distribution of soil parameters covering the full simulation domain. Doing so helped us to assess the impact of different soil parameter sources on the modelled groundwater recharge levels. Groundwater recharge was simulated in monthly time steps using the ensemble approach and analysed in its spatial and temporal variability. The soil parameters originating from both sources led to very similar groundwater recharge rates, proving that soil parameters derived from SAR images may replace traditionally used soil maps in regions where soil maps are sparse or missing. Additionally, we showed that the variance in different GCM–RCMs influences the projected magnitude of future groundwater recharge change significantly more than the variance in the soil parameter distributions derived from the two different sources. For the period between 1950 and 2100, climate change impacts based on the climate model ensemble indicated that overall groundwater recharge will possibly show a low to moderate decrease in the Thau catchment. However, as no clear trend resulted from the ensemble simulations, reliable recommendations for adapting the regional groundwater management to changed available groundwater volumes could not be derived. [ABSTRACT FROM AUTHOR]

Future food production is expected to be affected by climate change, because it will alter the crop water balance components, such as water storage, evapotranspiration and drainage. Variations in weather conditions could explain more than 50% of the variability of wheat yield. Higher temperatures and lower rainfall amounts mainly limit the actual evapotranspiration and reduce soil water storage, which in turn affect crop yield and water use efficiency. To study these effects, soil monoliths were moved to sites with contrasting climatic conditions (space for time concept) and monitored.In this contribution, yield, evapotranspiration, and changes in soil water storage from lysimeters soils for a period from 2011 until 2017 were analyzed. Data were obtained from a German wide monitoring network of lysimeter stations (TERENO-SOILCan), which was established across a rainfall and temperature transect, and lysimeters were transferred between the stations to subject them to different climate regimes. A uniform crop management (crop type, fertilizer, growth regulator, tillage, and use of pesticides) and crop rotation allows investigating the response of soil water storage and cropping water use efficiency for different soil types to a change in climate conditions.Main results showed a characteristic decrease of water availability of soils with a finer texture and smaller pores under drier and warmer climate conditions. The drier and warmer climate significantly increase crop yield and reduce at the same time evapotranspiration. This result confirms a more efficient use of water by plants under less optimal water availability in the root zone. [ABSTRACT FROM AUTHOR]

In 2008 the TERENO project was initiated with the general aim to conduct integrated and long-term observation studies of climate change and global change impacts on the terrestrial system across Germany. Central elements of the TERENO network are "terrestrial observatories" at the catchment scale which were selected in climate sensitive regions of Germany. Within these observatories small scale research facilities and test areas were placed in order to accomplish energy, water, carbon and nutrient process studies across the different compartments of the terrestrial environment. Following a hierarchical scaling approach (point-plot-field) these detailed information and the knowledge gained is transferred to the regional scale using integrated modelling approaches. In addition, mobile ground-based and airborne measurement platforms are used to monitor spatial patterns of dynamic processes at the regional scale. By combining the observatories within Germany, large-scale atmospheric feedbacks and impacts can be investigated, and thus a more pronounced general link to the atmospheric research community can be established. A data policy statement was developed in a common approach by all TERENO partners. As a rule, all TERENO data are freely accessible for the scientific community and a data portal facilitates the online data provision. In the ten years since its foundation, TERENO has become a key infrastructure in the German and international research landscape and has made a significant contribution to the development of integrated approaches in long-term environmental research. In this contribution the concept of TERENO will be illustrated with example key findings of the ongoing interdisciplinary research work aiming to advance the understanding of complex hydrological and biogeochemical processes and interactions. [ABSTRACT FROM AUTHOR]