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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]

Soil and water resources represent some of the great wealth with which nature has endowed our planet. The purpose of the paper is the study of these resources (soil and water), from Zăvoi commune, Caraș Severin county, considering the recent climate changes, which tend to negatively influence this area as well, with repercussions on the entire evolution plant development. The health of the soil and the purity of the water are essential to be able to talk about the quality of life, environmental factors (soil, water, climate, air, etc.) can influence the well-being and health of people. For the preparation of the paper, data obtained both from observations in the field and data taken from previous researches, including OSPA Caraș Severin, were used. The town of Zăvoi has a total area of 39600 ha, of which 53.66% (21249 ha) are agricultural land and 43.30%, i.e. 17145 ha, is forest. The diversity of the relief units made the area divided: the area of the hills, where luvosol and eutricambosol soils are found and which offer the possibility of a more varied agriculture and obtaining large productions; the hilly floor, which includes a mixed agricultural area, thanks to various soils, represented by regosols, lithosols, districambosols, prepodzols and antrosols, here the largest area of land is forested and the meadow area, where we find alluvial soils, along with stagnosols and gleosols, the most common being soils with excess phreatic moisture and requiring drainage improvement works. In this area, a number of plants are cultivated such as: wheat, corn, sunflower, oats, orzoaica, up to vegetables, potatoes and beets. The general capacity of these soils in terms of agricultural production capacity is medium. [ABSTRACT FROM AUTHOR]

Projections of West African Monsoon (WAM) precipitation are uncertain. To address this, an improved understanding of the mechanisms driving WAM precipitation change is needed to shed light on inter-model differences and aid model development. The full forcing of increased CO2 can be decomposed into different components such as the impact of ocean warming, or the direct radiative effect of increased CO2. This paper investigates such a decomposition, analysing the effect of a uniform 4K ocean warming whilst keeping atmospheric CO2 concentrations constant. The analysis highlights several mechanisms acting to decrease WAM precipitation over a range of timescales, from days after the abrupt ocean warming, to the long-term equilibrium response. The initial decrease in WAM precipitation is caused by warming and enhanced convection over the ocean, stabilising the atmosphere inland and disrupting the monsoon inflow at low levels. Later in the response (after about 5 days), the WAM precipitation is reduced through a strengthening of the shallow circulation over West Africa, associated with changes in the large-scale temperature gradients and a local warming of the atmosphere related to a soil moisture feedback mechanism over the Sahel. Finally, from around 20 days after the SST increase, the WAM precipitation is also reduced through changes in specific humidity gradients that lead to increased potency of dry air advection into the monsoon rainband. The analysis concludes by demonstrating that the processes affecting precipitation in the early stages of the response are also relevant to the long-term equilibrium response. [ABSTRACT FROM AUTHOR]

Simple Summary: In this paper, the differences in carbon sequestration microbial communities in different wetland types and their main influencing factors are investigated. It was found that Proteobacteria was the dominant group of carbon sequestration microorganisms in the marsh wetland and river source wetland, and Cyanobacteria was the dominant group of carbon sequestration microorganisms in the lakeside wetland. The α diversity, relative abundance of Proteobacteria and total carbon content of the marsh wetland were the highest, followed by the river source wetland and lakeside wetland. The soil temperature and moisture and the total carbon content were the most important factors affecting the structures of carbon-sequestering microbial communities. Compared with the riverhead and lakeside wetlands, the marsh wetland has the highest carbon storage. The soil carbon storage in the Qinghai–Tibet Plateau wetlands is affected by microbiota and wetland types, but the response mechanisms of carbon sequestration microorganisms on the Qinghai–Tibet Plateau to different wetland types are still poorly described. To explore the differences in carbon sequestration microbial communities in different wetlands and the main influencing factors, this study took a marsh wetland, river source wetland and lakeside wetland of Qinghai Lake as the research objects and used high-throughput sequencing to study the functional gene, cbbL, of carbon sequestration microorganisms. The results showed that the dominant bacterial group of carbon sequestration microorganisms in marsh and river source wetlands was Proteobacteria, and the dominant bacterial group in the lakeside wetland was Cyanobacteria. The alpha diversity, relative abundance of Proteobacteria and total carbon content were the highest in the marsh wetland, followed by the river source wetland, and they were the lowest in the lakeside wetland. In addition, the physical and chemical characteristics of the three wetland types were significantly different, and the soil temperature and moisture and total carbon content were the most important factors affecting the community structures of carbon-sequestering microorganisms. There was little difference in the total nitrogen contents between the marsh wetland and river source wetland. However, the total nitrogen content was also an important factor affecting the diversity of the carbon sequestration microbial community. In summary, the wetland type significantly affects the process of soil carbon sequestration. Compared with the riverhead and lakeside wetlands, the marsh wetland has the highest carbon storage. [ABSTRACT FROM AUTHOR]

The paper presents the study of bread wheat's chlorophyll content and grain yield traits under changing environmental conditions -- optimal water supply and simulated water-deficit conditions. Selecting 15 wheat cultivars from different regions (Russia, Kazakhstan, Kyrgyzstan, Tajikistan, Turkey, and CIMMYT) based on economically valuable characteristics became the specimens for the presented study that evaluated the SPAD indicators in correlation with the grain yield in bread wheat and determined the vital role of genotypes, environments, and genotype by environment interaction effects. The relationship between chlorophyll content and yield parameters under different growing conditions was also well-defined. The results revealed that ecosystems had more influence on the chlorophyll content than the wheat genotypes. Several wheat cultivars with soil moisture tolerance have gained identification, along with the correlation coefficient between chlorophyll content and grain yield under varied environmental conditions of water supply. The study validated the role of genotypes and environments in the manifestation of responses to stress conditions. [ABSTRACT FROM AUTHOR]

The paper presents a physically based mathematical model of the key hydrophysical processes of runoff formation at a catchment point over a long-term period. The model describes the freezing and thawing of soil, the formation and melting of the snow cover, the migration of moisture to the freezing front and the infiltration of rain and melt moisture, evaporation from snow, soil cover, vegetation, and water surface. Average daily values of meteorological parameters are used as initial information for mathematical modeling. The relevance of the study is caused by a need to reveal the main links between the processes of vertical heat and moisture exchange in soil and the environmental factors that determine their climate-driven nature. Using observational data from water balance stations, numerical experiments and an analysis of the influence of long-term variability of the key meteorological factors on evaporation from the land and water surface and on vertical moisture flows in soil were carried out. [ABSTRACT FROM AUTHOR]

Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root-zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exist for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations. While the number of available RZSM datasets is growing, they usually do not contain estimates of their uncertainty. In this paper we derive a long-term RZSM dataset (2002–2020) from the Copernicus Climate Change Service (C3S) surface soil moisture (SSM) COMBINED product via the exponential filter (EF) method. We identify the optimal value of the method's model parameter T , which controls the level of smoothing and delaying applied to the surface observations, by maximizing the correlation of RZSM estimates with field measurements from the International Soil Moisture Network (ISMN). Optimized T -parameter values were calculated for four soil depth layers (0–10, 10–40, 40–100, and 100–200 cm) and used to calculate a global RZSM dataset. The quality of this dataset is then globally evaluated against RZSM estimates of the ERA5-Land reanalysis. Results of the product comparison show satisfactory skill in all four layers, with the median Pearson correlation ranging from 0.54 in the topmost to 0.28 in the deepest soil layer. Temporally dynamic product uncertainties for each of the RZSM product layers are estimated by applying standard uncertainty propagation to SSM input data and by estimating structural uncertainties in the EF method from ISMN ground reference measurements taken at the surface and at varying depths. Uncertainty estimates were found to exhibit both realistic absolute magnitudes and temporal variations. The product described here is, to the best of our knowledge, the first global, long-term, uncertainty-characterized, and purely observation-based product for RZSM estimates up to 2 m depth. [ABSTRACT FROM AUTHOR]

Analyzing the future changes in runoff is crucial for efficient water resources management and planning in arid regions with large river systems. This paper investigates the future runoffs of the headwaters of the Tarim River Basin under different emission scenarios by forcing the hydrological model SWAT-Glacier using six regional climate models from the Coordinated Regional Downscaling Experiment (CORDEX) project. Results indicate that compared to the period of 1976~2005, temperatures are projected to increase by 1.22 ± 0.72 °C during 2036~2065 under RCP8.5 scenarios, with a larger increment in the south Tianshan mountains and a lower increment in the north Kunlun Mountains. Precipitation is expected to increase by 3.81 ± 14.72 mm and 20.53 ± 27.65 mm during 2036–2065 and 2066–2095, respectively, under the RCP8.5 scenario. The mountainous runoffs of the four headwaters that directly recharge the mainstream of the Tarim River demonstrate an overall increasing trend in the 21st century. Under the RCP4.5 and RCP8.5 scenarios, the runoff is projected to increase by 3.2% and 3.9% (amounting to 7.84 × 108 m3 and 9.56 × 108 m3) in 2006–2035. Among them, the runoff of the Kaidu River, which is dominated by rainfall and snowmelt, is projected to present slightly decreasing trends of 3~8% under RCP4.5 and RCP8.5 scenarios. For catchments located in the north Kunlun Mountains (e.g., the Yarkant and Hotan Rivers which are mix-recharged by glacier melt, snowmelt, and rainfall), the runoff will increase significantly, especially in summer due to increased glacier melt and precipitation. Seasonally, the Kaidu River shows a forward shift in peak flow. The summer streamflow in the Yarkant and Hotan rivers is expected to increase significantly, which poses challenges in flood risk management. [ABSTRACT FROM AUTHOR]

Key message: The integration of known and latent environmental covariates within a single-stage genomic selection approach provides breeders with an informative and practical framework to utilise genotype by environment interaction for prediction into current and future environments. This paper develops a single-stage genomic selection approach which integrates known and latent environmental covariates within a special factor analytic framework. The factor analytic linear mixed model of Smith et al. (2001) is an effective method for analysing multi-environment trial (MET) datasets, but has limited practicality since the underlying factors are latent so the modelled genotype by environment interaction (GEI) is observable, rather than predictable. The advantage of using random regressions on known environmental covariates, such as soil moisture and daily temperature, is that the modelled GEI becomes predictable. The integrated factor analytic linear mixed model (IFA-LMM) developed in this paper includes a model for predictable and observable GEI in terms of a joint set of known and latent environmental covariates. The IFA-LMM is demonstrated on a late-stage cotton breeding MET dataset from Bayer CropScience. The results show that the known covariates predominately capture crossover GEI and explain 34.4% of the overall genetic variance. The most notable covariates are maximum downward solar radiation (10.1%), average cloud cover (4.5%) and maximum temperature (4.0%). The latent covariates predominately capture non-crossover GEI and explain 40.5% of the overall genetic variance. The results also show that the average prediction accuracy of the IFA-LMM is 0.02 - 0.10 higher than conventional random regression models for current environments and 0.06 - 0.24 higher for future environments. The IFA-LMM is therefore an effective method for analysing MET datasets which also utilises crossover and non-crossover GEI for genomic prediction into current and future environments. This is becoming increasingly important with the emergence of rapidly changing environments and climate change. [ABSTRACT FROM AUTHOR]

Appropriate adaptation planning is contingent upon information about the potential future impacts of climate change, and hydrological impact assessments are of particular importance. The UKSCAPE-G2G datasets were produced, as part of the Natural Environment Research Council (NERC) UK-SCAPE (UK Status, Change and Projections of the Environment) programme, to contribute to this information requirement. They use the Grid-to-Grid (G2G) national-scale hydrological model configured for both Great Britain and Northern Ireland (and the parts of the Republic of Ireland that drain to rivers in NI). Six separate datasets are provided, for two sets of driving data – one observation-based (1980–2011) and one climate-projection-based (1980–2080) – for both river flows and soil moisture on 1 km × 1 km grids across Great Britain and Northern Ireland. The river flow datasets include grids of monthly mean flow, annual maxima of daily mean flow, and annual minima of 7 d mean flow (m 3 s -1). The soil moisture datasets are grids of monthly mean soil moisture content (m water / m soil), which should be interpreted as depth-integrated values for the whole soil column. The climate-projection-based datasets are produced using data from the 12-member 12 km regional climate model ensemble of the latest UK climate projections (UKCP18), which uses RCP8.5 emissions. The production of the datasets is described, along with details of the file format and how the data should be used. Example maps are provided, as well as simple UK-wide analyses of the various outputs. These suggest potential future decreases in summer flows, annual minimum 7 d flows, and summer/autumn soil moisture, along with possible future increases in winter flows and annual maximum flows. References are given for published papers providing more detailed spatial analyses, and some further potential uses of the data are suggested. The datasets are listed in Table 1. [ABSTRACT FROM AUTHOR]

Rapid Arctic warming is expected to result in widespread permafrost degradation. However, observations show that site-specific conditions (vegetation and soils) may offset the reaction of permafrost to climate change. This paper summarizes 43 years of interannual seasonal thaw observations from tundra landscapes surrounding the Marre-Sale on the west coast of the Yamal Peninsula, northwest Siberia. This robust dataset includes landscape-specific climate, active layer thickness, soil moisture, and vegetation observations at multiple scales. Long-term trends from these hierarchically scaled observations indicate that drained landscapes exhibit the most pronounced responses to changing climatic conditions, while moist and wet tundra landscapes exhibit decreasing active layer thickness, and river floodplain landscapes do not show changes in the active layer. The slow increase in seasonal thaw depth despite significant warming observed over the last four decades on the Yamal Peninsula can be explained by thickening moss covers and ground surface subsidence as the transient layer (ice-rich upper permafrost soil horizon) thaws and compacts. The uneven proliferation of specific vegetation communities, primarily mosses, is significantly contributing to spatial variability observed in active layer dynamics. Based on these findings, we recommend that regional permafrost assessments employ a mean landscape-scale active layer thickness that weights the proportions of different landscape types. [ABSTRACT FROM AUTHOR]

Soil moisture is a key variable in monitoring climate and an important component of the hydrological, carbon, and energy cycles. Satellite products ameliorate the sparsity of field measurements but are inherently limited to observing the near-surface layer, while water available in the unobserved root zone controls critical processes like plant water uptake and evapotranspiration. A variety of approaches exists for modelling root-zone soil moisture (RZSM), including approximating it from surface layer observations. While the number of available RZSM datasets is growing, they usually do not contain estimates of their uncertainty. In this paper we derive a long-term RZSM dataset (2002–2020) from the Copernicus Climate Change Service (C3S) surface soil moisture (SSM) COMBINED product via the exponential filter (EF) method. We identify the optimal value of the method’s model parameter T, which controls the level of smoothing and delaying applied to the surface observations, by maximizing the correlation of RZSM estimates with field measurements from the International Soil Moisture Network (ISMN). Optimized T-parameter values were calculated for four soil depth layers (0–10 cm, 10–40 cm, 40–100 cm, and 100–200 cm) and used to calculate a global RZSM dataset. The quality of this dataset is then globally evaluated against RZSM estimates of the ERA5-Land reanalysis. Results of the product comparison show satisfactory skill in all four layers with median Pearson correlation ranging from 0.54 in the topmost to 0.28 in the deepest soil layer. Temporally-dynamic product uncertainties for each of the RZSM product layers are estimated by applying standard uncertainty propagation to SSM input data and by estimating structural uncertainties of the EF method from ISMN ground reference measurements taken at the surface and in varying depths. Uncertainty estimates were found to exhibit both realistic absolute magnitudes as well as temporal variations. The product described here is, to our best knowledge, the first global, long-term, uncertainty-characterized, and purely observation-based product for RZSM estimates up to 2 m depth. [ABSTRACT FROM AUTHOR]

The paper presents the estimated changes in the soil water content, the total runoff, the sediment yield and the actual evapotranspiration for the small Bystra catchment in the east of Poland. The findings are based on the results of three simulations covering the years of 2041–2050. The simulations were based on a calibrated and validated SWAT model (2010–2017). The first variant covers just the climate change and the existing structure of soil cultivation for the three regional climate models supported by the EC-EARTH global climate model in the emission scenarios RCP4.5 and RCP8.5. Variants two and three are based on the first variant in terms of the changing climate. The second variant, however, involves placing a pond in each farm in the catchment, while the third variant involves designing huge reservoirs as a result of land consolidation. Variants two and three occur in five adaptation scenarios each. The first adaptation scenario (V2.1 and V3.1) involves only increasing the number of ponds on the farm or increasing the number of reservoirs for non-irrigated arable land crops, i.e., WWHT (winter cereals), BARL (spring cereals), CANP (rapeseed) and CRDY (other crops). The second adaptation scenario (V2.2 and V3.2) involves growing vegetables without irrigation (instead of cereals). The third adaptation scenario (V2.3 and V3.3) involves growing vegetables with irrigation (instead of cereals). The fourth adaptation scenario (V2.4 and V3.4) involves partial cultivation of vegetables and cereals. The fifth adaptation scenario (V2.5 and V3.5) involves partial cultivation of orchards and cereals. The adaptation scenarios of the irrigation of vegetables from deep water-bearing layers (second variant) or reservoirs (third variant) contribute to the increase in water content in the soil, especially in summer, in comparison with the adaptation scenarios for vegetable cultivation without irrigation. What is more, the actual evapotranspiration was higher in the adaptation scenarios involving irrigation than in scenarios without irrigation. It is known that the changes in water content in soil and the intensification of water erosion are gravely affected by modifications in crops and soil cultivation. A change from cereal cultivation to irrigated vegetable cultivation or orchards increased the water content in the soil in most climatic projections. However, the increase in the number of ponds in the second variant had little impact on the soil water content, actual evapotranspiration and overall runoff, while the erosion loss decreased. With the lower precipitation levels in the years 2041–2050 relative to 2010–2017, as presented in the emissive scenario RCP 4.5, the soil water content decreases by up to 14% for most variants. Total runoff for most variants will also be lower by 4–35%. The percentage change in sediment yield will fluctuate between −86% and 116%. On the other hand, the actual evapotranspiration for most variants will be higher. With higher precipitation levels in the years 2041–2050 relative to 2010–2017, as presented in the emissive scenario RCP 8.5, the soil water content changes slightly from −7% to +3%. Total runoff for most variants will also be higher by as much as 43%. Sediment yield for most scenarios may increase by 226%. The actual evapotranspiration for most variants will also be higher. Irrigation variants tend to increase soil available water while increasing evapotranspiration and total outflow in the catchment as compared to non-irrigated LULC. The largest increase in the soil water content is observed in most irrigation variants for RCP 4.5 (annual average 316–319 mm) (V2.3-V2.5, V3.2, and V3.3) and RCP 8.5 (annual average 326–327 mm) (V2.3-V2.5 and V3.3) as compared to V1 (BaU) (315 mm–RCP 4.5 and 324 mm–RCP 8.5) for the years 2041–2050. On the other hand, the lowest increase in soil water content is observed in the V3.5 variant, with an annual average of 292 mm for RCP 4.5 and an annual average of 311 mm for RCP 8.5. Thus, for future climate change scenarios, irrigation with water reservoirs (ponds and storage reservoirs) should be considered. The study proves the rationale behind building ponds in small catchments in order to increase water resources in a landscape and also to counteract adverse effects of climate changes, i.e., sediment outflow and surface water erosion. [ABSTRACT FROM AUTHOR]

Appropriate adaptation planning is contingent upon information about the potential future impacts of climate change, and hydrological impact assessments are of particular importance. The UKSCAPE-G2G datasets were produced, as part of the NERC UK-SCAPE programme, to contribute to this information requirement. They use the Grid-to-Grid (G2G) national-scale hydrological model configured for both Great Britain and Northern Ireland (and the parts of the Republic of Ireland that drain to rivers in NI). Six separate datasets are provided, for two sets of driving data -- one observation-based (1980-2011) and one climate projection-based (1980-2080) -- for both river flows and soil moisture on 1 km x 1 km grids across GB and NI. The river flow datasets include grids of monthly mean flow, annual maxima of daily mean flow, and annual minima of 7-day mean flow (m³s-1). The soil moisture datasets are grids of monthly mean soil moisture content (m water/m soil), which should be interpreted as depth-integrated values for the whole soil column. The climate projection-based datasets are produced using data from the 12-member 12km regional climate model ensemble of the latest UK climate projections (UKCP18), which uses RCP8.5 emissions. The production of the datasets is described, along with details of the file format, and how the data should be used. Example maps are provided, as well as simple UK-wide analyses of the various outputs. These suggest potential future decreases in summer flows, annual minimum 7-day flows, and summer/autumn soil moisture, along with possible future increases in winter flows and annual maximum flows. References are given for published papers providing more detailed spatial analyses, and some further potential uses of the data are suggested. [ABSTRACT FROM AUTHOR]

Surface soil moisture (SSM) is an important variable for controlling the energy exchange between earth's surface and atmosphere. Accurate estimation of the distribution of SSM and its dynamic changes is increasingly essential in the study of hydrology, ecology, agriculture, geological hazard monitoring, and global climate change. This paper presents a new model for SSM retrieval (named, KSSM) through assimilating soil porosity with a two-dimensional feature space composed of land surface temperature and vegetation index (LST-VI). The KSSM model takes into account the physical properties of soil porosity, so it is suitable for SSM retrieval of various soil types in different regions. The KSSM model was validated using the measured data, and a comparison analysis with other data was conducted. Through the sensitivity analysis, it is concluded that the error of SSM retrieved by the KSSM model is less than 0.04 m3 m−3 and the KSSM model is robust. High accuracy of volumetric SSM estimation, error within 10% compared with the measured data, can be achieved by the KSSM model without the need for an in-situ SSM. [ABSTRACT FROM AUTHOR]

Climate change will have an impact on not only flood magnitude but also on flood timing. This paper studies the shifting in flood timing at 6167 gauging stations from 1970 to 2010, globally. The shift in flood timing and its relationship with three influential factors (maximum 7-day precipitation, soil moisture excess, and snowmelt) are investigated. There is a clear global pattern in the mean flooding date: winter (Dec–Feb) across the western Coastal America, western Europe and the Mediterranean region, summer (Jun–Aug) in the north America, the Alps, Indian Peninsula, central Asia, Japan, and austral summer (Dec–Feb) in south Africa and north Australia area. The shift in flood timing has a trend from − 22 days per decade (earlier) to 28 days per decade (delayed). Earlier floods were found extensively in the north America, Europe and northeast Australia while delayed floods were prevailing in the Amazon, Cerrado, south Africa, India and Japan. Earlier flood timing in the north America and Europe was caused by earlier snowmelt while delayed extreme soil moisture excess and precipitation have jointly led to delayed floods around the monsoon zone, including south Africa, India and Japan. This study provides an insight on the shifting mechanism of flood timing, and supports decisions on the global flood mitigation and the impact from future climate change. [ABSTRACT FROM AUTHOR]

Regional climate projections indicate that European summer precipitation may change considerably in the future. Southern Europe can expect substantial drying while Northern Europe could actually become wetter. Model spread and internal variability in these projections are large, however, and unravelling the processes that underlie the changes is essential to get more confidence in these projections. Large-scale circulation change is one of the contributors to model spread. In this paper we quantify the role of future large-scale circulation changes to summer precipitation change, using a 16-member single-model ensemble obtained with the regional climate model RACMO2, forced by the global climate model EC-Earth2.3 and the RCP8.5 emission scenario. Using the method of circulation analogues three contributions to the future precipitation change are distinguished. The first is the precipitation change occurring without circulation change (referred to as the thermodynamic term). This contribution is characterised by a marked drying-to-wetting gradient as one moves north from the Mediterranean. The second contribution measures the effects of changes in the mean circulation. It has a very different spatial pattern and is closely related to the development of a region of high pressure (attaining its maximum west of Ireland) and the associated anti-cyclonic circulation response. For a large area east of Ireland including parts of western Europe, it is the major contributor to the overall drying signal, locally explaining more than 90% of the ensemble-mean change. In regions where the patterns overlap, the signal-to-noise ratio of the total change is either enhanced or reduced depending on their relative signs. Although the second term is expected to be particularly model dependent, the high-pressure region west of Ireland also appears in CMIP5 and CMIP6 ensemble-mean projections. The third contribution records the effects of changes in the circulation variability. This term has the smallest net contribution, but a relatively large uncertainty. The analogues are very good in partitioning the ensemble-mean precipitation change, but describe only up to 40% of the ensemble-spread. This demonstrates that other precipitation-drivers (SST, spring soil moisture etc.) will generally strongly influence trends in single climate realisations. This also re-emphasises the need for large ensembles or using alternative methods like the Pseudo Global Warming approach where signal to noise ratios are higher. Nevertheless, identifying the change mechanisms helps to understand the future uncertainties and differences between models. [ABSTRACT FROM AUTHOR]

Snow plays an important role in the water cycle and global climate change, and the accurate monitoring of changes in snow depth is an important task. However, monitoring snow properties is still challenging and unclear, particularly in the Tibetan Plateau, which has rough land and uneven terrain. The traditional monitoring methods have some limitations in monitoring snow depth changes, and the Global Navigation Satellite System-Reflectometry (GNSS-R) provides a new opportunity for snow monitoring. This paper employed data from the Cyclone Global Navigation Satellite System (CYGNSS) to discover the effect of snow properties. Firstly, the observations of CYGNSS were used to find the sensitive to snow properties, and the relationships between signal to noise ratio (SNR), leading edge slope (LES), surface reflectivity (SR), and snow depth were studied and analyzed, respectively. It is found that the correlation between the first two parameters and snow depth is poor, while SR can indicate the changes in snow depth, and is proposed as an indicator of SR change, namely, surface reflectivity–difference ratio factor (SR–DR factor). Furthermore, the long-time series data in the Tibetan Plateau (2018–2019) are used to analyze its effects on the time series of the SR–DR factor, while the influences of the soil freeze/thaw (F/T) process and soil moisture are excluded during the analysis. The results indicate that the SR–DR factor can be a good indicator and discriminator for snow depth. Our work shows that space-borne GNSS-R has the potential for the monitoring of snow properties. [ABSTRACT FROM AUTHOR]

Soil and water are some of the prime components of nature. The development of life depends directly and indirectly on the health and quality of the land. Regardless of its composition, the soil contains substances that allow the growth and development of many plant species and microorganisms. The increase in temperatures, the decrease in rainfall, and the applied agricultural technologies have contributed over the years to ruining the structure and components of the soil, which negatively affected its humidity. The paper aims to identify the type of tillage in the dry-farming system and the agricultural species cultivated, which can achieve optimal harvests without leaving the soil devoid of moisture. The amount of water in the soil in the agricultural year 2019-2020, although it was deficient, exceeded the value of the withering coefficient, thus allowing crops to grow. However, this was not enough to obtain rich harvests. [ABSTRACT FROM AUTHOR]

This paper introduces the Flexible Global Ocean‐Atmosphere‐Land System Model: Grid‐Point Version 3 (FGOALS‐g3) and evaluates its basic performance based on some of its participation in the sixth phase of the Coupled Model Intercomparison Project (CMIP6) experiments. Our results show that many significant improvements have been achieved by FGOALS‐g3 in terms of climatological mean states, variabilities, and long‐term trends. For example, FGOALS‐g3 has a small (−0.015°C/100 yr) climate drift in 700‐yr preindustrial control (piControl) runs and smaller biases in climatological mean variables, such as the land/sea surface temperatures (SSTs) and seasonal soil moisture cycle, compared with its previous version FGOALS‐g2 during the historical period. The characteristics of climate variabilities, for example, Madden‐Julian oscillation (MJO) eastward/westward propagation ratios, spatial patterns of interannual variability of tropical SST anomalies, and relationship between the East Asian Summer Monsoon and El Niño–Southern Oscillation (ENSO), are well captured by FGOALS‐g3. In particular, the cooling trend of globally averaged surface temperature during 1940–1970, which is a challenge for most CMIP3 and CMIP5 models, is well reproduced by FGOALS‐g3 in historical runs. In addition to the external forcing factors recommended by CMIP6, anthropogenic groundwater forcing from 1965 to 2014 was incorporated into the FGOALS‐g3 historical runs. Plain Language Summary: The sixth phase of the Coupled Model Intercomparison Project (CMIP6) is a crucial support for the sixth Assessment Report of Intergovernmental Panel on Climate Change (IPCC AR6) and will also provide important foundation for research in climate change in the next few years. This paper gives the description of FGOALS‐g3 model, its experiment configures, and the experiments conducted according to the experimental design of CMIP6 and evaluates the preliminary performance of model simulation. This work offers references to CMIP6 data users and provides enormous output data sets for assessing and understanding climate change. Key Points: This paper describes FGOALS‐g3 and its experiment design for CMIP6Historical, preindustrial, and scenario simulations are evaluatedClimate drift is small in preindustrial simulation, and mean climate and climate variabilities at different temporal scales are realistic in historical runs [ABSTRACT FROM AUTHOR]

Background and Aims Foliar water uptake has recently been suggested as a possible mechanism for the restoration of hydraulically dysfunctional xylem vessels. In this paper we used a combination of ecophysiological measurements, X-ray microcomputed tomography and cryo-scanning electron microscopy during a drought treatment to fully evaluate this hypothesis. Key Results Based on an assessment of these methods in beech (Fagus sylvatica L.) seedlings we were able to (1) confirm an increase in the amount of hydraulically redistributed water absorbed by leaves when the soil water potential decreased, and (2) locate this redistributed water in hydraulically active vessels in the stem. However, (3) no embolism repair was observed irrespective of the organ under investigation (i.e. stem, petiole or leaf) or the intensity of drought. Conclusions Our data provide evidence for a hydraulic pathway from the leaf surface to the stem xylem following a water potential gradient, but this pathway exists only in functional vessels and does not play a role in embolism repair for beech. [ABSTRACT FROM AUTHOR]

Changing pathways of soil moisture loss, either directly from soil (evaporation) or indirectly through vegetation (transpiration), are an indicator of ecosystem and land hydrological cycle responses to the changing climate. Based on the ratio of transpiration to evaporation, this paper investigates soil moisture loss pathway changes across China using five reanalysis-type datasets for the past and Coupled Model Intercomparison Project Phase 6 (CMIP6) climate projections for the future. The results show that across China, the ratio of vegetation transpiration to soil evaporation has generally increased across vegetated land areas, except in grasslands and croplands in north China. During 1981–2014, there was an increase by 51.4 percentage points (pps, p < 0.01) on average according to the reanalyses and by 42.7 pps according to 13 CMIP6 models. The CMIP6 projections suggest that the holistic increasing trend will continue into the twenty-first century at a rate of 40.8 pps for SSP585, 30.6 pps for SSP245, and −1.0 pps for SSP126 shared socioeconomic pathway scenarios for the period 2015–2100 relative to 1981–2014. Major contributions come from the increases in vegetation transpiration over the semiarid and subhumid grasslands, croplands, and forestlands under the influence of increasing temperatures and prolonged growing seasons (with twin peaks in May and October). The future increasing vegetation transpiration ratio in soil moisture loss implies the potential of regional greening across China under global warming and the risks of intensifying land surface dryness and altering the coupling between soil moisture and climate in regions with water-limited ecosystems. [ABSTRACT FROM AUTHOR]

The periodicities of the climate change have long been explored by researchers not only because they reflect the inherent characteristics of the climate systems, but also because they are the foundations of climate-change predictability. This paper reports the periodicities of the hydroclimate variations reconstructed from a lacustrine sequence at Tiancun section (TC section) in the Luoyang Basin within the Central Plains of China and the sequence covers the first half of the Holocene. Our reconstruction shows that the hydroclimate variations at the TC section during the period from ∼10,135 and ∼ 5890 cal. yr BP were well corresponding with the effective soil moisture variations recorded by the stalagmite δ13C sequence at the Magou Cave. This corresponding relationship suggests that when the effective soil moisture increases (i.e., more negative δ13C values), the ratio of evaporation over precipitation in the paleolake at the TC section decreased, resulting in lower CaCO 3 content. It also suggests that when the effective soil moisture increases, more inflowing water entered the paleolake, resulting in coarser sediments. Our reconstruction also shows that the hydroclimate variations or lake level variations in the Luoyang Basin were characterized by millennial-scale quasi-periodicities that were most likely paced by the changes in ITCZ (Inter-tropical Convergent Zone) position and also by alterations in ENSO-like phase. And, both (ITCZ and ENSO) were most likely regulated by the solar activity. Our further analysis shows that the hydroclimate in the Luoyang Basin also experienced centennial-scale variations. Specifically, the grain size data express the following cycles: 692-year, 538-year, 217-year, 170-year and 123-year, all at the 99% confidence level. And, the CaCO 3 content data express the following cycles: 202-year, 184-year, 169-year and 85-year, all at the 99% confidence level. These cycles are approximately coincident with the widely-reported solar-activity cycles. • This paper reports the periodicities of the hydroclimate variations reconstructed from a lacustrine sequence in the Central Plains of China and the sequence covers the first half of the Holocene. • The hydroclimate variations were primarily paced by changes in ITCZ position and also by alterations in ENSO-like phase. And, both (ITCZ and ENSO) were most likely regulated by solar activity. • The centennial-scale hydroclimate variations were approximately coincident with the widely-reported solar-activity cycles. [ABSTRACT FROM AUTHOR]

The geographical area between the Danube and the Black Sea, Dobrogea, represents a region with the highest aridity indices. The average precipitation in the period 1961-2016 was 464 mm. Climate changes in recent years have accentuated this phenomenon and, due to this, low production levels of 1-2 tons/ha were achieved on large areas of corn. In the year 2022/2023, over 40,000 ha cultivated with corn in Constanta county were deeply affected by the lack of rainfalls, high temperatures and long and severe drought. In these particularly dry conditions, sorghum becomes an essential alternative. This study aimed to continue the experiments with sorghum hybrids which have been carried out during the last 15 years at SPORT AGRA Ltd from Amzacea Village, Constanta County, in order to adapt the technologies to climate changes. The novelty of this research is that the adapted technologies include, among other things, the following elements: changing the planting period by approximately 25-30 days compared to the recommendations of classical technologies (planting starting from the first decade of May in order to use the moisture in the soil layer at the depth of seed incorporation 4-5 cm.), the use of early hybrids in order to overcome the periods of heat that in this area start from mid-June, the use of technological means of crop protection that include pre- and post-emergent herbicides, seed treatment prior to planting. In these conditions of development of non-irrigated sorghum technology, we propose planting this crop earlier (25-30 days compared to classic technology). In this way, the sorghum will benefit from the water reserve accumulated during the fall of the previous year. The productions of the sorghum hybrids used in the observation research fields were over 10 to/ha in most of the tested hybrids. [ABSTRACT FROM AUTHOR]

Unfavourable trends have been identified in the evolution of climate factors (temperatures, precipitation, etc.) over the past years, with a direct impact on the vegetative and productive potential of the vine. This calls for a reassessment of climate resources and the adaptation of cultivation technologies to the new conditions. Our paper analyses the climate data recorded between 1991 and 2020 for the Iaşi vineyard ecosystem, which allowed for the calculation of a series of bioclimatic indices and coefficients, deviations from the multiannual average values, soil moisture dynamics, and their influence on development of vegetation phenophases and grape production. The increasing tendency of the average annual temperature and the decreasing amounts of precipitation registered point to a marked warming of the vineyard climate, especially after 2000. The high values of temperatures, corroborated with the soil water deficit, determined an intensification of the atmospheric and pedological drought, a shift in vegetation phenophases, shortened development periods and a forced ripening of grapes, with a negative impact on yields, which fluctuated from one year to another. The analysis of the ecoclimate conditions over the past 30 years has highlighted an alternation of periods, a colder and wetter one between 1991 and 2006, and a warmer and dried one between 2007 and 2020. [ABSTRACT FROM AUTHOR]

Canopy phenology is sensitive to variability in local environmental settings. In temperate climates, urban phenological processes and their determinants are relatively well understood. Equivalent understanding of processes in tropical urban settings is, however, less resolved. In this paper, we explore the influence of local urban environmental characteristics (that is, degree of urbanization, land cover and urban climate) on canopy phenology of two deciduous tree species (Jacaranda mimosifolia, n = 48, and Tabebuia rosea, n = 24) in a tropical city (Kampala, Uganda). Our study design involved ground monitoring and field sampling in 2017, with a focus on the dry season. We found that both species experienced significantly higher rates of canopy cover decline in heavily built-up neighborhoods (p < 0.05 for both species). Moreover, Jacaranda was more sensitive to differences in the degree of urbanization than Tabebuia, both in terms of total percentage tree canopy cover (p < 0.01) and net leaf loss (p < 0.05). Total percentage tree canopy cover for Jacaranda declined with increasing proportion of impervious cover (that is, roads and paved cover) and was positively related to relative humidity (p < 0.01), a variable correlated with soil moisture. Net leaf loss in Jacaranda increased with the decreasing proportion of pervious land cover and as nighttime air temperature increased (p < 0.01). In contrast, land cover and urban climate had no significant influence on either measure of phenological traits for Tabebuia. These results provide new evidence of the effect of urbanization on canopy phenology of different tree species in the tropics. Such knowledge offers new insights into the spatial and temporal differences in the physiological functional traits of trees and also serves as a proxy for possible species responses under future climate change. [ABSTRACT FROM AUTHOR]

Further, the vegetal sector encounters serious problems and is often dependent on a number of factors such as climate, whether the crops are irrigated or not. This factors can make a difference between gain and loss. There are other factors such as economic factors where this market is extremely volatile, but also a number of other factors described in this paper. This case study was carried out on a sample of 60 farms with a vegetal profile showing the level of this region compared to the national average, identifying the main strengths and weaknesses that farmers in this region have. Account should also be taken of the marketing capacity of agricultural crop production. Interviewing the representatives of 60 agricultural crops we could analyse a number of relevant issues for this sector through which we can contribute with a series of solutions and recommendations. [ABSTRACT FROM AUTHOR]

It is now well established that our warming planet is experiencing changes in extreme storms and floods, resulting in a need to better specify hydrologic design guidelines that can be projected into the future. This paper attempts to summarize the nature of changes occurring and the impact they are having on the design flood magnitude, with a focus on the urban catchments that we will increasingly reside in as time goes on. Two lines of reasoning are used to assess and model changes in design hydrology. The first of these involves using observed storms and soil moisture conditions and projecting how these may change into the future. The second involves using climate model simulations of the future and using them as inputs into hydrologic models to assess the changed design estimates. We discuss here the limitations in both and suggest that the two are, in fact, linked, as climate model projections for the future are needed in the first approach to form meaningful projections for the future. Based on the author's experience with both lines of reasoning, this invited commentary presents a theoretical narrative linking these two and identifying factors and assumptions that need to be validated before implementation in practice. This article is part of a discussion meeting issue 'Intensification of short-duration rainfall extremes and implications for flash flood risks'. [ABSTRACT FROM AUTHOR]

One of the greatest challenges in the 21st century is the question of how humanity will adapt to a changing climate to continue producing food at the production levels that will be necessary to feed an increasing global population while conserving soil and water resources. While there are political, social and economic factors that impact agricultural development, this paper will not be focusing on those factors, instead focusing on the potential use of cover crops as a nutrient management tool, a soil and water conservation practice, and a good approach to adapting to a changing climate. The potential of using cover crops for climate change adaptation and mitigation will be reviewed. Cover crops are a key tool that could contribute to increased yields, conservation of surface and groundwater quality, reduced erosion potential, sequestration of atmospheric carbon (C), and improved soil quality and health across the tropics. However, there are a lot of research gaps, and there is a need for additional research about the potential use of cover crops for soil, human, and animal health, as well as a need for an open-access data information system about research on cover crops in the tropics. While cover crops show a lot of promise, they are not a silver bullet, and in some circumstances, they can also contribute to reduced yields. We evaluated the use of cover crops and we ranked the different ways that cover crops can contribute to climate change adaptation, on a scale ranging from very low potential to contribute to climate change adaptation to very high potential. For example, cover crops have very high potential to reduce erosion generated by a changing climate in humid systems. On average, cover crops appear to be a good practice for climate change adaptation and mitigation across the tropics, and nutrient managers, agronomists, and soil and water conservation practitioners could add them to their management toolbox for different regions of the tropics. The 4 Rs of cover crops should be applied when using this tool (the right cover crop, the right timing of placement, the right timing of killing, and the right management). [ABSTRACT FROM AUTHOR]

Variability in soil moisture has implications for regional terrestrial environments under a warming climate. This paper focuses on the spatiotemporal variability in the intra-annual persistence of soil moisture in China using the fifthgeneration reanalysis dataset by the European Centre for Medium-Range Weather Forecasts for the period 1979-2018. The results show that in China, the mean intra-annual persistence in the humid to arid zones increased from 60 to 115 days in the lower layer but decreased from 19 to 13 days and from 25 to 14 days in the upper and root layers, respectively. However, these changes were strongly attenuated in extremely dry and wet regions due to the scarcity of soil moisture anomalies. Large changes in persistence occurred in the lower soil layer in dryland areas, with a mean difference of up to 40 days between the 2010s and the 1980s. Overall increasing trends dominated the large-scale spatial features, despite regional decreases in the eastern arid zone and the North and Northeast China plains. In the root layer, the two plains experienced an expanded decrease while on the Tibetan Plateau it was dominated by decadal variability. These contrasting changes between the lower and root layers along the periphery of the transition zone was a reflection of the enhanced soil hydrological cycle in the root layer. The enhanced persistence in drylands lower layer is an indication of the intensified impacts of soil moisture anomalies (e.g., droughts) on terrestrial water cycle. These findings may help the understanding of climate change impacts on terrestrial environments. [ABSTRACT FROM AUTHOR]

Soil moisture and soil temperature, reflecting a synthetic climate regime, are vitally important for climate change assessments and adaption. As historical in situ measurements of soil states are extremely scarce and spatially uneven, reanalysis products play an increasingly important role in filling these gaps. The focus of this paper is on water–heat covariations in reanalysis products and a joint evaluation of soil moisture and soil temperature in five widely used atmospheric and land reanalyses is presented using in situ observations from 25 networks during various periods from 1979 to 2017. At the network scale, the five reanalyses show statistically significant correlations with observations, and the European Centre for Medium‐Range Weather Forecasts ERA5 shows higher skills than the other four products and a significant improvement over its predecessor. The National Centers for Environmental Prediction Climate Forecast System Reanalysis performs better in terms of long‐term trends. The most skilful signals in the five reanalyses are the seasonal cycles, with correlation coefficients of over 0.9. However, long‐term trends are substantially weaker than the observed trends and still tend to perform poorly over the high latitudes during cold seasons. Soil temperature reanalyses show even better skills, with mean correlation coefficients over 0.9 between anomalies; ERA5 shows enhanced annual ranges toward the high latitudes and altitudes. A joint evaluation of soil temperature and soil moisture showed physically consistent water–heat covariations in the soil in conjunction with atmospheric fluxes during the growing season over the Northern Hemisphere. This report suggests a good future for reanalysis products and their potential role in land surface climate change assessments. [ABSTRACT FROM AUTHOR]

Irrigated areas, mainly in arid regions, are threatened by salinization processes. Climate change inducing temperature rise and rainfall depletion are expected to enhance these processes. Numerical models are often used to predict salinization in the root zone as well as water and solute fluxes reaching groundwater. Climatic data, mainly rainfall, have an important influence on the estimation of those fluxes. The present paper studies the impact of rainfall structure and climate change on soil and groundwater salinization. Soil samples were collected in three drip-irrigated plots in Korba semi-arid coastal plain in Tunisia during dry and wet seasons. Collected field data (water contents and soil salinities) are used to define the initial solute and flow conditions and to estimate the soil hydraulic parameters for numerical modeling. Daily rainfall structure and annual rainfall transition under both Markov Chain and climate change (RCP4.5 and RCP8.5) are assessed. Different climatic scenarios are then introduced as boundary conditions in HYDRUS-1D, to test the influence of rainfall on the salinity evolution in the soil profile and groundwater. Results show that both annual rainfall amounts and daily structure have an impact on soil concentrations and solute fluxes quantities reaching groundwater. The influence of rainfall paths is more important for larger unsaturated zone thickness when considering the dry and median rainfall conditions. Climate change scenarios show significant accumulation of salts in the root zone implying the imperative use of adequate irrigation practices. [ABSTRACT FROM AUTHOR]

Changes in soil electrical parameters can affect the distribution of earth potential in high-voltage direct-current (HVDC) ground electrodes when climatic conditions changes. This paper proposes a model to describe the relationship between surface-layer soil moisture and surface-layer soil resistivity under short-term climatic influence, by using image recognition technology. Based on the relatively stable resistivity of lower soil layers, a soil model more reflective of the actual operating conditions is established for soils near the ground electrode, and a finite element method is adopted to calculate the earth-surface potential (ESP). The experimental results indicate the following: (1) Compared with other measurement methods, image recognition of surface soil resistivity is a low-cost, real-time, online, and accurate method; and (2) changes in surface-layer soil moisture affect both ESP and step voltage. These effects are large in the case of high resistivity for the soil layer where the ground electrode is buried. This large fluctuation in step voltage particularly results in a potential safety hazards during ground electrode operation. Therefore, in order to ensure personal safety and obtain more accurate electrical parameters, it is necessary to consider the effect of natural climate on the soil surface resistivity. Finally, the value of the step voltage can be observed using image recognition, this also provides a new method for the safety monitoring of the DC ground electrode. [ABSTRACT FROM AUTHOR]

This paper demonstrates a climate change impact study on the hydrological process of a data-scarce Greek watershed. The Soil and Water Assessment Tool (SWAT) and, particularly, the ArcSWAT interface was used for the watershed simulation. The ERA-Interim reanalysis climate data regarding the period from 1981 to 2000 were used for the historical simulation of the watershed. The ArcSWAT simulated data were evaluated against the observed discharge data for the periods with the available data. The statistical evaluation confirmed the ArcSWAT model's capability in simulating the hydrological process of the research area. The climate change consequences on the hydrological components of the research area until the end of the twenty-first century were estimated by driving the ArcSWAT model with the Regional Climate Model Version 4 (RegCM4) forcing data under the extreme RCP 8.5 scenario, namely the simulations of the MPI and HadGEM2 general circulation models (GCMs), resulted from the spatio-temporal kriging approach. Based on the results, the increase in the minimum and the maximum temperature contributed to an increase in the actual evapotranspiration and the surface runoff. In contrast, the temperature increase caused a reduction in the infiltration. An increase (reduction) in the precipitation led to an increase (reduction) in the hydrological components. The climate change impact analysis of the Greek watershed showed that not only the precipitation changes but the temperature changes as well directly influence the water balance components of the research area and particularly the infiltration. [ABSTRACT FROM AUTHOR]

After the hot and very dry autumn of 2019, which ended, from a pluviometric point of view, with a secondary rainfall maximum in November, the 2019-2020 winter was overall very warm with a general annual average of 2.91°C and a 3.86°C deviation compared to normal values. December 2019 was hot and very dry. January was hot, and, from a pluviometric point of view, it was excessively dry. February was warm as a whole and excessively dry, but the water supply in the soil remained almost optimal due to the rainfall in November. The climate variability of this winter was particularly high, and the warming continued although the solar activity was at a minimum and the El Niño climatic process was absent. At the level of Romania, the 2019-2020 winter was the second warmest winter in the history of climate records and so far, the first being 2006-2007, and the third 2015-2016, which is also valid for Oltenia. The paper is part of an extensive series of studies on climate variability in southwestern Romania and climate change at the regional level and is useful to all those interested in climate issues and its evolution in this part of Romania. [ABSTRACT FROM AUTHOR]

[Display omitted] • Droughts and floods are increasing worldwide. • Changes in soil moisture affect the soil microbiome. • Climate change affects the soil environment. • Changes in the soil environment affect crop production. • Drought and floods have a negative impact on agriculture. Climate change is progressing and is already visible to the naked eye around the world. Hydrological events associated with climate change, i.e. floods and droughts, have reached extreme levels in recent years. Researchers warn that these phenomena will continue to intensify. According to recent reports, the number of extreme weather events, including hydrological phenomena, has increased by 60% in Europe over the last three decades. Both water shortages and water surpluses affect the soil environment and its functions. This in turn has a direct impact on crops and agriculture. For example, in the US alone, droughts and floods were responsible for more than 70% of the decline in cereal yields in 2011 alone. However, the soil environment is a complex ecosystem that is not yet fully understood, making it difficult to predict the impact of climate change on its quality and functioning. In this paper, we discuss the effects of floods and droughts on the soil microbiome and the implications of these changes for agriculture. We suggest that changes in soil moisture are an important factor affecting crop growth and yield, which is of great importance for global food security. [ABSTRACT FROM AUTHOR]

The global temperature has been increasing over the years due to climate change that, directly or indirectly, affects water and energy consumptions in the agriculture sector. The application of mulching practices reduces soil evaporation, conserves soil moisture, suppresses weed growth, controls soil structure and temperature, influences soil micro-organisms, and is aesthetically pleasing. This study has reviewed 189 published research papers, which described the effects of various mulching materials and methods on soil and environment that influence crop productivity. This paper describes the extent of influence of different mulching materials and methods on the hydrothermal environment of soils. It is imperative to know the processes that control soil environments under various mulching conditions and the effects of mulching materials on crop yield, productivity and water use efficiency. These issues of mulching are the prime concerns of this review study. Plastic mulching materials have a greater importance than the organic ones to control soil environment and increase crop yield. But, the organic mulching materials are inexpensive and environment friendly. The selection of an appropriate mulching material is, however, guided by crop type, crop management practices and climatic conditions. Future research is needed on the effects of low-cost biodegradable mulching materials on microclimate modifications, soil biota, soil fertility, crop growth and crop yields. [ABSTRACT FROM AUTHOR]

The SECHIBA module of the ORCHIDEE land surface model describes the exchanges of water and energy between the surface and the atmosphere. In the present paper, the adjoint semi-generator software called YAO was used as a framework to implement a 4D-VAR assimilation scheme of observations in SECHIBA. The objective was to deliver the adjoint model of SECHIBA (SECHIBA-YAO) obtained with YAO to provide an opportunity for scientists and end users to perform their own assimilation. SECHIBA-YAO allows the control of the 11 most influential internal parameters of the soil water content, by observing the land surface temperature or remote sensing data such as the brightness temperature. The paper presents the fundamental principles of the 4D-VAR assimilation, the semi-generator software YAO and a large number of experiments showing the accuracy of the adjoint code in different conditions (sites, PFTs, seasons). In addition, a distributed version is available in the case for which only the land surface temperature is observed. [ABSTRACT FROM AUTHOR]

Abstract Soil moisture (SM) is a key state variable in understanding the climate system through its control on the land surface energy, water budget partitioning, and the carbon cycle. Monitoring SM at regional scale has become possible thanks to microwave remote sensing. In the past two decades, several satellites were launched carrying on board either radiometer (passive) or radar (active) or both sensors in different frequency bands with various spatial and temporal resolutions. Soil moisture algorithms are in rapid development and their improvements/revisions are ongoing. The latest SM retrieval products and versions of products that have been recently released are not yet, to our knowledge, comprehensively evaluated and inter-compared over different ecoregions and climate conditions. The aim of this paper is to comprehensively evaluate the most recent microwave-based SM retrieval products available from NASA's (National Aeronautics and Space Administration) SMAP (Soil Moisture Active Passive) satellite, ESA's led mission (European Space Agency) SMOS (Soil Moisture and Ocean Salinity) satellite, ASCAT (Advanced Scatterometer) sensor on board the meteorological operational (Metop) platforms Metop-A and Metop-B, and the ESA Climate Change Initiative (CCI) blended long-term SM time series. More specifically, in this study we compared SMAPL3 V4, SMOSL3 V300, SMOSL2 V650, ASCAT H111, and CCI V04.2 and the new SMOS-IC (V105) SM product. This evaluation was achieved using four statistical scores: Pearson correlation (considering both original observations and anomalies), RMSE, unbiased RMSE, and Bias between remotely-sensed SM retrievals and ground-based measurements from >1000 stations from 17 monitoring networks, spread over the globe, disseminated through the International Soil Moisture Network (ISMN). The analysis reveals that the performance of the remotely-sensed SM retrievals generally varies depending on ecoregions, land cover types, climate conditions, and between the monitoring networks. It also reveals that temporal sampling of the data, the frequency of data in time and the spatial coverage, affect the performance metrics. Overall, the performance of SMAP and SMOS-IC products compared slightly better with respect to the ISMN in situ observations than the other remotely-sensed products. Highlights • Performances of SMOS, SMAP, CCI, and ASCAT soil moisture products were evaluated against ISMN datasets. • High performances of all products were found over Africa and Australia. • Performances of SMOS, SMAP, CCI, and ASCAT are complementary depending on the evaluation protocol, climate and vegetation. • SMAP and SMOS-IC follow slightly better the temporal dynamics of in situ observations. [ABSTRACT FROM AUTHOR]

Active and passive microwave signatures respond differently to the land surface and provide complementary information on the characteristics of the observed scenes. The objective of this paper is to explore the synergy of active radar and passive radiometer observations at the same spatial scale to constrain a discrete radiative transfer model, the Tor Vergata (TVG) model, to gain insights into the microwave scattering and emission mechanisms over grasslands. The TVG model can simultaneously simulate the backscattering coefficient and emissivity with a set of input parameters. To calibrate this model, in situ soil moisture and temperature data collected from the Maqu area in the northeastern region of the Tibetan Plateau, interpolated leaf area index (LAI) data from the Moderate Resolution Imaging Spectroradiometer LAI eight-day products, and concurrent and coincident Soil Moisture Active Passive (SMAP) radar and radiometer observations are used. Because this model needs numerous input parameters to be driven, the extended Fourier amplitude sensitivity test is first applied to conduct global sensitivity analysis (GSA) to select the sensitive and insensitive parameters. Only the most sensitive parameters are defined as free variables, to separately calibrate the active-only model (TVG-A), the passive-only model (TVG-P), and the active and passive combined model (TVG-AP). The accuracy of the calibrated models is evaluated by comparing the SMAP observations and the model simulations. The results show that TVG-AP can well reproduce the backscattering coefficient and brightness temperature, with correlation coefficients of 0.87, 0.89, 0.78, and 0.43 and root-mean-square errors of 0.49 dB, 0.52 dB, 7.20 K, and 10.47 K for $\sigma _{\mathrm{ HH}}^{o} $ , $\sigma _{\mathrm{ VV}}^{o} $ , $T_{\mathrm {BH}}$ , and $T_{\mathrm {BV}}$ , respectively. In contrast, TVG-A and TVG-P can only accurately model the backscattering coefficient and brightness temperature, respectively. Without any modifications of the calibrated parameters, the error metrics computed from the validation data are slightly worse than those of the calibration data. These results demonstrate the feasibility of the synergistic use of SMAP active radar and passive radiometer observations under the unified framework of a physical model. In addition, the results demonstrate the necessity and effectiveness of applying GSA in model optimization. It is expected that these findings can contribute to the development of model-based soil moisture retrieval methods using active and passive microwave remote sensing data. [ABSTRACT FROM AUTHOR]

The European Space Agency's Climate Change Initiative for Soil Moisture (ESA CCI SM) merging algorithm generates consistent quality-controlled long-term (1978–2018) climate data records for soil moisture, which serves thousands of scientists and data users worldwide. It harmonises and merges soil moisture retrievals from multiple satellites into (i) an active-microwave-based-only product, (ii) a passive-microwave-based-only product and (iii) a combined active–passive product, which are sampled to daily global images on a 0.25∘ regular grid. Since its first release in 2012 the algorithm has undergone substantial improvements which have so far not been thoroughly reported in the scientific literature. This paper fills this gap by reviewing and discussing the science behind the three major ESA CCI SM merging algorithms, versions 2 (https://doi.org/10.5285/3729b3fbbb434930bf65d82f9b00111c; Wagner et al., 2018), 3 (https://doi.org/10.5285/b810601740bd4848b0d7965e6d83d26c; Dorigo et al., 2018) and 4 (https://doi.org/10.5285/dce27a397eaf47e797050c220972ca0e; Dorigo et al., 2019), and provides an outlook on the expected improvements planned for the next algorithm, version 5. [ABSTRACT FROM AUTHOR]

The Regional Atmospheric Modeling System (RAMS) is being used for different and diverse purposes, ranging from atmospheric and dispersion of pollutants forecasting to agricultural meteorology and ecological modelling as well as for hydrological purposes, among others. The current paper presents a comprehensive assessment of the RAMS forecasts, comparing the results not only with observed standard surface meteorological variables, measured at FLUXNET stations and other portable and permanent weather stations located over the region of study, but also with non-standard observed variables, such as the surface energy fluxes, with the aim of evaluating the surface energy budget and its relation with a proper representation of standard observations and key physical processes for a wide range of applications. In this regard, RAMS is assessed against in-situ surface observations during a selected period within July 2011 over Eastern Spain. In addition, the simulation results are also compared with different surface remote sensing data derived from the Meteosat Second Generation (MSG) Spinning Enhanced Visible and Infrared Imager (SEVIRI) (MSG-SEVIRI) as well as the uncoupled Land Surface Models (LSM) Global Land Data Assimilation System (GLDAS). Both datasets complement the available in-situ observations and are used in the current study as the reference or ground truth when no observations are available on a selected location. Several sensitivity tests have been performed involving the initial soil moisture content, by adjusting this parameter in the vertical soil profile ranging from the most superficial soil layers to those located deeper underground. A refined adjustment of this parameter in the initialization of the model has shown to better represent the observed surface energy fluxes. The results obtained also show an improvement in the model forecasts found in previous studies in relation to standard observations, such as the air temperature and the moisture fields. Therefore, the application of a drier or wetter soil in distinct soil layers within the whole vertical soil profile has been found to be crucial in order to produce a better agreement between the simulation and the observations, thus reiterating the determining role of the initial soil moisture field in mesoscale modelling, but in this case considering the variation of this parameter vertically. [ABSTRACT FROM AUTHOR]

The design of reclamation soil covers at oil sands mines in northern Alberta, Canada, has been conventionally based on the calibration of soil–vegetation–atmosphere transfer (SVAT) models against field monitoring observations collected over several years, followed by simulations of long-term performance using historical climate data. This paper evaluates the long-term water balances for reclamation covers on two oil sands landforms and three natural coarse-textured forest soil profiles using both historical climate data and future climate projections. Twenty-first century daily precipitation and temperature data from CanESM2 were downscaled based on three representative concentration pathways (RCPs) employing a stochastic weather generator [Long Ashton Research Station Weather Generator (LARS-WG)]. Relative humidity, wind speed, and net radiation were downscaled using the delta change method. Downscaled precipitation and estimated potential evapotranspiration were used as inputs to simulate soil water dynamics using physically based models. Probability distributions of growing season (April–October) actual evapotranspiration (AET) and net percolation (NP) for the baseline and future periods show that AET and NP at all sites are expected to increase throughout the twenty-first century regardless of RCP, time period, and soil profile. Greater increases in AET and NP are projected toward the end of the twenty-first century. The increases in future NP at the two reclamation covers are larger (as a percentage increase) than at most of the natural sites. Increases in NP will result in greater water yield to surface water and may accelerate the rate at which chemical constituents contained within mine waste are released to downstream receptors, suggesting these potential changes need to be considered in mine closure designs. [ABSTRACT FROM AUTHOR]

The MaRIUS‐G2G datasets were produced for the MaRIUS (Managing the Risks, Impacts and Uncertainties of drought and water Scarcity) project, using the Grid‐to‐Grid (G2G) national‐scale hydrological model for Great Britain. There are six separate datasets, with each of three combinations of meteorological driving data (two observation‐based and one from climate model ensembles) used to produce two types of outputs (daily time‐series of natural river flow for 260 sites, and monthly 1 × 1 km grids of natural flow and soil moisture in the unsaturated zone). The driving data required by G2G are rainfall and potential evaporation (PE). Two of the datasets from observation‐based driving data use rainfall from CEH‐GEAR (CEH‐Gridded Estimates of Areal Rainfall) with PE from MORECS (Met Office Rainfall and Evaporation Calculation System), and cover the period 1960–2015, while the other two use CEH‐GEAR rainfall with PE derived from 5 km temperature data using the Oudin method, and cover 1891–2015. The two datasets based on driving data (rainfall and PE) from the climate model ensembles cover three periods: Historical Baseline (1900–2006), Near‐Future (2020–2049), and Far‐Future (2070–2099). Data for a 30‐year Baseline period (1975–2004), against which the Near‐Future and Far‐Future periods should be compared, are also available directly. There are 100 members in each ensemble, and the future periods use the RCP8.5 emissions scenario. This paper provides details of the G2G model and the different sets of meteorological driving data, as well as the availability and formatting of the output datasets. It also describes some recent and potential applications of the datasets, which have already been used to support historical and future analyses of low flow and drought characteristics across Britain, and provides some guidance on how the climate model‐driven datasets should (and should not) be used. Open Practices: This article has earned an Open Data badge for making publicly available the digitally‐shareable data necessary to reproduce the reported results. The data is available at DOI 10.5285/5f3c1a02-d5c4-4faa-9353-e8b68ce2ace2. Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki. [ABSTRACT FROM AUTHOR]

Climate change and demographic pressures are affecting both the urban water balance and microclimate, thus amplifying urban flooding and the urban heat island phenomena. These issues need to be addressed when engaging in urban planning activities. Local authorities and stakeholders have therefore opted for more nature-based adaptation strategies, which are especially suitable in influencing hydrological and energy processes. Assessing the multiple benefits of such strategies on the urban microclimate requires highperformance numerical tools. This paper presents recent developments dedicated to the water budget in the Town Energy Balance for vegetated surfaces (TEB-Veg) model (surface externalisée; SURFEX v7.3), thus providing a more complete representation of the hydrological processes taking place in the urban subsoil. This new hydrological module is called TEB-Hydro. Its inherent features include the introduction of subsoil beneath built surfaces, the horizontal rebalancing of intra-mesh soil moisture, soil water drainage via the sewer network and the limitation of deep drainage. A sensitivity analysis is then performed in order to identify the hydrological parameters required for model calibration. This new TEB-Hydro model is evaluated on two small residential catchments in Nantes (France), over two distinct periods, by comparing simulated sewer discharge with observed findings. In both cases, the model tends to overestimate total sewer discharge and performs better under wet weather conditions, with a Kling-Gupta efficiency (KGE) statistical criterion greater than 0.80 vs. approximately 0.60 under drier conditions. These results are encouraging since the same set of model parameters is identified for both catchments, irrespective of meteorological and local physical conditions. This approach offers opportunities to apply the TEB-Hydro model at the city scale alongside projections of climate and demographic changes. [ABSTRACT FROM AUTHOR]

Highlights • We propose a Lattice Boltzmann model to solve 2D fractional advection-dispersion equation. • The model is verified against the analytical solution of a benchmark problem. • We apply the model to simulate Cl− movement in a tracer experiment. • We discuss the pros and cons of the model in comparison with other numerical models. Abstract Natural soils and aquifers are inherently heterogenous and chemical transport through them is anomalous characterized by an early arrival followed by a persistent tail. How to describe such anomalous phenomena has been an interest and, as a result, a number of approaches have been proposed over the past few decades. Among others, the fractional advection-dispersion equation (FADE) is a model able to describe anomalous transport when the dispersion is regional rather than local as presumed in the classical advection-dispersion equation. Practical application of FADE needs numerical solutions, which is challenging because its spatial discretization gives rise to a full coefficient matrix. In this paper, we propose a Lattice Boltzmann model to solve the two-dimensional FADE. Given that the anomalous dispersion in soils and aquifers is hydrodynamic and caused by spatial variation in water velocity across the pore space and that the chemical plume spreads preferentially along the mean water-flow direction, the dispersion coefficient and the order of the fractional derivative should be both anisotropic. The anisotropies are solved by the two-relaxation time Lattice Boltzmann model using different relaxation parameters in different directions. Compared with existing numerical methods for the FADE, the proposed model has advantages that it is explicit, second-order accurate in both time and space, mass-conservative, and free of numerical dispersion; its stability is independent of dispersion coefficient. We verify the model against the analytical solution of a benchmark problem and then apply it to simulate Cl− movement in a tracer experiment conducted on an up-catchment hillslope. The results show that the FADE with backward skewness can reproduce the breakthrough curves measured from the experiment. [ABSTRACT FROM AUTHOR]

The objective of this paper is to understand how large-scale processes, cloud cover and surface fluxes affect the temperature variability over the SIRTA site, near Paris, and in a regional climate simulation performed in the frame of HyMeX/Med-CORDEX programs. This site is located in a climatic transitional area where models usually show strong dispersions despite the significant influence of large scale on interannual variability due to its western location. At seasonal time scale, the temperature is mainly controlled by surface fluxes. In the model, the transition from radiation to soil moisture limited regime occurs earlier than in observations leading to an overestimate of summertime temperature. An overestimate of shortwave radiation (SW), consistent with a lack of low clouds, enhances the soil dryness. A simulation with a wet soil is used to better analyse the relationship between dry soil and clouds but while the wetter soil leads to colder temperature, the cloud cover during daytime is not increased due to the atmospheric stability. At shorter time scales, the control of surface radiation becomes higher. In the simulation, higher temperatures are associated with higher SW. A wet soil mitigates the effect of radiation due to modulation by evaporation. In observations, the variability of clouds and their effect on SW is stronger leading to a nearly constant mean SW when sorted by temperature quantile but a stronger impact of cloud cover on day-to-day temperature variability. Impact of cloud albedo effect on precipitation is also compared. [ABSTRACT FROM AUTHOR]