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Human-generated aerosol pollution gradually modifies the atmospheric chemical and physical attributes, resulting in significant changes in weather patterns and detrimental effects on agricultural yields. The current study assesses the loss in agricultural productivity due to weather and anthropogenic aerosol variations for rice and maize crops through the analysis of time series data of India spanning from 1998 to 2019. The average values of meteorological variables like maximum temperature (TMAX), minimum temperature (TMIN), rainfall, and relative humidity, as well as aerosol optical depth (AOD), have also shown an increasing tendency, while the average values of soil moisture and fraction of absorbed photosynthetically active radiation (FAPAR) have followed a decreasing trend over that period. This study's primary finding is that unusual variations in weather variables like maximum and minimum temperature, rainfall, relative humidity, soil moisture, and FAPAR resulted in a reduction in rice and maize yield of approximately (2.55%, 2.92%, 2.778%, 4.84%, 2.90%, and 2.82%) and (5.12%, 6.57%, 6.93%, 6.54%, 4.97%, and 5.84%), respectively. However, the increase in aerosol pollution is also responsible for the reduction of rice and maize yield by 7.9% and 8.8%, respectively. In summary, the study presents definitive proof of the detrimental effect of weather, FAPAR, and AOD variability on the yield of rice and maize in India during the study period. Meanwhile, a time series analysis of rice and maize yields revealed an increasing trend, with rates of 0.888 million tons/year and 0.561 million tons/year, respectively, due to the adoption of increasingly advanced agricultural techniques, the best fertilizer and irrigation, climate-resilient varieties, and other factors. Looking ahead, the ongoing challenge is to devise effective long-term strategies to combat air pollution caused by aerosols and to address its adverse effects on agricultural production and food security. [ABSTRACT FROM AUTHOR]

Drought stress poses a significant risk to soybean production, as it relies on optimum rainfall under rainfed conditions. Exposure to brief dry periods during early vegetative growth impacts soybean growth and development. Choosing a genotype that can withstand stress with minimal impact on physiology and growth might help sustain biomass or yields under low rainfall conditions. Therefore, this study characterized 64 soybean genotypes for traits associated with drought tolerance during the early vegetative stage under two soil moisture treatments, 100% evapotranspiration (well-watered) and 50% evapotranspiration (drought), using the Soil–Plant–Atmosphere Research (SPAR) units. Eighteen morpho-physiological traits responses were assessed, and their relationship with the early vegetative drought tolerance was investigated. Drought stress significantly increased root weight, root volume, and root-to-shoot ratio but reduced shoot weight. Drought-stressed plants increased the canopy temperature by 3.1 °C. Shoot weight positively correlated with root surface area (r = 0.52, P < 0.001) and root weight (r = 0.65, P < 0.001). There was a strong negative correlation between shoot weight and root-to-shoot ratio (P < 0.01). Further, the combined drought response index was strongly associated with the root response index and weakly with the physiological response index. These findings suggest that genotypes (S55-Q3 and R2C4775) with high above-ground biomass with a balanced root-to-shoot ratio improves drought tolerance during the early vegetative. These genotypes could serve as valuable genetic resources to dissect the molecular networks underlying drought tolerance and ultimately be used in breeding programs to improve root ability at the early vegetative stage. [ABSTRACT FROM AUTHOR]

Rainwater is the main water source in arid and semiarid areas of the Loess Plateau, where rainfall is generally insufficient, ineffective and underutilized during the growing season. Thus, improving rainwater utilization efficiency is essential for sustainable agricultural development. A new system composed of rainwater harvesting, an infiltrator bucket with multiple holes and mulching (RHM), was designed to maintain soil moisture at a proper level in rain-fed orchards in arid and semiarid areas of the Loess Region of China. However, there is a lack of clarity on the effectiveness of RHM. In this study, changes in the soil environment and the growth and physiology of apricot trees were monitored via two treatments: (1) Rain-harvesting irrigation system (RHM) treatment and (2) traditional orchard treatment (CK) as a baseline. The results showed that (1) RHM could effectively improve soil water storage at depths of 0–45 cm and at a horizontal distance of 40 cm from the trunk. For the 1.4 mm light rain event, the soil water content increased by 6.3–12%, and for the two moderate rains, the soil water content increased by 12–25%. The change in the soil relative water content predicted by the LSTM model is consistent with the overall trend of the measured value and gradually decreases, and the prediction accuracy is high, with an error of 0.65. (2) The average soil temperatures at 5 cm, 20 cm and 40 cm under RHM were 17.0% (2.4 °C), 13.6% (1.9 °C) and 7.5% (1 °C) greater than those under CK, respectively. (3) Compared with the control treatment, RHM improved the growth and WUEL of apricot trees. The results highlighted the efficiency of the RHM system in enhancing the soil environment and regulating the growth and physiology of apricot trees, which has greater popularization value in arid and semiarid areas. [ABSTRACT FROM AUTHOR]

Two physical models were used to simulate the infiltration and redistribution process of light crude oil after leakage in a heterogeneous soil layer following water level variation and rainfall. Migration fronts and redistribution characteristics of oil during gravity seepage, water level variation, and rainfall were obtained using charge-coupled device (CCD) camera shooting and cyan–magenta–yellow‒black (CMYK)-based gray analysis, which were employed efficiently and at a low cost. Then, the influencing factors and migration mechanisms were examined. Finally, the soil water and oil contents were measured to verify the simulation results. The results are as follows: (1) the geologic lens and fine–coarse interface can intercept oil, resulting in a local highly contaminated area. (2) The crude oil infiltration path and velocity varied greatly with the different soil types and initial water contents. Within a certain range, the higher the initial water content is, the higher the lateral and vertical infiltration speeds. (3) The oil redistribution process was dominated by vertical infiltration under the condition of water level variation or rainfall, but oil–water displacement and the capillary pressure caused some oil to move horizontally near the geologic lens and fine–coarse interface. (4) Water level variation resulted in a synchronous rise or fall of the oil accumulation area, but rainfall caused it to move up. (5) Water level variation and rainfall imposed a certain influence on the periodic accumulation and release of crude oil in heterogeneous soil, especially in the presence of geologic lenses and lithologic interfaces. [ABSTRACT FROM AUTHOR]

Extreme rainfall prior to a flood event is often a necessary condition for its occurrence; however, rainfall alone is not always an indicator of flood severity. Antecedent wetness condition of a catchment is another important factor which strongly influences the flood magnitudes. The key role of soil moisture in driving floods is widely recognized; however, antecedent conditions of deeper saturated zone may contribute to river floods. Here, we assess how closely the flood magnitudes are associated to extreme rainfall, soil moisture and baseflow in 70 catchments of Peninsular India for the period 1979–2018. Annual flood magnitudes have declined across most of the catchments. Effect of flow regulations is also assessed to understand the impact of human interventions on flood characteristics. Reservoir regulation has positive effect by reducing the flood peak and volume, whereas the duration of flood events has increased after the construction of dams. Baseflow exhibits similar patterns of trends as floods, whereas trends in rainfall and soil moisture extremes are weakly correlated with trends in flood magnitudes. Baseflow is found to be more strongly influencing the flood magnitudes than soil moisture at various time lags. Further analysis with event coincidence analysis confirms that baseflow has stronger triggering effect on river floods in Peninsular India. [ABSTRACT FROM AUTHOR]

Latent heat released during orographic precipitation over the Western Ghat (WG) Mountain drives the Indian Summer Monsoon. Instrumental data record a considerable spatiotemporal variation of rainfall amount along the mountain. Although Indian teak (Tectona grandis LF) samples from WG have been used earlier for reconstructing past monsoon rainfall, the effect of rainfall variation on the annual ring growth pattern along the mountain has not been extensively studied yet. To address this issue, tree-ring width data series from three locations—Dahanu (1763 -1985), Nagerhole (1703–2016), and Tekkedy (1785–2003) are presented in this study. The locations are situated along WG from north to south. Monthly mean rainfall data obtained from the nearest observatories show a decreasing (increasing) rainfall amount from north to south during summer monsoon (pre and post-monsoon). We obtain a significant positive correlation between ring width indices and monsoon rainfall and a negative correlation with summer (especially May) temperature suggesting a contrasting response of summer temperature and monsoon rain on teak growth. The correlation between rainfall and ring width varies from southern to northern WG (both in significance level and the number of months with significant correlation). While the southernmost location exhibits positive (significant) correlations for both pre and summer monsoon months, the correlations are found for only two summer monsoonal months in the northernmost location. This spatial correlation trend reflects the variation of the pre-monsoon to monsoon rainfall ratio observed in our study locations. This observation is further substantiated by soil moisture-ring width relationship. Furthermore, our study shows that ring width indices respond to a variation of western equatorial Pacific sea surface temperature and vapor pressure deficit. Our study, therefore, suggests that the Indian teak samples can be used for understanding regional and seasonal scale rainfall/soil moisture variation along the WG and teleconnection studies. [ABSTRACT FROM AUTHOR]

Early-season agricultural drought is frequent over South Asian region due to delayed or deficient monsoon rainfall. These drought events often cause delay in sowing and can even result in crop failure. The present study focuses on monitoring early-season agricultural drought in a semi-arid region of India over 5-year period (2016–2020). It utilizes hydro-climatic and biophysical variables to develop a combined drought index (CDI), which integrates anomalies in soil moisture conditions, rainfall, and crop-sown area progression. Synthetic aperture radar (SAR)–based soil moisture index (SMI) represents in situ measured soil moisture with reasonable accuracy (r=0.68). Based on the highest F1-score, SAR backscatter in VH (vertical transmit-horizontal receive) polarization with specific values for parameter threshold (−18.63 dB) and slope threshold (−0.072) is selected to determine the start of season (SoS) with a validation accuracy of 73.53%. The CDI approach is used to monitor early-season agricultural drought and identified drought conditions during June–July in 2019 and during July in 2018. Conversely, 2020 experienced consistently wet conditions, while 2016 and 2017 had near-normal conditions. Overall, the study highlights the use of SAR data for early-season agricultural drought monitoring, which is mainly governed by soil moisture–driven crop-sowing progression. The proposed methodology holds potential for effective monitoring, management, and decision-making in early-season agricultural drought scenarios. [ABSTRACT FROM AUTHOR]

With its predisposition to adapt to different environments, Cucurbita moschata grows well in various ecosystems. It is not a very exigent plant and has an inherent capacity for plasticity that underlies its large variability. An assessment of the accessions of C. moschata in Cote d'Ivoire shows that the plant exhibits large morphological and phenological variability for all the 28 measured traits. There are outliers among most measured traits. Further analysis indicates the emergence of three ecotypes in congruence with the three distinct ecosystems and their respective bioclimatic characteristics. In the savannah region, characterized by a short rainy season followed by a long dry season, a total yearly rainfall of 900 mm, an elevated daily temperature of 29 °C, and a high relative humidity of 80%, the cline of C. moschata is long and thin, with small leaves, small peduncles and small fruits. It has a high growth rate and accelerated phenology. The mountain region has a very long rainy season followed by a short dry season, a total pluviometry of 1400 mm, an average daily temperature of 27 °C and a relative humidity of 69%. The cline of C. moschata in the mountain region is characterized by a delayed flowering and a delayed fruit maturity, large number of small seeds and large fruits. The forest region has a favorable climate for the growth of C. moschata in Cote d'Ivoire. It has two rainy seasons that alternate with two dry seasons of unequal durations, an annual rainfall of 1200 mm, an average daily temperature of 27 °C and a relative humidity of 70%. The cline of C. moschata in that region has a large girth size, large dimensions of the leaves, long peduncles and larger and heavier fruits. The seeds are also large but in small number. It appears that the anatomy and physiology of the clines are differentiated primarily in response to soil water content and availability for the ontogeny of the plant. [ABSTRACT FROM AUTHOR]

Climate change severely affects sub-Saharan African economies in several ways: increased temperatures, erratic rainfall variability patterns, and recurrent droughts and floods. Such adverse climate change effects may result in a greater incidence of crop pests, loss of soil moisture content, rapid soil nutrient depletion and substantial decreases in crop productivity and yields. These effects in combination with lack of access to improved, high-yielding crop varieties, limited agricultural extension services and poor access to irrigation infrastructure could further threaten access to food, limit export earnings and markedly lower net crop revenue. Several definitions, assessment approaches and methods for the concepts related to "vulnerability" and "adaptation" exist due to complex nature of climate impact and strategies used to deal with them. Based on the context of such studies, this paper reviews climate change risks, people's vulnerability to such risks as well as synthesize different approaches, methods and models used to assess vulnerability and adaptation in the area of agriculture in sub-Saharan Africa. As climate change effects are complex and site-specific, the understanding of several concepts, approaches and methods provides detailed information on farmers' vulnerability and adaptation process. Such information would be useful to inform adaptation interventions and agricultural policies that build farmers' resilience. [ABSTRACT FROM AUTHOR]

Europe witnessed a strong increase in climate variability and enhanced climate-induced extreme events, such as hot drought periods, mega heat waves, and persistent flooding and flash floods. Intensified land degradation, land use, and landcover changes further amplified the pressure on the environmental system functionalities and fuelled climate change feedbacks. On the other hand, global satellite observations detected a positive spectral greening trend—most likely as a response to rising atmospheric CO2 concentrations and global warming. But which are the engines behind such shifts in surface reflectance patterns, vegetation response to global climate changes, or anomalies in the environmental control mechanisms? This article compares long-term environmental variables (1948–2021) to recent vegetation index data (Normalized Difference Vegetation Index (NDVI), 2001–2021) and presents regional trends in climate variability and vegetation response across Europe. Results show that positive trends in vegetation response, temperature, rainfall, and soil moisture are accompanied by a strong increase in climate anomalies over large parts of Europe. Vegetation dynamics are strongly coupled to increased temperature and enhanced soil moisture during winter and the early growing season in the northern latitudes. Simultaneously, temperature, precipitation, and soil moisture anomalies are strongly increasing. Such a strong amplification in climate variability across Europe further enhances the vulnerability of vegetation cover during extreme events. [ABSTRACT FROM AUTHOR]

India receives more than 70% of its annual rainfall in the summer monsoon from June to September. The rainfall is scanty and scattered for the rest of the year. Combining satellite data and model simulations, we show that the soil-vegetation continuum works as a natural capacitor of water, storing the monsoon pulse and releasing the moisture to the atmosphere through evapotranspiration over approximately 135 days when the moisture supply from precipitation is less than the evapotranspiration losses. The total Gross Primary Productivity of vegetation in India during the capacitor period accounts for almost 35% of the total annual GPP value. It primarily depends on the soil moisture at the beginning of the period, a measure of moisture capacitance of soil, with a correlation of 0.6. Given that India is the second largest contributor to recent global greening, its soil-vegetation water capacitance plays a significant role in the global carbon balance. [ABSTRACT FROM AUTHOR]

The effects of inoculations with a N2-fixing cyanobacterium (Anabaena cylindrica) on nutrient and microbial dynamics of an arable Mollisol were studied under simulated high intensity rainfall. Inoculated and non-inoculated pots (controls) were incubated for 14 days and then subjected to three rain events in 1 week, followed by three weekly events for a total of six events. Soil samples at three depth layers (0–1, 5–6, and 10–11 cm) were taken at four time points: 1 day after inoculation, 14 days after inoculation, after rain 1, and after rain 6. Soil chlorophyll a (Chla), soluble fractions of N (SolN) and organic C (SolC), microbial biomass C (MBC) and N (MBN), microbial activity (FDA hydrolysis), and soil respiration (CO2 efflux) were determined. Results revealed depth-related changes in Chla, SolC, SolN, MBC, MBN, and FDA hydrolysis with greater effects at the surface layer (0–1 cm). Soil respiration varied with soil moisture and increased in inoculated treatments. After all rain simulations (49 days after inoculation), higher SolC, MBC, MBN, and FDA hydrolysis in surface soil of inoculated treatments indicated positive changes that persisted after consecutive rains. These findings suggest that cyanobacterial soil amendments might enhance soil quality and resiliency in agricultural soils exposed to high intensity rainfall. [ABSTRACT FROM AUTHOR]

Evaporative loss of interception (Ei) is the first process occurring during rainfall, yet its role in large-scale surface water balance has been largely underexplored. Here we show that Ei can be inferred from flux tower evapotranspiration measurements using physics-informed hybrid machine learning models built under wet versus dry conditions. Forced by satellite and reanalysis data, this framework provides an observationally constrained estimate of Ei, which is on average 84.1 ± 1.8 mm per year and accounts for 8.6 ± 0.2% of total rainfall globally during 2000–2020. Rainfall frequency regulates long-term average Ei changes, and rainfall intensity, rather than vegetation attributes, determines the fraction of Ei in gross precipitation (Ei/P). Rain events have become less frequent and more intense since 2000, driving a global decline in Ei (and Ei/P) by 4.9% (6.7%). This suggests that ongoing rainfall changes favor a partitioning towards more soil moisture and runoff, benefiting ecosystem functions but simultaneously increasing flood risks. Canopy rainfall interception (Ei) is a key component of global water cycle. Here, the authors quantify Ei using flux tower data and machine learning, and find that rainfall gets less partitioned into Ei as it gets more intense and less frequent. [ABSTRACT FROM AUTHOR]

Vegetation and rainfall pattern are two important factors affecting the infiltration-runoff processes in slopes. Rainfall events in the eastern margin of the Tibetan Plateau, monitored from June 2019 to October 2020, were classified into four patterns using the self-organizing mapping method. To determine the relationship between infiltration potential, runoff generation, soil erosion, and rainfall parameters, the four rainfall patterns were simulated on the bare and vegetated slopes, and soil moisture content, surface runoff, subsurface flow, and sediment yield were measured. The results showed that rainfall characteristics and meteorological parameters significantly affected soil moisture supply. Rainfall intensity and soil moisture content mainly affected the initial infiltration rate, soil properties and root characteristics determined the stable infiltration rate. Vegetation could accelerate the rate and amplitude of soil moisture absorption and dehumidification. Soil erosion intensity and rainfall duration were found to follow a power function (R2 > 0.84) in the bare slope and an exponential function (R2 > 0.64) in the vegetated slope. Vegetation could significantly mitigate soil erosion by altering the hydrodynamic parameters of overland flow, and the mitigating effect was found to be more pronounced for light rainfall events. Moreover, the existence of an optimal initial moisture content for minimizing soil erodibility could be ascertained. These results provide insight into the dynamic responses of infiltration potential and erosion process in bare and vegetated slopes to different rainfall patterns and could guide the prevention of slope instability and soil erosion in response to complex climate change in the next two decades. [ABSTRACT FROM AUTHOR]

Most land surface system models and observational assessments ignore detailed soil characteristics while describing the drought attributes such as growth, duration, recovery, and the termination rate of the event. With the national-scale digital soil maps available for India, we assessed the climate-catchment-soil nexus using daily observed streamflow records from 98 sites in tropical rain-dominated catchments of peninsular India (8–25° N, 72–86° E). Results indicated that climate-catchment-soil properties may control hydrological drought attributes to the tune of 14–70%. While terrain features are dominant drivers for drought growth, contributing around 50% variability, soil attributes contribute ~ 71.5% variability in drought duration. Finally, soil and climatic factors together control the resilience and termination rate. The most relevant climate characteristics are potential evapotranspiration, soil moisture, rainfall, and temperature; temperature and soil moisture are dominant controls for streamflow drought resilience. Among different soil properties, soil organic carbon (SOC) stock could resist drought propagation, despite low-carbon soils across the Indian subcontinent. The findings highlight the need for accounting feedback among climate, soil, and topographical properties in catchment-scale drought propagations. [ABSTRACT FROM AUTHOR]

River flooding has large societal and economic impacts across Africa. Despite the importance of this topic, little is known about the main flood generating mechanisms in Africa. This study is based on 13,815 flood events that occurred between 1981 and 2018 in 529 catchments. These flood events are classified to identify the different flood drivers: excess rains, long rains and short rains. Out of them, excess rains on saturated soils in Western Africa, and long rains for catchments in Northern and Southern Africa, are the two dominant mechanisms, contributing to more than 75% of all flood events. The aridity index is strongly related to the spatial repartition of the different flood generating processes showing the climatic controls on floods. Few significant changes were detected in the relative importance of these drivers over time, but the rather short time series available prevent a robust assessment of flood driver changes in most catchments. The major implication of these results is to underline the importance of soil moisture dynamics, in addition to rainfall, to analyze the evolution of flood hazards in Africa. [ABSTRACT FROM AUTHOR]

Climate change is altering precipitation regimes globally, with expectations of intensified precipitation patterns (for example, larger but fewer rainfall events) and more frequent and extreme drought. Both aspects of precipitation change can impact ecosystem function individually, but it is more likely that they will occur in combination. In a central US mesic grassland, we imposed an extreme 2-year drought (growing season precipitation reduced by 66%) on plots with a long-term (16-year) history of exposure to either ambient or intensified precipitation patterns (average threefold increase in event size and threefold decrease in event number during the growing season). While this intensified pattern did not alter total precipitation amount, it generally led to ecosystem responses consistent with a drier environment (for example, reduced soil moisture, aboveground net primary production (ANPP), and soil CO2 flux, but little evidence for altered root biomass). Surprisingly, this history of intensified precipitation patterns did not affect the response of ANPP to the subsequent extreme drought. In contrast, previous exposure to intensified precipitation patterns reduced root production and muted soil CO2 flux responses to rainfall events during drought. Reduced root production in plots experiencing compounded precipitation extremes was driven not by the dominant C4 grass species, Andropogon gerardii, but collectively by the subdominant species in the plant community. Overall, our results reveal that compound changes in precipitation patterns and amount affected this grassland in ways that were less apparent (that is, belowground) than responses to either change individually and significantly reduced ecosystem carbon uptake. [ABSTRACT FROM AUTHOR]

Climate change leads to changes in climatic variables, with rainfall being one of them. Changes in rainfall influence rainfall erosivity and subsequently erosion rates. This study analysed rainfall data from 1901 to 2017 in Odisha, focusing on different agro-climatic zones to discern annual rainfall pattern, its spatial variation, and trend, particularly concerning the rainfall erosivity factor and its impact on soil erosion and agricultural productivity. Notably, the Eastern Ghats Highland region received the highest average annual rainfall of 1578.5 mm, while the Western Undulating Zone received the lowest (1308.4 mm). The rainfall distribution showed spatial variability largely influenced by topography, with areas experiencing orographic lifting receiving higher rainfall. The study observed significant trend in annual rainfall, noting a maximum decline of 1.2 mm yr−1 in the North Western Plateau, Western Central Table Land, and Western Undulating Zone, whereas the East and South Eastern Plain, Mid Central Table Land, North Eastern Coastal Plain, North Eastern Ghats, and South Eastern Ghats exhibited a noteworthy increase in annual rainfall (0 to 3.9 mm yr−1). The decline in rainfall can result in the drying up of water bodies and reduced soil water availability to crop, thereby influencing agricultural production. On the other hand, areas with increased rainfall, may face extreme events which can aggravate soil erosion and thereby loss of soil fertility. Considering the scarcity of pluviographic data in countries like India, Modified Fournier Index (MFI) may be considered as one of the useful methods to capture rainfall’s aggressiveness towards soil erosion through rainfall erosivity (R-factor). Therefore, to evaluate potential soil erosion levels, the Modified Fournier Index method was employed, revealing varying degrees of soil erosiveness across different regions. The Eastern Ghats Highlands exhibited the highest erosion potential. The R-factor, aligned with these spatial patterns, with the Eastern Ghats Highland (12,965.4 MJ mm ha−1 h−1 yr−1) and South Eastern Ghats (12,242.3 MJ mm ha−1 h−1 yr−1) regions displaying the highest R-factor values. Furthermore, the research identified areas prone to soil erosion by overlaying R-factor, slope, and land use maps, highlighting vulnerable regions such as Eastern Ghats Highlands, North Eastern Ghats, South Eastern Ghats, and Western Undulating Zone. This comprehensive analysis allows for informed prioritization of conservation efforts and the implementation of appropriate measures like strip cropping of finger millet with groundnut, intercropping finger millet with hedgerows of Gliricidia and Leucaena, bio-engineering measures such as earthen or stone bunds with broom grass in arable land and growing of aromatic grasses like lemon and citronella grass, construction of staggered trenches in non-arable land to mitigate erosion in these susceptible areas. [ABSTRACT FROM AUTHOR]

Meteorological drought is among the key climate-related risks affecting Ethiopia. It indicates a shortage of precipitation over a long period, usually for a season or a year. This study uses copula theory to analyze meteorological drought in the upper Tekeze river basin, Northern part of Ethiopia. Meteorological drought analysis using copula theory provides a promising opportunity to deal with such risks in advance and to improve sectoral resilience. In this study, long-year (1982–2020) rainfall and soil moisture data were used to analyze standardized precipitation index (SPI) and standardized soil moisture index (SSI), respectively. The best-fit copula family was selected to construct the joint probability distribution (JPD) of SPI and SSI. Multivariate standardized drought index (MSDI) at 3-, 6-, and 12-month timescales was analyzed using the MSDI toolbox. The nonparametric Mann–Kendall (M–K) statistical test was used for trend detection. We found that the newly developed MSDI captures all drought events during the observation period compared with SPI and SSI. MSDI particularly showed the most recent drought of 2015, with the drought duration and severity of 4 months and 6.4, respectively, and its joint return period was 5.24 years. The M–K and Sen's Slope estimator statistical tests indicated a positive trend for all drought timescales in the basin. The spatial extent of MSDI shows most frequently extreme drought occurred in the basin. Meteorological drought analysis using multiple indices is better than a single drought index. This approach can better inform adaptation policies and interventions that are aimed at monitoring and reducing drought risk in the basin and beyond. [ABSTRACT FROM AUTHOR]

Forest management practices play an important role in regulating the soil water-holding capacity of plantation. However, most studies focus on soil water dynamics present during large-scale forest loss and afforestation events, while little is known about how soil water under different forest management practices responds to rainfall events and which factors mainly regulate soil water-holding capacity. In this study, a stable hydrogen isotope was used to explore the contribution of three natural rainfall events (8.9, 13.3 and 67.7 mm) to soil water (CRSW) in a Pinus massoniana plantation under four forest management practices (no thinning (NTN), understory removal (USR), light-intensity thinning (LIT) and heavy-intensity thinning (HIT)) in the Three Gorges Reservoir Area of the Yangtze River Basin in China. Furthermore, a structural equation model was employed to determine the effects of vegetation biomass and soil properties on the CRSW. The results showed that plantation soil under different forest management practices exhibited different water-holding capacities. Following light (8.9 mm) and moderate (13.3 mm) rainfall events, the CRSW in the HIT stand was slightly higher than that in the other stands. Following heavy (66.7 mm) rainfall event, the CRSW of most layers in USR stand was not different from the other three stands, while the CRSW in the LIT and NTN stands was significantly higher than that in the HIT stand in the 0–100 cm soil layers, suggesting that soil in the LIT and NTN stands had a greater water-holding capacity than that in the HIT stand. In addition, soil properties were the main factors directly affecting the CRSW, explaining 60% and 37% of the variation in the CRSW on the first and seventh days after heavy rainfall, respectively. Overall, compared to the HIT stand, the LIT and NTN stands showed greater capacity in retaining rainwater. Therefore, under expected global changes with frequent occurrences of extreme precipitation events, methods involving light-intensity and no thinning should be employed to build up soil and water conservation functions, which will be critical for keeping water-holding capacity and moderating floods. [ABSTRACT FROM AUTHOR]

The combination of extended dry periods and high intensity rainfall, common in the southeastern US, leads to greater variability in soil moisture and consequently increases uncertainty to microbial processes pertinent to soil carbon (C) mineralization. However, field-based findings on soil moisture sensitivity to soil C cycling are very limited. Therefore, a field experiment was conducted in 2018 and 2019 on a soybean (Glycine max L.) cropland in the southeastern US with three soil moisture treatments: drought (simulated using rainout-shelter from June to October in each year), rainfed (natural precipitation), and irrigated (irrigation and precipitation). Soil respiration was measured weekly from May to November in both years. Soil samples were collected multiple times each year from 0–5, 5–15, and 15–30 cm depths to determine microbial biomass C (MBC), extractable organic C (EOC), hydrolytic enzyme activities, and fungal abundance. The cumulative respiration under drought compared to other treatments was lower by 32% to 33% in 2018 and 38% to 45% in 2019. Increased MBC, EOC, and fungal abundance were observed under drought than other treatments. Specific enzyme activity indicated fewer metabolically active microbes under drought treatment compared to rainfed and irrigated treatments. Also, maintenance of enzyme pool was observed under drought condition. These results provide critical insights on microbial metabolism in response to soil moisture variation and how that influences different pools of soil C under field conditions. [ABSTRACT FROM AUTHOR]

Rainfall is one of the most significant natural factors for inducing landslides. The shallow saturated zone formed in slopes during rainfall is an important factor in inducing shallow landslides. In this paper, the characteristics and influencing factors of the saturated zone in soil slopes, and the relationship between the soil surface permeability coefficient and the rainfall intensity are analyzed. In this research, the equation that characterizes the rainfall intensity by the soil saturation is built based on the Mualem-van Genuchten model, which mathematically describes the soil water characteristics of unsaturated soils. Using this model, the target saturation of the slope surface during rainfall can be determined accurately, with an average deviation of − 0.008. Based on the equations, the innovative critical curve model of the rainfall intensity−time required to form the shallow saturated zone is established and calculated. The influence of the soil material, slope angle, rainfall intensity and antecedent rainfall on the critical curve for the shallow saturated zone is analyzed. The results indicate that for slopes of 30°~40°, it is easy for the shallow saturated zone to form, and the previous rainfall after more than 16 days has little impact on the critical curve. Furthermore, an innovative landslide prediction model, based on the critical curve for the shallow saturated zone and I-D modeling, is proposed to provide benchmarks for the prediction-specific characteristics of deep or shallow landslides, which is verified by the case of the Madiwan landslide. [ABSTRACT FROM AUTHOR]

Moderate Resolution Imaging Spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data were analyzed to study the vegetation dynamics over different meteorological subdivisions in India for the period 2000–2016. Soil moisture (SM), rainfall (RF), and land use land cover (LULC) data were analyzed to identify the climatic and anthropogenic drivers that cause vegetation changes at the subdivision scale. Principal component analysis and MK (Mann-Kendall) test showed significant greening trend over semi-arid regions of Northwest India (NWI) and South India (SI) while slight browning trend seen over some of the subdivisions in Indo-Gangetic (IG) plains and Western Ghats (WG). It is found that the NDVI has superior correlation with soil moisture compared with rainfall and the croplands (CL) found to have significant increasing trend over the NWI and SI. Increasing trend in soil moisture over the NWI and SI may have contributed to increase in CL area and the greening trend. Over IG plains, the NDVI showed moderate correlation with SM and RF, and the greening trend (browning trend) in some regions can be attributed to increase in natural vegetation mosaic (decrease of CL). The NDVI has shown browning trend over the core monsoon regions of Madhya Pradesh (an increase of barren lands over west MP and decrease of CL over east MP) and Western Ghats (significant decrease of CL over Konkan and Goa). This study revealed that the soil moisture and LULC changes are the major driving factors for the vegetation changes over majority of the subdivisions in India. [ABSTRACT FROM AUTHOR]

Satellite precipitation products have been largely improved in the recent years particularly with the launch of the global precipitation measurement (GPM) core satellite. Moreover, the development of techniques for exploiting the information provided by satellite soil moisture to complement/enhance precipitation products have improved the accuracy of accumulated rainfall estimates over land. Such satellite enhanced precipitation products, available with a short latency (< 1 day), represent an important and new source of information for river flow prediction and water resources management, particularly in developing countries in which ground observations are scarcely available and the access to such data is not always ensured. In this study, three recently developed rainfall products obtained from the integration of GPM rainfall and satellite soil moisture products have been used; namely GPM+SM2RAIN, PRISM-SMOS, and PRISM-SMAP. The prediction of observed daily river discharge at 10 basins located in Europe (4), West Africa (3) and South Africa (3) is carried out. For comparison, we have also considered three rainfall products based on: (1) GPM only, i.e., the Early Run version of the Integrated Multi-Satellite Retrievals for GPM (GPM-ER), (2) rain gauges, i.e., the Global Precipitation Climatology Centre, and (3) the latest European Centre for Medium-Range Weather Forecasts reanalysis, ERA5. Three different conceptual and lumped rainfall-runoff models are employed to obtain robust and reliable results over the 3-year data period 2015–2017. Results indicate that, particularly over scarcely gauged areas (West Africa), the integrated products outperform both ground- and reanalysis-based rainfall estimates. For all basins, the GPM+SM2RAIN product is performing the best among the short latency products with mean Kling–Gupta Efficiency (KGE) equal to 0.87, and significantly better than GPM-ER (mean KGE = 0.77). The integrated products are found to reproduce particularly well the high flows. These results highlight the strong need to disseminate such integrated satellite rainfall products for hydrological (and agricultural) applications in poorly gauged areas such as Africa and South America. [ABSTRACT FROM AUTHOR]

The simulation of overland flow, wherein runoff yield and concentration are influenced by topography, is fundamental to hydrological forecasting. Therefore, critically evaluating the characteristics of overland flow under the influence of topographic depressions—which are one of the most common microtopographic structures—is vital for improving current hydrological models. In this study, we developed a solution for the real-world application of overland flow simulations under the influence of depressions in hydrological models. A relative depression storage–outflow curve (RDOC) was proposed to investigate surface outflow processes. Experiments were conducted based on the variable-controlling approach using three rainfall return periods, four slopes, and four depression rates while ensuring a consistent initial soil moisture content. A homogenized RDOC was achieved based on shape analysis; it was parameterized by the outflow threshold and the reciprocal of the curve index of two outflow stages (B and D). A relative depression storage–outflow function (RDOF) was generated and a complete calculation procedure was applied within a hydrological model. Furthermore, we analyzed the hydrological responses to parameters of different hydrological factors to improve our understanding of the parameter determination of the RDOF. [ABSTRACT FROM AUTHOR]

The Green-Ampt (GA) model is one of the most widely used analytical methods of slope stability under rainfall. However, it may overestimate the soil water content above the wetting front. In this study, a novel approach to evaluate the time-dependent slope stability during intense rainfall based on a modified GA model is presented, and is known as the stratified Green-Ampt (SGA) model. By considering the stratified soil water content above the wetting front, the soil above the wetting front can be divided into saturated and transitional layers, and the SGA model is used to analyze the infiltration process of intense rainfall into slopes. Thereafter, safety factors (Fs) of infinite and finite slopes are derived using the SGA model. In the analysis of an infinite slope, the conventional limit equilibrium method is adopted to calculate the safety factor; as for a finite slope, the residual thrust method is introduced to obtain the safety factor with sliding mass divided into multiple soil slices. The performance of the SGA model is illustrated in two cases: an infinite slope and the Majiagou landslide as a finite slope. The results indicate that compared to the GA model, the calculated wetting front based upon the SGA model moves faster, and the wetting front depth shows a positive correlation with the slope surface angle and rainfall intensity. The evolution of the safety factor above the sliding surface can be divided into three phases, while the evolution of the safety factor above the wetting front can be divided into two phases. The critical time of the slope reaching a less stable state (safety factor is 1.05) or unstable state (safety factor is 1.00) decreases exponentially with an increase in rainfall intensity. In addition, the rainfall has a significant influence on the design of stabilizing piles for the Majiagou landslide. The presented SGA model appears to be accurate to investigate slope stability during intense rainfall events. [ABSTRACT FROM AUTHOR]

Rainfall anomaly during crop-growing season can have large impact on the agricultural output of a country, especially like India, where two-thirds of the crop land is rain-fed. In such situation, decreased agricultural production not only challenges food security of the country but directly and immediately hits the livelihood of its farming community. In a vast country like India, rainfall or its anomalies hardly follow a specific pattern, rather it is having high variability in spatial domain. This study focused on the trends of national and regional rainfall anomalies (wetness/dryness) along with their interrelationship using time series data of past 158 years. The significant reducing wetness trend (p < 0.05) over north mountainous India was prominent with an increasing trend over southern peninsular India (p < 0.10). However, long-term annual wetness was increasing over entire peninsular India. The results of change point tests indicate that major abrupt changes occurred between early to mid-twentieth century having regional variations. The regional interrelationship was studied using principal component, hierarchical clustering, and pair-wise difference test, which clearly indicated a significantly different pattern in rainfall anomalies for north east India (p = 0.022), north central India (p = 0.022), and north mountainous India (p = 0.011) from that of the all India. Result of this study affirmed high spatial variability in rainfall anomaly and most importantly established the unalike pattern in trends of regional rainfall vis-à-vis national level, ushering towards paradigm shift in rainfall forecast from country scale to regional scale for pragmatic planning. [ABSTRACT FROM AUTHOR]

Soil water content is a key parameter for representing water dynamics in soils. Its prediction is fundamental for different practical applications, such as identifying shallow landslides triggering. Support vector machine (SVM) is a machine learning technique, which can be used to predict the temporal trend of a quantity since training from past data. SVM was applied to a test slope of Oltrepò Pavese (northern Italy), where meteorological parameters coupled with soil water content at different depths (0.2, 0.4, 0.6, 1.0, 1.2, 1.4 m) were measured. Two SVM models were developed for water content assessment: (i) model 1, considering rainfall amount, air temperature, air humidity, net solar radiation, and wind speed; (ii) model 2, considering the same predictors of model 1 together with antecedent condition parameters (cumulated rainfall of 7, 30, and 60 days; mean air temperature of 7, 30, and 60 days). SVM model 2 showed significantly higher satisfactory results than model 1, for both training and test phases and for all the considered soil levels. SVM models trends were implemented in a methodology of slope safety factor assessment. For a real event occurred in the tested slope, the triggering time was correctly predicted using data estimated by SVM model based on antecedent meteorological conditions. This confirms the necessity of including these predictors for building a SVM technique able to estimate correctly soil moisture dynamics in time. The results of this paper show a promising potential application of the SVM methodologies for modeling soil moisture required in slope stability analysis. [ABSTRACT FROM AUTHOR]

Understanding the relationship between gradually varying soil moisture (SM) conditions and monsoon rainfall anomalies is crucial for seasonal prediction. Though it is an important issue, very few studies in the past attempted to diagnose the linkages between the antecedent SM and Indian summer monsoon rainfall. This study examined the relationship between spring (April-May) SM and June rainfall using observed data during the period 1979-2010. The Empirical Orthogonal Function (EOF) analyses showed that the spring SM plays a significant role in June rainfall over the Central India (CI), South India (SI), and North East India (NEI) regions. The composite anomaly of the spring SM and June rainfall showed that excess (deficit) June rainfall over the CI was preceded by wet (dry) spring SM. The anomalies in surface-specific humidity, air temperature, and surface radiation fluxes also supported the existence of a positive SM-precipitation feedback over the CI. On the contrary, excess (deficit) June rainfall over the SI and NEI region were preceded by dry (wet) spring SM. The abnormal wet (dry) SM over the SI and NEI decreased (increased) the 2-m air temperature and increased (decreased) the surface pressure compared to the surrounding oceans which resulted in less (more) moisture transport from oceans to land (negative SM-precipitation feedback over the Indian monsoon region). [ABSTRACT FROM AUTHOR]

Many local weather station networks that measure a number of meteorological variables (i.e., mesonetworks) have recently been established, with soil moisture occasionally being part of the suite of measured variables. These mesonetworks provide data from which detailed estimates of various hydrological parameters, such as precipitation and reference evapotranspiration, can be made which, when coupled with simple surface characteristics available from soil surveys, can be used to obtain estimates of soil moisture. The question is Can meteorological data be used with a simple hydrologic model to estimate accurately daily soil moisture at a mesonetwork site? Using a state-of-the-art mesonetwork that also includes soil moisture measurements across the US State of Delaware, the efficacy of a simple, modified Thornthwaite/Mather-based daily water balance model based on these mesonetwork observations to estimate site-specific soil moisture is determined. Results suggest that the model works reasonably well for most well-drained sites and provides good qualitative estimates of measured soil moisture, often near the accuracy of the soil moisture instrumentation. The model exhibits particular trouble in that it cannot properly simulate the slow drainage that occurs in poorly drained soils after heavy rains and interception loss, resulting from grass not being short cropped as expected also adversely affects the simulation. However, the model could be tuned to accommodate some non-standard siting characteristics. [ABSTRACT FROM AUTHOR]

The moisture of soil profile changes both in time and space and depends on many factors. Changes of the quantity of water in soil can be determined on the basis of in situ measurements, but numerical methods are increasingly used for this purpose. The quality of the results obtained using pertinent software packages depends on appropriate description and parameterization of soil medium. Thus, the issue of providing for the soil anisotropy phenomenon gains a big importance. Although anisotropy can be taken into account in many numerical models, isotopic soil is often assumed in the research process. However, this assumption can be a reason for incorrect results in the simulations of water changes in soil medium. In this article, results of numerical simulations of moisture distribution in the selected soil profile were presented. The calculations were conducted assuming isotropic and anisotropic conditions. Empirical verification of the results obtained in the numerical investigations indicated statistical essential discrepancies for the both analyzed conditions. However, better fitting measured and calculated moisture values was obtained for the case of providing for anisotropy in the simulation model. [ABSTRACT FROM AUTHOR]

Hydrological models are widely used to investigate practical issues of water resources. Parametric uncertainty is considered as one of the most important sources of uncertainty in environmental researches. Generally, it is assumed that the parameters are independent mutually, but correlation within the parameter space is an important factor having the potential to cause uncertainty. The objective and innovation of this study was to address the effects of parameters correlation on a continuous hydrological model uncertainty. HEC-HMS with soil moisture accounting (SMA) infiltration method was used to model daily flows and simulate certainty bounds for Karoon III basin, southwest of IRAN, in two scenarios, independent and correlated parameters using 2-copula. The parameters were represented by probability distributions, and the effect on prediction error were evaluated using Latin hypercube sampling (LHS) on Monte Carlo simulation (MCS). Saturated hydraulic conductivity (K), Clark storage-coefficient (R), and time of concentration (tc) were chosen for investigation, based on observed sensitivity analysis of simulated peak over threshold (POT). One hundred runs were randomly generated from 100 parameter sets captured from LHS of parameters distributions in each sub-basin. Using generated parameter sets, 100 continuous hydrographs were simulated and values of certainty bounds calculated. Results showed that when 2-copula correlated R and tc, with 0.656 Kendall's Tau and 0.818 Spearman's Rho coefficients, were propagated, decreasing of outputs' sharpness was more than when considering K and R (K-R), with 0.166 and 0.262; therefore, incorporation of correlations in the MCS is important, especially when the correlation coefficients exceed 0.65. The model was evaluated at the outlet of the basin using daily stream flow data. Model reliability was better for above-normal flows than normal and below-normal. Reliability increases of simulated flow when considering correlated R-tc was more than K-R because of the correlation values. Incorporation of copula for K-tc not only did not improve the model reliability but also decreased it. Results showed improvement of model reliability, by decreasing predicted error of hydrologic modeling, when dealing with correlated parameters in the system. [ABSTRACT FROM AUTHOR]

Precipitation variability has been predicted to increase in a global warmer climate, and is expected to greatly affect plant growth, interspecies interactions, plant community composition, and other ecosystem processes. Although previous studies have investigated the effect of intra-annual rainfall variability on plant growth and ecosystem dynamics, the impacts of interannual rainfall variability remain understudied. This paper uses satellite data and develops a new mechanistic model to investigate the response of tree-grass composition to increasing interannual rainfall variability in arid to sub-humid ecosystems along the Kalahari Transect in Southern Africa. Both satellite data and model results show that increasing interannual rainfall fluctuations favor deep-rooted trees over shallow-rooted grasses in drier environments (that is, mean annual rainfall, MAP < 900-1000 mm) but favor grasses over trees in wetter environments (that is, MAP > 900-1000 mm). Trees have a competitive advantage over grasses in dry environments because their generally deeper root systems allow them to have exclusive access to the increased deep soil water resources expected to occur in wet years as a result of the stronger interannual rainfall fluctuations. In relatively wet environments, grasses are favored because of their high growth rate that allows them to take advantage of the window of opportunity existing in years with above average precipitation and thus increase fire-induced tree mortality. Thus, under increasing interannual rainfall fluctuations both direct effects on soil water availability and indirect effects mediated by tree-grass interactions and fire dynamics are expected to play an important role in determining changes in plant community composition. [ABSTRACT FROM AUTHOR]

Climate change-induced rainfall reductions in Mediterranean forests negatively affect the decomposition of plant litter through decreased soil moisture. However, the indirect effects of reduced precipitation on litter decomposition through changes in litter quality and soil microbial communities are poorly studied. This is especially the case for fine root litter, which contributes importantly to forests plant biomass. Here we analyzed the effects of long-term (11 years) rainfall exclusion (29% reduction) on leaf and fine root litter quality, soil microbial biomass, and microbial community-level physiological profiles in a Mediterranean holm oak forest. Additionally, we reciprocally transplanted soils and litter among the control and reduced rainfall treatments in the laboratory, and analyzed litter decomposition and its responses to a simulated extreme drought event. The decreased soil microbial biomass and altered physiological profiles with reduced rainfall promoted lower fine root-but not leaf-litter decomposition. Both leaf and root litter, from the reduced rainfall treatment, decomposed faster than those from the control treatment. The impact of the extreme drought event on fine root litter decomposition was higher in soils from the control treatment compared to soils subjected to long-term rainfall exclusion. Our results suggest contrasting mechanisms driving drought indirect effects on above-(for example, changes in litter quality) and belowground (for example, shifts in soil microbial community) litter decomposition, even within a single tree species. Quantifying the contribution of these mechanisms relative to the direct soil moisture-effect is critical for an accurate integration of litter decomposition into ecosystem carbon dynamics in Mediterranean forests under climate change. [ABSTRACT FROM AUTHOR]

The objectives of this study were to (1) evaluate earthworm-induced leaching of water and salt from salt-affected agricultural soils with constant and fluctuating soil moisture conditions and (2) determine the effects of earthworms on the distribution of soil salt in casts, burrow walls, and surrounding soils responsible for salt leaching. Soils were kept in mesocosms at constant moisture (CM) or underwent one wet-dry process (WD). Each soil moisture treatment had three earthworm treatments, including (1) inoculation with high abundance of earthworms (five endogeic Aporrectodea trapezoides), (2) inoculation with moderate abundance of earthworms (three endogeic A. trapezoides), and (3) no earthworm treatment. The presence of earthworms significantly increased total leaching water volume compared to the same treatment without earthworms in both moisture treatments. In the treatment following the wet-dry process, more than 65 % of water leaching occurred during the rainfall event, whereas in the treatment following constant moisture, more than 60 % of water leaching occurred after the rainfall event. The presence of earthworms produced a higher salt amount in the leaching water than the same moisture treatment without earthworms, but only the low number of earthworms (three endogeic A. trapezoides) caused a significantly higher total amount of leached salt than the same moisture treatment without earthworms. The percentage of leached salt in leaching water during the rainfall event ranged from 75.31 to 79.93 % in the wet-dry treatment and from 41.28 to 50.65 % in the constant moisture treatment. The wet-dry process significantly increased the total amount of leached salt from salt-affected agricultural soil compared to the constant moisture treatment when earthworms were present, which may be due to the significantly higher electrical conductivity of saturation extract (EC) of earthworm casts than those of burrow walls and surrounding soils in the 0- to 10-cm soil layer. [ABSTRACT FROM AUTHOR]

Landslides are a serious problem for humans and infrastructure in many parts of Europe. Experts know to a certain degree which parts of the continent are most exposed to landslide hazard. Nevertheless, neither the geographical location of previous landslide events nor knowledge of locations with high landslide hazard necessarily point out the areas with highest landslide risk. In addition, landslides often occur unexpectedly and the decisions on where investments should be made to manage and mitigate future events are based on the need to demonstrate action and political will. The goal of this study was to undertake a uniform and objective analysis of landslide hazard and risk for Europe. Two independent models, an expert-based or heuristic and a statistical model (logistic regression), were developed to assess the landslide hazard. Both models are based on applying an appropriate combination of the parameters representing susceptibility factors (slope, lithology, soil moisture, vegetation cover and other- factors if available) and triggering factors (extreme precipitation and seismicity). The weights of different susceptibility and triggering factors are calibrated to the information available in landslide inventories and physical processes. The analysis is based on uniform gridded data for Europe with a pixel resolution of roughly 30 m × 30 m. A validation of the two hazard models by organizations in Scotland, Italy, and Romania showed good agreement for shallow landslides and rockfalls, but the hazard models fail to cover areas with slow moving landslides. In general, the results from the two models agree well pointing out the same countries with the highest total and relative area exposed to landslides. Landslide risk was quantified by counting the number of exposed people and exposed kilometers of roads and railways in each country. This process was repeated for both models. The results show the highest relative exposure to landslides in small alpine countries such as Lichtenstein. In terms of total values on a national level, Italy scores highest in both the extent of exposed area and the number for exposed population. Again, results agree between the two models, but differences between the models are higher for the risk than for the hazard results. The analysis gives a good overview of the landslide hazard and risk hotspots in Europe and allows a simple ranking of areas where mitigation measures might be most effective. [ABSTRACT FROM AUTHOR]

Background and aims: The frequency of rain is predicted to change in high latitude areas with more precipitation in heavy, intense events interspersed by longer dry periods. These changes will modify soil drying cycles with unknown consequences for plant performance of temperate species. Methods: We studied plant growth and root traits of juveniles of four grasses and four dicots growing in a greenhouse, when supplying the same total amount of water given either regular every other day or pulsed once a week. Results: Pulsed water supply replenished soil moisture immediately after watering, but caused substantial drought stress at the end of the watering cycle, whereas regular watering caused more moderate but consistent drought. Grasses had lower water use efficiency in the pulsed watering compared to regular watering, whereas dicots showed no difference. Both grasses and dicots developed thinner roots, thus higher specific root length, and greater root length in the pulsed watering. Growth of dicots was slightly increased under pulsed watering. Conclusions: Temperate species coped with pulsed water supply by eliciting two responses: i) persistent shoot growth, most likely by maximizing growth at peaks of soil moisture, thus compensating for slower growth during drought periods; ii) plasticity of root traits related to increased resource uptake. Both responses likely account for subtle improvement of growth under changed water supply conditions. [ABSTRACT FROM AUTHOR]

The East Asian upper-tropospheric jet stream (EAJS) typically jumps north of 45°N in midsummer. These annual northward jumps are mostly classified into two dominant types: the first type corresponds to the enhanced westerly to the north of the EAJS's axis (type A), while the second type is related to the weakened westerly within the EAJS's axis (type B). In this study, the impacts of these two types of northward jumps on rainfall in eastern China are investigated. Our results show that rainfall significantly increases in northern Northeast China and decreases in the Yellow River-Huaihe River valleys, as well as in North China, during the type A jump. As a result of the type B jump, rainfall is enhanced in North China and suppressed in the Yangtze River valley. The changes in rainfall in eastern China during these two types of northward jumps are mainly caused by the northward shifts of the ascending air flow that is directly related to the EAJS. Concurrent with the type A (B) jump, the EAJS-related ascending branch moves from the Yangtze-Huai River valley to northern Northeast (North) China when the EAJS's axis jumps from 40°N to 55°N (50°N). Meanwhile, the type A jump also strengthens the Northeast Asian low in the lower troposphere, leading to more moisture transport to northern Northeast China. The type B jump, however, induces a northwestward extension of the lower-tropospheric western North Pacific subtropical high and more moisture transport to North China. [ABSTRACT FROM AUTHOR]

Lantana camara L. (Verbenaceae) is a weed of great significance in Australia and worldwide, but little is known about connections among components of its life history. We document over a 3-year period, the links between L. camara seed-bank dynamics and its above-ground growth, including size asymmetry in four land-use types (a farm, a hoop pine plantation and two open eucalypt forests) invaded by the weed near Brisbane, Queensland Australia. Seed-bank populations varied appreciably across sites and in response to rainfall and control measures, and they were higher (~1,000 seeds/m) when annual rainfall was 15-30 % below the long-term yearly average. Fire reduced seed-bank populations but not the proportion germinating (6-8 %). Nearly a quarter of fresh seeds remain germinable after 3 years of soil burial. For small seedlings (<10 cm high), the expected trade-offs in two life-history traits-survival and growth-did not apply; rather the observed positive association between these two traits, coupled with a persistent seed-bank population could contribute to the invasiveness of the plant. Relationships between absolute growth rate and initial plant size (crown volume) were positively linear, suggesting that most populations are still at varying stages of the exponential phase of the sigmoid growth; this trend also suggests that at most sites and despite increasing stand density and limiting environmental resources of light and soil moisture, lantana growth is inversely size asymmetric. From the observed changes in measures of plant size inequality, asymmetric competition appeared limited in all the infestations surveyed. [ABSTRACT FROM AUTHOR]

Land surface properties, such as vegetation cover and soil moisture, influence the partitioning of radiative energy between latent and sensible heat fluxes in daytime hours. During dry periods, soil-water deficit can limit evapotranspiration, leading to warmer and drier conditions in the lower atmosphere. Soil moisture can influence the development of convective storms through such modifications of low-level atmospheric temperature and humidity, which in turn feeds back on soil moisture. Yet there is considerable uncertainty in how soil moisture affects convective storms across the world, owing to a lack of observational evidence and uncertainty in large-scale models. Here we present a global-scale observational analysis of the coupling between soil moisture and precipitation. We show that across all six continents studied, afternoon rain falls preferentially over soils that are relatively dry compared to the surrounding area. The signal emerges most clearly in the observations over semi-arid regions, where surface fluxes are sensitive to soil moisture, and convective events are frequent. Mechanistically, our results are consistent with enhanced afternoon moist convection driven by increased sensible heat flux over drier soils, and/or mesoscale variability in soil moisture. We find no evidence in our analysis of a positive feedback-that is, a preference for rain over wetter soils-at the spatial scale (50-100?kilometres) studied. In contrast, we find that a positive feedback of soil moisture on simulated precipitation does dominate in six state-of-the-art global weather and climate models-a difference that may contribute to excessive simulated droughts in large-scale models. [ABSTRACT FROM AUTHOR]

Global climate models forecast an increase in the frequency and intensity of extreme weather events, including severe droughts. Based on multi-year relationships between precipitation amount and aboveground annual net primary production (ANPP), semi-arid grasslands are projected to be among the most sensitive ecosystems to changes in precipitation. To assess sensitivity to drought, as well as variability within the shortgrass steppe biome, we imposed moderate and severe rainfall reductions for two growing seasons in three undisturbed grasslands that varied in soil type and climate. We predicted strong drought-induced reductions in ANPP at all sites and greater sensitivity to drought in sites with lower average precipitation, consistent with continental-scale patterns. Identical experimental infrastructure at each site reduced growing season rainfall events by 50 or 80%, and significantly reduced average soil moisture in both years (by 21 and 46% of control levels, respectively). Despite reductions in soil moisture, ANPP responses varied unexpectedly-from no reduction in ANPP to a 51% decrease. Although sensitivity to drought was highest in the semi-arid grassland with lowest mean annual precipitation, patterns in responses to drought across these grasslands were also strongly related to rainfall event size. When growing season rainfall patterns were dominated by many smaller events, ANPP was significantly reduced by drought but not when rainfall patterns were characterized by large rain events. This interaction between drought sensitivity and rainfall event size suggests that ANPP responses to future droughts may be reduced if growing season rainfall regimes also become more extreme. [ABSTRACT FROM AUTHOR]

Aims: Plant diversity has been shown to significantly increase topsoil aggregate stability of machine-graded ski slopes. We hypothesise that this effect is specific for these disturbed sites and that at sites of low and no disturbance the effect decreases. Methods: We determined plant species richness, cover percentage of five functional groups, root (length) density, and biomass as well as soil aggregate stability, gravimetric soil moisture, soil density, and particle size distribution at different levels of disturbance (i.e. graded and un-graded ski slopes and the surrounding area). Results: Plant species richness, vegetation cover, aggregate stability and soil moisture were significantly reduced on machine-graded slopes compared to control plots but hardly on un-graded slopes. On the contrary, machine-grading increased soil density and friction angle compared to un-graded ski slopes. The influence of species richness on aggregate stability was only positive on gravely soils and graded ski slopes. Aggregate stability increased linearly up to approximately eight plant species, 70% vegetation cover and 0.006 g cm root density. Conclusions: Our study showed that the relationship between plant diversity and aggregate stability was strongest on slopes with high disturbance and relatively low species numbers. We suggest that high plant diversity, vegetation cover and root density need to be established after major human disturbance such as grading. [ABSTRACT FROM AUTHOR]

Competition for light has driven forest trees to grow exceedingly tall, but the lack of a single universal limit to tree height indicates multiple interacting environmental limitations. Because soil nutrient availability is determined by both nutrient concentrations and soil water, water and nutrient availabilities may interact in determining realised nutrient availability and consequently tree height. In SW Australia, which is characterised by nutrient impoverished soils that support some of the world's tallest forests, total [P] and water availability were independently correlated with tree height ( r = 0.42 and 0.39, respectively). However, interactions between water availability and each of total [P], pH and [Mg] contributed to a multiple linear regression model of tree height ( r = 0.72). A boosted regression tree model showed that maximum tree height was correlated with water availability (24%), followed by soil properties including total P (11%), Mg (10%) and total N (9%), amongst others, and that there was an interaction between water availability and total [P] in determining maximum tree height. These interactions indicated a trade-off between water and P availability in determining maximum tree height in SW Australia. This is enabled by a species assemblage capable of growing tall and surviving (some) disturbances. The mechanism for this trade-off is suggested to be through water enabling mass-flow and diffusive mobility of P, particularly of relatively mobile organic P, although water interactions with microbial activity could also play a role. [ABSTRACT FROM AUTHOR]

Rainfall distribution and the soil moisture regime have been recognized to be the key drivers of the phenological rhythms in Sahelian woody plants, although different climate triggers have been assumed to be involved in determining the date of the onset of the phenophase. However, almost no comparisons have been made of the actual relative predictive power of these environmental factors. The aim of our study was to quantify the ability of several factors to predict phenophase occurrence in the dominant woody populations of northern Mali. Canopy leafing, flowering and fruiting were monitored from May 2005 to July 2007. Multiple logistic regressions were used to test the predictive power of cumulative rainfall, soil moisture, air temperature, air humidity and day length, with time lags of up to 2 months. Artificial variables derived from time lags observed in phenophases were included as predictors to account for possible auto-correlation and cross-correlation among phenophases. Surprisingly, a decrease in temperature associated with different time lags was most often found to be the strongest predictor of both leafing and reproductive phenophases. In Sahelian shrubs, morphological and physiological adaptations strongly contribute to the relative independence of their activity from water availability, leaf phenology being a way to adjust the plant water balance to current water availability and atmospheric water content. This study provides insight towards the development of a mechanistic understanding of phenological control in the Sahel, which is becoming increasingly important in the context of expected climate changes. [ABSTRACT FROM AUTHOR]

Passive open-top chambers (OTCs) and rainout shelters (RSs) have been used for over two decades to manipulate temperature and water availability in experiments on plant communities. These types of manipulations have been independently evaluated; however, as experiments become more complex and multiple factors are evaluated the potential for unknown or undesirable treatment effects increases. We present the effects of temperature manipulations (with OTCs), water manipulations (with RSs and water additions), and a clipping treatment, implemented in a fully factorial design, on soil moisture and temperature over 2 years in a temperate grassland. Temperature was increased 0.2°C by OTCs. Soil volumetric water content was reduced 3% by RSs and increased 2% by watering. However, clipping vegetation, treatment interactions, and weather conditions also affected soil temperature and moisture. For example, in OTCs RSs increased the temperature an additional 0.4°C, watering lowered it 0.4°C, and clipping raised temperature 2°C. Similarly, changes in soil moisture due to the RSs decreased VWC by 3% and increased 1% by clipping whereas soil moisture due to watering was reduced 1% by the OTCs and clipping. We also found that OTCs are more effective at raising temperatures on cooler days when soil temperatures are below 16.3°C. Our results suggest that all treatment types generally affect soil variables in predicable ways, but use of such devices should be adopted with caution, as they do not act independently, or exclusively, on the target variables. [ABSTRACT FROM AUTHOR]

Winter wheat (Triticum aestivum L.) grows in dry season but summer maize (Zea mays L.) coincides with rainfall in the North China Plain (NCP). Increasing rainfall use efficiency and harmonizing its utilization between the two species is an effective way to mitigate impact on groundwater deriving from wheat irrigation. One to four times water supply (W1, to W4) were employed in wheat, three water treatments (W1, W2, and W4) in 2007-2008 and four (W1, W2, W3, and W4) in 2008-2009 were established in the field condition, the characteristics of water consumption in wheat and effects on rainfall utilization during subsequent maize were studied. The maximum wheat grain yield and the maximum water use efficiency were observed on the limited water treatment W2. Wheat consumed. water mainly came from irrigation and precipitation on excessive water treatments. Limited water supply enhanced water consumption from soil and vacated more water storage space. Compared with W4, the vacated water storage space increased 103-116 mm (W2) and 162-168 mm (W1). The difference of soil water content derived from previous wheat disappeared (P>0.05) around at maize elongation stage because of subsequent summer rainfall, and the rainfall stored in 2 m soil body increased more 83-88 mm (W1), and 69 mm (W2) than the treatment of W4, respectively. Drainage from 2 m soil profile on excessive water treatments (55-61 mm on W4, 9 mm on W3 during wheat growth period, and 36-40 mm on W4, 18 mm on W3 from wheat harvest to maize elongation) was determined but not on limited water treatments. These results indicate that the limited irrigation would be an effective practice for water-saving and high-yielding production of wheat in the NCP. [ABSTRACT FROM AUTHOR]

In semi-arid grassland ecosystems, soil biogeochemical processes are controlled by seasonal and inter-annual rainfall variation and temperature, which may override the long-term impact of grazers on N availability and N dynamics. In a three-year (2004-2006) case study of an Inner Mongolian grassland, we analysed time-integrated (ion-exchange resins) and instantaneous (soil mineral N extractions) inorganic N availability at three sites of varying grazing intensities and combined these data with information on soil water content (SWC), aboveground net primary productivity (ANPP) and plant N uptake. Additionally, the effects of rainfall and grazing on N-form availability (NO-N, NH-N) were considered. Grazing had less impact on N availability compared to seasonal and annual rainfall distribution. One of the three study years (2004) showed a grazing effect with higher resin-N availability at the ungrazed site compared to the heavily grazed site. Inorganic N availability was low in the driest year (2005) and highest in a year of average rainfall amount and favourable distribution (2004). In general, we found a positive relationship between inorganic N availability and both plant productivity and plant N uptake. Rainfall also controlled the plant available NO-N and NH-N pools; NH-N dominated the available inorganic N-form in times of low SWC, while the available NO-N increased with SWC. We observed N availability and plant productivity in a temporal synchronized pattern. Increased rainfall variability and land-use practices affecting SWC will likely alter N availability dynamics (and the relation of N-forms) and, therefore, important processes of semi-arid natural grassland carbon and N cycling. [ABSTRACT FROM AUTHOR]

Rainfed agriculture has experienced important transformations in the Mediterranean area over the last decades. This is particularly true for traditional vineyards which have been restructured after levelling operations designed to facilitate the use of machinery. Levelling operations change soil properties and structure, negatively affecting soil hydrological processes, decreasing soil water intake and storage in the soil profile. This effect may become exacerbated under a climate change scenario as a result of increased water losses due to runoff after high intensity events and the resulting decrease in water availability for crops. This paper examines the effects of land levelling, carried out before the establishment of new vineyards, on soil water availability for vineyards in a Mediterranean climate area. These effects have been analysed taking into account the different rainfall distribution patterns in the study area, including extreme events. Soil moisture was analysed at depths of from 0 to 80 cm, for a 12 year period, in areas with different degrees of disturbance as a result of land levelling operations. Simulated rainfall was applied at the same points to evaluate the steady infiltration rate and to estimate runoff rates. Precipitation, runoff, crop evapotranspiration and changes in soil moisture were assessed for each crop stage and year for the vine varieties Macabeo, Chardonnay and Parellada. Precipitation was not enough to satisfy crop water requirements in many years, particularly during the bloom–veraison and ripening stages. Soil water content had a significant effect on grape yield, particularly the available water content during the budburst–bloom and bloom–veraison stages. Differences in yield of about 50% between years and of over 28% between levelled and non-levelled areas under similar management practices were observed. [ABSTRACT FROM AUTHOR]

In water-limited grassland ecosystems, discrete and occasional precipitation events trigger brief but important episodes of biological activity. Differential responses of above- and below-ground biota to precipitation pulses may constrain biogeochemical transformations at the ecosystem scale. We examined the short-term dynamics of the whole ecosystem response to small precipitation events during 2003 and 2004 in a steppe on the Inner Mongolia Plateau. The results indicate that changes in soil moisture occur, with a 1–2 day time lag, only when the amount of precipitation exceeds 3 mm (from day of year [DOY] 120 to DOY 180) or 5 mm (after DOY 180). The interception of the developing plant canopy is a primary reason for the different temporal precipitation threshold. The lower threshold of effective rain is different between Net Ecosystem Exchange (NEE, 3 mm), Ecosystem Respiration ( Re, 3 mm) and Gross Ecosystem Production (GEP, 5 mm). The NEE reached a maximum 4–5 days after the end of effective rain events and dropped to 60–70% of the original fluxes after 10 days. However, the drop in GEP was greater than that of NEE and reached 30–50% of the original fluxes after 10–15 days without “effective rainfall.” The characteristics of the response time can be attributed to the variation in soil water content and the time of readjusting for the ecological processes after the effective rainfall. In addition, the independent responses of photosynthesis, respiration and evapotranspiration to precipitation probably contributed to this time lag. The results support the hypothesis that the concept of an ecologically significant rainfall event can be developed for an ecosystem. [ABSTRACT FROM AUTHOR]

The cycling of surface water, energy, nutrients, and carbon is different between semiarid grassland and shrubland ecosystems. Although differences are evident when grasslands are compared to shrublands, the processes that contribute to this transition are more challenging to document. We evaluate how surface redistribution of precipitation and plant responses to the resulting infiltration patterns could contribute to the changes that occur during the transition from grassland to shrubland. We measured soil water potential under grasses ( Bouteloua eriopoda), shrubs ( Larrea tridentata) and bare soil and changes in plant water relations and gas exchange following a 15 mm summer storm in the grassland–shrubland ecotone at the Sevilleta National Wildlife Refuge in central New Mexico USA. Following the storm, soil water potential (Ψs) increased to 30 cm depth beneath both grass and shrub canopies, with the greatest change observed in the top 15 cm of the soil. The increase in Ψs was greater beneath grass canopies than beneath shrub canopies. Ψs under bare soil increased only to 5 cm depth. The substantial redistribution of rainfall and different rooting depths of the vegetation resulted in high Ψs throughout most of the rooting volume of the grasses whereas soil moisture was unchanged throughout a large portion of the shrub rooting volume. Consistent with this pattern, predawn water potential (ΨPD) of grasses increased more than 5 MPa to greater than −1 MPa whereas ΨPD of shrubs increased to −2.5 MPa, a change of less than 2 MPa. Transpiration increased roughly linearly with ΨPD in both grasses and shrubs. In grasses, assimilation was strongly correlated with ΨPD whereas there was no relationship in shrubs where assimilation showed no significant response to the pulse of soil moisture following the storm. These data show that preferential redistribution of water to grass canopies enhances transpiration and assimilation by grasses following large summer storms. This process may inhibit shrubland expansion at the ecotone during periods without extreme drought. [ABSTRACT FROM AUTHOR]