Impact Of Soil Moisture Research Articles

Experimental Soil Warming Impacts Soil Moisture and Plant Water Stress and Thereby Ecosystem Carbon Dynamics

AbstractExperimental soil heating experiments have found a consistent increase in soil‐surface CO2 emissions (Fs), but inconsistent soil organic carbon (SOC) responses. Interpretation of heating effects is complicated by spatial heterogeneity and soil moisture, nitrogen availability, and microbial and plant responses. Here we applied a mechanistic ecosystem model to interpret heating impacts on a California forest subjected to 1 m deep, 4°C heating. The model accurately simulated control‐plot CO2 fluxes, SOC stocks, fine root biomass, soil moisture, and soil temperature, and the observed increases in Fs and decreases in fine root biomass. We show that a complex suite of interactions can lead to a consistent increase in Fs (∼17%) over the 5‐year study period, with very small changes in SOC stocks (<1%). Modeled increases in leaf water stress from soil drying reduced GPP and NPP. The resulting reduction in leaf and fine root allocation increased fine root litter inputs to the soil and reduced root exudation. Soil heating led to about a 50% larger increase in root autotrophic respiration than in heterotrophic respiration, with the heating effect on both these fluxes decreasing over the simulation period. Increased heterotrophic respiration led to increased soil N availability and plant N uptake. These heating responses are mechanistically linked, of magnitudes that can affect ecosystem dynamics, and long‐term observations of them are rarely made. Therefore, we conclude that a coupled observational and mechanistic modeling framework is needed to interpret manipulation experiments, and to improve projections of climate change impacts on terrestrial ecosystem carbon dynamics.

Evaporative characteristics of winter wheat in the guanzhong loess plateau region of shaanxi, china

This study explain the evaporative characteristics of winter wheat in the Guanzhong Loess Plateau region of Shaanxi through stem flow meters and weighing lysimeters. It examines the diurnal variations in evapotranspiration rates, leaf area index, and soil moisture's impact on winter wheat evaporation. Additionally, it explores the ratio of transpiration to evaporation and compares the evaporation measured by the water balance method with that of the lysimeters. The findings reveal distinct diurnal variations in transpiration rates under different weather conditions, with sunny days exhibiting an unimodal curve while cloudy and rainy days showcase irregular multi-peaked curves. The evaporation curve generally follows an unimodal pattern, with both leaf area index and soil moisture significantly influencing the evaporation process. From heading to early grain filling, the ratio of transpiration to evaporation ranges from 80.3 to 83.4%. Evaporation obtained through the water balance method (0-220 cm) is 6% less than that measured by the lysimeters. Bangladesh J. Bot. 53(3): 689-695, 2024 (September) Special

Understanding Terrestrial Water and Carbon Cycles and Their Interactions Using Integrated SMAP Soil Moisture and OCO‐2 SIF Observations and Land Surface Models

AbstractRecently, more advanced synchronous global‐scale satellite observations, the Soil Moisture Active Passive enhanced Level 3 (SMAP L3) soil moisture product and the Orbiting Carbon Observatory 2 (OCO‐2) solar‐induced chlorophyll fluorescence (SIF) product, provide an opportunity to improve the predictive understanding of both water and carbon cycles in land surface modeling. The Simplified Simple Biosphere Model version 4 (SSiB4) was coupled with the Top‐down Representation of Interactive Foliage and Flora Including Dynamics Model (TRIFFID) and a mechanistic representation of SIF. Incorporating dynamic vegetation processes reduced global SIF root‐mean‐squared error (RMSE) by 12%. Offline experiments were conducted to understand the water and carbon cycles and their interactions using satellite data as constraints. Results indicate that soil hydraulic properties, the soil hydraulic conductivity at saturation (Ks) and the water retention curve, significantly impact soil moisture and SIF simulation, especially in the semi‐arid regions. The wilting point and maximum Rubisco carboxylation rate (Vmax) affect photosynthesis and transpiration, then soil moisture. However, without atmospheric feedback processes, their effects on soil moisture are undermined due to the compensation between soil evaporation and transpiration. With optimized parameters based on SMAP L3 and OCO‐2 data, the global RMSE of soil moisture and SIF simulations decreased by 15% and 12%, respectively. These findings highlight the importance of integrating advanced satellite data and dynamic vegetation processes to improve land surface models, enhancing understanding of terrestrial water and carbon cycles.

Seasonal drought treatments impact plant and microbial uptake of nitrogen in a mixed shrub grassland on the Colorado Plateau.

For many drylands, both long- and short-term drought conditions can accentuate landscape heterogeneity at both temporal (e.g., role of seasonal patterns) and spatial (e.g., patchy plant cover) scales. Furthermore, short-term drought conditions occurring over one season can exacerbate long-term, multidecadal droughts or aridification, by limiting soil water recharge, decreasing plant growth, and altering biogeochemical cycles. Here, we examine how experimentally altered seasonal precipitation regimes in a mixed shrub grassland on the Colorado Plateau impact soil moisture, vegetation, and carbon and nitrogen cycling. The experiment was conducted from 2015 to 2019, during a regional multidecadal drought event, and consisted of three precipitation treatments, which were implemented with removable drought shelters intercepting ~66% of incoming precipitation including: control (ambient precipitation conditions, no shelter), warm season drought (sheltered April-October), and cool season drought (sheltered November-March). To track changes in vegetation, we measured biomass of the dominant shrub, Ephedra viridis, and estimated perennial plant and ground cover in the spring and the fall. Soil moisture dynamics suggested that warm season experimental drought had longer and more consistent drought legacy effects (occurring two out of the four drought cycles) than either cool season drought or ambient conditions, even during the driest years. We also found that E. viridis biomass remained consistent across treatments, while bunchgrass cover declined by 25% by 2019 across all treatments, with the earliest declines noticeable in the warm season drought plots. Extractable dissolved inorganic nitrogen and microbial biomass nitrogen concentrations appeared sensitive to seasonal drought conditions, with dissolved inorganic nitrogen increasing and microbial biomass nitrogen decreasing with reduced soil volumetric water content. Carbon stocks were not sensitive to drought but were greater under E. viridis patches. Additionally, we found that under E. viridis, there was a negative relationship between dissolved inorganic nitrogen and microbial biomass nitrogen, suggesting that drought-induced increases in dissolved inorganic nitrogen may be due to declines in nitrogen uptake from microbes and plants alike. This work suggests that perennial grass plant-soil feedbacks are more vulnerable to both short-term (seasonal) and long-term (multiyear) drought events than shrubs, which can impact the future trajectory of dryland mixed shrub grassland ecosystems as drought frequency and intensity will likely continue to increase with ongoing climate change.

Recent multispecies tree-growth decline reveals a severe aridity change in Mediterranean Chile

Soil moisture (SM) is a crucial factor in the water cycle, sustaining ecosystems and influencing local climate patterns by regulating the energy balance between the soil and atmosphere. Due to the absence of long-term, in-situ measurements of SM, studies utilizing satellite-based data and tree-ring analysis have become valuable in assessing variations of SM at regional and multi-century scales, as well as determining its effects on tree growth. This information is particularly pertinent in biodiversity hotspots made up of semi-arid ecosystems currently threatened by climate change. In the Mediterranean Chile region (MC; 30°–37° S), an ongoing megadrought since 2010 has resulted in a significant decline in the forest throughout the area. However, the impact of SM on tree growth at a multi-species and regional level remains unexplored. We analyzed a new network of 22 tree-ring width chronologies across the MC to evaluate the main spatiotemporal tree-growth patterns of nine woody species and their correlation with SM, using PCA. We also reconstructed the SM variations over the past four centuries and assessed its connection with large-scale climate forcings. Our results indicate that the primary growth patterns (PC1) explained 27% of the total variance and displayed a significant relationship with SM between 1982–2015 (r = 0.91), accurately reflecting the current megadrought. The tree-ring SM reconstruction covers the period 1616–2018 and shows a strong decrease around the year 2007, revealing an unprecedented recent change in aridity with respect to the last four centuries. The intensity of the South Pacific subtropical anticyclone, which primarily owe their existence to the subsiding branch of the Hadley Cell, appears as the primary climatic mechanism correlated with the reconstruction and the present aridity conditions in MC. The current SM conditions align with anticipated aridity changes in MC, providing a bleak perspective of future regional climate.

Response of Vegetation to Drought in the Source Region of the Yangtze and Yellow Rivers Based on Causal Analysis

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this area under the influence of climate–permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the source area and provide reference for ecological protection in permafrost regions.

Interplay of Soil and Plant Characteristics in Determining Soil Moisture Content in Sal Forest

This research paper delves into the intricate dynamics between soil and plant characteristics and their combined influence on soil moisture content in Sal forests. Sal (Shorea robusta), a dominant tree species in various parts of Asia, plays a crucial role in forest ecosystems, particularly in terms of water cycling and soil fertility. This study utilizes a multidisciplinary approach, encompassing soil science, botany, and environmental physics, to dissect the factors influencing soil moisture retention in these forests. The methodology involves a comprehensive analysis of soil propertiesand plant traits. The paper posits that a synergistic relationship between these soil and plant characteristics significantly impacts soil moisture levels, with implications for forest health and management. Findings from this research not only contribute to a deeper understanding of Sal Forest ecosystems but also offer practical insights for sustainable forest management practices, particularly in the context of climate change and water scarcity. Through its novel integration of various scientific disciplines, the study highlights the complexity of forest ecosystems and the need for holistic management approaches that consider both soil and plant factors in maintaining ecological balance.

FOSTERING SUSTAINABLE AGRICULTURE: ANALYZING THE INFLUENCE OF DIVERSE RAINFALL SEASONS ON FRUIT YIELD USING PREDICTIVE MACHINE LEARNING MODELS

Rainfall is critical in fruit production because it provides plants with essential water. Fruit trees suffer stress when there is not enough rainfall, making it difficult to yield fruits of the best quality. Rainfall also significantly impacts soil moisture regulation, essential for fruit trees' healthy growth and development. The impact of rainfall on fruit production during the last ten years is examined in this study. The four districts of Sindh Larkana, Mirpur Khas, Khairpur, and Thatta were selected based on agricultural data and rainfall figures. The Climate Data Processing Center in Karachi of the Pakistan Meteorological Department provided the annual rainfall data in millimeters. At the same time, data on the tons of fruit produced annually between 2007 and 2016 were acquired from Pakistan's Agriculture Extension Department. The study analyzes how seasonal rainfall affects fruit production in the area using machine learning multiple regression techniques. The study's conclusions highlight the substantial effects of seasonal and annual rainfall fluctuations on fruit production in the study areas. Rainfall after monsoon has a negative impact on the production of mangoes in Larkana and guavas in the Sindh regions of Mirpur Khas and Thatta. Rainfall during the winter also has a negative effect on Khairpur's mango crop. Pre-monsoon rainfall in the Thatta region causes guava production to decline, while monsoon rainfall in the Larkana region has a negative impact on mango production. The study finds that implementing sustainable water management practices and investigating climate-resilient agricultural techniques are necessary to mitigate the adverse effects of weather conditions on fruit production. In the designated areas, these actions could increase fruit yields.

Response of Ecosystem Productivity to High Vapor Pressure Deficit and Low Soil Moisture: Lessons Learned From the Global Eddy‐Covariance Observations

AbstractAlthough there is mounting concern about how high vapor pressure deficit (VPD) and low soil moisture (SM) affect ecosystem productivity, their relative importance is still under debate. Here, we comprehensively quantified the relative impacts of these two factors on ecosystem gross primary production (GPP) using observations from a global network of eddy‐covariance towers and two approaches (sensitivity analysis and linear regression model). Both approaches agree that a higher percentage of sites experience GPP reduction from high VPD than from low SM over the growing season. However, the constraint of high VPD and low SM on GPP reduction is tightly linked with climates and plant functional types. Humid and mesic ecosystems including forests and grasslands are dominated by VPD, while the semi‐arid and arid ecosystems including shrublands and savannas are dominated by SM. The varying dominant role of these two factors on GPP is closely related to plant stomatal behavior, as predicted by a stomatal conductance model. Additionally, we highlight the non‐linear impact of SM on GPP during droughts and the possible underestimation of the SM effects for deep‐rooted plants when only using surface‐layer SM. Our results shed light on a better understanding of the impacts of VPD and SM on vegetation productivity, with important implications for modeling the response and feedback of ecosystem dynamics to current and future climates.

How does the explicit treatment of convection alter the precipitation–soil hydrology interaction in the mid-Holocene African humid period?

Abstract. Global climate models with coarse horizontal resolution are largely unable to reproduce the monsoonal precipitation pattern over North Africa during the mid-Holocene. Here we present the first regional, storm-resolving simulations with an idealized but reasonable mid-Holocene vegetation cover. In these simulations, the West African monsoon expands farther north by about 4–5∘, and the precipitation gradient between the Guinea coast and the Sahara decreases compared to simulations with a barren Sahara as it is today. The northward shift of monsoonal precipitation is caused by land surface–atmosphere interaction, i.e., the coupling of soil moisture and precipitation, as well as interactions of the land surface with the large-scale monsoon circulation (e.g., the African easterly jet). The response of the monsoon circulation to an increased vegetation cover is qualitatively similar but more pronounced in parameterized convection simulations. We attribute the differences in monsoonal precipitation to differences in soil moisture that are strongly controlled by runoff and precipitation characteristics. If precipitation is intense and falls over a spatially small region, as in our storm-resolving simulations, about 35 % of all precipitation water goes into runoff instead of filling soil moisture storage. In contrast, in light and spatially more homogeneous precipitation, as produced in our parameterized convection simulations, only some 20 % leaves the grid cell as runoff. Therefore, much more water is available to maintain high soil moisture content. We confirm the significant role of soil moisture and runoff by performing simulations with the same constant soil moisture field in both storm-resolving and parameterized convection simulations. These constant soil moisture simulations cancel the effect of lower soil moisture on the land–atmosphere feedback cycle in our storm-resolving simulations. We show that precipitation strongly increases in the storm-resolving simulations, especially in moisture-controlled regions, such as the northern Sahel and Sahara, and reaches equally high values as in parameterized convection simulations. Our study highlights how the type of rainfall (e.g., local and intense or widespread and light) impacts soil moisture and thus land–atmosphere feedbacks. This is contrary to many studies that focus mainly on the amount of rainfall and how it modifies land–atmosphere feedbacks. Moreover, this study suggests that comprehensive land-surface schemes, which appropriately respond to varying precipitation characteristics, are needed for studying land surface–atmosphere interaction.

Unsaturated Zone: Advances in Experimental and Theoretical Investigations

The unsaturated zone has a crucial role in subsurface processes that, in turn, impact soil moisture, groundwater quality and quantity, and ecosystem function [...]

Does Shade Impact Coffee Yield, Tree Trunk, and Soil Moisture on Coffea canephora Plantations in Mondulkiri, Cambodia?

Shade is a natural condition for coffee plants; however, unshaded plantations currently predominate in Asia. The benefits of shading increase as the environment becomes less favorable for coffee cultivation, e.g., because of climate change. It is necessary to determine the effects of shade on the yield of Coffea canephora and on the soil water availability. Therefore, three coffee plantations (of 3, 6, and 9 ha) in the province of Mondulkiri, Cambodia, were selected to evaluate the effect of shade on Coffea canephora yields, coffee bush trunk changes, and soil moisture. Our study shows that shade-grown coffee delivers the same yields as coffee that is grown without shading in terms of coffee bean weight or size (comparing average values and bean variability), the total weight of coffee fruits per coffee shrub and the total weight of 100 fruits (fresh and dry). Additionally, fruit ripeness was not influenced by shade in terms of variability nor in terms of a possible delay in ripening. There was no difference in the coffee stem diameter changes between shaded and sunny sites, although the soil moisture was shown to be higher throughout the shaded sites.

Groundwater from perennial springs provide refuge from wildfire impacts in mountainous semiarid watershed

Warming temperatures, earlier snowmelt, and the elongation of dry seasons are contributing to the propensity for more frequent and severe wildfires in semiarid, mountainous watersheds, which act as source watersheds for communities, especially in the southwestern United States. Research on how vegetation and water sources will respond following wildfires in these watersheds is critical for water resource, land, and forest managers. Little research has been completed on the effect of groundwater discharged from springs on revegetation of burned forests. We test whether springs, as perennial sources of water in semiarid watersheds, have the potential to protect roots and seeds from being damaged and facilitate the regrowth of native vegetation in areas affected by wildfires, thereby creating zones of fire refugia and mitigating the propensity for floods, erosion, and incursion of invasive species. The effect of springs on revegetation is studied in the Asaayi Creek Watershed located in the Chuska Mountains, NM/AZ, and in the Royal Gorge Park located near Cañon City, CO. In the Asaayi Creek watershed, remote sensing imagery and ground surveys show that springs facilitated revegetation following a June 2014 wildfire. Post-fire time lapse photography reveal more abundant vegetation around springs and more diverse vegetation in areas where there are multiple springs. Significantly higher Enhanced Vegetative Index (EVI) values are observed around perennial springs in the Asaayi Creek watershed and also around intermittent springs in the Royal Gorge area, one year after wildfires occurred in each study area. However, the revegetation around the perennial springs in the Asaayi Creek Watershed is widespread compared to Royal Gorge. There are multiple perennial springs that are clustered close together in Asaayi Creek Watershed, and only three intermittent flowing springs are located in the Royal Gorge burn area. Springs in the Asaayi Creek watershed provide a critical source of water that directly impacts soil moisture near the springs and in turn, protects roots and buds allowing native vegetation to regenerate.

Observed variability in soil moisture in engineered urban green infrastructure systems and linkages to ecosystem services

Soil-water-climate-vegetation interactions jointly determine the ability of landscapes to provide ecosystem functions and services. In particular, spatio-temporal patterns in soil moisture underpin landscape ecohydrology. Though these patterns have been of interest to researchers for some time, there is new interest in the topic today as city managers engineer green infrastructure (GI) into urban landscapes. This paper presents soil moisture data collected from 2012 to 2014, and weighing lysimeter observations continuing through 2016, in two urban GI systems. Relationships between precipitation history, season, soil depth, hydraulic loading ratio (HLR) on the frequency and magnitude of soil moisture responses are described quantitatively. A logistic regression model is used to quantify the odds that each of these variables triggers a detectable soil moisture response. The results suggest that the higher HLR site (Site 2, HLR = 3.8) had 129.7% higher odds of a soil moisture response than Site 1 (HLR = 1). The results also indicate that there are 82.9% lower odds of a response in summer than in winter. Moreover, the odds of a response decrease with increasing soil depth. The linkage between GI siting and design decisions that impact soil moisture and ecosystem services is illustrated by also reporting evapotranspiration (ET) rates at the sites as determined by the lysimeter. Higher ET observed during wetter conditions supports the hypothesis that GI siting and design factors that lead to higher moisture content can engender greater ecosystem services associated with this hydrologic process. Indeed, the higher HLR of Site 2 sustained higher soil moisture levels during the summer compared to Site 1.

A Case Study of Soil Moisture and Infiltration after an Urban Fire

There is an increased risk of future fire disturbances due to climate change and anthropogenic activity. These disturbances can impact soil moisture content and infiltration, which are important antecedent conditions for predicting rainfall–runoff processes in semi-arid regions. Yet these conditions are not well documented. This case study provides critical field measurements and information, which are needed to improve our understanding of mechanisms such as precipitation and temperature that lead to the variability of soil properties and processes in urban and burned landscapes. In June 2018, a fire burned a portion of the riparian zone in Alvarado Creek, an urban tributary of the San Diego River in California, United States. This fire provided an opportunity to observe soil moisture content and infiltration for one year after the fire. Three transects (one burned and two unburned) were monitored periodically to evaluate the complex spatial and temporal dynamics of soil moisture and infiltration patterns. Average dry season soil moisture content was less than five percent volume water content (%VWC) for all transects, and the burned transect exhibited the lowest %VWC during the wet season. Infiltration rates displayed a high degree of spatial and temporal variability. However, the location with the highest burn severity had the lowest average infiltration rate. The observed differences between the burned and unburned transects indicate that the fire altered hydrologic processes of the landscape and reduced the ability of the soil to retain water during the wet season. This research provides the first high-resolution soil moisture and infiltration field analysis of an urban fire-disturbed stream in southern California and a method to characterize post-fire hydrologic conditions for rainfall–runoff processes.

Root‐zone soil moisture variability across African savannas: From pulsed rainfall to land‐cover switches

AbstractThe main source of soil moisture variability in savanna ecosystems is pulsed rainfall. Rainfall pulsing impacts water‐stress durations, soil moisture switching between wet‐to‐dry and dry‐to‐wet states, and soil moisture spectra as well as derived measures from it such as soil moisture memory. Rainfall pulsing is also responsible for rapid changes in grassland leaf area and concomitant changes in evapotranspirational (ET) losses, which then impact soil moisture variability. With the use of a hierarchy of models and soil moisture measurements, temporal variability in root‐zone soil moisture and water‐stress periods are analysed at four African sites ranging from grass to miombo savannas. The normalized difference vegetation index (NDVI) and potential ET (PET)‐adjusted ET model predict memory timescale and dry persistence in agreement with measurements. The model comparisons demonstrate that dry persistence and mean annual dry periods must account for seasonal and interannual changes in maximum ET represented by NDVI and to a lesser extent PET. Interestingly, the precipitation intensity and soil moisture memory were linearly related across three savannas with ET/infiltration ∼ 1.0. This relation and the variability of length and timing of dry periods are also discussed.

The pantropical response of soil moisture to El Niño

Abstract. The 2015–2016 El Niño event ranks as one of the most severe on record in terms of the magnitude and extent of sea surface temperature (SST) anomalies generated in the tropical Pacific Ocean. Corresponding global impacts on the climate were expected to rival, or even surpass, those of the 1997–1998 severe El Niño event, which had SST anomalies that were similar in size. However, the 2015–2016 event failed to meet expectations for hydrologic change in many areas, including those expected to receive well above normal precipitation. To better understand how climate anomalies during an El Niño event impact soil moisture, we investigate changes in soil moisture in the humid tropics (between ±25∘) during the three most recent super El Niño events of 1982–1983, 1997–1998 and 2015–2016, using data from the Global Land Data Assimilation System (GLDAS). First, we use in situ soil moisture observations obtained from 16 sites across five continents to validate and bias-correct estimates from GLDAS (r2=0.54). Next, we apply a k-means cluster analysis to the soil moisture estimates during the El Niño mature phase, resulting in four groups of clustered data. The strongest and most consistent decreases in soil moisture occur in the Amazon basin and maritime southeastern Asia, while the most consistent increases occur over eastern Africa. In addition, we compare changes in soil moisture to both precipitation and evapotranspiration, which showed a lack of agreement in the direction of change between these variables and soil moisture most prominently in the southern Amazon basin, the Sahel and mainland southeastern Asia. Our results can be used to improve estimates of spatiotemporal differences in El Niño impacts on soil moisture in tropical hydrology and ecosystem models at multiple scales.

Towards a Long-Term Reanalysis of Land Surface Variables over Western Africa: LDAS-Monde Applied over Burkina Faso from 2001 to 2018

This study focuses on the ability of the global Land Data Assimilation System, LDAS-Monde, to improve the representation of land surface variables (LSVs) over Burkina-Faso through the joint assimilation of satellite derived surface soil moisture (SSM) and leaf area index (LAI) from January 2001 to June 2018. The LDAS-Monde offline system is forced by the latest European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalysis ERA5 as well as ERA-Interim former reanalysis, leading to reanalyses of LSVs at 0.25° × 0.25° and 0.50° × 0.50° spatial resolution, respectively. Within LDAS-Monde, SSM and LAI observations from the Copernicus Global Land Service (CGLS) are assimilated with a simplified extended Kalman filter (SEKF) using the CO2-responsive version of the ISBA (Interactions between Soil, Biosphere, and Atmosphere) land surface model (LSM). First, it is shown that ERA5 better represents precipitation and incoming solar radiation than ERA-Interim former reanalysis from ECMWF based on in situ data. Results of four experiments are then compared: Open-loop simulation (i.e., no assimilation) and analysis (i.e., joint assimilation of SSM and LAI) forced by either ERA5 or ERA-Interim. After jointly assimilating SSM and LAI, it is noticed that the assimilation is able to impact soil moisture in the first top soil layers (the first 20 cm), and also in deeper soil layers (from 20 cm to 60 cm and below), as reflected by the structure of the SEKF Jacobians. The added value of using ERA5 reanalysis over ERA-Interim when used in LDAS-Monde is highlighted. The assimilation is able to improve the simulation of both SSM and LAI: The analyses add skill to both configurations, indicating the healthy behavior of LDAS-Monde. For LAI in particular, the southern region of the domain (dominated by a Sudan-Guinean climate) highlights a strong impact of the assimilation compared to the other two sub-regions of Burkina-Faso (dominated by Sahelian and Sudan-Sahelian climates). In the southern part of the domain, differences between the model and the observations are the largest, prior to any assimilation. These differences are linked to the model failing to represent the behavior of some specific vegetation species, which are known to put on leaves before the first rains of the season. The LDAS-Monde analysis is very efficient at compensating for this model weakness. Evapotranspiration estimates from the Global Land Evaporation Amsterdam Model (GLEAM) project as well as upscaled carbon uptake from the FLUXCOM project and sun-induced fluorescence from the Global Ozone Monitoring Experiment-2 (GOME-2) are used in the evaluation process, again demonstrating improvements in the representation of evapotranspiration and gross primary production after assimilation.

Spatiotemporal impact of soil moisture on air temperature across the Tibet Plateau

The Himalayan Tibet Plateau (HTP) is regarded as the third pole of the globe and is highly sensitive to global climate change. The hydrothermal properties of HTP greatly impacts the water cycle of the HTP and climate change in its surrounding regions. Using the NCEP-CFSR dataset, this study investigated the spatiotemporal pattern of soil moisture (SM) during different seasons considering vegetation types. The response of the evaporation fraction (EF) to SM and the impact of SM on air temperature through evapotranspiration were analyzed. Results showed that the spatial distribution of SM across the HTP was persistent during different seasons. A decreasing SM trend was observed from southeastern to northwestern HTP. Further, results of this study indicated a wetting tendency in past thirty years, espcially in desert region. In addition, the majority of the HTP regions were dominated by persistent transitional SM conditions which could be identified in the Himalayas and the southeastern HTP, whereas a persistent SM deficit in the Qaidam basin. The sensitivity of temperature response to EF was the strongest during spring and summer. Moreover, the spatial distribution of sensitivity was highly consistent with the vegetation regionalization, indicating the remarkable impact of vegetation type on the sensitivity of temperature to EF changes in summer.

Stemflow in a neotropical forest remnant: vegetative determinants, spatial distribution and correlation with soil moisture

Tree size and exposure is a key driver of stemflow; canopy heterogeneity leads to spatial randomness of stemflow; stemflow impacts soil moisture in superficial layers. Stemflow (SF) plays a relevant role in forest hydrology by delivering rain to the soil around trees. This study sought to explore the effects of tree traits on the amount of SF in an Atlantic Forest remnant in Southeast Brazil using stepwise regressions from April 2016 to March 2017. In addition, we evaluated the spatial association among trees in regard to SF using bivariate Ripley’s K as well as the impact of SF on soil water content (SWC) at five different layers (up to 1 m) using linear regression. We found that the diameter at breast height (DBH), percentage of mosses on the tree trunk, average leaf area, and relative position of the tree within the canopy were selected as explanatory variables in total and monthly average SF models. For the wet season SF models, crown area, percentage of mosses cover on the trunk, average leaf area, and relative position within the canopy were the selected variables, whereas for the dry period SF models, DBH and percentage of mosses were selected. A complete spatial randomness (CSR) between the SF classes was confirmed. We observed that SF impacted the SWC in the superficial layers. Therefore, tree size, exposure, and seasonal differences were the key drivers of SF amount due to the leaf losses during the dry period. Heterogeneity of the canopy is probably responsible for the CSR of SF in the study area. We expect that this study will contribute to the understanding of the hydrological processes in the Atlantic forest hotspot by clarifying the aspects of water capture by trees.