Volumetric Soil Moisture Content Research Articles

Spatial variability and uncertainty associated with soil moisture content using INLA-SPDE combined with PyMC3 probability programming

Spatial variability and uncertainty associated with soil volumetric moisture content (SVMC) is crucial in moisture prediction accuracy, this paper sets out to address this point of SVMC by developing data-driven model. Grid samples of SVMC covered approximately a 3-ha field during the jointing growth stage of winter wheat, and SVMC were measured by Time Domain Reflectometry (TDR), located in North China Plain, China. Bayesian inference was performed to explore spatial heterogeneity, robustness, transparency, interpretability and uncertainty related to SVMC using python-based PyMC3 combined with Integrated Nested Laplace Approximation with the Stochastic Partial Differential Equation (INLA-SPDE) model. The results showed that the prediction surface of SVMC, the lower and upper limits of 95% credible intervals quantified uncertainty associated with SVMC, cauchy prior of the flexibility and adaptability to obtain state-of-the-art predictive performance is more robust than gaussian prior for SVMC prediction, the transparency and interpretability of SVMC prediction model were revealed by MCMC (Markov-Chain Monte-Carlo) trace plots, KDE (Kernel density estimates), and rank plots. The uncertainty associated with SVMC can explicitly be described using the highest-posterior density interval, the prediction lower and upper limits.

Modelling Soil Moisture Content with Hydrus 2D in a Continental Climate for Effective Maize Irrigation Planning

In light of climate change and limited water resources, optimizing water usage in agriculture is crucial. This study models water productivity to help regional planners address these challenges. We integrate CROPWAT-based reference evapotranspiration (ETo) with Sentinel 2 data to calculate daily evapotranspiration and water needs for maize using soil and climate data from 2021 to 2023. The HYDRUS model predicted volumetric soil moisture content, validated against observed data. A 2D hydrodynamic model within HYDRUS simulated temporal and spatial variations in soil water distribution for maize at a non-irrigated site in Hungary. The model used soil physical properties and crop evapotranspiration rates as inputs, covering crop development stages from planting to harvest. The model showed good performance, with R² values of 0.65 (10 cm) and 0.81 (60 cm) in 2021, 0.51 (10 cm) and 0.50 (60 cm) in 2022, and 0.38 (10 cm) and 0.72 (60 cm) in 2023. RMSE and NRMSE values indicated reliability. The model revealed water deficits and proposed optimal irrigation schedules to maintain soil moisture between 32.2 and 17.51 V/V%. This integrated approach offers a reliable tool for monitoring soil moisture and developing efficient irrigation systems, aiding maize production’s adaptation to climate change.

Assessment of Soil Structural Quality Under Area Closure and Open Grazing Land in Hidabu Abote District, North Shewa Zone, Oromia Regional State, Ethiopia

The experiment was conducted at Sire Morise kebele, Hidabu Abote district, to assess soil structural quality of different land management system (area closure and open grazing land). In this study, area closure land management practice was compared with open grazing land management practice in similar slope positions for soil structural quality build up. Soil samples were collected from both land management system at three slope position with three times replication. Totally 36 undisturbed soil blocks were collected from both land management system at 10 and 20 cm sampling depths. The finding of the study showed that the average value of volumetric moisture content and saturated hydraulic conductivity of soil were greater at area closure than open grazing land management system and also higher at bottom slope position than middle and upper slope position. The mean value of air-filled porosity and bulk density were lower at both area closure management practices and bottom slope position. Bulk density, volumetric soil moisture content and saturated hydraulic conductivity at 20 cm sampling depth were shows significantly different with respect to management practices. According to visual assessment in the field, soil physical quality was unfavourable in open grazing land management system and upper part of landscape position soils and the visual assessment scores showed that the soils under area closure had a good soil structural quality. There were strong relations among the three visual field assessment methods and also between visual assessment methods and laboratory determined soil properties of both land management system. In general, the result of the study showed that physical and structural quality of soil in area closure was improved due to good land management system. Based on the result of study it can be conclude that area closure improves soil physical and soil structural qualities and from the technical point of view, open grazing lands in hilly area should be changed to area closure before soil properties and soil nutrient contents are exhausted more.

Effects of Drought at Anthesis on Flag Leaf Physiology and Gene Expression in Diverse Wheat (Triticum aestivum L.) Genotypes

The current study aimed to quantify the effects of two drought intensities achieved by deprivation of watering for 45 and 65% of the volumetric soil moisture content (VSMC) for 14 days after wheat anthesis to identify physio-biochemical and molecular changes associated with drought tolerance in six genotypes with different drought tolerance. Drought at 65% of VSMC induced a significant decrease in the chlorophyll a content in the drought-sensitive genotype, which indicated a strong loss of photosynthetic reaction centres. Further, in the drought-tolerant genotype, the content of carotenoids, which could play a vital role in resisting water shortage stress, tended to increase. The increased production of malondialdehyde showed that the antioxidant system in the drought-sensitive genotypes was not properly activated. A significant decrease in catalase (CAT; EC 1.11.1.6) was observed at a 45% reduction in VSMC, compared to the control, in the drought-sensitive genotype, and at a reduction in VSMC of 65%, in all medium sensitive genotypes. Further, the drought-tolerant and -medium tolerant genotypes responded to drought with a decline in total glutathione concentrations with the intention to reinforce their defence system. Thereby, dehydroascorbate reductase (DHAR; EC 1.8.5.1), monodehydroascorbate reductase (MDHAR; EC 1.6.5.4), and glutathione reductase (GR; EC 1.6.4.2) were critical enzymes involved in the ascorbate–glutathione cycle together with CAT, showing their main role in the detoxification of ROS produced with the reduction in VSMC by 65%. The results of gene expression analysis showed that severe drought increased the levels of the DHN5 and WZY2 genes (that were significantly positively correlated) in the drought-tolerant genotype, whose grain weight, area, and length did not change in maturity. Also, it was seen that DHN5 expression showed a significant positive correlation with grain length and proline content at a 45% reduction in VSMC. The identification of different mechanisms under drought can contribute to the selection of drought-tolerant genotypes.

Effect of Evapotranspiration on Soil Moisture Dynamics in Top Surface Layer of a Loamy Land in Climate Change Condition

Abstract Evapotranspiration affects uncertain changes in volumetric soil moisture content (θ) of earth surface, which is considerably controlled by temporal variability of weather parameters like rainfall and ambient temperature. Accurate measurement of temporal variation and spatial distribution of θ in a particular land is very challenging. Numerical modelling with any suitable computer code might be useful in such cases. Thus, Hydrus 2D modelling of θ variation in the soil at Odisha University of Agriculture and Technology (OUAT) in Bhubaneswar is undertaken as main objective of present study to investigate soil moisture dynamics in top surface layer. For the study, the θ in OUAT land was measured daily by 5 TM water content sensor for the duration of two years spanning from January 2021 to December 2022. Meteorological data for these 2 years are collected from a nearby weather station at OUAT and used for calculating evapotranspiration (ET) based on five different well known ET models. Soil hydraulic parameters of OUAT land were also evaluated by laboratory investigation. The evapotranspiration so calculated along with precipitation and materials properties were then assigned as the inputs in Hydrus 2D simulations. The simulated results are found to be in good agreement with field observations. It is proven by Pearson’s coefficient of determination (R2) and Nash-Sutcliffe efficiency (NSE) which are found to be 0.83 and 0.84 respectively. The soil moisture simulation was the most accurate only when measured soil parameters along with atmospheric boundary involving Penman-Monteith (PM) ET model were considered as model inputs.

Observations of reduced ET and persistent elevated water table beneath a riparian forest gap following emerald ash borer invasion and tree mortality

AbstractEmerald ash borer (EAB) (Agrilus planipennis Fairmaire), an invasive, phloem‐feeding beetle native to Asia, has killed millions of ash (Fraxinus spp.) trees in North America since it was detected in southeast Michigan in 2002. Consistently high mortality of black ash (Fraxinus nigra) and green ash (F. pennsylvanica) which often occur in riparian forests is a concern given their role in regulating soil moisture and shallow groundwater levels. We monitored and compared hydrologic processes in a riparian forest impacted by EAB invasion and an adjacent unimpacted riparian forest site in southwest Michigan. From 2018 to 2022, we recorded soil moisture, depth to groundwater and meteorological variables at 15‐min intervals throughout the growing season in a canopy gap following EAB‐caused ash mortality and in adjacent, unaffected forest in the Augusta Creek riparian zone. Groundwater contributions to evapotranspiration (ETG) were estimated using a groundwater level fluctuation (WLF) method. Significant differences in volumetric soil moisture content (16%–26% higher in the gap than forest), average depth to water (10 cm in the gap vs. 70 cm below land surface in the forest) and mean daily ETG (0.6 in the gap vs. 3.0 mm per day in the forest) persisted across four growing seasons. Within the gap, prolonged saturation of the near surface may be contributing to a shift from a forested riparian ecosystem to herb and sedge‐dominated wetland. These differences have implications for an array of riparian zone ecosystem services, a concern given the extent of ash mortality already sustained in much of eastern North America.

Effects of train vibration load on the structure and hydraulic properties of soils

Investigating the impact of train-induced vibration loads on soil hydraulic properties, this study conducted experiments using a self-designed indoor soil seepage platform that incorporates vibration loads. The experiments were complemented with scanning electron microscopy to analyze the influence of train-induced vibration loads on soil hydraulic conductivity and its evolutionary characteristics under different vibration frequencies. The experimental results indicated that as the vibration frequency increases from no vibration (0 Hz) to 20 Hz, the time required for the soil volumetric moisture content to reach its peak and stabilize decreases rapidly. However, after the vibration frequency exceeds 20 Hz, the rate at which the time required for the volumetric moisture content to reach its peak and stabilize decreases slows down. Furthermore, the soil pore water pressure increases with the increase in vibration frequency. At a vibration frequency of 80 Hz, the peak value of pore water pressure increases by 105% compared to the non-vibration state, suggesting that higher vibration frequencies promote the development and acceleration of soil pore moisture migration. Additionally, as the vibration frequency increases, the soil hydraulic conductivity initially experiences a rapid increase, with a growth rate ranging from 40.1 to 47.4%. However, after the frequency exceeds 20 Hz, this growth rate significantly decreases, settling to only 18.6% to 7.8%. When the soil was subjected to a vibration load, the scanning electron microscopy test revealed alterations in its pore structure. Micropores and small pores transformed into macropores and mesopores. Additionally, the microstructural parameters indicated that vibration load decreased the complexity of soil pores, thereby speeding up the hydraulic conduction process. This, in turn, affected the hydraulic properties of the soil and established a relationship between pore structure complexity and soil hydraulic properties.

Microtopography causes small‐scale variation in harvest and forage quality of high‐yielding silage grassland in northern Germany

AbstractBackgroundLocal sward dieback, especially in grasslands on peat soil, in response to the extreme 2018/2019 drought demonstrates climate vulnerability of intensive grasslands in northern Central Europe.MethodsWe explore the influence of microtopography, that is, the within‐field mosaic of depressions and elevated patches, on soil volumetric moisture content, standing biomass and biomass crude protein (CP) and fibre content in intensively managed grassland on peat soil in a moist year (2021) and a dry year (2022) for quantifying small‐scale spatial heterogeneity within a field.ResultsWe found high within‐field variation in soil moisture, biomass and forage quality and a moisture dependence of productivity that was stronger in the dry year. CP ranged from 10% to 25% within a field, being lower in moist depressions than elevated patches in the wet (but not in the dry) summer.ConclusionsThe moister depressions help to limit the overall productivity decline in dry summers, whereas, in moist summers, the higher dry patches produce more protein‐rich forage than the depressions, where productivity is higher but quality is lower. We recommend adapting grassland management to this heterogeneity through spatially differentiated management regimes in order to better cope with an increasingly drier and more variable climate.

Response of Carbon-Fixing Bacteria to Patchy Degradation of the Alpine Meadow in the Source Zone of the Yellow River, West China.

This study aims to enlighten our understanding of the distribution of soil carbon-fixing bacteria (cbbL-harboring bacteria) and their community diversity in differently degraded patches at three altitudes. MiSeq high-throughput sequencing technology was used to analyze the soil carbon-fixing bacteria community diversity of degraded patches and healthy meadow at three altitudes. Redundancy analysis (RDA) and structural equation model (SEM) were used to analyze the correlation and influence path between environmental factors and carbon-fixing bacteria. The results showed that degradation reduced the relative abundance of Proteobacteria from 99.67% to 95.57%. Sulfurifustis, Cupriavidus, and Alkalispirillum were the dominant genera at the three altitudes. Hydrogenophaga and Ectothiorhodospira changed significantly with altitude. RDA results confirmed that available phosphorus (AP) was strongly and positively correlated with Proteobacteria. AP and total nitrogen (TN) were strongly and positively correlated with Hydrogenophaga. Grass coverage and sedge aboveground biomass were strongly and positively correlated with Sulfurifustis and Ectothiorhodospira, respectively. Elevation adversely affected the relative abundance of dominant carbon-fixing bacteria and diversity index by reducing the coverage of grass and soil volumetric moisture content (SVMC) indirectly, and also had a direct positive impact on the Chao1 index (path coefficient = 0.800). Therefore, increasing the content of nitrogen, phosphorus and SVMC and vegetation coverage, especially sedge and grass, will be conducive to the recovery of the diversity of soil carbon-fixing bacteria and improve the soil autotrophic microbial carbon sequestration potential in degraded meadows, especially in high-altitude areas.

Impact of soil and water conservation structures on the spatial variability of topsoil moisture content and crop productivity in semi-arid Ethiopia

Plant available soil moisture and its spatial variability is among the most important limiting factors for crop and livestock productivity in semi-arid Ethiopia. The objectives of this study were therefore: 1) to measure the effects of land use and slope gradient on spatial variability of topsoil moisture content. 2) to analyze the variability of topsoil moisture content and crop responses under different soil and water conservation (SWC) structures and 3) to analyze whether topsoil moisture content, grain and biomass yields vary in relation to SWC structures. In total, 21 large runoff plots (600–1000 m2) were installed and treated with stone bunds, trenches, stone bunds with trenches and a control plot at each site. Plot sites were located on gentle (5%), medium (12%) and steep (16%) slopes of cropland and rangeland. Topsoil (0–15 cm) moisture content for plots were monitored daily using soil moisture probes (Theta-Probes) and weekly using manual sampling over two growing seasons. Crop performance was monitored during two growing seasons and grain and biomass yield were measured at harvest. Results show that average gravimetric moisture content of the topsoil during growing seasons is remarkably higher for cropland (33–25 g/100 g) compared to rangelands (24–20 g/100 g). This is due to tillage-induced runoff retention and infiltration. Soil moisture content decreases with increasing slope gradients, owing to increased drainage. Considering the effects of SWC structures, average topsoil moisture contents at accumulation and erosion zones are generally higher as compared to middle zone between two successive SWC structures. Average seasonal volumetric soil moisture content of 38.2 (cm3/100 cm3) in 2011 and 39.4 (cm3/100 cm3) in 2012 for accumulation zone of plots with stone bunds with trenchers are significantly higher than at other sampling locations. Crop growth performance, grain and biomass yield varied among plots and depended on slope gradients and SWC structures. Grain yields of wheat in 2011 and barley in 2012 were significantly higher for plots with SWC structures as compared to control plots and are highly correlated to topsoil moisture content (r = 0.64; p < 0.04 in 2011 and r = 0.59, p < 0.01 in 2012). Even when taking into account the cropland area occupied by SWC structures, grain yield increased by (4.2%−33%) for plots with SWC structures as compared to control plots. Overall, our results show that implemented measures may not only reduce runoff and soil loss, but also increase crop productivity by enhancing soil moisture and thus can significantly contribute to sustainability of agro-ecosystems in semi-arid environments.

Increasing cotton lint yield and water use efficiency for subsurface drip irrigation without mulching.

Planting without mulching can eliminate the residual film pollution caused by the long-term use of plastic film covers, but it will increase soil moisture evaporation and heat loss and severely reduce water use efficiency and cotton productivity in cotton (Gossypium hirsutum L.) fields in arid regions. It is unclear whether the advantages of subsurface drip irrigation and nighttime irrigation can be leveraged to reduce the amount of irrigation applied in fields, improve the soil and leaf hydrothermal environments, and increase the synchronicity of yield and water use efficiency (WUE). Therefore, in a two-year field experiment (2019-2020), cotton was grown under different irrigation treatments (I5, 3753 m3 ha-1; I4, 3477 m3 ha-1; I3, 3201 m3 ha-1; I2, 2925 m3 ha-1; and I1, 2649 m3 ha-1). The soil volumetric moisture content, soil temperature, leaf relative water content (RWC), daily changes in gas exchange parameters, lint yield, and WUE were evaluated. The results showed that reducing irrigation can reduce the soil volumetric moisture content (0-40cm soil layer), increase the soil temperature and soil temperature conductivity, and increase the leaf temperature, intercellular carbon dioxide concentration (Ci), and WUE; however, reducing irrigation is not conducive to increasing the leaf RWC, net photosynthetic rate (Pn), stomatal conductance (Gs), or transpiration rate (Tr). There was no significant difference in WUE between the I3 and I4 treatments from 8:00 to 20:00, but the lint yield in these treatments increased by 2.8-12.2% compared to that in the I5 treatment, with no significant difference between the I3 and I4 treatments. In addition, a related analysis revealed that the positive effects of the leaf hydrothermal environment on the Pn and soil temperature on the WUE occurs during the same period (10:00-16:00). Overall, an irrigation amount of 3201-3477 m3 ha-1 applied with a subsurface nighttime irrigation system without mulching can enhance the soil moisture content and soil temperature, maintain a high photosynthetic capacity, and increase the lint yield and WUE. These results revealed that the negative impacts of plastic film contamination in arid areas can be alleviated.

Variation of Stem CO2 Efflux and Estimation of Its Contribution to the Ecosystem Respiration in an Even-Aged Pure Rubber Plantation of Hainan Island

The stem CO2 efflux (Es) plays an important role in the carbon balance in forest ecosystems. However, a majority of studies focus on ecosystem flux, and little is known about the contribution of stem respiration to ecosystem respiration (Reco) for rubber (Hevea brasiliensis) plantations. We used a portable CO2 analyzer to monitor the rate of Es in situ at different heights (1.5 m, 3.0 m and 4.5 m) in an even-aged rubber plantation from 2019 to 2020. Our results showed that Es exhibited a significant seasonal difference with a minimum value in April and a maximum in September. The mean annual rate of Es at 3.0 m in height (1.65 ± 0.52 μmol·m−2·s−1) was slightly higher than Es at 4.5 m in height (1.56 ± 0.59 μmol·m−2·s−1) and Es at 1.5 m in height (1.51 ± 0.48 μmol·m−2·s−1). No obvious differences in vertical variations were found. An area-based method (Ea) and a volume-based method (Ev) were used to estimate stem respiration at stand levels. One-way ANOVA showed that Ea had no obvious differences in vertical variation (p = 0.62), and Ev indicated differences in vertical variation (p &lt; 0.05). Therefore, the Ea chamber-based measurements at breast height were reasonable and practical extrapolation proxies of stem respiration in an even-aged rubber plantation. With the use of the area-based method, the stem carbon values released from a mature rubber forest were estimated to be 1.214 t C·hm−2·a−1 in 2019 and 1.414 t C·hm−2·a−1 in 2020. Ea/Reco and Ev/Reco showed seasonal changes, with a minimum value in April and a maximum value in December. The leaf area index (LAI) and soil volumetric moisture content (VWC) were the major impact factors of Ea/Reco in an even-aged pure rubber plantation.

Long Term Seasonal Variability on Litterfall in Tropical Dry Forests, Western Thailand

Nutrient recycling is one of the most important services that supports other processes in ecosystems. Changing litterfall patterns induced by climate change can cause imbalances in nutrient availability. In this study, we reported the long-term (28-year) interplay between environmental factors and variability among litterfall fractions (leaves, flowers, and fruit) in a tropical dry forest located in Kanchanaburi, Thailand. A long-term litter trap dataset was collected and analyzed by lagged generalized additive models. Strong seasonality was observed among the litter fractions. The greatest leaf and flower litterfall accumulated mostly during the cool, dry season, while fruit litterfall occurred mostly during the rainy season. For leaf litter, significant deviations in maximum temperature (Tmax), volumetric soil moisture content (SM), and evapotranspiration (ET) during the months prior to the current litterfall month were the most plausible factors affecting leaf litter production. Vapor pressure deficit (VPD) and ET were isolated as the most significant factors affecting flower litterfall. Interestingly, light, mean temperature (Tmean), and the southern oscillation index (SOI) were the most significant factors affecting fruit litterfall, and wetter years proved to be highly correlated with elevated fruit litterfall. Such environmental variability affects both the triggering of litterfall and its quantity. Shifting environmental conditions can therefore alter nutrient recycling rates through the changing characteristics and quantity of litter.

A Deep Learning Data Fusion Model Using Sentinel-1/2, SoilGrids, SMAP, and GLDAS for Soil Moisture Retrieval

Abstract We develop a deep learning–based convolutional-regression model that estimates the volumetric soil moisture content in the top ∼5 cm of soil. Input predictors include Sentinel-1 (active radar) and Sentinel-2 (multispectral imagery), as well as geophysical variables from SoilGrids and modeled soil moisture fields from SMAP and GLDAS. The model was trained and evaluated on data from ∼1000 in situ sensors globally over the period 2015–21 and obtained an average per-sensor correlation of 0.707 and ubRMSE of 0.055 m3 m−3, and it can be used to produce a soil moisture map at a nominal 320-m resolution. These results are benchmarked against 14 other soil moisture evaluation research works at different locations, and an ablation study was used to identify important predictors. Significance Statement Soil moisture is a key variable in various agriculture and water management systems. Accurate and high-resolution estimates of soil moisture have multiple downstream benefits such as reduced water wastage by better understanding and managing the consumption of water, utilizing smarter irrigation methods and effective canal water management. We develop a deep learning–based model that estimates the volumetric soil moisture content in the top ∼5 cm of soil at a nominal 320-m resolution. Our results demonstrate that machine learning is a useful tool for fusing different modalities with ease, while producing high-resolution models that are not location specific. Future work could explore the possibility of using temporal input sources to further improve model performance.

Effect of Terracing on Soil Moisture of Slope Farmland in Northeast China’s Black Soil Region

The impact of terracing construction on the soil moisture content of slope farmland was analyzed at three sites in northeast China’s black soil region, across a range of latitudes and hydrological, temperature and soil quality conditions. At each research site, slope farmland with terracing was compared to unterraced slope farmland with a similar shape and gradient. During the wet crop growth period (July) and dry postharvest period (October) of 2022, the TRIME-PICO64TDR soil moisture measuring instrument was used to measure the soil moisture content at depths of 0–60 cm. Terracing increased soil moisture content by up to 2.83 percentage points during the crop growth period and by up to 1.69 percentage points during the postharvest period. Terracing had a significant impact on the volumetric soil moisture content of the shallower soil layer (0–30 cm) during the growing period, and on the volumetric soil moisture content of the deeper soil layer (30–60 cm) during the postharvest period. Terracing weakens the effect of slope position on volumetric soil moisture, reducing differences in volumetric soil moisture content among different slope positions. The difference in the water conservation benefit of terracing among the sites is mainly related to soil quality: the lower the soil bulk density and the higher the silt clay content is, the greater the benefit of terracing for retaining moisture. The findings of this study can be beneficial for guiding management measures for slope arable soil in black soil regions around the world.

Effect of Soil Volumetric Water Content on the CO2 Diffusion Coefficient

Purpose: The soil air diffusion coefficient (Ds) is particularly important for the study of soil gas diffusion movement, and there are still many uncertainties in the widely used methods; as such, a method was designed to in situ measure the soil gas diffusion coefficient. Methods: Four different soil media were selected and studied by means of a designed in situ measurement of soil gas diffusion coefficients, and these were compared and analyzed with the predictions of several commonly used prediction models. In addition, they were combined with gas transport models to validate the results of the empirical models that were obtained by the in situ measurements. Results: The results of the data indicate that increasing the volumetric soil moisture content decreases the soil gas diffusion coefficient, with changes in the soil gas diffusion coefficient for the small-grained quartz sand medium being similar to those predicted by the Buckingham model. The soil gas diffusion coefficients for the large-grained quartz sand were similar to the Millington and Quirk model predictions at low humidity; for increased humidity, it was instead similar to the Buckingham model predictions. The soil gas diffusion coefficients of the two active media were closer to those of the SWLR model with high Cm. In addition, the R2 of the measured data was verified, by empirical modeling, to be greater than 0.54, and inversion experiments were conducted to verify that the results were consistent with those of the SWLR model. Conclusion: When measuring relative diffusion coefficients in the field, we recommend the in situ measurement method, which is more reflective of the actual situation in natural environments and provides more accurate data support for soil carbon flux studies.

Combined effects of shade and drought on physiology, growth, and yield of mature cocoa trees

Climate models predict decreasing precipitation and increasing air temperature, causing concern for the future of cocoa in the major producing regions worldwide. It has been suggested that shade could alleviate stress by reducing radiation intensity and conserving soil moisture, but few on-farm cocoa studies are testing this hypothesis. Here, for 33 months, we subjected twelve-year cocoa plants in Ghana to three levels of rainwater suppression (full rainwater, 1/3 rainwater suppression and 2/3 rainwater suppression) under full sun or 40 % uniform shade in a split plot design, monitoring soil moisture, physiological parameters, growth, and yield. Volumetric soil moisture (ϴw) contents in the treatments ranged between 0.20 and 0.45 m3m−3 and increased under shade. Rainwater suppression decreased leaf water potentials (ѱw), reaching −1.5 MPa in full sun conditions indicating severe drought. Stomatal conductance (gs) was decreased under the full sun but was not affected by rainwater suppression, illustrating the limited control of water loss in cocoa plants. Although pre-dawn chlorophyll fluorescence (Fv/Fm) indicated photoinhibition, rates of photosynthesis (Pn) were highest in full sun. On the other hand, litter fall was highest in the full sun and under water stress, while diameter growth and carbon accumulation increased in the shade but was negatively affected by rainwater suppression. Abortion of fruits and damage to pods were high under shade, but dry bean yield was higher compared to under the full sun. The absence of interactions between shade treatments and rainwater suppression suggests that shade may improve the performance of cocoa, but not sufficiently to counteract the negative effects of water stress under field conditions.

Topographic Drivers of Soil Moisture Across a Large Sensor Network in the Southern Appalachian Mountains (USA)

AbstractUnderstanding the distribution of soil moisture is notoriously difficult in topographically complex regions that are subject to both large‐scale climate gradients and fine‐scale effects of terrain, vegetation, and soil structure. Remote sensing approaches capture large‐scale moisture patterns but are limited in spatial and temporal resolution, while commercial field sensors remain too expensive to deploy intensively over large spatial extents. Here, we demonstrate the use of low‐cost (&lt;20 USD) custom sensors to create a large monitoring network of surficial (0–15 cm depth) volumetric soil moisture content (VMC) across Great Smoky Mountains National Park (GSMNP) (NC, TN, USA). In laboratory tests, temperature‐calibrated VMC values approached the accuracy of commercial probes. We deployed over 80 sensors across multiple watersheds, topographic positions, and a 1,800‐m elevation gradient, and created hierarchical models to understand associations of VMC with spatial (30‐m resolution) and temporal (daily) variables related to water supply and demand. Elevation had the strongest association with VMC, with a fivefold increase across the gradient reflecting 1.5‐fold changes in both (increased) precipitation and (decreased) evapotranspiration; slope angle was a strong mediating factor. Common proxies for moisture including topographic convergence index were not associated with VMC, likely due to limited contributions of surface drainage to local water balance. Our model predicted daily VMC of a set of validation sensors with a root mean square error of 4.8%, which may be improved by site‐specific field calibration. Our study indicates that spatially extensive, field‐based soil moisture networks are practical, accurate, and an important component of regional environmental monitoring.

Soil moisture, stressed vegetation and the spatial structure of soil erosion in a high latitude rangeland

AbstractSoil erosion has been a persistent problem in high‐latitude regions and may worsen as climate change unfolds and encourages increased anthropogenic exploitation. We propose that soil moisture is likely to shape future erosion trends, as moisture stress reduces the capacity of vegetation cover to retard erosive processes. However, the spatial variability of soil moisture in high‐latitude soils—and the ways in which this variability drives the spatial distribution of erosion features—is poorly understood. We addressed this knowledge gap with a study of andosol erosion in southern Iceland. Our study used a combination of high‐resolution (&lt;3 cm) remote sensing data (using normalised difference vegetation index (NDVI) and normalised difference red edge as metrics of plant vitality) and long‐term, in situ measurements of soil moisture to unpick the relationship between moisture stress, vegetation vitality and patchy soil erosion. Mean NDVI increased with distance from eroded areas, varying from ~0.6 in vegetated areas on the margins of erosion patches to ~0.8 in areas &gt;10 m from eroded terrain. We found lower moisture availability close to existing erosion features: mean volumetric soil moisture content varied from 17% (proximal to erosion patch) to 36% (distal to erosion patch). We also found that variability in soil moisture decreased with distance from eroded areas: the coefficient of variation (CV) in soil moisture varied from 0.33 (proximal to erosion patch) to 0.13 (distal to erosion). Our findings indicate that the margins of erosion patches have a stressful soil environment due to exposure to the atmosphere. The vegetation in these locations grows less vigorously, and the exposed soil becomes more vulnerable to erosion, leading to erosion patch expansion and coalescence. If these conditions hold more generally, they may represent a feedback mechanism that facilitates the lateral propagation of soil erosion in high‐latitude regions.

A dataset of the observations of carbon, water and heat fluxes over an alpine meadow in Haibei (2015–2020)

Covering an area of 5.04×105 km2 on the Qinghai-Tibetan Plateau, Alpine meadow is essential to the plateau ecological barrier function and regional sustainable development. Since May 2014, Haibei National Field Research Station for Alpine Grassland (Haibei Station hereafter) has been accumulating amounts of valuable data by employing eddy covariance techniques to continuously measure carbon and water cycles and energy exchanges between an alpine Graminoid-Kobresia meadow ecosystem and the atmosphere. In the following of data processing such as outlier removal and flux data gaps filled by boosted regression tree model, Haibei Station plans to publish a dataset of the continuous observations of carbon, water, and heat fluxes of the alpine meadow from 2015 to 2010. This dataset consists of the subsets of carbon, water, and heat fluxes data (i.e. net ecosystem CO2 exchange, ecosystem CO2 respiration, gross ecosystem CO2 exchange, latent heat flux, and sensible heat flux) and the subsets of routine meteorological data (i.e. air temperature, air relative humidity, total solar radiation, net radiation, photosynthetically active radiation, precipitation, soil temperature, volumetric soil moisture content). The temporal resolutions of the dataset are half-hourly, daily, monthly, and yearly scales. This dataset can be used to validate the parameters of processes-based ecological models of carbon and water cycles and to evaluate the spatiotemporal patterns and evolution trends in ecological functions of carbon sequestration and water-holding capacity in alpine meadow ecosystems.