Soil Moisture Content Research Articles

Method for remote measurement of specific conductivity and moisture of subsurface soil horizons

The aim of the research is to develop a radar method for determining the physical and chemical parameters of subsurface soil horizons, providing rapid determination of moisture and specific conductivity in the area of the plant root system. The proposed method is based on a set of Fresnel equations which describe reflection of electromagnetic waves from the interface between dielectric media in vertical and horizontal polarization of the probing signal. For the practical implementation of the method, it is proposed to use two unmanned aerial vehicles that form a bistatic radar system which irradiates the Earth's surface obliquely in order to create the Brewster's effect and increase the fraction of the radio signal reflected from subsurface horizons. The percentage of moisture and the specific conductivity of soil are calculated from the measured values of the imaginary part of the complex permittivity. The required accuracy of moisture and conductivity measurements is achieved by two-step calibration of the measuring device. The values of the moisture content and specific conductivity of soil obtained by radar at a frequency of 469 MHz are in good agreement with the results of measuring these parameters using the soil moisture meter TDR 150 Spectrum Technologies, Inc.

Effects of Biochar Pyrolysis Temperature and Application Rate on Saline Soil Quality and Maize Yield

The application of biochar to improve the quality of saline soils has attracted widespread attention. However, the impact of saline soil amendments with biochar prepared at different pyrolysis temperatures remains unclear. Therefore, we conducted a two-year (2022–2023) field experiment in the Hetao Irrigation District, China, to evaluate the effects of the biochar pyrolysis temperature (C1: 300 °C, C2: 500 °C, and C3: 700 °C) and application rate (T1: 10 t/ha and T2: 20 t/ha) on the soil quality and maize yield. The results indicated that (1) all biochar treatments significantly decreased the soil bulk density and increased the soil porosity; (2) treatment C3T1 significantly increased the soil moisture content and decreased soil salinity. The C3T2 treatment significantly increased the soil’s organic carbon content, and the soil’s available phosphorus content was greatest in the C1T2 treatment. (3) The maize yield increased linearly with the soil quality index (SQI), which was attributed mainly to improvements in the soil water–salt conditions and increases in the soil organic carbon content. In summary, biochar produced at high pyrolysis temperatures, when applied at a low application rate (C3T1), can result in high corn yields and improve saline soil quality.

Effects of different afforestation years on soil moisture and nutrient content in Maxian Mountain of the Loess Plateau

In the area of “returning farmland to forest” on the Loess Plateau in China, it is difficult to cultivate artificially planted trees into forests. In the current study, abandoned cultivated land after 10 years of natural restoration served as controls (CK), while the treatments included afforestation periods of 2, 4, 6, 8, and 10 years. Soil samples were collected from various depths: 0–20, 20–40, 40–60, 60–80, to 80–100 cm. The findings revealed that with increasing years of artificial afforestation, soil pH gradually increased, and soil moisture content rose in the 0–20 cm layer while declining in deeper layers (20–100 cm) in the Maxian Mountain region of the Loess Plateau. Moreover, the total carbon, nitrogen, phosphorus, and potassium content initially increased and then decreased with the duration of artificial afforestation, reaching peak values after 8 years. Contents of organic matter, ammonium nitrogen, nitrate nitrogen, available phosphorus, and available potassium in the same soil layer increased with each year of afforestation. However, upon reaching 10 years of artificial afforestation, the effective nutrient content in the 60–80 and 80–100 cm soil layers exhibited a decrease. The values of Integrated Fertility Index (IFI) in different afforestation years were ranked as follows: 8 years > 6 years > 10 years > 4 years > 2 year, but all of them were significantly smaller than those of natural restoration plot CK (P < 0.05). Overall, soil fertility in the Maxian Mountain area of the Loess Plateau increases with each additional year of artificial afforestation. However, when the artificial afforestation period is 10 years, soil fertility decreases and marking a shift from enhancement to decline beyond this duration.

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.

Mulching practices alter soil moisture, physico-chemical properties and pineapple (Smooth cayenne) yield

This field experiment was conducted in Chichu Kebele in the Dilla Zuria area from 2020 to 2023. The objective of the experiment was to determine the optimal mulching strategy for enhancing soil fertility and pineapple production by comparing three treatments (grass mulch, plastic mulch, and farmers’ practices without any mulch) using a RCB (Randomized Complete Block) design. The study’s findings showed that the treatments with plastic mulch had the greatest soil moisture content values (18.41%), while the treatments with no mulch had the lowest values (11.39%). Compared to mulched treatments, pineapple planted without mulch had the greatest bulk density values (1.43 g/cm3). Total nitrogen and organic carbon has increase by 34 and 25%, respectively due to plastic mulching. However, total nitrogen and organic carbon has increase by 43 and 37.5%, respectively due to grass mulching. Fruit length was larger by 42.7 and 33.2%, respectively due to plastic and grass mulch compared to the control. However, fruit girth was wider by 54.1 and 43.8%, respectively due to plastic and grass mulches compared to the control. The pineapple with the most fruit yield (71.39 t/ha), fruit length (17.4 cm), fruit girth (46.67 cm), and sucker number (15 pieces) was obtained using plastic mulching. However, pineapple grown without mulch had the lowest yield ever noted. Plastic mulch outperformed farmers’ practices and grass mulching in terms of conserving soil moisture, which increased yield and yield characteristics. For the baseline, the marginal rate of return generated by the plastic and grass mulch treatments was 118.5 and 93.65%, respectively. Thus, the study’s best recommendation for improving soils and achieving a high pineapple fruit yield is to grow pineapples using plastic mulch.

Effects of Drip Irrigation Flow Rate and Layout Designs on Soil Salt Leaching and Cotton Growth under Limited Irrigation

Optimal drip irrigation management in shallow groundwater areas needs to clarify the effects of flow rate and layout designs on the soil moisture, salt distribution, cotton root length density, plant height, leaf area, and yield. In this study, a one-year field experiment was conducted from April to October 2018 in the fifth company of the 16th Regiment in Alar City, Xinjiang, to investigate the effects of various drip flow rates and layout designs of cotton growth. Two drip flow rates (2.8 and 5.6 L·h−1) and two layout designs (one film, two drip tapes, and six rows; one film, three drip tapes, and six rows) were applied to explore the optimal combination, resulting in a total of four treatments that were irrigated three times in the whole growth period. Soil moisture, salt distribution, cotton root length density, plant height, and leaf area were measured. The main results were as follows: (1) Under the same layout designs, the soil moisture content was higher and the soil salinity was lower when the drip flow rate was 5.6 L·h−1, and the cotton root length density, plant height, leaf area, and yield were significantly higher than that of 2.8 L·h−1. (2) Under the same drip flow rate, the soil desalination rate, cotton growth indexes, and yield under the three-tapes treatment were significantly higher than the values of the two-tapes treatment. The actual yield of treatment D was 21.56%, 19.23%, and 11.71% higher than that of treatments A, B, and C, respectively. (3) The crop evapotranspiration of cotton during the two irrigation cycles showed an increasing trend, and the groundwater contribution showed a smaller and then increasing trend. Overall, the combination of three tapes and a drip flow rate of 5.6 L·h−1 had the highest cotton yield and net income, which were 6211.36 kg·hm−2 and 4820.21 kg·hm−2 for the theoretical and actual yields. The results of this study can provide a reference for the management of limited irrigation leaching soil salinity and cotton cultivation in shallow groundwater areas.

Photosynthetic Acclimation of Larch to the Coupled Effects of Light Intensity and Water Deficit in Regions with Changing Water Availability.

The impact of frequent water deficits on dominant tree species in boreal forests has received increased attention, particularly towards addressing the global climate change scenarios. However, the impacts of coupled light intensity and water deficit in the regeneration and growth of Larix gmelinii seedlings, a dominant species in China's boreal forests, are still unclear. We conducted a dual-factor controlled experiment with four light intensities (natural sunlight, 50% shading, 75% shading, and 90% shading) and three soil water conditions (80%, 60%, and 40% soil saturated water content). The results showed that the coupling of light and water has a significant effect on the growth and development of Larix gmelinii seedlings. In 40% of the saturated soil moisture content, net photosynthetic rate, transpiration rate, chlorophyll a, and total phenol-leaf were significantly lower than the same light conditions under 80% soil saturated water content. Under the coupling treatment of 60% soil saturated water content and 50% shading treatment, the plant height increment, net photosynthetic rate, stomatal conductance, transpiration rate, chlorophyll a, and phenolic compound content were significantly higher than those of other coupling treatments; however, more than 75% shading inhibited photosynthetic parameters, chlorophyll a, total flavonoid-leaf, and total flavonoid-branch. Our results have important implications for forest management practices; they provide a scientific reference for the early growth of Larix gmelinii seedlings under the coupling of light and water and promote the survival and growth of seedlings.

Relationships among soil moisture at various depths under diverse climate, land cover and soil texture

Soil moisture is an important component of the hydrological cycle and a key mediator between land surface and atmospheric interactions. Although substantial progress has been made in remote sensing of soil moisture at different spatial scales, the shallow penetration depth of remote sensors greatly limits their utility for applications in meteorological modelling and hydrological studies where the critical variable of interest is the root-zone soil moisture content. Therefore, this study assesses the relationship between soil moisture at the surface (10 cm) and in lower soil layers (20, 40, 60, 80, 100, and 120 cm) under varying climates, soils, and crop types. Cross-correlation analysis is applied to daily in-situ soil moisture measurements from 4712 locations in agricultural lands across the contiguous United States. Our analysis demonstrates that zero-day lag always produced the highest correlation between 10 cm soil moisture and soil moisture in the lower layers. In addition, a positive and strong relationship between 10 and 20 cm soil moisture (r = 0.84) was observed, while the relationships between 10 and 40 cm soil moisture were moderate (r = 0.52). The decline in cross-correlation continued to the deeper soil layers, which indicated that, on a daily timescale, the surface soil moisture gradually becomes decoupled with soil moisture at greater depths. Therefore, our research suggests that the estimation of soil moisture in the soil layers up to 40 cm based on surface soil moisture is most promising. However, the influence of climate, crop type, and soil texture on the strength of relationships between surface and lower layers makes the prediction difficult. The comparatively weak relationship between precipitation and soil moisture (0.09–0.32), as well as the relationship between reference evapotranspiration (ETo) and soil moisture (−0.19–0.18), in this study can be attributed to scale mismatching from different data sources.

Advancing process-based flood frequency analysis for assessing flood hazard and population flood exposure

Recent studies have showcased the use of process-based hydrological models with Stochastic Storm Transposition (SST) techniques to conduct Flood Frequency Analysis (FFA). This framework, referred hereby FFA-SST, has proved to be a robust strategy to estimate peak flows of specific annual exceedance probability (e.g., 100-year peak flow) that can reflect natural and anthropogenic disturbances, including changes in land use and meteorological patterns. With the objective of advancing the FFA-SST framework, this study presents for the first time the use of a spatially-resolved Integrated Surface-Subsurface Hydrological Model (ISSHM) to conduct FFA-SST. This allows us to extend the analysis from peak flow responses to flood extent, enabling a unique view and analysis of flood hazard and population flood exposure at the basin scale. As a proof-of-concept, we used the ISSHM, Amanzi–ATS, and the SST model, RainyDay, to conduct FFA-SST by simulating the flood response to 5000 annual synthetic storm events in a ∼2000km2 Southeast Texas watershed. We demonstrate that ATS, without site-specific calibration, provides a robust process-based representation of peak flows, flood extent, streamflow, evapotranspiration, soil moisture content, and water storage changes. Our results and analyses, covering frequency curves up to a 500-year return period for peak flows, basin inundation fractions, and the number of people exposed to flooding, offer a unique perspective to analyze flood impacts across spatial scales. Overall, this study provides critical insights for flood risk management by extending the FFA-SST framework to include both flood hazard and population flood exposure analyses at the basin scale. Such an approach will empower stakeholders and disaster emergency agencies with a more comprehensive understanding of flood impacts across the entire basin domain, facilitating informed decision-making for flood risk assessment and management.

Mechanisms of spring freshet generation in southern Quebec, Canada

Seasonal forecasting of spring floods in snow-covered basins is challenging due to the ambiguity in the driving processes, uncertain estimations of antecedent catchment conditions, and the choice of predictor variables. In this study, we attempt to improve the prediction of spring flow peaks in southern Quebec, Canada, by studying the preconditioning mechanisms of runoff generation and their impact on inter-annual variations in the timing and magnitude of spring peak flow. Historical observations and simulated data from a hydrological and snowmelt model were used to study the antecedent conditions that control flood characteristics in 12 unregulated snow-dominated catchments. Maximum snow accumulation (peak SWE), snowmelt and rainfall volume and intensity, soil moisture, river baseflow, and the air freezing index, a proxy for soil freezing, were estimated during the pre-flood period. Stepwise multiple linear regression was used to identify the most relevant predictors and assess their relative contribution to interannual variability flood variability. Peak SWE was not by itself a strong predictor of spring flood magnitude and timing. The snowmelt rate during the pre-flood period was the most ubiquitous and skillful predictor of spring flood magnitude, followed by the rainfall intensity. The ‘soil memory’ effect, represented here by the simulated soil moisture content and freezing depth, was generally poorly related to flood characteristics. SWE and snowmelt dynamics dominated the interannual variability of flood magnitude in the southern and agricultural basins while rainfall intensity had a stronger influence in the northern, snowier forested basins. More complex machine learning models (random forest and support vector regression) did not perform better than the simple linear models to predict peakflow from antecedent hydroclimatic factors. These results highlight the impact of climate and land cover and use on spring flood generation mechanism and the moderate predictability potential of spring floods based on antecedent hydrological factors.

Synergistic enhancement of regeneration capacity and ecological functions of Robinia pseudoacacia L. plantations in the Loess Plateau

Contemporary forestry research prioritizes the advancement of high-quality forestry, especially in ecologically vulnerable areas. To this end, enhancing the ecological function and natural regeneration capacity of planted forest stands is crucial. This study investigated synergistic or trade-off relationships between stand regeneration capacity and the ecological functions (including water conservation, soil conservation, carbon sequestration, and understory plant diversity) of Robinia pseudoacacia L. (RP) plantations in the Caijiachuan watershed of the Loess Plateau using Root Mean Square Deviation. The results indicated that stand regeneration capacity exhibited synergistic, moderate trade-off, and high trade-off relationships with soil and water conservation, stand carbon sequestration, and understory plant diversity, respectively. Notably, stand regeneration capacity had a synergistic relationship with the overall forest ecological function (sum of the above functions), suggesting that the overall forest ecological function can be simultaneously improved by enhancing stand regeneration capacity. Redundancy analyses revealed that the regeneration capacity was primarily influenced by soil moisture content (SMC), stand density (SD), total transmitted light, herbaceous species richness, litter accumulation, and soil available phosphorus (AP). According to the stand optimization model, the highest regeneration capacity of RP was observed under the following conditions: 1742 trees·hm−2 for SD, 15.29 % for SMC (higher than the mean value of 33.53 % for the existing RP), 41.69 mg·kg−1 for AP (higher than the mean value of 15.84 %), and 1.84 for LAI (lower than the mean value of 20.0 %). Therefore, to achieve the simultaneous enhancement of the regeneration capacity and overall ecological function of RP stands, foresters should prioritize adjusting SD to an appropriate range through thinning or replanting. Additionally, regular pruning of specific branches of individual trees is essential to mitigate the adverse effects of high LAI on stand regeneration. Where feasible, soil moisture and nutrients can also be increased, but excessive levels of AP should be avoided.

Fuel Consumption Pattern for Disc Plough and Cultivator Tillage Implement

This study evaluated the effects of different (Disc plough and Cultivator) tillage implements on soil physical properties and operational cost under loam soil. Different (Disc plough and Cultivator) tillage implements were used in a field under separate plots. The fuel consumed by the tractor during the Disc plough and Cultivator tillage operations was measured by the field to determine the cost of both tillage operations. Results showed that the soil moisture content (MC) was 25.31%, while soil bulk density (BD) 1.3 under the plot (field) tilled with cultivator followed by disc plough compared to that tilled with cultivator only. The fuel consumed by the tractor during different tillage operations was 16.08 and 7.53 lit/ha for Disc plough and cultivator respectively. It is concluded that Cultivator can prepare better seedbed under loam soil as compared to Disc Plough only at almost same operational cost.

Monitoring soil moisture content in the root zone of winter wheat with multi-angle multispectral imagery

ABSTRACT Exploring the impact of different monitoring angles from unmanned aerial vehicle (UAV) on the monitoring accuracy of soil moisture content (SMC) is crucial for precision irrigation. To this end, experiment was conducted to monitor the SMC of winter wheat at different growth stages under different irrigation treatments in Yangling, Shaanxi, China. At a solar zenith angle of 45°, multispectral remote sensing data from a UAV were collected at thirteen different monitoring zenith angles. Simultaneously, the SMC in the wheat root zone was measured. From the UAV multispectral images, spectral reflectance was extracted for the construction of vegetation indices. Then the correlation between the vegetation indices and the measured SMC was analyzed. With the vegetation indices as input variables, SMC monitoring models were constructed using Extreme Learning Machine (ELM), Random Forest (RF), and Back Propagation Neural Network (BPNN). The study also examined the effect of specific angles (hotspot and dark spot angles) on the estimation accuracy of the SMC at the nadir angle. The results indicated that different monitoring angles significantly impact the SMC estimation accuracy. Band reflectance and vegetation indices exhibited significant peak values and angular effects at the monitoring zenith angle of 45°. The models achieved the optimal inversion accuracy at the hotspot angle (at a monitoring zenith angle of 45° in the solar principal plane), and the accuracy was ranked as follows: BPNN (R2 = 0.71; RMSE = 1.69) > ELM (R2 = 0.52; RMSE = 1.94) > RF (R2 = 0.48; RMSE = 2.10). By eliminating shadows at the nadir angle through the threshold of dark spot, inversion accuracy similar to the hotspot direction is achieved. This study provides a basis for appropriate selection of UAV flight angles for the monitoring of SMC in the root zone of winter wheat.

Effects of Stand Density on Tree Growth, Diversity of Understory Vegetation, and Soil Properties in a Pinus koraiensis Plantation

The regulation of stand density has been studied in specific aspects of plantations with different age categories. A clearer understanding is still required of the extent to which stand density impacts multiple plantation attributes such as tree growth, understory vegetation diversity, and soil properties in Korean pine (Pinus koraeinsis Sieb. et Zucc) plantations. This study utilized a 43-year-old middle-aged Korean pine plantation in Qingping Forest Farm in northeast China to answer the research question posed. Three stand density levels, low stand density (LSD, 716 trees/ha), medium stand density (MSD, 850 trees/ha), and high stand density (HSD, 916 trees/ha) were studied for their effects on plantation attributes enumerated above. The results revealed a significant (p &lt; 0.05) effect of stand density on mean stand volume (m3). Medium stand density had the highest mean stand volume of 26.16 (±0.27) m3 while the lowest stand volume was recorded for the low stand density at 14.90 (±1.72) m3. Also, significant differences in total nitrogen, total potassium, available nitrogen, available potassium, and percentage soil moisture content were observed among stand density levels. Additionally, stand density was found to have significant effects on species richness, Shannon–Wiener, and Simpson’s diversity indexes for the shrub and herb layers of the plantation. This study shows that a medium stand density is the most optimal for promoting tree growth and understory biodiversity, as well as enhancing the status of certain soil nutrients. Thus, medium density achieves a balance between growth, nutrient availability, and biodiversity in middle-aged Korean pine plantations after a short period of thinning. These findings provide valuable knowledge for forest management, emphasizing the significance of continuous, long-term, and site-specific research.

Integrating Machine Learning for Improved Prediction of Temperature and Moisture in Pavement Granular Layers

Abstract Pavement temperature and moisture content within the base and subgrade layers affect the load-bearing capacity of the pavement and dominate the pavement performance in cold regions. Accurately predicting pavement temperature and moisture content can improve pavement design and management. Conventional approaches, including numerical and statistical models, have been implemented to predict pavement temperature and soil moisture content. However, they have weaknesses, such as being only suitable for warm regions or only for predicting pavement temperature within the asphalt layer. Furthermore, none of them can simultaneously predict the pavement temperature and moisture content. To address this issue, data collected from an instrumented test road in Alberta, Canada, were used to train a model to predict the daily average pavement temperature and moisture content at various depths through three parameters, namely depth, day of the year, and air temperature. The MATLAB toolbox, Neural Net Fitting, was used, and the performance of three built-in algorithms, Levenberg–Marquardt, Bayesian regularization, and Scaled conjugate gradient backpropagation, was compared. The model with Bayesian regularization showed the highest accuracy, with an R2 value of 0.99 and a root mean square error (RMSE) of 1.49°C for pavement temperature prediction, and an R2 value of 0.95 and an RMSE of 0.025 m3/m3 for moisture content prediction. The model developed in this research is the first to simultaneously estimate pavement temperature and moisture content, so its performance was separately compared with two existing models in the literature. The artificial neural network (ANN) model shows higher accuracy than the two existing models, so it was found that the ANN could be a robust method for pavement temperature and moisture content prediction at various depths.

Vegetation and Soil Dynamics : Insights from Prosopis juliflora- Intruded Areas in Hastinapur Wildlife Sanctuary

Ecological study on plant diversity and soil characteristics of two contrasting sites (Prosopis juliflora-invaded and non-invaded) in Hastinapur Wildlife Sanctuary was undertaken to understand the structure of vegetation and soils and implication of exotic dominance in a dry tropical region of India. Seasonal floristic composition was recorded for one year through monthly visits. Phytosociological study of the two sites in each of three seasons was carried out by sampling a total of 120 quadrats (each 1mx1m, n= 20×3×2). Plant species density and abundance was estimated for both sites in each season. Seasonal surface soil (0–10 cm) samples were analyzed for soil pH, moisture content, organic C, and total N. Species occurrences and their relative abundance data were used to estimate alpha and beta diversity. A total of 76 plant species from 29 families were recorded (Malvaceae, Fabaceae and Asteraceae being top dominants). Maximum flora was recorded in rainy season at both sites, higher at non-invaded sites in all seasons. Beta diversity followed similar trend, higher in rainy season and at non-invaded than invaded sites, highest being 13.2 at non-invaded site in rainy season. Dominants changed with site and season. Vegetation patches were distinct in drier seasons compared to rainy months. Soil organic carbon, total nitrogen and C : N ratios were high at invaded sites compared to non-invaded sites except in summer season. While higher diversity and higher similarity amongst different sites in rainy season indicated a homogenization impact in Indian dry tropical regions, higher diversity at non-invaded site suggested implication of diversity-reducing impact of tree invader Prosopis juliflora.

Impact of three decades of warming, increased nutrient availability, and increased cloudiness on the fluxes of greenhouse gases and biogenic volatile organic compounds in a subarctic tundra heath.

Climate change is exposing subarctic ecosystems to higher temperatures, increased nutrient availability, and increasing cloud cover. In this study, we assessed how these factors affect the fluxes of greenhouse gases (GHGs) (i.e., methane (CH4), nitrous oxide (N2O), and carbon dioxide (CO2)), and biogenic volatile organic compounds (BVOCs) in a subarctic mesic heath subjected to 34 years of climate change related manipulations of temperature, nutrient availability, and light. GHGs were sampled from static chambers and gases analyzed with gas chromatograph. BVOCs were measured using the push-pull method and gases analyzed with chromatography-mass spectrometry. The soil temperature and moisture content in the warmed and shaded plots did not differ significantly from that in the controls during GHG and BVOC measurements. Also, the enclosure temperatures during BVOC measurements in the warmed and shaded plots did not differ significantly from temperatures in the controls. Hence, this allowed for assessment of long-term effects of the climate treatment manipulations without interference of temperature and moisture differences at the time of measurements. Warming enhanced CH4 uptake and the emissions of CO2, N2O, and isoprene. Increased nutrient availability increased the emissions of CO2 and N2O but caused no significant changes in the fluxes of CH4 and BVOCs. Shading (simulating increased cloudiness) enhanced CH4 uptake but caused no significant changes in the fluxes of other gases compared to the controls. The results show that climate warming and increased cloudiness will enhance CH4 sink strength of subarctic mesic heath ecosystems, providing negative climate feedback, while climate warming and enhanced nutrient availability will provide positive climate feedback through increased emissions of CO2 and N2O. Climate warming will also indirectly, through vegetation changes, increase the amount of carbon lost as isoprene from subarctic ecosystems.

River–aquifer interactions enhancing evapotranspiration in a semiarid riparian zone: A modelling study

AbstractThe hydrologic flows across the river–aquifer interface play an important role in groundwater dynamics and biogeochemical reactions within the subsurface; however, little is known about the effects of river–aquifer interactions on land surface processes. In this study, we developed a fully coupled three‐dimensional (3D) land surface and subsurface model at a high resolution (~1 km) that accounts for high‐frequency hydrologic exchange flow conditions to investigate how river–aquifer interactions modulate surface water budgets in the Upper Columbia‐Priest Rapids watershed, a typical semiarid watershed located in the northwestern United States where river stage fluctuates in response to reservoir releases changing. Our results show that the spatiotemporal dynamics of river–aquifer interactions are highly heterogeneous, driven mainly by river‐stage fluctuations. Adding 6.64 × 106 m3 year−1 of water over the watershed from the river to groundwater owing to the lateral flow, river–aquifer interactions led to an increase in soil evaporation and transpiration supplied by higher soil moisture content, particularly in deeper subsurface. In a hypothetic future scenarios where a 5‐m rise in river stage was assumed, the hydrologic flow exchange rates were intensified, resulting in higher surface water over the entire watershed. Overall, lateral flow induced by river–aquifer exchanges leads to an increase in evapotranspiration of ~75% in the historical period and of ~83% in the hypothetical future scenario. Our study demonstrates the potential of coupled model as an effective tool for understanding river–aquifer–land surface interactions, and indicates that river–aquifer interactions fundamentally alter the water balance of the riparian zone for the semiarid watershed and will likely become more frequent and intense in the future under the effects of climate change.

The pivotal role of water potential in phenology and seed germination of Abies spectabilis in the western Himalayan treeline region

Abies spectabilis (East Himalayan Fir), a dominant timber-producing species in the Himalayas, plays a dynamic role in ecological balance and sustains various habitats across temperate to subalpine altitudes. Himalayan montane forests express signs of changes in the growth, regeneration, and population density of forest tree species due to ongoing climate change, including its upper distribution limit. The research was conducted at 30°11´02˝N and 79°39′36˝E, ranging from 3,100 to 3,500 m asl elevation in the treeline ecotone of western Himalaya. The study presents a comprehensive perspective on how water availability and its intricate interactions with climatic and ecological variables shape the dynamics of treeline ecosystems. The study’s phytosociological analysis of treeline sites revealed the complex interplay between species composition, adaptability, and regeneration potential. The eco-physiological aspects of water balance were thoroughly explored, underscoring how plants employ various strategies to cope with changing water availability. The soil moisture content ranged from 32.17 to 73.50%. The dynamic nature of water potential (pre-dawn (ΨPD) and mid-day (ΨMD)) across seasons and years reflects and varies between −0.13 and − 1.25 MPa, the species’ ability to adjust and manage water balance according to environmental shifts. Osmotic potential at full turgor varied from −0.72 to −1.77 MPa, these adjustments are crucial for key life cycle events of vegetative and reproductive phases of species. The strong correlation of water potential (Ψ) and phenophases emphasizes the importance of water status in regulating these vital processes. Furthermore, the study delved into the maturation and germination processes, highlighting the significance of Ψ and moisture content in seed development and germination success. The maximum germination of 46.33% was observed when the seed moisture content was 30.90 ± 3.11%. The observed correlations between cone characteristics and seed parameters indicate the existence of trade-offs that impact seed size, weight, and germination capacity, contributing to the overall fitness of the species.

Effects of Seasonal Freezing and Thawing on Soil Moisture and Salinity in the Farmland Shelterbelt System in the Hetao Irrigation District

Water resources are scarce, and secondary soil salinization is severe in the Hetao Irrigation District. Farmland shelterbelt systems (FSS) play a critical role in regulating soil water and salt dynamics within the irrigation district. However, the understanding of soil water and salt migration within FSS during the freeze–thaw period remains unclear due to the complex and multifaceted interactions between water and salt. This study focused on a typical FSS and conducted comprehensive monitoring of soil moisture, salinity, temperature, and meteorological parameters during the freeze–thaw period. The results revealed consistent trends in air temperature and soil temperature overall. Soil freezing durations exceeded thawing durations, and both decreased with an increasing soil depth. At the three critical freeze–thaw nodes, the soil moisture content at a 0–20 cm depth was significantly lower than at a 40–100 cm depth (p &lt; 0.05). The soil water content increased with time and depth at varying distances from the shelterbelt, with an average increase of 7.63% after freezing and thawing. The surface water content at the forest edge (0.3H, 4H) was lower than inside the farmland (1H, 2H, 3H). Soil salt accumulation occurred during both freezing stable periods and melting–thawing periods in the 0–100 cm soil layer near the forest edge (0.3H, 4H), with the highest soil salinity reaching 0.62 g·kg−1. After the freeze–thaw period, the soil salt content in each layer increased by 11.41–47.26% compared to before the freeze–thaw period. Salt accumulation in farmland soil near the shelterbelt was stronger than in the far shelterbelt. The multivariate statistical model demonstrated goodness of fit for soil water and salt as 0.94 and 0.72, respectively, while the BP neural network model showed goodness of fit for soil water and salt as 0.82 and 0.85, respectively. Our results provide an efficient theoretical basis for FSS construction and agricultural water management practices.