Humid Subtropical Regions Research Articles

Soil test correlation of Olsen‐P for corn and soybean in a subtropical humid region

AbstractAccurate phosphorus (P) fertilizer recommendations for soybean [Glycine max (L.) Merr.] and corn (Zea mays L.) are crucial for maximizing productivity and economic return while minimizing the environmental impact of fertilizer use. Currently, there are no calibrations for diagnosing P deficiencies in croplands of Bolivia. This study aimed to define and compare the P critical soil test value (CSTV) for corn and soybean using the Olsen method. Twenty fertilization field trials were conducted for corn and 75 for soybean in the Santa Cruz de la Sierra region, including treatments with and without P fertilization. Soil pre‐planting (0–20 cm) organic matter, Olsen P, pH, as well as yield were determined. Relative yield (RY) was estimated as the ratio of grain yield between the control and P‐fertilized treatments. The CSTV was calculated using the arcsine‐logarithm method, with data resampling through bootstrapping. The average yield response to added P was 259 kg ha−1 (+11.0%) for soybean and 545 kg ha−1 (+13.7%) for corn. For soybean, CSTVs were determined as 6.1 and 11.0 mg kg−1 (r = 0.34, p = 0.002) for 90% and 95% of RY, respectively. For corn, the CSTVs were 8.1 and 13.9 mg kg−1 (r = 0.34, p = 0.14) for 90% and 95% of RY, respectively. The confidence intervals suggest no differences between crops. The Olsen‐P is a promising tool for soil fertility recommendations in Bolivia. Yet, the modest goodness of fit obtained suggests the need for further research refining the performance of soil test P diagnosis in the region.

Which Machine Learning Algorithm Is Best Suited for Estimating Reference Evapotranspiration in Humid Subtropical Climate?

ABSTRACTTimely and reliable estimates of reference evapotranspiration (ET0) are imperative for robust water resources planning and management. Applying machine learning (ML) algorithms for estimating ET0 has been evolving, and their applicability in different sectors is still a compelling field of research. In this study, four Gaussian process regression (GPR) algorithms—polynomial kernel (PK), polynomial universal function kernel (PUK), normalized poly kernel (NPK), and radial basis function (RBF)—were compared against widely used random forest (RF) and a simpler locally weighted linear regression (LWLR) algorithm at a humid subtropical region in India. The sensitivity analysis of the input variables was followed by application of the best combination of variables in algorithm testing and training for generating ET0. The results were then compared against the Penman–Monteith method at both daily and monthly time steps. The results indicated that ET0 is least sensitive to wind speed at 2 m height. Additionally, at a daily time step, RF, followed by PUK, generated the best results during both training and testing phases. In contrast, at a monthly time step, using multiple model evaluation matrices, PUK followed by RF performed best. These results demonstrate the application of the ML algorithms is subjected to user‐required time steps. Although this study focused on Northwest India, the findings are relevant to all humid subtropical regions across the world.

Preliminary Evaluation of a Numerical System of Prediction for Surface Solar Irradiance and Cloudiness in a Site with a Subtropical Humid Climate

This study explores a prediction system for global horizontal irradiance and cloudiness in a humid subtropical terrestrial region. This system consists of regional simulations performed with the Weather Research and Forecasting model using the initial and boundary conditions from the Global Forecast System. The predictions show significant biases for the variable of interest, with notable variations within the daily and annual cycles. This study also finds significant biases in cloud incidence and clarity index predictions, with relevant diurnal and seasonal variations. During austral summer, multiplying the relative humidity of initial and boundary conditions by a fixed factor improves the forecasts of global horizontal irradiance and cloud incidence for the central hours of the day and the afternoon. During austral winter, an empirical correction of the clarity index obtained from the simulation’s outputs also shows the potential to improve the forecasts’ biases. This work proposes a hypothesis about the causes of the forecast biases.

Impacts of tropical cyclones on extreme precipitation and flooding in a humid subtropical inland basin of China

Impacts of tropical cyclones on extreme precipitation and flooding in a humid subtropical inland basin of China

Estimation of Cation Exchange Capacity for Low-Activity Clay Soil Fractions Using Experimental Data from South China

The cation exchange capacity (CEC) of the clay fraction (<2 μm), denoted as CECclay, serves as a crucial indicator for identifying low-activity clay (LAC) soils and is an essential criterion in soil classification. Traditional methods of estimating CECclay, such as dividing the whole-soil CEC (CECsoil) by the clay content, can be problematic due to biases introduced by soil organic matter and different types of clay minerals. To address this issue, we introduced a soil pedotransfer functions (PTFs) approach to predict CECclay from CECsoil using experimental soil data. We conducted a study on 122 pedons in South China, focusing on highly weathered and strongly leached soils. Samples from the B horizon were used, and eight models and PTFs (four machine learning methods, multiple linear regression (MLR) and three PTFs from publication) were evaluated for their predictive performance. Four covariate datasets were combined based on available soil data and environmental variables and various parameters for machine learning techniques including an artificial neural network, a deep belief network, support vector regression and random forest were optimized. The results, based on 10-fold cross-validation, showed that the simple division of CECsoil by clay content led to significant overestimation of CECclay, with a mean error of 14.42 cmol(+) kg−1. MLR produced the most accurate predictions, with an R2 of 0.63–0.71 and root mean squared errors (RMSE) of 3.21–3.64 cmol(+) kg−1. The incorporation of environmental variables improved the accuracy by 2–10%. A linear model was fitted to enhance the current calculation method, resulting in the equation: CECclay = 15.31 + 15.90 × (CECsoil/Clay), with an R2 of 0.41 and RMSE of 4.48 cmol(+) kg−1. Therefore, given limited soil data, the MLR PTFs with explicit equations were recommended for predicting the CECclay of B horizons in humid subtropical regions.

Resilience and Resistance of Vegetation in Response to Droughts in a Subtropical Humid Region Dominated by Karst

The resilience and resistance of vegetation are important indicators of the vegetation’s response to droughts. Owing to the uniqueness of the environment in humid karst areas, results from studies on other climatic zones may not necessarily present the status of vegetation resilience and resistance in humid karst areas. Herein, We calculated vegetation resilience and resistance by autoregressive modeling using Enhanced Vegetation Index (EVI), Total Water Storage Anomaly (TWSA), temperature (TA), precipitation (PRE) data, An analysis of variance (ANOVA) was then conducted to compare the differences in resilience and resistance of different vegetation types in the study area, as well as the differences in resilience and resistance of vegetation in different sub-geomorphic zones. Finally, natural factors affecting vegetation resilience and resistance were quantified using partial least squares structural equation modeling (PLS-SEM). The results demonstrate the following points. First, vegetation resilience, total-water-storage anomaly resistance, and vegetation resistance against precipitation anomalies were lower in karst areas of the study area than in non-karst areas of the study area (except for vegetation resistance against temperature anomalies). Second, vegetation resilience was the lowest in some sub-geomorphic zones within karst areas, and it was still comparable to that in semiarid areas. Third, precipitation and temperature were important factors that affected the resilience and resistance of vegetation in karst areas, and the geochemical indicators (CaO, MgO, and SiO2) of soil parent material were major factors that affected the resistance and resilience of vegetation in non-karst areas. In summary, this study was undertaken to reveal the natural characteristics of vegetation resilience and resistance in humid karst regions. Our findings complement and expand the existing body of knowledge on vegetation resilience and resistance in other ecologically fragile zones limited by moisture.

Unirrigated extensive green roofs in humid subtropics – Plant selection and substrate design for low maintenance and climate resilience

Unirrigated extensive green roofs in humid subtropics – Plant selection and substrate design for low maintenance and climate resilience

Quantifying human thermal adaptation for indoor environments through field surveys and climate chamber experiments

ABSTRACT Thermal comfort boundaries established through climate chamber experiments are often found to significantly vary in real-world conditions based on the potential for thermal adaptation. In this context, this research aims to quantify the extent of thermal adaptation using a personalized ventilation system. We hypothesize that a personalized ventilation system can enhance thermal adaptation compared to real-world settings with limited opportunity for thermal adaptation. The study is based on thermal comfort surveys in mixed-mode open-plan office spaces of a humid subtropical region (Cwa), and a controlled climate chamber with a provision for personalized ventilation. We obtained 5629 subjective thermal responses through longitudinal field surveys accompanied by environmental measurements. In a climate chamber, 16 acclimatized volunteers were subjected to 140 different set-points with air temperature (Ta), relative humidity (RH), and air velocity (Va) variations yielding 19,200 subjective responses. A thermo-neutral temperature (Tn) of 26.5°C with an acceptability band of ±5.9°C was obtained through the field surveys. The Tn obtained from climate chamber surveys varied from 28.0°C to 29.3°C with an acceptability band of ±3.6°C depending on the ventilation rate. An empirical relationship between thermal sensation vote (TSV) and multiple environmental variables (Calidity) suggests 2°C higher Tn for Caliditychamber, Thermal adaptation correction factor of 2.1°C for warm-dry indoor environment and 1°C for warm-humid indoor environment were deduced through comparative analysis.

Rootstock selection for ‘Swatow’ Mandarin trees grown at different locations throughout the Brazilian subtropics

Evaluating citrus rootstocks is of paramount importance in determining their suitability for a certain region and promoting resilience in orchards by increasing the genetic pool, thereby potentially contributing to a more strategic establishment of new plantings. This long-term field study (2000-2013) aimed to evaluate different rootstocks for 'Swatow' mandarin grown at two locations (Paranavaí and Londrina) in the Brazilian subtropics. Nine rootstocks were evaluated, including 'Rangpur' lime, 'Swingle' citrumelo, 'Volkamer' lemon, 'Caipira DAC' sweet orange, 'Cleopatra' and 'Sunki' mandarins, 'Trifoliate' orange, 'Carrizo', and 'Fepagro C-13' citranges. Trees were assessed for vegetative growth, yield, fruit quality, density, and yield estimates. The experimental design was a randomized block arranged in a 9×2 setting (rootstock×location) with 6 replicates and 4 trees per plot. 'Swatow' trees grew more vigorously in Londrina than Paranavaí, particularly for 'Cleopatra' and 'Sunki' pairings. Tree vigor was reduced with 'Trifoliate', resulting in higher tree density estimates and yield efficiency. This rootstock, along with 'Rangpur', 'Swingle', and 'Carrizo' provided superior yield to the scion. All tested rootstocks conferred good fruit quality. Fruits were larger and heavier in 'Sunki' pairings, showing higher soluble solids (SS) content, along with 'Caipira DAC', 'Trifoliate', 'Swingle', and 'Carrizo' at both locations. Our findings confirm the suitability of 'Trifoliate' orange, 'Carrizo' citrange, or 'Caipira DAC' orange rootstocks as promising candidates for 'Swatow' mandarin cultivation in humid subtropical and analogous regions. Further investigations are invoked to improve the horticultural performance of 'Swatow' mandarin trees grafted onto these rootstocks.

Nutritive value and condensed tannins of tree legumes in silvopasture systems

Introducing legumes into C4-dominated tropical pastures, may enhance their sustainability but has some pasture management constraints. One potential alternative is using arboreal legumes, but several of these species have relatively high condensed tannin (CT) concentrations, which negatively impact forage quality. There is limited knowledge, however, on how arboreal legume leaf CT content varies over the year and how this might impact forage quality. The objective of this 2 year study was to assess the seasonal variation of CT and nutritive value for ruminants of the tropical tree legumes gliricidia [Gliricidia sepium (Jacq.) Kunth ex. Walp.] and mimosa (Mimosa caesalpiniifolia Benth). The research was carried out in the sub-humid tropical region of Brazil on well-established pastures in which either legume was present with signalgrass (Urochloa decumbens Stapf.). We determined CT and nitrogen concentrations, in vitro digestible organic matter (IVDOM), and leaf δ13C and δ15N from January to October of 2017 and 2018. All parameters were affected (P < 0.05) by the interaction between legume species and sampling time, with generally higher leaf CT content for mimosa than gliricidia, and both were reduced at the start of the dry season, although much more drastically for mimosa. The IVDOM was strongly affected by CT content and increased at the start of the dry season, coincidentally when C4 grass forage quality typically decreased. There is a marked species effect, with CT from gliricidia impacting IVDOM more than the same CT content from mimosa. While N concentration from mimosa also increased at the start of the dry season, that for gliricidia did not vary over the year. We conclude that although these arboreal legumes have relatively high CT contents, these reduce during the dry season when CT concentrations coinciding with a reduced forage quality as the protein content for C4 grasses is usually inadequate in this season.

Effects of Design Factors and Multi-Stage Environmental Factors on Hydrological Performance of Subtropical Green Roofs

Environmental and design factors determine the stormwater management capacity of green roofs; however, the design and environmental factors that impact their hydrological performance in subtropical humid regions are poorly understood. In particular, meteorological factors have received little attention. Meteorological factors vary greatly at different stages of a rainfall event (e.g., during the rainfall and outflow). Therefore, the impact of meteorological factors at different stages on hydrological performance should be considered separately to obtain a more accurate picture of their effects on hydrological performance. In this study, experimental green roofs were established based on four substrate types and two depths. For the first time, this study systematically explored the effects of design factors for the substrate (type and depth) and multi-stage environmental factors on the hydrological performance of green roofs. Environmental factors, including meteorological factors, from three critical stages (before and during a rainfall event and during the outflow), and rainfall characteristics (e.g., rainfall depth and rainfall duration) were incorporated to determine the variation in hydrological performance. The effects of multi-stage environmental factors on retention and peak reduction were analyzed, with a ranking of each factor’s relative importance. Environmental factors played a leading role in determining hydrological performance. However, the impact of multi-stage environmental factors was not as important as that of rainfall depth and antecedent volumetric water content. Differences in hydrological performance were compared across combinations of design factors. No significant differences were observed across substrate types and depths. However, potential interactive effects might exist, though these were not significant compared to environmental factors (e.g., rainfall depth and rainfall duration). These results confirmed that the meteorological factors in the different event-related stages significantly impacted the hydrological performance. Quantifying the effects of design and environmental factors is critical for hydrological performance evaluation. The results provided a broader perspective on understanding influence mechanisms of hydrological performance and highlighted the impact of microclimates on hydrological performance.

No‐till impacts on soil organic carbon and soil quality in the Lower Mississippi River basin: Implications for sustainable management

AbstractNo‐till (NT) alleviates adverse effects of agricultural production on environmental quality, improves soil health, and reduces greenhouse gas emissions, yet this has not been demonstrated in humid subtropical Mississippi. Research objectives were to evaluate nutrient and C dynamics and soil quality via Soil Management Assessment Framework (SMAF) following 15 years of continuous management under corn (Zea mays L.) (2008–2018) and soybean [Glycine max (L.) Merr.] (2019–2022) on a Dundee silt loam soil. After 15 years, soil organic carbon (SOC) stocks (0‐ to 30‐cm depth) under NT were 25% higher than conventional tillage (CT). Between 2020 and 2022, SOC stocks increased 3 Mg ha−1 under NT and decreased 2 Mg ha−1 under CT. Increased SOC retention under NT could represent an opportunity for increasing the systems’ profitability as C markets expand. Greater SOC and aggregation scores improved SMAF soil quality index (SQI) under NT (71%), compared to CT (66%), underscoring the critical role of organic matter in soil functioning in managed agrosystems. Soybean yields were not linked to SMAF SQI (p &gt; 0.05), suggesting that crop yields are mostly affected by non‐edaphic factors (e.g., climate extremes). SMAF illustrated positive impacts of NT on SOC sequestration and soil health, which may foster its adoption as a conservation practice in the Lower Mississippi River basin. As such, NT stands as a climate‐smart management practice that allows for sustainable intensification in humid subtropical regions.

Exploring Microbial Influence on Flavor Development during Coffee Processing in Humid Subtropical Climate through Metagenetic-Metabolomics Analysis.

Research into microbial interactions during coffee processing is essential for developing new methods that adapt to climate change and improve flavor, thus enhancing the resilience and quality of global coffee production. This study aimed to investigate how microbial communities interact and contribute to flavor development in coffee processing within humid subtropical climates. Employing Illumina sequencing for microbial dynamics analysis, and high-performance liquid chromatography (HPLC) integrated with gas chromatography-mass spectrometry (GC-MS) for metabolite assessment, the study revealed intricate microbial diversity and associated metabolic activities. Throughout the fermentation process, dominant microbial species included Enterobacter, Erwinia, Kluyvera, and Pantoea from the prokaryotic group, and Fusarium, Cladosporium, Kurtzmaniella, Leptosphaerulina, Neonectria, and Penicillium from the eukaryotic group. The key metabolites identified were ethanol, and lactic, acetic, and citric acids. Notably, the bacterial community plays a crucial role in flavor development by utilizing metabolic versatility to produce esters and alcohols, while plant-derived metabolites such as caffeine and linalool remain stable throughout the fermentation process. The undirected network analysis revealed 321 interactions among microbial species and key substances during the fermentation process, with Enterobacter, Kluyvera, and Serratia showing strong connections with sugar and various volatile compounds, such as hexanal, benzaldehyde, 3-methylbenzaldehyde, 2-butenal, and 4-heptenal. These interactions, including inhibitory effects by Fusarium and Cladosporium, suggest microbial adaptability to subtropical conditions, potentially influencing fermentation and coffee quality. The sensory analysis showed that the final beverage obtained a score of 80.83 ± 0.39, being classified as a specialty coffee by the Specialty Coffee Association (SCA) metrics. Nonetheless, further enhancements in acidity, body, and aftertaste could lead to a more balanced flavor profile. The findings of this research hold substantial implications for the coffee industry in humid subtropical regions, offering potential strategies to enhance flavor quality and consistency through controlled fermentation practices. Furthermore, this study contributes to the broader understanding of how microbial ecology interplays with environmental factors to influence food and beverage fermentation, a topic of growing interest in the context of climate change and sustainable agriculture.

Comparative analysis of HEC-HMS and SWAT hydrological models for simulating the streamflow in sub-humid tropical region in India.

Assessment of water availability in sub-humid regions is important due to distinct climatic and environmental conditions. In this study, Soil and Water Assessment Tool (SWAT) and Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) models have been assessed in simulating streamflows in the sub-humid tropical Kabini basin in Kerala, India, spanning 1260 km2. Calibration and validation utilized daily weather data from 1997 to 2015 from the Muthankera gauging station. The study investigated the impact of routing methods on runoff simulation in the ArcSWAT, exploring Muskingum and Variable Storage methods. Evaluation metrics encompassed Nash-Sutcliffe Efïciency (NSE), Coefficient of Determination (R2), Percent bias (PBIAS), RMSE-observations standard deviation ratio (RSR), and Peak Percent Threshold Statistics (PPTS) approach for high-flow values. The result indicates that HEC-HMS outperforms SWAT concerning R2 and NSE values during daily calibration and validation. Monthly simulations showed HEC-HMS closely aligning with SWAT (Variable storage), outperforming SWAT (Muskingum). The PPTS approach proved effective in simulating high-flow values. Both models exhibited proficiency in streamflow analysis within the study area, promising predictive potential for future hydrological studies in sub-humid regions.

Intrinsic microbial temperature sensitivity and soil organic carbon decomposition in response to climate change.

Soil microbes are essential for regulating carbon stocks under climate change. However, the uncertainty surrounding how microbial temperature responses control carbon losses under warming conditions highlights a significant gap in our climate change models. To address this issue, we conducted a fine-scale analysis of soil organic carbon composition under different temperature gradients and characterized the corresponding microbial growth and physiology across various paddy soils spanning 4000 km in China. Our results showed that warming altered the composition of organic matter, resulting in a reduction in carbohydrates of approximately 0.026% to 0.030% from humid subtropical regions to humid continental regions. These changes were attributed to a decrease in the proportion of cold-preferring bacteria, leading to significant soil carbon losses. Our findings suggest that intrinsic microbial temperature sensitivity plays a crucial role in determining the rate of soil organic carbon decomposition, providing insights into the temperature limitations faced by microbial activities and their impact on soil carbon-climate feedback.

Maize/soybean intercropping increases nutrient uptake, crop yield and modifies soil physio-chemical characteristics and enzymatic activities in the subtropical humid region based in Southwest China

Intercropping, a widely adopted agricultural practice worldwide, aims to increase crop yield, enhance plant nutrient uptake, and optimize the utilization of natural resources, contributing to sustainable farming practices on a global scale. However, the underlying changes in soil physio-chemical characteristics and enzymatic activities, which contribute to crop yield and nutrient uptake in the intercropping systems are largely unknown. Consequently, a two-year (2021–2022) field experiment was conducted on the maize/soybean intercropping practices with/without nitrogen (N) fertilization (i.e., N0; 0 N kg ha−1 and N1; 225 N kg ha−1 for maize and 100 N kg ha−1 for soybean ) to know whether such cropping system can improve the nutrients uptake and crop yields, soil physio-chemical characteristics, and soil enzymes, which ultimately results in enhanced crop yield. The results revealed that maize intercropping treatments (i.e., N0MI and N1MI) had higher crop yield, biomass dry matter, and 1000-grain weight of maize than mono-cropping treatments (i.e., N0MM, and N1MM). Nonetheless, these parameters were optimized in N1MI treatments in both years. For instance, N1MI produced the maximum grain yield (10,105 and 11,705 kg ha−1), biomass dry matter (13,893 and 14,093 kg ha−1), and 1000-grain weight (420 and 449 g) of maize in the year 2021 and 2022, respectively. Conversely, soybean intercropping treatments (i.e., N0SI and N1SI) reduced such yield parameters for soybean. Also, the land equivalent ratio (LER) and land equivalent ratio for N fertilization (LERN) values were always greater than 1, showing the intercropping system’s benefits in terms of yield and improved resource usage. Moreover, maize intercropping treatments (i.e., N0MI and N1MI) and soybean intercropping treatments (i.e., N0SI and N1SI) significantly (p < 0.05) enhanced the nutrient uptake (i.e., N, P, K, Ca, Fe, and Zn) of maize and soybean, however, these nutrients uptakes were more prominent in N1MI and N1SI treatments of maize and soybean, respectively in both years (2021 and 2022) compared with their mono-cropping treatments. Similarly, maize-soybean intercropping treatments (i.e., N0MSI and N1MSI) significantly (p < 0.05) improved the soil-based N, P, K, NH4, NO3, and soil organic matter, but, reduced the soil pH. Such maize-soybean intercropping treatments also improved the soil enzymatic activities such as protease (PT), sucrose (SC), acid phosphatase (AP), urease (UE), and catalase (CT) activities. This indicates that maize-soybean intercropping could potentially contribute to higher and better crop yield, enhanced plant nutrient uptake, improved soil nutrient pool, physio-chemical characteristics, and related soil enzymatic activities. Thus, preferring intercropping to mono-cropping could be a preferable choice for ecologically viable agricultural development.

Kudzu invasion and its influential factors in the southeastern United States

Kudzu invasion and its influential factors in the southeastern United States

Experimental Study on the Effect of Wetting-Drying Cycles on Crack Development and Radon Retardation of the Covering Soil in Uranium Mill Tailing Impoundments.

The majority of uranium mill tailing impoundments in the southern part of China are located in humid subtropical regions where persistent rainfall and rapid evaporation of water after rain often occur. Under the prolonged influence of alternating wet and dry conditions, the covering soil layer of uranium mill tailing impoundments develops cracks, leading to the issue of degradation or even failure of the radon retardation effect. A beach surface of uranium mill tailing impoundments in the southern part of China is selected as the research object. Through use of a self-made simulation test device, a degradation experiment of uranium mill tailing covering soil models under wetting-drying cycles was conducted indoors. The experimental results indicate that with a constant amplitude of wetting-drying cycles, microcracks characterized by a narrow width and high abundance were mainly generated in the early-to-mid-stage of wetting-drying cycles. The main cracks, characterized by their wide width and less abundance, were mainly formed in the mid-to-late stage of wetting-drying cycles. After seven wetting-drying cycles, the total length of cracks showed a "stair-step" increase and the surface crack ratio exhibited a trend of moving from rapid growth to stable growth and then to a slight decline. The cumulative damage degree showed a rapid increase to stable growth with an increase in the number of wetting-drying cycles. Grey relational analysis revealed that, compared to other surface crack indicators, radon exhalation rate was the most closely correlated with the surface crack ratio. With a constant amplitude of wetting-drying cycles, the radon exhalation rate underwent four stages as the number of wetting-drying cycles increased: stage I witnessed a rapid increase, stage II witnessed a rapid decrease, stage III witnessed a gradual increase, and stage IV witnessed a stable or even slight decrease. With a constant number of wetting-drying cycles, the radon exhalation rate correspondingly increased with the amplitude of wetting-drying cycles, particularly noticeable when the alternation amplitude was 30 ± 20%. From the early mid-stage to the late stage of wetting-drying cycles, the curves of the radon exhalation rate, surface crack ratio, and cumulative damage degree tended to be consistent, showing a gradual increase. The research provided in this study offers valuable insights into radon control measures and environmental assessments on the beach surface of uranium mill tailing impoundments.

Monitoring spatio-temporal variations of terrestrial water storage changes and their potential influencing factors in a humid subtropical climate region of Southeast China

Monitoring spatio-temporal variations of terrestrial water storage changes and their potential influencing factors in a humid subtropical climate region of Southeast China

Improving soil water storage with no‐till cover cropping in the Mississippi River Alluvial Basin

AbstractExcessive tillage reduces soil water storage and increases surface runoff. Cover crops can modify the effect of tillage on soil water dynamics, but limited information is available for the Mississippi River Alluvial Basin. This study was conducted to determine whether soil–water dynamics could be manipulated through conservation production systems affecting surface residue management. Effects of tillage (conventional tillage [CT] vs. no‐tillage [NT]) and cover cropping (no cover crop and Austrian pea [Pisum sativum L.] cover crop [CC]) on soil water balance during the CC season in sorghum (Sorghum bicolor L.) and cotton (Gossypium hirsutum L.) crops were modeled using the root zone water quality model for a site near Stoneville, MS, on “Commerce” silty‐loam soil. Capacitance sensors measured soil volumetric water content to 120 cm during CC growth in 2019 and 2020. Field calibration of sensors reduced root mean square error from 0.05 to 0.03 m3 m−3. Pooled across years, NT increased volumetric water content in the 0–40 and 40–120 soil layers by 8.5% and 6.8%, respectively, compared to CT. Regardless of the CC treatment and cropping system, NT reduced surface runoff by 24.5% over its conventional counterpart, while soil water storage increased from 2.35 to 5.23 cm within the 1.2‐m profile, resulting in a 17% increase in consumptive use of water (evapotranspiration). CC treatments did not impact soil water storage and consumptive water use. The results demonstrate that NT systems can affect water dynamics by increasing infiltration and soil water storage in the humid subtropical region of the United States.