Moisture Patterns Research Articles

Bridging spatio-temporal discontinuities in global soil moisture mapping by coupling physics in deep learning

The launch of Soil Moisture Active Passive (SMAP) satellite in 2015 has resulted in significant achievements in global soil moisture mapping. Nonetheless, spatiotemporal discontinuities in the soil moisture products have arisen due to the limitations of its orbit scanning gap and retrieval algorithms. To address these issues, this paper presents a physics-constrained gap-filling method, PhyFill for short. The PhyFill method employs a partial convolutional neural network technique to explore spatial domain features of the original SMAP soil moisture data. Then, it incorporates variations in soil moisture induced by precipitation events and dry-down events as penalty terms in the loss function, thereby accounting for monotonicity and boundary constraints in the physical processes governing the dynamic fluctuations of soil moisture. The PhyFill model was applied to SMAP soil moisture data, resulting in continuous spatially daily soil moisture data on a global scale. Three validation strategies are employed: visual inspection through global pattern, simulated missing-region validation, and soil moisture validation with in situ measurements. The results indicated that the reconstructed soil moisture achieved a higher spatial coverage with satisfactory spatial continuity with neighbouring pixels. The simulated validation of the missing regions revealed that the averaged unbiased root mean square difference (ubRMSD) and correlation coefficient (R) were 0.01 m3/m3 and 0.99, respectively versus the gap filled SMAP product. The core validation sites demonstrated that the reconstructed soil moisture data has a consistent ubRMSD compared with the original SMAP soil moisture data (0.04 m3/m3vs. 0.04 m3/m3). The PhyFill method can generate globally continuous, high accurate soil moisture estimates, providing remarkable support for advanced hydrological applications, e.g., global soil moisture dry-down events and patterns.

Effects of vegetation types on soil wetting pattern and preferential flow in arid mountainous areas of northwest China

Understanding the mechanisms governing the infiltration of precipitation into soil is crucial in eco-hydrological processes. However, the effect of vegetation types on the wetting front depth and velocity is poorly understood. Here, we analyzed 1234 infiltration events based on a large-scale long-term in-situ soil moisture monitoring network in arid mountainous area of northwest China. Our results show that the proportion of preferential flow was the largest in shrub (52.38 %), followed by alpine meadow (36.55 %), grassland (11.51 %), and barren (0.70 %). The wetting front velocity was consistent with the order of the proportion of preferential flow, with values of 11.42, 4.96, 2.32, and 1.16 cm/h, respectively. The mean velocity of preferential flow events was 2.05 times (0.06–71 times) higher in the shallow soil layer and 3.86 times (0.3–68 times) higher in the deep soil layer compared to matrix flow events. The wetting front depth was shallowest in alpine meadow (14.31 cm), followed by barren (15.70 cm), grassland (18.95 cm), and shrub (39.81 cm). Moreover, the wetting front depth and velocity reach their peak values in summer, primarily influenced by precipitation. Random Forests analysis results demonstrate that preferential flow is the primary factors influencing the profile wetting front depth, with control factors varying across different soil depths, soil water characteristic curve in shallow soil layers, and vegetation in deep soil layers, respectively. Meanwhile, soil organic carbon emerged as the most important factor impacting wetting front velocity. These findings contribute to a deeper understanding of infiltration processes in arid mountainous areas and offer a theoretical foundation for refining and enhancing mountain hydrological models.

Reinterpreting ENSO's Role in Modulating Impactful Precipitation Events in California

AbstractWater years (WY) 2017 and 2023 were anomalously wet for California, each alleviating multiyear drought. In both cases, this was unexpected given La Niña conditions, with most seasonal forecasts favoring drier‐than‐normal winters. We analyze over seven decades of precipitation and snow records along with mid‐tropospheric circulation to identify recurring weather patterns driving California precipitation and Sierra Nevada snowpack. Tropical forcing by ENSO causes subtle but important differences in these wet weather patterns, which largely drives the canonical seasonal ENSO‐precipitation relationship. However, the seasonal frequency of these weather patterns is not strongly modulated by ENSO and remains a primary source of uncertainty for seasonal forecasting. Seasonal frequency of ENSO‐independent weather patterns was a major cause of anomalous precipitation in WY2017, record‐setting snow in WY2023, and differences in precipitation outcome during recent El Niño winters 1983, 1998, and 2016. Improved understanding of recurrent atmospheric weather patterns could help to improve seasonal precipitation forecasts.

Impact of Meteorological Factors on the Wire Icing Thickness and Growth Rate in Mountain Areas under Dry and Wet Growth Patterns

Wire icing events pose a significant threat to the southern power grid’s transmission lines in China. Fifteen such events were identified from 2018 to 2020 on the Guilin-Haiyang Mountain transmission line. Hourly measurements of ice thickness and concurrent meteorological data were analyzed using the Makkonen model’s freezing rate formula to categorize the events into distinct growth patterns: dry and wet. The relationship between wire icing and meteorological factors across different micro-topography (windward slope, leeward slope, and pass) was further explored. Several key conclusions can be drawn. First, the altitude is positively correlated to the icing thickness, but relatively independent of the icing rate; however, such independence between the icing rate and altitude cannot be interpreted by the negative correlation of altitude with temperature and the positive relationship between wind speed and liquid water content. Second, a pronounced connection of the icing rate with meteorological factors is not shown until the wet and dry patterns are separated. Notably, the correlations differ between these two patterns, with icing rate being negatively correlated with temperature for the wet growth process, but positively correlated with wind speed and liquid water content for the dry growth process. Third, both wet and dry growth processes exist across the icing events. A shift from wet to dry growth was evident with increasing altitude. At the mountain’s base, wet growth predominates, with the icing rate determined by the temperature close to the freezing point, whereas the higher temperature and lower liquid water flux account for the shorter wire icing duration, lower icing rate, and thus the thinner icing thickness at the leeward slope compared to the windward slope at a similar altitude. This study sheds light on the variations in icing rates under different micro-topographies and the underlying physical mechanisms governing icing growth patterns and provides a much-needed understanding of these distinct growth processes on the development of a more sophisticated predictive model for conductor icing.

Responses of Soil Moisture to Gully Land Consolidation in Asian Areas with Monsoon Climate

Groundwater resources are essential for sustaining ecosystems and human activities, especially under the pressures of climate change. This study employed Electrical Resistivity Tomography (ERT) to assess the impact of Gully Land Consolidation (GLC) engineering on the groundwater hydrological field of small watersheds in the China Loess Plateau (CLP). Results revealed ample subsurface water storage in backfilled areas, primarily migrating along the original river path owing to topographical limitations. Although the distribution patterns of soil moisture in each backfilling block varied slightly, the boundaries of soil moisture content and variation mainly appeared at depths of 8 m and 20 m underground. Significant moisture variation occurred across the 0–20 m underground layers, suggesting the 8–20 m layer could function as a groundwater collection zone in the study area. Human activities could disturb groundwater, altering migration pathways from the original river path. An optimized “Drainage–Conveyance–Barrier” system is proposed to enhance GLC sustainability, involving upstream groundwater level control, midstream soil moisture management, and downstream hydrological connectivity improvement. These findings carry substantial implications for guiding the planning and execution of GLC engineering initiatives. The novelty of this study lies in its application of ERT to provide a detailed spatial and temporal understanding of soil moisture dynamics in the GLC areas. Future research should focus on factors such as soil types and topographical changes for a comprehensive assessment of GLC’s impact on small watershed groundwater hydrology.

Moisture patterns and fluxes in evolving tafoni developed in arkosic sandstone in temperate climate

AbstractCavernous weathering forms have long been studied and discussed as enigmas in geomorphology. Recently, their evolution has been shown to be controlled by moisture patterns, which are still poorly understood. For the first time, capillary water and vapor fluxes were characterized in detail at tafone in a temperate climate of central Europe using a wide range of methods adapted from soil hydrology. Time domain reflectometry showed that moisture flows from the rock interior to the evaporation front in the shallow subsurface of both — the backwalls and the outer surface. When overland flow occurs on the outer surfaces (after heavy rains), 10 mm/day can infiltrate and flow toward the backwalls. The main sources of water for tafone are the influx of water from the rock interior and the infiltration of overland flow after heavy rains, while condensation of air humidity is a minor source. Influx from the rock interior is coupled to the evaporation rate, which varies between 100 and 300 kg/m2/year in summer and less than 15 kg/m2/year in winter. More water evaporates from the backwall of the tafone than from the outer surface, and more salt is deposited in the backwalls, resulting in predominant salt weathering in the backwalls. The tafoni studied thus evolve, and the cavities deepen. Tafoni in arid and semi‐arid environments generally show a much higher contrast between evaporation rates from backwalls and outer surfaces than tafoni and honeycombs in temperate and coastal environments. Tafoni in temperate settings are therefore more susceptible to degradation when evaporation decreases or inflow to the tafone increases. This study also shows that microtensiometers can be used to determine moisture content with high spatial resolution, while time domain reflectometry allows accurate characterization of moisture patterns with depth.

Effects of landscape position on perennial biomass and food crop performance in buffer areas

AbstractDue to the environmental consequences of annual‐dominated cropping systems, there is an increasing need to identify agronomic strategies that incorporate perennial crops. One strategy for increasing perennial cover is through the targeted use of annually harvested perennial food and bioproduct crops in buffer strips, which has the potential to create new revenue streams for farmers and substantially mitigate agricultural nutrient pollution from conventional cropping systems. As buffers are typically installed on marginal land, it is critical to understand how landscape position influences the success of perennial crops. The objectives of this study were to determine the relatively early influence of landscape position on the productivity of a variety of perennial crops and their subsequent soil nutrients and soil water storing capabilities. In this experiment, nine perennial (alfalfa, alsike clover, indiangrass, switchgrass, big bluestem, prairie cordgrass, intermediate wheatgrass, high‐diversity polyculture, low‐diversity polyculture) and two annual (corn, soybean) crops were planted across two landscape positions (hillslope and deposition). Plant biomass, plant tissue nitrogen, soil moisture, and soil NO3‐N and NH4‐N were measured and compared at two different locations in Minnesota. Overall, the polyculture mixes, and to some extent intermediate wheatgrass, performed the best with respect to biomass production while also providing ecosystem services across most soil by landscape position combinations tested in this study. However, there were some important findings specific to each soil and landscape position combination, mainly oriented toward biomass production. We also observed temporal patterns in soil moisture and depth‐related patterns in soil N reductions. This study presents an opportunity to optimize the use of perennial crops on marginal agricultural lands for improved environmental and economic benefit.

Correction: Using machine learning to enhance agricultural productivity in Turkey: insights on the importance of soil moisture, temperature and precipitation patterns

Correction: Using machine learning to enhance agricultural productivity in Turkey: insights on the importance of soil moisture, temperature and precipitation patterns

Quantifying soil moisture and evapotranspiration heterogeneity within a solar farm: Implications for stormwater management

As solar energy becomes a cheap source of renewable energy, the number of major utility-scale ground solar panel installations, often called ‘solar farms,’ are growing. With these solar farms often covering hundreds of acres, there is potential for impacts on natural hydrologic processes, including runoff generation and erosion. There is still limited research in this area, and best management practices to address these impacts are variable and not well understood. To fill this gap, we conducted a field investigation of soil moisture patterns, solar radiation, and vegetation at two solar farms in central Pennsylvania, USA that are representative of the complex terrain in the region (e.g., high or variable slopes). Both solar farms also included engineered infiltration basins or trenches that were investigated. Analysis of soil moisture patterns reveals redistribution of water relative to panels, with dripline soil moisture 19 % higher than the reference, and underpanel moisture 25 % lower than the reference, on average at both solar farms over a year. There are also the greatest periods of saturation and runoff generation at the panel driplines. However, an open interspace between panel rows and existing infiltration basins and trenches are playing a critical role in managing runoff. Micrometeorological monitoring indicates reduced evapotranspiration (ET) under panels, with potential underpanel ET 37–67 % lower in summer, and minimal difference in winter. However, a survey of vegetation revealed almost complete ground coverage under panels, which is critical for supporting infiltration and reducing erosion. As solar farms expand to meet important renewable energy goals, it is essential that care be taken to design the landscape to minimize runoff generation and erosion. This work demonstrates that healthy vegetation and well-draining soils can help manage runoff on solar farms; where necessary on more challenging landscapes, engineered stormwater controls can manage any unmitigated runoff.

On the Variability in the Temporal Stability Pattern of Soil Moisture Under Mediterranean Conditions

In recent decades, there has been increasing interest in studying the variability in soil water properties and, specifically, the spatiotemporal variability in the soil water content. This is motivated by the notable theoretical and applied research interests in soil moisture dynamics and their implications for many natural processes. This study aimed to study whether there are variations in the spatial pattern of the temporal stability of soil moisture over time and to analyze the possible influences of certain hydroclimatic (soil water content, precipitation, and evapotranspiration) and soil factors (texture, bulk density, and organic matter content) on these variations. This study was conducted within the Soil Moisture Measurement Stations Network of the University of Salamanca (REMEDHUS, Spain) under Mediterranean conditions, with daily surface moisture data (0–5 cm depth) obtained from 20 stations for the 2006-2023 period. The results showed differences between the average pattern obtained with the 18-year data series and that obtained with the data series for each year. In more than half of the years studied, the representative station differed from that derived from the average pattern. The mean annual precipitation and summer precipitation characteristics seem to be the main factors influencing the variability in the spatial pattern of the temporal stability of soil moisture.

Precision Turfgrass Irrigation: Capturing Spatial Soil Moisture Patterns with ECa and Drone Data

Precision Turfgrass Irrigation: Capturing Spatial Soil Moisture Patterns with ECa and Drone Data

Observations of enhanced rainfall variability in Kenya, East Africa

Understanding local patterns of rainfall variability is of great concern in East Africa, where agricultural productivity is dominantly rainfall dependent. However, East African rainfall climatology is influenced by numerous drivers operating at multiple scales, and local patterns of variability are not adequately understood. Here, we show evidence of substantial variability of local rainfall patterns between 1981 and 2021 at the national and county level in Kenya, East Africa. Results show anomalous patterns of both wetting and drying in both the long and short rainy seasons, with evidence of increased frequency of extreme wet and dry events through time. Observations also indicate that seasonal and intraseasonal variability increased significantly after 2013, coincident with diminished coherence between ENSO (El Nino Southern Oscillation) and rainfall. Increasing frequency and magnitude of rainfall variability suggests increasing need for local-level climate change adaptation strategies.

Empirical models for calculating soil wetting patterns under surface drip irrigation systems: A comprehensive analysis

AbstractAccurate estimation of the surface wetted radius (R) and vertical wetted depth (Z) of wetting patterns in drip irrigation systems is crucial for ensuring that the designs of such systems are effective. This study compared 14 empirical models for estimating drip irrigation wetting patterns by assessing their accuracy using published measurement data and HYDRUS‐2D/3D simulations. The technique for order of preference by similarity to the ideal solution (TOPSIS) was employed to comprehensively rank the models. The results indicate that the empirical model proposed by Fan et al. (2023) (FY) exhibited the highest accuracy when the estimations of R and measured and simulated values were compared, with mean absolute error (MAE), root mean square error (RMSE), Nash–Sutcliffe modelling efficiency (NSE), and percent bias (PB) values of 2.2 cm, 3.4 cm, 0.79, and −7.1% and 5.2 cm, 7.0 cm, 0.50, and −14.1%, respectively. The empirical model proposed by Amin and Ekhmaj (2006) (AE) demonstrated the highest accuracy when the estimations of Z were compared with measured and simulated values, with MAE, RMSE, NSE and PB values of 1.7 cm, 2.0 cm, 0.95 and 4.15% and 4.4 cm, 5.9 cm, 0.82 and 4.7%, respectively. The comprehensive rankings of available models in the present study indicate that the FY model is the most universally applicable, followed by the Li et al. (2022) (LY) model, with comprehensive indices of 0.960 and 0.936, respectively. This research can aid in the selection of universally applicable, reliable and straightforward empirical models for estimating wetting patterns in drip irrigation systems.

Combined effects of rainfall‐runoff events and antecedent soil moisture on runoff generation processes in an upland forested headwater area

AbstractIn this study, we investigate the combined effect of different rainfall‐runoff event types and antecedent soil moisture (ASM) on runoff processes in the headwater elementary discharge area of a small forested upland catchment. The study focuses on (i) the relationship between soil moisture thresholds and runoff generation; (ii) the combined effect of ASM and tree vicinity and (iii) the relationship between different rainfall‐runoff event types and different types of runoff (baseflow and stormflow). The results suggest that ASM has a strong impact on local runoff generation processes. Soil water content (35%–36%) threshold exceedance was related to stormflow runoff generation caused by the activation of quick preferential flow paths in the soil during storm events, especially in the upper and the deepest soil layers. At the same time, unexpected non‐linear increases in baseflow runoff ratios were documented during dry, precipitation‐free, periods and when the 31%–34% soil moisture threshold was exceeded, presumably due to the hydrological connection of farther slope areas during these conditions. Multiple stormflow periods, which exhibited the lowest runoff coefficient, were the most significant events in terms of water retention and soil water recharge due to increased vertical hydrological connectivity enabling more rapid transport to deeper soil layers. However, this rainfall type occurred least often over the study period. The important role of forest stands (individual trees) in creating spatial patterns of soil moisture and preferential infiltration paths to deeper soil layers was also confirmed. These results contribute towards a better conceptualisation of hydrological behaviour in elementary headwater discharge areas and highlight the potential dangers associated with expected increases in extreme weather events.

Assessing a semi-empirical model performance to predict the wetting patterns in subsurface drip irrigation

ContextBecause of the complexity of soil water distribution, accurate prediction of wetting pattern is not easily accessible and this has led to a inefficiency in some proposed models in the literature. These models do not consider the hydraulic characteristics of the irrigation system and are developed solely on the basis of the water volume or infiltration rate, soil hydrodynamic properties, and other conditions of the percolation environment. ObjectiveDue to the importance of the estimation of wetting front beneath Subsurface Drip Irrigation (SDI) laterals, a semi-empirical model using easily accessible data of the SDI system is proposed to predict the wetting patterns in both distribution and redistribution phases. The aforementioned model has been developed based on a novel approach that couples the governing equations of the lateral hydraulics with empirical equations derived by dimensional analysis. MethodsTo develop the model and evaluate its performance, three 16-mm drip line pipes with 0.2, 0.4, and 0.5 m emitter spacing, and 2–5 l/h discharge were placed at 0.20 m depth in a soil box filled with clay loam soil. Water was applied for 3 hours at 50, 100, and 150 kPa operating pressures, and the wetting patterns’ geometries were measured in each lateral after 1, 2, 3, and 24 h. The performance of the model was then assessed and compared with that of three other models. Results and conclusionThe result demonstrated that the proposed model provides the most accurate estimations of the wetting depths and widths. RMSE and MAE statistical indexes of the wetting depth were 0.001–0.002 m and 0.004–0.009 m, respectively, whereas those associated with the wetting width were 0.001–0.003 m and 0.005–0.016 m, respectively. These values resulted in the lowest error when compared with the corresponding obtained from other well-known models. Consequently, the model allows acceptable predictions of the wetting patterns using accessible hydraulic parameters of the SDI system. SignificanceUniquely, the results of the lateral hydraulic analysis were applied to determine the wetting front dimensions in this study. Also, the results demonstrated that the model was successful in wetting pattern prediction beneath the lateral as a line source. While other models usually are used to estimate the wetting front around a point source.

Effect of Nostoc commune cover on shallow soil moisture, runoff and erosion in the subtropics

Nostoc commune (Nostoc commune Vaucher ex Born & Flahault) is widely distributed in grasslands within the subtropical region. Because of its morphological changes are more sensitive to moisture, it may affect the soil’s response to infiltration-runoff processes, thus significantly influencing soil moisture dynamics, runoff, and soil loss. However, the exact effects of this phenomenon are not yet fully understood. This study established a one-year monitoring experiment of soil moisture, runoff and soil erosion in the karst area of Southwest China from September 2021 to November 2022. Using bare soil (CK) as the control, two treatments of Nostoc commune cover at 100 % coverage (C1) and 50 % coverage (C2) were set up in 3 repetitions to investigate the shallow soil’s response to Nostoc commune cover and rainfall and to quantify the effects of land cover and rainfall type on runoff and soil loss. The results showed that Nostoc commune cover significantly increased the shallow-soil water content, and the effect of increasing soil water content was more significant with increasing coverage. The cumulative soil water increment (CSWI) varied greatly under different types of rainfall due to the high water-absorbing capacity of Nostoc commune. The CSWI showed C1 < C2 < CK under light rain and moderate rain events, while the CSWI showed C1 > C2 > CK under heavy rain and rainstorm events. The temporal pattern of soil moisture changed greatly under different cover treatments and rainfall events. In particular, the response time under different rainfall types varied from 10 min to 250 min. The runoff depth and soil loss in CK were 1.19–2.15 times and 1.92–14.43 times that of C1 and C2, respectively. This indicates that Nostoc commune cover has a significant effect on controlling runoff and soil erosion. In addition, the sensitivity of runoff and soil loss to the maximum 10-min rainfall intensity was higher than that of the maximum 30-min rainfall intensity, which was attributed to the rapid swelling of Nostoc commune in the hydration process, which greatly reduced runoff and soil erosion. This study can contribute to further understanding the hydrological process and soil erosion characteristics under different surface covers in humid karst areas.

Moisture and Temperature Profiles of Heartwood Pinus pinaster Ait. Wood Specimens during Microwave Drying

Microwave (MW) drying of wood has gained popularity in the field of wood modification. The rise in temperature during MW drying leads to increased steam pressure, enhancing wood permeability but potentially decreasing mechanical properties. Understanding temperature and moisture behaviors during MW drying is crucial for its industrial application in wood drying. Therefore, this study aimed to characterize the temperature and moisture behaviors during MW drying of small Portuguese maritime pine (Pinus pinaster Aiton.) wood samples to support a wider use of this technology. The effects on water uptake and the compressive strength parallel to the grain were also investigated. The results indicated three distinct phases in the MW drying rates, with an average of 0.085% of water removed per second. Moreover, the temperature underwent three distinct stages: an initial rapid increase, a period of constant temperature, and a slight decrease until drying was complete. At the beginning of MW drying, the temperatures were below 100 °C, with average temperatures ranging from 126 to 145 °C. Specimens with lower initial moisture content had higher temperatures, and a positive correlation was found between initial moisture content and drying time. In contrast, negative correlations were found between the initial moisture content and average temperature, as well as average temperature and MW drying time. Additionally, the operating condition parameters used in MW drying of pine samples enhanced water impregnability by 65%, generating a slight reduction of 11% in compressive strength. It was also noticed that the initial moisture content did not impact MW-dried samples’ water uptake or compressive strength. Finally, although small clear wood samples of maritime pine were utilized, the temperature and moisture patterns observed closely matched real-scale specimens. Thus, the findings corroborate a wide utilization of MW technology for wood drying, mainly demonstrating positive possibilities for structural-sized wood specimens.

Suppressing the invasive common milkweed (Asclepias syriaca L.) saves soil moisture reserves

Common milkweed (Asclepias syriaca L.) is a widespread invasive alien forb in dry sandy habitats of Central Europe. It adversely affects native plant and animal communities, but its ecosystem-level effects, particularly on hydrology, are little known. Since milkweed has an extensive, deep root system and large, broad leaves, we assumed a negative effect on the soil moisture content of the hosting ecosystem. Following the before-after control-impact protocol, we first compared the soil moisture content of the top 120 cm of the soil under seven milkweed stands to that of non-invaded reference sites. We then treated half of the stands by mechanically removing all aboveground milkweed biomass and repeated the comparative soil moisture measurements. We found that milkweed stands had significantly drier soils than reference grasslands during the growing season, but the soil under milkweed stands recharged to the level of the references in autumn and winter. However, the amount of moisture needed for this recharge was lost from deeper percolation to groundwater. Milkweed treatment prevented the depletion of moisture during the growing season, saving 21.6 l m−2 of water on average. Treatment did not affect non-milkweed plant biomass, thus, moisture patterns could fully be attributed to the milkweed stands. Our results reinforce the importance of milkweed suppression in invaded grasslands, as, besides enabling the recovery of the native grassland ecosystem, it promotes groundwater recharge, which is particularly important in the dry regions of Central Europe, currently facing severe aridification due to climate change and unfavourable land use trends.

Subsurface flow model for estimating 2D wetting pattern in drip irrigation

AbstractNumerical model using 2D Richard’s equation in cylindrical polar coordinate system was developed to assess the soil wetting patterns in a drip irrigation system. A fully implicit finite‐difference scheme was used to solve equations with suitable initial and boundary conditions. The developed model was validated with an experimental result available in the literature, which shows a high level of concordance with low values of RMSE and R2 greater than 0.93 for all discharge rates. Furthermore, the versatility and applicability of the model were demonstrated for complex subsurface conditions considering homogeneous and heterogeneous soil profiles. Water ponding on the surface was observed in clay loam soil, contrasting with deep percolation in sandy loam soil. This underscores the significance of adjusting both discharge rate and irrigation frequency in accordance with prevailing soil conditions.

Responses of soil moisture at different topographic positions to rainfall events along a steep subtropical forested hillslope

AbstractUnderstanding the dynamic response of soil moisture to rainfall is crucial for describing hydrological processes at the hillslope scale. However, because of sparse monitoring coupled with the complexity of water movement and steep topography, the findings of rainfall‐related soil moisture dynamics have not always been consistent, indicating a need for systematic investigations of soil moisture dynamics and infiltration patterns following rainfall inputs at multiple topographic positions along a hillslope. This study aimed to examine the nature of these responses by characterizing and quantifying the response amplitude, rate and time for 37 large rainfall events at 25 combinations of topographic positions and soil depths along a steep forested hillslope. Our results showed that soil moisture responses under different rainfall patterns could be attributed to one or the other rainfall characteristics, such as rainfall intensity and amount. However, soil moisture dynamics at different hillslope positions after rainfall varied widely due to the controls of soil properties, topography, and non‐equilibrium flow. Preferential flow was more evident under dry initial soil conditions than under wet initial soil conditions. Findings of this study reveal that the dynamic response patterns of soil moisture to rainfall do not always follow topographic controls, which can improve our understanding of water cycling related to the infiltration process at the hillslope scale, and support water resources management in subtropical mountain ecosystems.