Antecedent Soil Moisture Research Articles

Quantification of Soil Water Dynamics Response to Rainfall in Forested Hillslope Based on Soil Water Potential Measurement

Soil hydrological response is crucial for controlling water flow and biogeochemical processes on hillslopes. Understanding soil water dynamics in response to rainfall is essential for accurate hydrological modeling but remains challenging in humid mountainous regions characterized by high antecedent moisture and substantial heterogeneity. We sought to elucidate soil water response patterns to rainfall by estimating lag time, wetting front velocity, rainfall threshold, and preferential flow (PF) frequency in 166 rainfall events across 36 sites on two hillslopes within the Hailuogou catchment, located on the eastern Qinghai–Tibet Plateau. Results indicated that over 90% of the events triggered rapid soil water potential (SWP) responses to depths of 100 cm, with faster responses observed at steeper upslope positions with thinner O horizons. Even light rainfall (2–3 mm) was sufficient to trigger SWP responses. PF was prevalent across the hillslopes, with higher occurrence frequencies at upslope and downslope positions due to steep terrain and consistently moist conditions, respectively. Using the Multivariate Adaptive Regression Splines (MARS) model, we found that site factors (e.g., soil properties and topography) had a greater influence on SWP responses than rainfall characteristics or antecedent soil wetness conditions. These findings highlighted the value of SWP in capturing soil water dynamics and enhancing the understanding and modeling of complex hillslope hydrological processes.

Nonstationarity assessment in extreme temperatures and its association with antecedent soil moisture levels across diverse climate zones in Pakistan

Nonstationarity assessment in extreme temperatures and its association with antecedent soil moisture levels across diverse climate zones in Pakistan

Enhancing rainwater harvesting efficiency in karst terrains: The role of road intercepted soil-epikarst lateral flow.

In karst landscapes, where sustainable water management is increasingly challenged by drought-induced water scarcity, the adoption of road-based rainwater harvesting (RBWH) systems has emerged as a promising solution for improving water accessibility. Despite the growing implementation of such systems, the effectiveness of many RBWH projects in karst terrains remains suboptimal due to an inadequate understanding of runoff generation mechanisms associated with hilly road networks. This study focuses on quantifying the contributions of intercepted surface runoff (SR) and soil-epikarst lateral flow (SEF) from a newly exposed road-cut slope in a dolomite hillslope, with data collected across 156 rainfall events from May 2019 to May 2022. Our findings revealed that SEF, with an annual average volume of 2.065×106L for the experimental karst catchment (with a projected area of 7850m2), was the main contributor to road-cut slope flow (RCF), significantly surpassing SR, which accounted for an annual average of 0.283×10⁶ L. The annual runoff coefficients for SR, SEF, and RCF were quantified at 2.2%, 16.0%, and 18.2%, respectively. Both rainfall depth and antecedent soil moisture content were identified as pivotal factors influencing SEF, indicative of a saturation-excess runoff mechanism within the context of the karstic road-cut slope. Notably, the contribution of SEF to the overall runoff was approximately twice that of SR from both the upslope and road surface combined. These findings highlight the importance of incorporating the rainstorm runoff potential of road-cut slopes into the design and optimization of RBWH systems within dolomitic karst terrains. To improve water collection efficiency for various purposes in such initiatives, it is essential to consider the hydrological characteristics of the upslope terrain and the geometric properties of the soil-epikarst interface in the planning process.

Steady infiltration rate: Relation to antecedent soil moisture, soil permeability, and measurement method and period

ABSTRACT Soil steady water infiltration rate (SIR) is a key variable in hydrological modeling, but its relationship to antecedent soil moisture is not yet well understood. We tested the hypothesis that the SIR decreases with the increase in antecedent moisture, and that this relationship depends on permeability to water on the soil surface, the measurement method, and the measurement period. We conducted an experiment in an Argissolo Vermelho-Amarelo Distrófico abrúptico (Psammentic Paleudult – Soil Taxonomy), measuring infiltration in up to 14 antecedent moisture conditions under two soil structural conditions (no-till and no-till with subsoiling), with two measurement methods (double ring and Cornell infiltrometers), and for up to 48 h, with ten replications. In addition, vertical effective hydraulic conductivity of the saturated profile (Kef) was determined with Darcy’s equation for N layers. Crop succession used in the area was black oats and ryegrass in the winter and soybean in the summer. The SIR decreased to as little as 7.7 % of its original value with the increase in antecedent moisture; it was ~200 % greater in the treatment with subsoiling compared to no-till alone, and ~80 % greater when measured with the Cornell infiltrometer than with the double ring infiltrometer. Nevertheless, the effects of the method and the soil structural condition declined with the increase in antecedent moisture, confirming our hypothesis. In soil initially nearly saturated (degree of saturation ~90 %), the SIR drew near Kef (12.7 mm h -1 ) under the two soil structural conditions, especially when measured with the double ring infiltrometer. In contrast, increasing the time for measuring infiltration (>2 h) did not generate a new lower SIR level. The SIR decreases with the increase in antecedent soil moisture, and this relationship depends on the permeability to water of the surface layers and the measurement method. The SIR determined with infiltrometers better corresponds to vertical infiltration the nearer the soil is to saturation before beginning measurement.

Drivers of Widespread Floods in Indian River Basins

Abstract Widespread floods affecting multiple subbasins in a river basin have implications for infrastructure, agriculture, environment, and groundwater recharge. However, the crucial linkage between widespread floods and their drivers remains unexplored for Indian subcontinental river basins. Here, we examine the occurrence and drivers of widespread flooding in seven Indian subcontinental river basins during the observed climate (1959–2020). The peninsular river basins have a high probability of widespread flooding, compared to the transboundary basins of the Ganga and Brahmaputra. Favorable antecedent baseflow and soil moisture conditions, uniform precipitation distribution, and precipitation seasonality determine the probability of widespread floods in Indian river basins. The widespread floods are associated with large atmospheric circulations that cause precipitation in a large part of a river basin. Our findings highlight the prominent drivers and mechanisms of widespread floods with implications for flood mitigation in India.

Spatiotemporal desynchronization in the propagation from meteorological to soil moisture drought in the Loess Plateau, China

Spatiotemporal desynchronization in the propagation from meteorological to soil moisture drought in the Loess Plateau, China

Effect of Soil Moisture on Future Heatwaves Over Eastern China: Convection‐Permitting Regional Climate Simulations

AbstractSoil moisture deficiencies exacerbate heatwaves through soil moisture‐temperature feedback, an effect that is expected to intensify with climate change, resulting in critical impacts on society and ecosystems. This study aims to investigate the evolving soil moisture‐heatwave relationship over eastern China in the future, using a convection‐permitting (CP, ∼4 km) regional climate model (RCM). The CP‐RCM model simulates historical (1998–2007) and future (2070–2099) climates over eastern China, with three pseudo‐global warming (PGW) experiments conducted under the RCP2.6, RCP4.5, and RCP8.5 scenarios. Results indicate a substantial increase in heatwave frequency (HWF) and magnitude (HWM) over eastern China, particularly under the RCP8.5 scenario. The largest HWF (up to 23 days) is expected in South China (SC), and the largest HWM (up to 3.25°C) is expected in Loess Plateau (LP) and North China Plain (NCP), indicating a pronounced future risk of heatwave in the region. Antecedent soil moisture exhibits a negative correlation with heatwave indices (HWM and HWF) in most areas of eastern China, suggesting its role in mitigating heatwaves. Quantile regression analysis shows that antecedent soil moisture exerts a stronger effect on the upper quantile of the HWF/HWM than on the lower quantile. With global warming, the amplifying effect due to soil moisture deficiency on future heatwaves is expected to expand spatially and become more pronounced. Increased soil moisture control on heatwaves can be attributed to reduced energy limitation and intensified water limitation. A comprehensive investigation across five sub‐regions reveals the role of various soil moisture regimes in modulating heatwaves over eastern China.

Analysis of short- and long-term controls on the variability of event-based runoff coefficient

Analysis of short- and long-term controls on the variability of event-based runoff coefficient

The Role of Antecedent Winter Soil Moisture Carryover on Spring Runoff Predictability in Snow-Influenced Western U.S. Catchments

Abstract Spring runoff is critical to agricultural, industrial, and municipal water supply as well as environmental uses in the western United States. Although spring runoff in this region has long been predicted based on late winter and early spring montane snow water storage, the role of soil moisture carryover from the previous winter is less understood and utilized in forecasts. We quantify the relationship between antecedent winter soil moisture and spring runoff for 85 unmanaged catchments in the western United States. Using a regression-based approach, we estimate the proportional reduction in error in seasonal runoff forecasts associated with soil moisture. We classify the catchments into two regimes: interior (cold and relatively dry) and maritime (warmer and wetter), based on seasonal variations in soil moisture. Soil moisture generally is relatively unchanged through the winter period in interior catchments, whereas it increases (mostly gradually, but occasionally rapidly) in maritime catchments. We find that winter temperature dominates soil moisture variability in both types of catchments. We find two patterns in the predictability of spring runoff. First, including antecedent winter soil moisture as a predictor enhances forecast accuracy and variance explanation in spring runoff for both interior and maritime catchments, particularly and with greater significance in interior catchments. Second, spring runoff prediction skill from antecedent winter soil moisture increases with elevation. Overall, we find strong evidence that the use of antecedent soil moisture can improve spring runoff forecast skill for catchments in the western United States. Significance Statement Spring runoff forecasts are crucial for water supply in the western United States, but typically exclude information about soil moisture despite its key role in the water balance. Our study explores how and why incorporating information about winter’s soil moisture levels affects spring runoff forecasts across 85 catchments in the western United States. We find that doing so can produce modest improvements in the prediction skill of spring runoff for both interior and maritime catchments but is particularly noticeable in interior catchments and at higher elevations where temperatures are lower. Overall, our research strongly supports the idea that using information about soil moisture from the previous winter can improve accuracy in spring runoff forecasts for the western United States.

Land and Atmospheric Drivers of the 2023 Flood in India

AbstractFloods in India are recurring natural disasters resulting from extreme precipitation during the summer monsoon season (June–September). The recent flood in North India in July 2023 caused substantial damage to lives, agriculture, and infrastructure. However, what led to the 2023 North India flood and the role of atmospheric and land drivers still need to be examined. Using in situ observations, satellite data, and ERA5 reanalysis combined with hydrological and hydrodynamical modeling, we examine the role of land and atmospheric drivers in flood occurrence and its impacts. Extreme precipitation in a large region during 7–10 July 2023 created favorable conditions for the flood in the hilly terrains and plains of north India. More than 300 mm of precipitation fell in just 4 days, which was eight times higher than the long‐term average (2001–2022). Anomalously high moisture transport over northern India was recorded on 7 July 2023, making atmospheric conditions favorable for intense landfall. Increased column water vapor and specific humidity at different pressure levels confirmed the continuous moisture presence before the extreme rainfall that caused floods in northern India from 7 to 12 July 2023. Atmospheric and land (high antecedent soil moisture) conditions contributed to a more than 200% rise in streamflow at several gauge stations. Satellite‐based flood extent shows a considerable flood inundation that caused damage in the Sutlej and Yamuna River basins. Our findings highlight the crucial role of the favorable land and atmospheric conditions that caused floods and flash floods in north India in July 2023.

Characterizing rapid infiltration processes on complex hillslopes: Insights from soil moisture response to rainfall events

Characterizing rapid infiltration processes on complex hillslopes: Insights from soil moisture response to rainfall events

A simple analytical method to estimate runoff generation and accumulation

A simple analytical method to estimate runoff generation and accumulation

RegionGrow3D: A Deterministic Analysis for Characterizing Discrete Three‐Dimensional Landslide Source Areas on a Regional Scale

AbstractRegional‐scale characterization of shallow landslide hazards is important for reducing their destructive impact on society. These hazards are commonly characterized by (a) their location and likelihood using susceptibility maps, (b) landslide size and frequency using geomorphic scaling laws, and (c) the magnitude of disturbance required to cause landslides using initiation thresholds. Typically, this is accomplished through the use of inventories documenting the locations and triggering conditions of previous landslides. In the absence of comprehensive landslide inventories, physics‐based slope stability models can be used to estimate landslide initiation potential and provide plausible distributions of landslide characteristics for a range of environmental and forcing conditions. However, these models are sometimes limited in their ability to capture key mechanisms tied to discrete three‐dimensional (3D) landslide mechanics while possessing the computational efficiency required for broad‐scale application. In this study, the RegionGrow3D (RG3D) model is developed to broadly simulate the area, volume, and location of landslides on a regional scale (≥1,000 km2) using 3D, limit‐equilibrium (LE)‐based slope stability modeling. Furthermore, RG3D is incorporated into a susceptibility framework that quantifies landsliding uncertainty using a distribution of soil shear strengths and their associated probabilities, back‐calculated from inventoried landslides using 3D LE‐based landslide forensics. This framework is used to evaluate the influence of uncertainty tied to shear strength, rainfall scenarios, and antecedent soil moisture on potential landsliding and rainfall thresholds over a large region of the Oregon Coast Range, USA.

Testing the hydrological performance of live pole drains (LPD) for mitigation of slope instability

Testing the hydrological performance of live pole drains (LPD) for mitigation of slope instability

Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors

Ensemble Predictions of Rainfall-Induced Landslide Risk under Climate Change in China Integrating Antecedent Soil-Wetness Factors

The nonlinear rainfall–quick flow relationships in a humid mountainous area: Roles of soil thickness and forest type

The nonlinear rainfall–quick flow relationships in a humid mountainous area: Roles of soil thickness and forest type

Empirical and physical modelling of soil erosion in agricultural hillslopes

Abstract Soil erosion is a complex and highly heterogeneous process with a wide range of environmental and economic impacts. Its estimation is particularly challenging and modelling is typically used for erosion estimation over large areas. The aim of this study was to compare the two leading empirical and physical erosion estimation models, i.e. the Revised Universal Soil Loss Equation (RUSLE) and the Water Erosion Prediction Project (WEPP). The models were calibrated and validated using data collected from field experiments conducted in agricultural lands of Mexico. The simulated rainfall experiments involved measuring erosion from field plots subjected to four tillage systems (No crop, Conventional tillage, Conventional tillage + residues, and Handspike) under two antecedent soil moisture conditions (dry and wet). Different calibration approaches based on the factors K and C for RUSLE, and interrill erodibility and hydraulic conductivity in WEPP were tested. The best-performing methods in RUSLE involved measuring the K factor and adopting the recommended C factor by the National Forestry Commission of Mexico. In WEPP, the best results were obtained when interrill erodibility was estimated from experimental measurements. Overall, RUSLE outperformed WEPP in most of the treatments except for CT under WAMC.

Bimodal hydrographs in a semi-humid forested watershed: characteristics and occurrence conditions

Abstract. Bimodal runoff behavior, characterized by two distinct peaks in flow response, often leads to significant stormflow and associated flooding. Understanding and characterizing this phenomenon is crucial for effective flood forecasting. However, this runoff behavior has been understudied and poorly understood in semi-humid regions. In this study, we investigated the response characteristics and occurrence conditions of a bimodal hydrograph based on the hydrometric and isotope data spanning 10 years in a semi-humid forested watershed in north China. The main findings include that (1) the onset of the bimodal hydrograph exhibits a threshold behavior, with delayed streamflow peaks occurring when the sum of event rainfall (P) and antecedent soil moisture index (ASI) prior to the rainfall exceeds 200 mm; (2) isotopic hydrograph separation reveals that the delayed stormflow process is primarily driven by pre-event water, with increasing contributions of pre-event water during catchment wetting up; and (3) the dynamic variation in groundwater level precedes that of streamflow, establishing a hysteretic relationship wherein the groundwater level peaks before streamflow during delayed stormflow. These findings, supported by on-site observations, emphasize the dominance of shallow groundwater flow in the generation of delayed stormflow.

Implementation of a slope stability method in the CRITERIA-1D agro-hydrological modeling scheme

AbstractThis paper presents the implementation of a slope stability method for rainfall-induced shallow landslides in CRITERIA-1D, which is an agro-hydrological model based on Richards’ equation for transient infiltration and redistribution processes. CRITERIA-1D can simulate the presence and development of roots and canopies over space and time, the regulation of transpiration activity based on real meteorological data, and the evaporation reduction caused by canopies. The slope can be considered composed of a multi-layered soil, leading to the possibility of simulating the bedrock and of setting an initial water table level. CRITERIA-1D can consider different soil horizons characterized by different hydraulic conductivities and soil water retention curves, thus allowing the simulation of capillarity barriers. The validation of the proposed physically based slope stability model was conducted through the simulation of the collected water content and water potential data of an experimental slope. The monitored slope is located close to Montuè, in the north-eastern sector of Oltrepò Pavese (northern Apennines—Italy). Just close to the monitoring station, a shallow landslide occurred in 2014 at a depth of around 100 cm. The results show the utility of agro-hydrological modeling schemes in modeling the antecedent soil moisture condition and in reducing the overestimation of landslides events detection, which is an issue for early warning systems and slope management related to rainfall-induced shallow landslides. The presented model can be used also to test different bioengineering solutions for slope stabilization, especially when data about rooting systems and plant physiology are known.

The Contradictory Issue of the Impact of Antecedent Soil Moisture to Interrill Erosion in Clay Soil: A Two-Year Field Study

The impact of antecedent soil moisture content on soil erosion has been a contradictory issue in erosion research, as well as process-based soil loss estimation models. The objective of this study was to investigate the impact of antecedent soil moisture content on the loss of clay soil through two-year runoff plot experiments under natural rainfall. Volumetric soil moisture sensors were used to monitor soil moisture changes, and readings were used along with rainfall records to quantify the antecedent soil moisture conditions. The results of this study show that the impact of antecedent soil moisture on interrill erosion is conditional, and the impact only exists in erosion events with a low Rainfall–Runoff Erosivity Index. The coefficient of determination between antecedent soil moisture content and soil loss per the Rainfall–Runoff Erosivity Index (Soil Loss/EI30) varies from 0.222 to 0.758, depending on the rainfall duration and Rainfall–Runoff Erosivity. The results of this study also suggest that accumulative rainfall within 48 h (Pp48) prior to an effective erosion event is strongly correlated with Soil Loss/EI30, particularly when the duration of an effective erosion event is either 3~7 h or 10~30 h. Hence, Pp48 can be considered as a replacement for antecedent soil moisture in process-based soil loss simulation models.