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[Display omitted] • The replenishment showed an increase–decrease trend with increased thinning intensity. • A 35 % thinning intensity improved the replenishment of soil water by rainfall. • The leaf area index and initial soil water content controlled the replenishment. • Reasonable thinning intensity is determined by replenishment and retention. Soil water plays a key role in vegetation growth and recovery, mainly replenished by rainfall in the water-limited areas. Thinning is an important practice for forest reconstruction and soil water regulation. However, the effects of different thinning intensities on the dynamics of soil water and its replenishment by rainfall have been inadequately quantified, which could provide a guide for reasonable thinning intensity determination for in high-density forests from a hydrological perspective. In this study, one nonthinning plot and 5 plots with different thinning intensities, i.e., 35 % (light), 45 % (medium), 55 % (moderate), 65 % (heavy) and 80 % (extremely heavy) in Robinia pseudoacacia plantations, which are widely planted on the Loess Plateau, were set up. The volumetric soil water content (SWC) at 0–200 cm depths and rainfall were observed simultaneously and continuously for up to two years. The soil properties and vegetation structure in each plot were also measured regularly. The results showed that (1) the SWC in all the thinning plots was significantly greater than that in the nonthining plot (P < 0.05). (2) The replenishment increased with increasing thinning intensity, and then decreased after reaching a maximum at T 35 % under most rainfall events except for light events. (3) The variations in the soil water response characteristics among the plots with different thinning intensities were mainly significantly correlated with the initial soil water content (ISWC), leaf area index (LAI) and understorey vegetation characteristics (P < 0.05). (4) Based on the relationship between soil water replenishment and retention with thinning intensity and stand density, quantitative equations were fitted to determine the reasonable thinning intensity (22–28 %) and retained stand density (1019–1091 trees/ha), respectively. Our study concluded that thinning could effectively improve soil water, especially light thinning, which could obviously enhance the replenishment of soil water by rainfall in Robinia pseudoacacia plantations. This study can provide a reference for determining forest thinning intensity or stand retention density, which is beneficial for water and reforestation management in water-limited regions. [ABSTRACT FROM AUTHOR]

• Soil moisture dynamics were compared between four typical types of land use and land cover in a humid mountainous watershed. • The bamboo forest had the largest variability in soil moisture content. • The cumulative infiltration increased but the infiltration rate decreased with the rainfall grade. • The runoff coefficient during representative rainfall events varied with the LULC. Identifying soil moisture dynamics is critical for understanding watershed hydrological processes. Soil moisture responses to rainfall vary with land use and land covers (LULCs) and thus influence rainfall-runoff processes, however, the knowledge about how different LULCs affect such processes was less revealed, especially in humid areas. In this study, we investigated the characteristics of soil moisture content (SMC) and rainfall-related soil moisture responses under four typical LULCs, i.e., waxberry forest, farmland, sloping farmland, and bamboo forest, based on in-situ observations in a humid mountainous watershed. We then used the HYDRUS-1D model to analyze the patterns of the rainfall-infiltration processes and quantified corresponding runoff generation to reveal the partitioning between infiltration and runoff at the event scale. We found significant differences of the average SMC at multiple depths for four LULCs. The deep soil (80 cm) had the largest SMC for the waxberry forest, farmland, and sloping farmland, while the surface soil (10 cm) was the wettest soil layer for the bamboo forest. During the representative rainstorms, although soil moisture responses exhibited depth gradients, the earlier responses at some deep layers indicated the occurrence of preferential flow. Generally, the cumulative infiltration increased while the infiltration rate decreased with the rainfall grade. Farmland and bamboo forest showed the most and the least infiltration, respectively. These results suggested that both the rainfall properties and LULCs had a strong impact on the soil moisture responses. Meanwhile, the estimated average runoff coefficients of four typical LULCs increased with rainfall grade, and the sloping farmland generated the most runoff during the representative rainfall events. Our findings provide new insights into soil moisture dynamics and infiltration regimes under different LULCs in humid areas, which can contribute to hydrological modeling at the field-scale and regional water resource management. [ABSTRACT FROM AUTHOR]

• Rare examples of highly instrumented observatories in African drylands. • Large water surplus during monsoon not represented by annual scale of aridity index. • Overland flow is rare and root zone achieves field capacity across hillslopes. • Stable isotopes indicate recharge season timing, not a link to heavy rainfall. • Recharge is diffuse in semi-arid Africa validating soil moisture balance model use. We use two comprehensively instrumented field observatories to understand groundwater recharge processes in African drylands. The observatories are located on crystalline basement geology in semi-arid parts of Ghana and Burkina Faso, aridity indices 0.43 and 0.29, respectively, and we report 2017–2019 observations. Groundwater recharge was quantified by inverse water table fluctuation models using specific yield estimates derived from magnetic resonance soundings. Evidence for recharge drivers and mechanisms comes from high resolution meteorological observations, soil moisture (logged hourly and weekly along hillslope transects), overland flow plots, river stage, and stable isotopes of O and H in rainfall events and groundwater. Groundwater recharge varied between 87 and 175 mm/y, i.e. 7–15 % of annual rainfall. Rainfall was twice the volume of water lost via actual evapotranspiration across the four peak months (Jun-Sep) of the monsoon. This seasonal water surplus of ∼ 350 mm/y is not characterised by the annual scale of the aridity index. Overland flow was rare and soil moisture deficits were overcome at all monitoring locations. Large rainfall events only produced appreciable recharge when the antecedent soil moisture was close to field capacity, yet always produced large responses in river stage. Stable isotopes of O and H in groundwater indicate no evidence of evapotranspiration prior to infiltration and their composition is akin to depleted isotopic rainfall at the monsoon peak. Stable isotopes indicate recharge season timing and not a relationship between intense rainfall and groundwater recharge. We contend that the mechanism for groundwater recharge is predominantly diffuse in these semi-arid African settings. [ABSTRACT FROM AUTHOR]

• Rainfall classification aided the understanding of deep soil moisture (DSM) recharge. • Groundwater overwhelmed the role of direct rainfall in recharging DSM. • A four-stage relationship between DSM and groundwater table was identified. • A conceptual model for DSM recharge was proposed. Deep soil moisture (DSM) plays a critical role in vadose zone hydrological processes. However, the recharge processes and their underlying mechanisms remain unclear due to the scarcity of comprehensive deep hydrological data, especially in regions characterized by active interactions between surface and subsurface hydrological processes. To address this knowledge gap, we performed an event-based study using a four-year hydrological monitoring dataset, encompassing rainfall, profile soil moisture, and groundwater along a hillslope at the Red Soil Critical Zone Observatory (CZO) in China. A total of 226 rainfall events were classified into four distinct types (I-IV) using a k -means clustering algorithm. The changes in DSM and groundwater table (GWT) were dependent on the rainfall type. The GWT (0.57–0.97) played a greater role in contributing to the DSM than the direct rainfall (0.48–0.64) based on a structural equation model, which was more pronounced from upper slope to foot slope. DSM recharge pattern can be described by a four-stage conceptual model, as indicated by the relationship between DSM and GWT: a slow and linear increase (stage 1), a small plateau (stage 2), a rapid linear rise (stage 3), and finally a great plateau (stage 4). DSM at the small and great plateau were closely related with the field capacity and saturation, respectively. Rainfall type, vadose zone features, and soil physical properties jointly shaped DSM recharge patterns. These findings can offer valuable insights into understanding the deep hydrological processes of the red soil region as well as regions with similar hydroclimatic conditions. [ABSTRACT FROM AUTHOR]

• Critical rainfall for recharging flat sandy lands is 15 mm in hyper-arid desert. • Lateral gravity water flow and surface flow on sandy slopes were identified. • Water flow on sandy slope improves the recharge rate of deep soil from rainfall. • Local rainfall has the capacity to sustain the development of Badain Jaran Lake. • Extreme rainfall does not play a decisive role in the sustaining of desert lake. To elucidate the slope hydrology and their influence on the regional water balance and desert lake development, water migration and soil water conditions were studied in the megadunes of Badain Jaran Desert. Simulated rainfall of 15–60 mm with infiltration depths of ∼ 0.3–0.5 m, the lateral water migration ratios of ∼ 52.9 %-86.2 % and the differential distribution of tracers with depth in the flat sand lands indicate that 15 mm rainfall is the critical rainfall for effective recharge of deep soil water and that there is a shift from piston flow to preferential flow of water during infiltration. Soil micro-bedding and 4.2 % soil gravity water from locally wet surface soils and 6 mm of natural rainfall resulted in lateral migration of the tracer ∼ 1.2 m and 0.4 m in the slope surface and soil respectively, indicate surface flow and lateral gravity water flow resulting from differences in hydraulic conductivity and water-holding capacity of the soil micro-bedding. Soil water storage at 0–4 m depth showed that the bottom of the slope was ∼ 30 mm higher than the middle of the slope after the rainy season and ∼ 9 mm higher before the rainy season; in general the post-rainy season was ∼ 30–40 mm higher than the pre-rainy season. Surface flow and lateral gravity water flow in unsaturated soils increase the intensity of lateral water movement on the slope and improve the effective conversion rate of rainfall to deep soil water, especially below 15 mm. Annual recharge of deep soil water, assessed using soil water change and critical rainfall, will not be less than 8.5 mm and may even reach an upper limit of ∼ 30–40 mm. The megadune slopes respond strongly to local precipitation, which is sufficient to maintain the lake, but extreme precipitation does not play a decisive role. The methods and results provided in this work can advance our understanding of the desert hydrological cycle and water resources. [ABSTRACT FROM AUTHOR]

• The runoff-imperviousness relationship has a segmented linear pattern. • The runoff-imperviousness relationship can be described by the R-I sensitivity. • The R-I sensitivity can be expressed by a simple equation (RISE). • A framework helps for LID adaptation was established based on RISE. The urban RPA (Receiving Pervious Area)-DIA (Disconnected Impervious Area) system is the sub-catchment with a typical land distribution pattern where the connectivity between impervious area and drainage is disconnected by pervious area in the context of Low Impact Development (LID). The rainfall-runoff response of the RPA-DIA system is complex and plays an important role in LID management, which is not yet fully understood. In this study, to systematically learn the rainfall-runoff response of the RPA-DIA system, an indoor rainfall simulation experiment was applied to a laboratory RPA-DIA system, and an integrated surface-subsurface flow model was used to simulate the hydrological processes of actual-scale RPA-DIA systems with consideration of numerous rainfall and underlying surface conditions. Both the laboratory experiment and the numerical simulations show a segmented linear runoff-imperviousness relationship for the RPA-DIA system. A threshold of impervious area exists in the runoff-imperviousness relationship, and when the impervious area is less than the threshold, the surface runoff coefficient is zero, otherwise the surface runoff coefficient increases with impervious area in a generally linear trend. We define the slope of the linear trend as the R-I sensitivity (sensitivity of runoff to imperviousness), which is the key metric to determine the runoff-imperviousness relationship. We further explored how the R-I sensitivity changes between different rainfall and RPA conditions (e.g., different LID facilities and initial soil moistures) and found that both the laboratory experiment and the numerical simulations suggest a very simple equation to express the R-I sensitivity (RISE, Runoff-Imperviosness Sensitivity Equation) in terms of rainfall depth and intensity, including three parameters indicating the specific RPA conditions. Based on the segmented linear relationship and RISE, we have established a framework that vividly presents the rainfall control behavior of a specific RPA under different rainfall events, which can be a simple tool to provide cost-effective guidelines for LID facilities adapting to current or future rainfall characters. [ABSTRACT FROM AUTHOR]

• Most of the Euro-Mediterranean region affected by drought conditions during 2021/22. • Recursive high-pressure systems & a poleward jet shift explain rainfall deficits. • Most severe drought since at least 1891 when considering evaporative demand (AED) • Enhanced AED caused unprecedented low soil moisture & runoff since at least 1965. • Potential worst-case droughts if historic rainfall deficits occur with current AED. The Euro-Mediterranean region experienced a remarkable drought during the hydrological year 2021/22. Substantial and widespread impacts on water supply systems, agricultural crops, and the production of hydroelectric power were observed. This assessment characterises the drought from a long-term perspective using a multi-index approach and analyses the associated atmospheric circulation at the annual and monthly time scales. The main dynamical forcing of the drought was the unusual recurrence of high-pressure systems over western Europe, at least partly due to an anomalous southward shift in blocking activity and a remarkable occurrence of low-latitude blocks. This led to record-breaking positive geopotential height anomalies over western Europe and a poleward displacement of the North Atlantic eddy-driven jet. Although most of the region was affected by mild drought conditions, the 2021/22 event was not unprecedented in terms of precipitation deficits since other periods of the 20th century (e.g., in the 1920s, 1940s and 1970s) displayed moderate and severe drought conditions over larger areas. However, the 2021/22 drought has been the most intense since at least 1891 because of high atmospheric evaporative demand (AED) values associated with extreme temperatures, especially during the summer of 2022. This enhanced AED also contributed to depleting soil moisture and reducing runoff generation, leading to unprecedented deficits since at least 1965. Finally, we find important differences in the 2021/22 event as compared to other major historical droughts over the Euro-Mediterranean region. In particular, the contrasting effect of AED evidences its increasing role over the last decades and warns about the current risk of experiencing unprecedented droughts. [ABSTRACT FROM AUTHOR]

• In-situ soil moisture is used to characterize the spatiotemporal scales of precipitation, especially for those under 10 km. • A sliding window approach is adopted to capture the spatiotemporally varying rainfall events. • The Central TP is dominated by precipitation with relatively short durations (0–6 h) and small spatial extents (< 16 km). The spatiotemporal scale of precipitation is crucial for understanding the local hydrometeorological processes. It also plays a significant role in determining the layout of rain gauges. Convectional rainfalls are typical in the Tibetan Plateau (TP), but the spatiotemporal scales of precipitation events in the TP, particularly at scales less than 10 km, remain unclear, which is mainly due to limited in-situ precipitation observations and the relative coarse spatial resolution of satellite precipitation products. Building upon the strong response of soil moisture changes to precipitation, this study attempts to reveal the spatiotemporal scales of precipitation in the central TP during summertime (June–September) by investigating the inter-station correlation of accumulated positive soil moisture increments obtained from in-situ soil moisture measurements in a mesoscale region of the central TP. The soil moisture-implied spatiotemporal scales are further verified against precipitation from the Integrated Multi-satellitE Retrievals for GPM (IMERG) at spatial scales larger than 10 km. Results show that: 1) the variations of surface soil moisture increase and precipitation are fairly consistent, making positive increments in surface soil moisture an effective surrogate for reflecting the spatiotemporal scales of precipitation in central TP; 2) the spatial extents of precipitation as indicated by the precipitation-induced positive soil moisture increments are positively correlated with the temporal scales; 3) precipitation events with relatively short durations (0–6 h) and spatial extents of less than 16 km (and in particular, 0–3 h for scales less than 10 km) dominate the central TP. This study provides a novel approach for characterizing precipitation scales in regions with scarce in-situ precipitation observations, and is expected to inspire new way of assessing large scale soil moisture and precipitation products. [ABSTRACT FROM AUTHOR]

• Proactive drought responses are crucial in a drought vulnerable future. • Antecedent conditions need to be considered in context of anticipated conditions. • We combine rainfall, soil moisture and evapotranspiration data with forecasts for early warning. • Validation efforts found promising accuracy in the drought early warning maps. • Proof-of-concept drought early warning system can aid proactive drought management. Droughts are a cyclical feature of Australia's climate that have compounding impacts on agricultural productivity and the wellbeing of drought-affected communities. Understanding anticipated drought conditions in context of antecedent observations is critical to providing early warning of drought. In this study we paired probabilistic seasonal rainfall forecasts with precipitation, soil moisture and evapotranspiration data that were objectively combined using Principal Component Analysis (PCA). The final Drought Early Warning System (DEWS) maps overlay forecasting information with the multi-variate PCA-weighted maps at 1-, 3- and 6-month timescales over the common period of overlap between all datasets (1982–2018). In this study period, the 1982–1983 Ash Wednesday tinder drought and the 1997–2001 Millennium drought were investigated. We validated PCA-weighted maps with satellite vegetation data and found performance was strongest over the Murray Darling Basin region (R = 0.63, p = 0.009) and poorest over Central interior Australia (insignificant correlations). We also validated PCA-weighted maps using agricultural commodity data from ABARES. Significant negative correlations at 95 %, 99 % and 99.9 % confidence intervals were found between %-Area in drought category and crop cultivation area; export volume/value; crop yield; and rural debt. Our findings indicate that early warning of drought can be categorised by concern – wherein dry antecedent conditions and dry forecasted conditions are of the highest concern. The developed proof-of-concept DEWS contributes to the growing body of proactive drought management research. In a drought vulnerable future, operationalising and communicating drought early warnings will be critical to reducing the harmful impacts of drought on communities, economies, and environments. [ABSTRACT FROM AUTHOR]

Hillslopes are the fundamental building blocks of catchments, however, fully disentangling their hydrological response remains an outstanding challenge. In natural settings, hillslope hydrology is challenged by the interplay of several factors, such as, heterogeneous morphology, vegetation, and complex soils. Herein, we attempt to clarify the mechanisms that control the rainfall-runoff relationship by investigating the response of an artificial outdoor slope setup with uniform geometry, soil properties, topography, and in the absence of vegetation located in a Mediterranean climate. Based on the analysis of more than 100 storms across six consecutive hydrological years, our results demonstrate that either pre-event soil water content or rainfall conditions alone are not sufficient to explain the slope response. Seasonality played a major role through soil moisture conditions, and pre-event soil moisture, peak rainfall intensity and rainfall duration influenced the slope runoff response. Observations suggest that in fall and winter subsurface flow was the prevalent runoff mechanism, while infiltration excess overland flow mostly occurred in the dry season. Our findings show that continuous measurement of runoff could be beneficial to understand the peak rainfall-peak runoff relationship. • Rainfall-runoff studied in artificial slope through more than 100 storms. • Peak rainfall intensity, rain distribution and soil moisture influence runoff. • Occurrence of runoff before peak rainfall beneficial to predict peak runoff. [ABSTRACT FROM AUTHOR]

• MASCP considers the effect of ponding by introducing a developing saturated zone. • MASCP reveals scaling relations of infiltration for sloping and horizontal surfaces. • New numerical algorithm can model slope infiltration with non-uniform initial SWC. Slope rainfall infiltration is a critical component of the Earth's hydrologic processes. Although various infiltration models have been proposed to simulate rainfall infiltration, simple and accurate ones are still scarce. This work developed a non-integral infiltration model for sloping surfaces, called modified approximate solutions under constant pressure conditions (MASCP). New expressions were proposed to improve slope infiltration simulation by introducing a developing saturated zone in soil water content (SWC) profile to quantify the role of ponding water during infiltration. The MASCP was then extended to simulate the infiltration with uniform and non-uniform initial SWC distributions under complex rainfall patterns. The model performance was evaluated by comparing with Hydrus-1D and the sloping Green-Ampt model for four distinct textured soils. The results demonstrated that the ponding time and infiltration rate simulated by the MASCP agreed well with those by Hydrus-1D at all given conditions. Besides, the MASCP yielded higher simulation accuracy than the sloping Green-Ampt model, especially for coarse-textured soils, low rainfall intensity, and long rainfall hiatus. In conclusion, the MASCP is a simple and accurate computation tool for slope rainfall infiltration modeling. [ABSTRACT FROM AUTHOR]

• Rainfall amount, duration, and intensity significantly affect Ec from diurnal to seasonal timescales. • Rainfall timing has a considerable impact on the magnitude, timing, and intra-daily distribution of Ec. • The responses of Ec to rainfall vary among canopy phenology periods. • The driving mechanisms of biophysical variables to Ec are more complex in days without rainfall events. Rainfall patterns affect vegetation water use through canopy transpiration (Ec) and are becoming increasingly variable due to global warming. However, Ec and its controlling mechanisms in boreal forests have rarely been investigated under various rainfall patterns. In this study, we measured the sap flow using thermal dissipation method in a boreal larch forest (Larix gmelinii) and observed biophysical variables simultaneously (e.g., air temperature, solar radiation, relative humidity, vapor pressure deficit, wind speed, soil water content, rainfall, and leaf area index) over two consecutive growing seasons (May–September) in 2021 and 2022. The responses of Ec to rainfall patterns were evaluated among three rainfall categories (classified based on rainfall amount, duration, and intensity), five types of rainfall timing, and two phenology periods (i.e., leaf expansion and defoliation periods). The results showed that daytime Ec significantly decreased, while nighttime Ec was less variable with increasing rainfall amount, duration, and intensity. The responses of Ec to rainfall categories with different rainfall amount, duration, and intensity were inconsistent at the monthly scale. The magnitude and diurnal dynamics of Ec were greatly influenced by the rainfall timing, and these effects got more considerable with increasing rainfall amount, duration, and intensity. Surprisingly, Ec showed opposite responses to rainfall in leaf expansion and defoliation periods, suggesting an enhanced impact in the leaf expansion period while a diminished impact in the leaf defoliation period. The significantly affected biophysical factors of Ec varied dramatically among rainfall categories. The interactions between biophysical factors and Ec were more complex and diverse in days without rainfall events than days with rainfall days. These findings highlight the importance of rainfall patterns in affecting Ec, provide new insight into the interactions between rainfall patterns, Ec, and biophysical factors, and are important supports for improving evapotranspiration simulations in the context of climate change. [ABSTRACT FROM AUTHOR]

• Funneling ratio of live C. korshinskii branches was 1.8 times higher than dead ones. • Funneling ratio of dead S. psammophila branches was 1.6 times higher than live ones. • Rainfall intensity significantly affected stemflow intensity and time lags to rain. Shrub mortality due to self-thinning and climate change is a natural consequence of the long residence times of standing dead branches in unmanaged shrub plantations. Stemflow (SF) represents a key point source of input water and nutrients into the soil in shrub ecosystems. However, little information is available about how shrub mortality affects SF variables. In this study, we measured the SF volume (SFV), funneling ratio (FR), SF intensity, time lag to rain, and rainfall characteristics for live and standing dead branches of two major shrub species comprising Caragana korshinskii and Salix psammophila during the rainy season in 2022 on the Chinese Loess Plateau. The results demonstrated that the SF variables and temporal dynamic processes differed between standing live and dead branches of the two shrubs. For C. korshinskii , the mean SFV and FR were 1.9 and 1.8 times higher for live branches than dead branches, respectively, whereas for S. psammophila , the mean SFV and FR were 1.3 and 1.6 times higher for dead branches than live branches. These contradictory results can be explained by differences in the canopy structures of the species, such as the surface area that contributes to the generation of SF in the upper canopy, branch angles, and the degree of branch bark decomposition and decay. In addition, the SF variables were significantly temporally dependent on the rainfall characteristics. SFV, SFI, and SFD were positively and linearly correlated with the rainfall amount, intensity, and duration at the inter-event scale (P < 0.001). The influence of rainfall intensity on SF time lag to rain were not significant at the intra-event scale (P > 0.05). Considering the enrichment ratio due to canopy dry deposition and bark decomposition, the periodic flattening of dead S. psammophila branches to restore their growth is less significant than allowing them to die and renew naturally. These findings may serve as a reference for developing management practices for shrub species in areas with soil water and nutrient deficiencies. [ABSTRACT FROM AUTHOR]

• Rainfall losses are a key input to event-based flood models widely used in practice. • Relationship between rainfall losses and antecedent soil moisture are quantified. • Climate change projections of soil moisture are used to project rainfall losses. • Both the magnitude and variance of future rainfall losses are projected to increase. • Climate change will affect rainfall losses and hence flood responses. Climate change is expected to impact the severity and frequency of floods, which has implications for flood risk management. Design floods and derived flood frequency curves obtained using event-based rainfall-runoff models are widely used in industry to assess flood risks for planning and design purposes. For these approaches it is necessary to have (a) rainfall inputs, and (b) rainfall losses specified, the latter representing the amount of rainfall that is either intercepted, stored on the surface, or infiltrated into the soil and does not contribute to the flood hydrograph. There is extensive research on changes in flooding under climate change that focus on projections of rainfall. However, there is little research into projections of rainfall losses under climate change, despite the knowledge that their changes will modulate the flood response. Here, we present one of the first studies seeking to quantify how rainfall losses, as represented by estimates of initial and continuing losses used in event-based models, are projected to change under climate change. We identify dependencies between rainfall losses and antecedent soil moisture in around half (over 200) of the largely unregulated catchments (i.e. watersheds) in Australia analysed in this study and use these relationships to project rainfall losses under climate change. Near universal increases in both the mean and variance of both initial losses and continuing losses are projected in these catchments, suggesting that increased rainfall losses could offset the impact of increased rainfalls for frequently occurring floods and result in an increased variance in flood responses. [ABSTRACT FROM AUTHOR]

• Rainfall isotopic signature dependence with air temperature and rainfall amount. • Development of a Local Meteoric Water Line for Vallcebre Research Catchments, Spain • Use of backward trajectories relating moisture source and isotopic signature. • Case studies analysis of moisture origin and intra-event isotopic variability. This study investigates moisture origin, characteristics and intra-event scale variability of the isotopic signature of rainfall in a Mediterranean mountain area, based on data from the Vallcebre Research Catchments, NE Spain. Weekly data and samples were used to analyse the general dynamics of the isotopic composition of precipitation and its relationship with meteorological variables at the sampling site. Then, based on the data and samples available at the intra-event scale, the variability of the isotopic signature during rainfall events was characterised and an explanation of what caused the observed variability was attempted. Results at the weekly time scale show that the maximum relative deviation of the heavy isotopic content with respect to Standard Mean Ocean Water (δ 18 O) of the precipitation signature occurred during summer months and, in contrast, the minimum during winter months. The intra-annual trend of rainfall δ 18 O roughly followed the mean monthly air temperature. Using intra-event information, three main types of δ 18 O isotopic trends were found during rainfall events: most of the events had a V-shaped isotopic trend, followed by L-shaped and constant trend events. Changes in moisture sources 'diagnosed using a Lagrangian approach and a previously existing contribution algorithm' were one of the causes of the isotopic variability and changes at the intra-event scale, but these may also have been influenced by sub-cloud processes that modified the isotopic signature. Moisture sources for analysed events showed the main influence of the Mediterranean area, but also an important influence of the Atlantic Basin. [ABSTRACT FROM AUTHOR]

• Changes in both soil moisture and extreme rainfall influence historical flood trends. • The influence of soil moisture and extreme rainfall depends on flood severity. • The more extreme a flood event is, the less dependent it is on soil moisture changes. • Changes in soil moisture need to be considered in projections of flooding. Despite the expectation that increases in rainfall with climatic change will result in increases in pluvial flooding, there is more historical evidence for decreases in flood magnitude. In Australia, as in many other parts of the world, flood magnitudes are mostly decreasing, despite increasing rainfall extremes. Here, we show how changes in soil moisture have led to decreasing flood magnitudes while rainfall extremes have been increasing. Using gauged streamflow, catchment average rainfall, and modelled soil moisture data across Australia we confirm that streamflow peaks (or floods) that occur at least once a year are strongly related to both the peak rainfall causing the flood and the antecedent soil moisture conditions preceding the storm event. Regions where the magnitude of the peak flow has decreased are visually and statistically correlated to regions of decreasing soil moisture. Flood magnitudes are more likely to increase only for the rarest events, with increases in rainfall offset by decreases in soil moisture for more frequent events. A recurrence interval dependent tipping point is identified beyond which trends in catchment rainfall outweigh those of soil moisture trends and dominate the flood response. For regions where soil moisture has decreased, this tipping point occurs at an average recurrence interval of ten years or more. As most studies investigating trends in flooding generally use annual maxima, changes in soil moisture are likely to be the dominant mechanism behind observed flood trends. Hence changes in soil moisture conditions need to be considered when predicting catchment flood response due to climatic change. [ABSTRACT FROM AUTHOR]

• Probabilistic threshold integrates antecedent soil moisture with rainfall threshold. • Bayes' theorem is applied to estimate the probability of landslide occurrences. • Soil moisture is estimated by the hydrological simulations. Various methods have been proposed to define the rainfall thresholds for the landslide prediction. Once the threshold is determined, it remains the same regardless of the antecedent soil moisture conditions. However, given the important role of the antecedent soil moisture in the initiation of landslides, it is considered if the rainfall threshold level varies according to the antecedent soil moisture conditions, the prediction performance will be improved. Therefore, in this study we propose a probabilistic threshold to integrate antecedent soil moisture conditions with rainfall thresholds. In order to take into account the conditions with landslides and without landslides, the Bayesian analysis is applied to estimate the landslide occurrence probability given the various combinations of two factors: the antecedent soil moisture and the severity of the recent rainfall event. These combinations are then divided into conditions that are likely to trigger landslides and those unlikely to trigger landslides by comparing their probabilities with a critical value. In this way, the probabilistic threshold is determined. Here the soil moisture is estimated using the distributed hydrological model, and the severity of the rainfall event is characterized by the cumulated event rainfall-rainfall duration (ED) thresholds with different exceedance probabilities. The proposed approach was applied to a sub-region of the Emilia-Romagna region in northern Italy. The results show that the probabilistic threshold has a better prediction performance than the ED rainfall threshold, especially in terms of reducing false alarms. This study provides an effective approach to improve the prediction capability of the ED rainfall threshold, benefiting its application in the landslide prediction. [ABSTRACT FROM AUTHOR]

• A novel algorithm named SM2RAIN-BayesOpt is proposed for estimating rainfall by integrating the SM2RAIN algorithm and Bayesian optimization. • The performance of the SM2RAIN-BayesOpt algorithm is evaluated against rain gauge data in three typical areas. • The SM2RAIN-BayesOpt rainfall estimates is compared with IMERG-V06B, and ERA5 reanalysis rainfall products. • Effects of soil freezing on SM2RAIN-BayesOpt rainfall estimation are investigated. • Effects of land cover on calibration parameters of SM2RAIN-BayesOpt are inspected. The rainfall product derived from the SM2RAIN (Soil Moisture to Rain) algorithm has been widely used. However, there is still a large uncertainty partly due to the soil moisture input and parameters estimation of the SM2RAIN algorithm, which limits the application of the model in alpine regions. Here, the SM2RAIN-BayesOpt algorithm was developed by integrating the SM2RAIN algorithm and Bayesian optimization to improve the estimation of parameters (Z, a, b, T base , T pot), subsequently incorporating SMAP Level-3 soil moisture products for rainfall estimation. The performance of the SM2RAIN-BayesOpt algorithm was evaluated based on observed rainfall data under different environmental conditions in three typical alpine regions, namely Tibetan Plateau, Heihe River Basin, and Shandian River Basin. Moreover, SM2RAIN-BayesOpt, IMERG-V06B, and ERA5 reanalysis rainfall estimates were also compared with in-situ rainfall observations. The results showed that the proposed SM2RAIN-BayesOpt algorithm can obtain more accurate rainfall estimates in all studied areas in terms of different evaluation metrics. It was also found that our proposed SM2RAIN-BayesOpt algorithm performs better in alpine meadows and grassland than in desert and forestland. SM2RAIN-BayesOpt algorithm can considerably improve the accuracy of rainfall estimation, and it is of significant value for rainfall monitoring in alpine regions where observational data are scarce. [ABSTRACT FROM AUTHOR]

• A Bayesian approach has been used for merging multiple satellite rainfall products. • We created a superior product that can be efficiently run in near-real time. • Soil moisture can provide useful information for improving satellite rainfall. This work investigates the potential of using the Bayesian-based Model Conditional Processor (MCP) for complementing satellite precipitation products with a rainfall dataset derived from satellite soil moisture observations. MCP – which is a Bayesian Inversion approach – was originally developed for predictive uncertainty estimates of water level and discharge to support real-time flood forecasting. It is applied here for the first time to precipitation to provide its probability distribution conditional on multiple satellite precipitation estimates derived from TRMM Multi-Satellite Precipitation Analysis real-time product v.7.0 (3B42RT) and the soil moisture-based rainfall product SM2RAIN-CCI. In MCP, 3B42RT and SM2RAIN-CCI represent a priori information (predictors) about the "true" precipitation (predictand) and are used to provide its real-time a posteriori probabilistic estimate by means of the Bayes theorem. MCP is tested across Italy during a 6-year period (2010–2015) at daily/0.25 deg temporal/spatial scale. Results demonstrate that the proposed methodology provides rainfall estimates that are superior to both 3B42RT (as well as its successor IMERG-early run) and SM2RAIN-CCI in terms of both median bias, random errors and categorical scores. The study confirms that satellite soil moisture-derived rainfall can provide valuable information for improving state-of-the-art satellite precipitation products, thus making them more attractive for water resource management and large scale flood forecasting applications. [ABSTRACT FROM AUTHOR]

• Effects of interpolation methods on rainfall data scarcity were compared. • Impacts of of data scarcity on model uncertainty were investigated. • The effects of the different imputed data sets on H/NPS results were quantified. • The EMB algorithm was proved to be superior to the traditional methods. • The threshold effect and monitoring during high-flow periods were highlighted. Rainfall data scarcity has caused enormous problems in hydrologic and non-point pollution (H/NPS) predictions, as rainfall data represent the key input to watershed models. In this study, the effects of different imputation methods such as the data augmentation (DA) and the expectation maximization with bootstrap (EMB) algorithms on rainfall data scarcity were compared. The effects of different data scarcity rates and periods on model performance and prediction uncertainty were then quantified. Finally, the effects of different imputed data sets on H/NPS results were evaluated with the soil and water assessment tool (SWAT). A real case study in the Daning River watershed, Three Gorges Reservoir Region, China, was evaluated. The results indicated that rainfall data scarcity during low flow periods would result in poorer model performance and larger prediction uncertainty, especially to some minimum values, and the time when the maximum values are more susceptible is the rainfall data scarcity during high flow periods. The repair of rainfall data and the H/NPS model performance obtained by the EMB algorithm are superior to the traditional DA and weather generator performances. This advantage of the EMB algorithm would be more definitive if a specific threshold of data scarcity is reached. It is noted that even if the best algorithm is used, the imputed value is always lower than the peak observed value. This paper reports important implications for the choice of imputation methods and the use of H/NPS models for solving data scarcity problems for watershed studies. [ABSTRACT FROM AUTHOR]

Highlights • SWAT and DE were coupled to provide a dynamic calculation of WEC for NPS pollution. • Three different WECs were analyzed to reveal the impacts of upstream on downstream. • Seasons change had impacts on the WEC, and the smallest value occurred in wet season. • WEC of nutrients in organic species was more affected by seasons than that in inorganic. • Controlling NPS pollution and enhancing the WEC should be carried out simultaneously. Abstract The objective of this study was to advance a new method to dynamically analyze the water environmental capacity (WEC) of non-point source (NPS) pollution. A Soil and Water Assessment Tool (SWAT) model and differential evolution (DE) algorithm were coupled to automatically provide a calculation of the WEC in a daily step. The results showed that the largest ideal WECs occurred in the wet season with values up to 4500 t and 80 t for total nitrogen (TN) and total phosphorus (TP), respectively. The ideal WEC had a positive correlation with the rainfall intensity, while the opposite was true for actual WEC. The smallest value of actual WEC for TN was −150 t in June, and a negative value also occurred in June for TP. This is because NPS pollution discharge was more sensitive to rainfall and flow change than the ideal WEC. Compared to phosphorus, the WEC of nitrogen was more affected by the hydrological and NPS pollution discharge conditions. In addition, the WEC of nitrogen and phosphorus in organic species was more affected by seasonal change than that of nitrogen and phosphorus in inorganic species. Spatially, the channels in the middle and southeast of the study area had the smallest actual WEC and even negative values were observed. The results of remnant WEC showed that the smallest value occurred in July and June with values of −800 t and −140 t for TN and TP, respectively. Thus, significant attention should be paid to controlling NPS pollution during the wet season, and organic nitrogen and phosphorus should be set as the priority pollutants to control. Furthermore, controlling the NPS pollution discharge and enhancing the WEC should be carried out simultaneously. Compared to previously used methods, the calculation method employed in this study had the ability to simulate the transformation and interaction between nitrogen and phosphorus in organic and inorganic species, and better considered dynamic changes in the input conditions. [ABSTRACT FROM AUTHOR]

Highlights • Soil moisture and soil water tension showed seasonally different characteristics at a steep hillslope. • The distribution of soil moisture characteristics curve was different between spring and autumn seasons. • The soil moisture transfer process was seasonally evolved from spring to autumn. Abstract Understanding variations in soil moisture and soil water potential is important for describing hydrological processes at the hillslope scale. An intensive field campaign to measure soil moisture, soil water potential, and rainfall events was performed at many locations and depths to obtain seasonal and spatial distributions of hydrometric measurements along steep hillslopes. Soil moisture and soil water tension analysis showed seasonally distinctive features in statistics and probability distributions. The relationship between soil moisture and soil water tension was explored to characterize seasonal and spatial variations. The recession slopes of soil moisture at several given points of the relationship were also seasonally different. The Brooks and Corey model and the van Genuchten model were used to estimate parameters for the measured data to explain the spatial and seasonal variations. Soil water storage analysis not only indicated that lateral flow tends to be abundant at greater depths but also revealed a seasonal trend in development of subsurface flow in the downslope direction. The combined impact of topography and vegetation determined the seasonal differences in hydrometric responses along the hillslope locations. [ABSTRACT FROM AUTHOR]

Highlights • Areal infiltration models are crucial for studies at different spatial scales. • Saturated hydraulic conductivity greatly influences areal infiltration modeling. • Experimental evidence of the accuracy of a model for areal infiltration is given. Abstract Operative distributed/semi-distributed rainfall-runoff formulations need a mathematically tractable component for estimating the expected areal-average infiltration rate, I , while point infiltration models are usually adopted for this purpose. A model for I , suitable for hydrological applications, was proposed by Morbidelli et al. (2006, Hydrological Processes, 20: 1465–1481). The main model tenet is the use of cumulative infiltration as an independent variable and replacement of time by its expected value. While this model - as with many other models for field-scale infiltration - was tested through Monte Carlo methods, it remains untested with experimental observations. In this study, a reassessment of the model's applicability is conducted through experimental evidence from several rainfall-runoff events observed under natural conditions at the plot scale over a slight slope characterized by a silty loam soil. During each experiment rainfall rate, surface runoff at the plot outlet and soil water content vertical profiles were monitored at short time intervals. An overall analysis of our results suggests that the model reliably simulates I and surface runoff as functions of time and is also suitable for applications under time-dependent rainfall events. The process of redistribution under rainfall hiatus is not addressed by this model. [ABSTRACT FROM AUTHOR]

Highlights • New grid-based model is used to compute flood and runoff-contributing area. • New proposed IRCA index combines runoff-contributing area and rain intensity on it. • IRCA for a characteristic duration is well correlated with flood peak discharge. • Land-uses with low runoff potential become dominant in large–extreme flood events. • Pre-peak soil moisture differs between flood magnitudes while pre-event does not. Abstract During the complex dynamic interactions between rainfall and basin properties, different portions of the basin produce runoff at different moments. Capturing this spatiotemporal variability is important for flood analysis, but knowledge of this subject is limited. The presented research aims at improving the understanding of runoff-contributing areas (RCA; hillslope sections from which water flows, reaches the stream network, and consequently the basin outlet) and at examining their relationship with the magnitude of a flash flood's peak discharge. A distributed hydrological model (GB-HYDRA) that enables computing RCA and flood discharge was developed. The model was applied to four medium-size basins (18–69 km2) in a Mediterranean climate and 59 flash flood events were analyzed. The correlation between basin input flux (basin area multiplied by the basin maximal rain intensity averaged over the time of concentration) and output flux (observed peak discharge) was poor (R2 = 0.16). However, using a newly developed index, termed IRCA, to calculate the input flux accounting only for the RCA extent and rainfall intensity over it, resulted in a substantially higher correlation (R2 = 0.64) across a wide range of flood magnitudes. The highest correlation was found using a 50-min time window, which is shorter than the time of concentration. Flood events were categorized according to their magnitude and the differences of several factors among the groups were examined. Pre-storm soil moisture content was found to be similar for all event magnitudes; however, pre-peak soil moisture content was substantially different between moderate and large–extreme events. Other important properties that differed between magnitudes were: RCA extent and its averaged rain intensity and ratio of convective rainfall. Finally, areas with land-uses characterized by low runoff potential became dominant and contributed mainly during large and extreme events. Although the RCA and its extent full potential is yet to be fulfilled, it is proposed as a significant tool for understanding processes of flash flood generation at the basin scale in future research. [ABSTRACT FROM AUTHOR]

Highlights • DfD model is proposed to estimate drainage from soil moisture (SM) drydowns. • Soil hydraulic properties are encoded in the shape of SM recession scatter plot. • The model best operate in permeable soil and humid climate. • By using SM2RAIN and DfD jointly, rainfall is estimated from SM data only. • There is a good potential of applying DfD to satellite soil moisture data. Abstract The large heterogeneity in soil surface conditions makes it impracticable to obtain reliable estimates of soil hydraulic parameters for areas larger than few squared kilometers. However, identifying these parameters on a global scale is essential for many hydrological and climatic applications. In this study, a new approach named Drainage from Drydown (DfD) is proposed to estimate the coefficients of drainage using soil moisture observations. DfD firstly selects multiple drydown events when surface runoff and evapotranspiration rates are negligible compared to the drainage rate. Secondly, by inverting the soil water balance equation, the drainage coefficients are obtained. Synthetic experiments are carried out in order to tune the overall procedure. DfD is then tested with in situ observations at 8 different sites worldwide characterized by different climates and soil types. The reliability of the DfD is evaluated by using the DfD drainage coefficients in a physically based soil water balance model (SWB) for simulating soil moisture and a rainfall estimation model (SM2RAIN). The results indicate that the climate and the soil conditions exert an important role in the occurrence and magnitude of drainage rate. DfD is found capable of correctly identify periods in which drainage rate is the dominant process. Drainage coefficients obtained from DfD are consistent with the expected soil hydraulic properties based on the soil texture and land cover at each site. By using DfD drainage coefficients to estimate rainfall and soil moisture via SM2RAIN and SWB, promising results are obtained with median correlation of 0.83 and 0.91 between estimated and in situ data. However, in sites characterized by high rate of evapotranspiration (>700 mm/year) and low permeable soil (e.g., clay) the DfD performance is reduced. Overall, DfD demonstrates the ability to decouple drainage and evapotranspiration processes and to estimate the drainage coefficients from in situ observations. [ABSTRACT FROM AUTHOR]

The goal of this study was to determine if assimilating a combination of various derived data products can help circumvent some of the difficulties associated with urban watershed modeling. Combinations of the SNODAS (Snow Data Assimilation System) snow water equivalent data, the SMOS (Soil Moisture and Ocean Salinity) L2 soil moisture, and streamflow observations were used for the data assimilation schemes. Combinations of these observation data sets were assimilated into lumped conceptual rainfall-runoff models of the highly-urbanized Don River basin (in southern Ontario) to determine if assimilation of geophysical variables will have a significant impact on simulations and forecasting in an urbanized watershed. The Ensemble Kalman Filter (EnKF) data assimilation method was used for these analyses, with various rainfall-runoff models that include GR4J, HyMod, MAC-HBV, and SAC-SMA models. The best data assimilation scheme for hydrologic modeling involved using a combination of streamflow, soil moisture, and snow water equivalent while performing both state and parameter updating. These results suggest that using a combination of soil moisture and snow water equivalent from the SMOS and SNODAS data products can improve simulations and ensemble forecasts in an urban basin. [ABSTRACT FROM AUTHOR]

When restoring dryland ecosystems, growing biological soil crust (biocrust) may greatly change the redistribution of rainfall in layered soils. However, ecohydrological modelling studies generally ignore biocrust and thus, the ecohydrological effects of biocrust on restorations remain largely unexplored. Using a long-term restoration case (located in the southeast edge of the Tengger Desert, northern China), we developed an ecohydrological model with explicit consideration of the infiltration in three layered soils (biocrust, shallow and deep sand layers) to investigate influences of biocrust on restoration dynamics in drylands. The proportion of infiltration that reaches ‘annual grass’ (including biocrust and shallow sand layers, 0–30 cm) and ‘shrub’ layers (30–150 cm) with biocrust significantly increased and decreased relative to the values without biocrust, respectively. Meanwhile, biocrust significantly decreased soil water content in deep sand layer, but not in shallow sand layer. As more water was used by transpiration than evaporation, the ecosystem with biocrust reached a final grass-dominated state (high grass cover of 40%, low shrub cover of 4%) rather than a shrub-dominated state (grass cover of 3%, shrub cover of 20%). This study suggests that we need to account for the roles of biocrust on rainfall infiltration to better understand vegetation and restoration dynamics in dryland ecosystems. [ABSTRACT FROM AUTHOR]

Satellite-based rainfall products (SRPs) are nowadays available at ever increasing accuracy and higher spatial and temporal resolution with respect to the past. Despite this, they are scarcely used in hydrological modeling. The main reasons may be related to: 1) the large bias characterizing satellite precipitation estimates, which is dependent on rainfall intensity and the season, 2) the relatively large spatial/temporal resolution with respect to the applications, 3) the timeliness, which is often insufficient for operational purposes, and 4) a general (often not justified) skepticism of the hydrological community in the use of satellite products for land applications. The objective of this study is to explore the feasibility of using SRPs to force a lumped hydrologic model – MISDc – over 15 basins in the Mediterranean area with different sizes and physiographic characteristics. Specifically, TMPA 3B42-RT, CMORPH, PERSIANN and a new soil moisture-derived rainfall datasets, SM2RAIN CCI , obtained through the application of SM2RAIN algorithm ( Brocca et al., 2014 ) to ESA CCI soil moisture product are used in the analysis. The performances obtained with the selected SRPs are compared with those obtained from a ground-based rainfall product (E-OBS). In addition, the performance obtained by an integration of the SRPs is investigated to see whether merged rainfall observations are able to improve flood simulations. The results highlight that SRPs provide relatively low performances when used to force MISDc model with respect to the case where ground observations are used. Worst results are obtained in smaller basins (<500 km 2 ) that, however, represent the main target for flood modelling in the Mediterranean area. Relatively better performances are obtained when independent SRPs are integrated each other, and particularly for the case where TMPA 3B42-RT is integrated with SM2RAIN CCI . In accordance with previous studies, this suggests that the exploitation (via integration) of independent sources of rainfall offers a potential way to reduce rainfall-induced streamflow errors, even in challenging areas like the Mediterranean. [ABSTRACT FROM AUTHOR]

Pines in semi-arid mountain environments manage to survive and thrive despite the limited soil water, due to shallow soil depths, and overall water scarcity. This study aims to develop a method for computing soil evaporation, bedrock water uptake and transpiration from a natural, open forest, based on sap flow (Heat Ratio Method), soil moisture and meteorological observations. The water balance of individual trees was conceptualized with a geometric approach, using canopy projected areas and Voronoi (Thiesen) polygons. The canopy approach assumes that the tree’s root area extent is equal to its canopy projected area, while the Voronoi approach assumes that the tree roots exploit the open area that is closer to the tree than to any other tree. The methodology was applied in an open Pinus brutia forest (68% canopy cover) in Cyprus, characterized by steep slopes and fractured bedrock, during two hydrologically contrasting years (2015 wet, 2016 dry). Sap flow sensors, soil moisture sensors, throughfall and stemflow gauges were installed on and around eight trees. Rainfall was 507 mm in 2015 and 359 mm in 2016. According to the canopy approach, the sum of tree transpiration and soil evaporation exceeded the throughfall in both years, which implies that the trees’ bedrock water uptake exceeds the surface runoff and drainage losses. This indicated that trees extend their roots beyond the canopy-projected areas and the use of the Voronoi polygons captures this effect. According to the stand scale water balance, average throughfall during the two years was 81% of the rainfall. Transpiration was 61% of the rainfall in 2015, but only 32% in 2016. On the contrary, the soil evaporation fraction increased from 26% in 2015 to 35% in the dry year of 2016. The contribution of bedrock water to tree transpiration was 77% of rainfall in 2015 and 66% in 2016. During the summer months, trees relied 100% on the uptake of water from the fractured bedrock to cover their transpiration needs. Average monthly transpiration areas ranged between 0.1 mm d −1 in October 2016 and 1.7 mm d −1 in April 2015. This study shows that bedrock uptake could be an essential water balance component of semi-arid, mountainous pine forests and should be accounted for in hydrologic models. [ABSTRACT FROM AUTHOR]

The feasibility of simulating the hydrological response of a grass swale to runoff inflows was examined using the hydrological model Mike SHE and the available input data from 12 irrigation events mimicking runoff from block rainfalls. The test swale channel had a trapezoidal cross-section, bottom slope of 1.5%, length of 30 m, and was built in loamy fine sand. The irrigation events consisted in releasing two equal constant inflows to the swale: a concentrated longitudinal flow at the upstream end and a distributed lateral inflow along the swale side slope adjacent to the contributing drainage area. The total inflows approximated runoff from two events with return periods of 2 months and 3 years, respectively, for durations of 30 min. Irrigation experiments were done for two states of the initial soil moisture, dry or wet antecedent moisture conditions (AMC). Mike SHE has been extensively used on catchments of various sizes, but rarely for small stormwater management facilities and their detailed topography investigated in this study. The latter application required high spatial and temporal resolutions, with computational cells of 0.2 × 0.2 m and time steps as short as 0.6 s to avoid computational instabilities. For dominant hydrological processes, the following computational options in Mike SHE were chosen: Soil infiltration – the van Genuchten equation, unsaturated zone flow – the one-dimensional Richards equation, and overland flow – the diffusive wave approximation of the St. Venant equations. For study purposes, the model was calibrated for single events representing one of four combinations of low and high inflows, and dry and wet AMC, and then applied to the remaining 11 events. This was complemented by calibration for two events, representing high inflow on wet AMC and low inflow in dry AMC. The goodness of fit was statistically assessed for observed and simulated peak flows, hydrograph volumes, Nash-Sutcliffe model efficiencies (NSE), and soil water content (SWC) in swale soil layers. The best fit (NSE > 0.8) was obtained for high inflows and wet AMC (i.e., when the primary swale function is flow conveyance); the least fit was noted for low inflows and dry AMC, when the primary swale function is flow attenuation. Furthermore, this observation indicates the overall importance of correct modelling of the soil infiltration. The effects of spatial variation of SWC on the swale discharge hydrograph could not be confirmed from simulation results, but high topographical accuracy was beneficial for reproducing well the locations of the observed water ponding. No significant increases in simulated SWC at 0.3 m or greater depths were noted, which agreed with field observations. Overall, the results indicated that Mike SHE was effective in process-oriented small-scale modelling of grass swale flow hydrographs. [ABSTRACT FROM AUTHOR]

• Extreme rainfall events that lead to floods in large rivers are expected to decrease. • Antecedent soil moisture is expected to be reduced in most of South America. • Soil moisture seems more impactful than precipitation regarding ordinary floods. A warmer atmosphere is able to hold more water which consequently intensifies the hydrological cycle. The projected increase in extreme precipitation has been associated with greater floods; however, most recent studies have argued that the reduced soil moisture could be causing the opposite effect. We aim to understand how the hydrometeorological variables affect flood discharge and what the projections are for South America, a vulnerable continent that has been barely studied regarding flood trends. We used climate data from Eta simulations nested in 4 global climate models (BESM, CanESM2, HadGEM2-ES, MIROC5) as input for the MGB-SA hydrological model to yield flood discharge estimates. Then we were able to project the climate impacts on extreme precipitation, antecedent soil moisture, and flood discharge for large rivers (>1,000 km2) and understand how these variables are related. Our results showed a strong sign that antecedent soil moisture is expected to be reduced in most of the continent except in Southeastern South America (SESA). On the other hand, there are mixed signs for rarer precipitation and a clear spatial pattern for 2-year precipitations (RP2), which is expected to increase on the SESA and west Amazon and decrease on Central South America (CSA). For basins>100,000 km2, results indicate a negative change sign for 2-year precipitations, meaning that rainfall events that generate ordinary floods in large South American rivers are expected to decrease in the XXI century due to climate change. The change signs for flood discharge and extreme precipitation are spatially similar but more basins show a decrease for flooding than for rainfall. While only half of the South American basins are expected to present reduced 2-year precipitations, nearly 70 % of the rivers present a negative sign for 2-year floods, which can be attributed to the reduced antecedent soil moisture. [ABSTRACT FROM AUTHOR]

A modified Green-and-Ampt model is formulated to quantify infiltration on sloping terrain underlain by homogeneous soil wetted by surficial water application. This paper’s theory for quantifying infiltration relies on the mathematical statement of the coupled partial differential equations (pdes) governing infiltration and runoff. These pdes are solved by employing an explicit finite-difference numerical method that yields the infiltration, the infiltration rate, the depth to the wetting front, the rate of runoff, and the depth of runoff everywhere on the slope during external wetting. Data inputs consist of a water application rate or the rainfall hyetograph of a storm of arbitrary duration, soil hydraulic characteristics and antecedent moisture, and the slope’s hydraulic and geometric characteristics. The presented theory predicts the effect an advancing wetting front has on slope stability with respect to translational sliding. This paper’s theory also develops the 1D pde governing suspended sediment transport and slope degradation caused by runoff influenced by infiltration. Three examples illustrate the application of the developed theory to calculate infiltration and runoff on a slope and their role on the stability of cohesive and cohesionless soils forming sloping terrain. [ABSTRACT FROM AUTHOR]

Summary In order to resolve contradictions in addressing a soil moisture–precipitation feedback mechanism over West Africa and to clarify the impact of antecedent soil moisture on subsequent rainfall evolution, we first validated various data sets (SMOS satellite soil moisture observations, NOAH land surface model, TRMM rainfall, CMORPH rainfall and HadGEM climate models) with the Analyses Multidisciplinaires de la Mousson Africaine (AMMA) field campaign data. Based on this analysis, it was suggested that biases of data sets might cause contradictions in studying mechanisms. Thus, by taking into account uncertainties in data, it was found that the approach of consecutive dry days (i.e. a relative comparison of time-series) showed consistency across various data sets, while the direct comparison approach for soil moisture state and rainfall did not. Thus, it was discussed that it may be difficult to directly relate rain with soil moisture as the absolute value, however, it may be reasonable to compare a temporal progress of the variables. Based upon the results consistently showing a positive relationship between the consecutive dry days and rainfall, this study supports a negative feedback often neglected by climate model structure. This approach is less sensitive to interpretation errors arising from systematic errors in data sets, as this measures a temporal gradient of soil moisture state. [ABSTRACT FROM AUTHOR]

Soil moisture is an important factor for understanding hydrological and solute transport processes at the hillslope scale. The selection of representative points for soil moisture measurement has been explored to investigate temporal variation of average soil moisture with minimum costs and maximum stability. The optimal selection of soil moisture monitoring points has been reevaluated to address hillslope hydrological processes and the impacts of seasonal differences. An alternative method to select soil moisture measurement points was developed to adequately represent immediate soil moisture response patterns to sequential rainfall events. To address the seasonal features of rainfall events and their impacts on soil moisture redistribution along the hillslope, field soil moisture data were collected at 49 points for three seasons over periods of 25 days with bi-hourly monitoring intervals. For effective characterization of soil moisture variation, soil moisture datasets were classified using cluster analysis based on Euclidean similarity. Points delineated using the proposed method not only provide better stability of average soil moistures but also adequately represent the response patterns of soil moisture to rainfall events on the hillslope. [ABSTRACT FROM AUTHOR]

[Display omitted] • A novel regionalization-based sediment-response similarity (SRS) method was proposed. • The physical similarity and SRS methods were compared using the SOM and SWAT model. • Results showed that SRS was superior to the conventional method. • The SRS method showed the potential to estimate catchment-wide sediment load. The development and application of reliable hydrological models are challenging in ungauged or poorly gauged catchments. Although several regionalization methods have been developed for predicting hydrological variables in ungauged catchments, a large uncertainty usually exists in the prediction because previous methods typically depended on several static catchment attributes or long-term mean climatic descriptors, thereby neglecting the spatiotemporal variability of the climate. In this study, we propose a new regionalization method called sediment-response similarity (SRS) using the soil and water assessment tool model and self-organizing maps to estimate sediment load in ungauged catchments, considering spatiotemporal variability and the sediment load relation to rainfall characteristics of individual catchments. The performance of SRS was evaluated by comparing it against the conventional regionalization method (i.e., physical similarity) and calibration model results, in four gauged catchments of the lower Mekong River basin. The SRS method showed improved performance over the conventional approach in estimating sediment loads, with an average Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2) of 0.75 and 0.76, respectively, which were close to the respective values of NSE and R2 = 0.77, of the calibration model. Additionally, the SRS approach showed an error reduction of up to 7 %, compared with that of the physical similarity method, indicating the potential of the proposed regionalization method in estimating catchment-wide sediment load in ungauged catchments. The findings indicate that the SRS method ideally determines the similarity of sediment loads between gauged and ungauged catchments. The SRS approach effectively tackled the main challenge of selecting catchment attributes in the conventional regionalization method and minimizing the uncertainty of sediment prediction in ungauged catchments. This novel SRS method is a promising method for estimating, not only sediment load, but also other hydrological variables and rainfall-driven phenomena in the ungauged catchments globally. [ABSTRACT FROM AUTHOR]

• Meadow tends to retain infiltration at the surface soil due to mattic epipedon. • Hillslope sites affect infiltration partitioning by influencing soil properties. • The quantitative indices improve our understanding of infiltration partitioning. Infiltration process controls how rainfall is stored in soil and subsequently used by plants, thus, plays a critical role in eco-hydrological processes. However, the vertical pattern of infiltration partitioning within a soil profile and the factors that control it remain poorly understood, especially in data-scarce mountainous areas. Based on a large-scale long-term soil moisture (SM) network in the Qilian Mountains, Northwest China, we explored infiltration partitioning and its control factors using a new metric, percentage of soil water storage increment in each layer to the soil profile during a rainfall infiltration event (PSTI). We found that both vegetations with deep roots and wet SM conditions facilitated infiltration into the deeper soil, although meadow favored infiltration within the surface layer. Hillslope stations showed a higher degree of infiltration partitioning in subsurface layers than the flatland stations due to the influence of topography on soil properties. Meanwhile, the increasing slope gradient will reduce the partition of infiltration at the subsurface layers. Among the soil properties, sand content, soil organic carbon, α (parameter of soil retention curve), and soil saturated hydraulic conductivity promoted infiltration into greater depth, while clay content and bulk density had the opposite effect. The major factors controlling the pattern of infiltration partitioning were n (parameter of soil retention curve) for 0–10 cm depth, α for 10–20 cm and 20–30 cm depths, and SM for PSTI below 30 cm. This quantitative analysis method for the infiltration partitioning improves our understanding of infiltration regimes, and supports water resources management in dryland mountains. [ABSTRACT FROM AUTHOR]

• Root water uptake of winter wheat across distinct rainfall years was quantified by using stable isotope. • Precipitation years led to significant differences in the isotopic signatures. • The appropriate irrigation wetting depth should be set as<60 cm for all kinds of rainfall years. Quantifying water availability in different soil layers to crop root water uptake (RWU) in different rainfall years helps deliver strategies to combat water scarcity and improve water productivity. To investigate the responses of RWU to soil water availability across distinct rainfall years, a field experiment of winter wheat was conducted in 2017–2018 (wet year), 2018–2019 (dry year), and 2019–2020 (ordinary year) in the North China Plain. Stable isotopes (δ18O and δD) in precipitation, irrigation water, xylem water, and soil water, as well as soil water content (SWC), were investigated during the three wheat growth seasons and were used to determine the soil water evaporation line (SWEL: the linear relationship between δD and δ18O in soil water), the line-conditioned excess (lc-excess: the deviation between δD and the local meteoric water line in the dual-isotope space) and the proportion of RWU from different soil layers with the MixSIAR model. The results indicated that there were significant differences in δ18O and δD in soil water and xylem water across different rainfall years. The slopes of SWEL and lc-excess of the 0–100 cm soil layer in the dry year were significantly smaller than those in the ordinary and wet years, which suggests that more substantial soil evaporation occurred in the dry year. The MixSIAR results revealed that the three-year wheat RWU exhibited different patterns, which were related to soil water availability. Wheat mainly utilized soil water from the 0–20 cm and 20–60 cm layers during the greening to filling stage under the dry year, while it mainly utilized the 0–20 cm soil layer under the wet and ordinary years. However, at the harvest stage, wheat under all precipitation years could transfer its main RWU zone to the 20–60 cm soil layer. There were significantly different proportions of RWU from 0 to 60 cm under different rainfall years, shown as 75.3 %, 67.5 %, and 69.5 % in the wet year, dry year, and ordinary year, respectively. These findings indicated that the appropriate irrigation wetting depth should be set as<60 cm for all kinds of rainfall years. [ABSTRACT FROM AUTHOR]

• Reduced natural rainfall led to a downgrade of soil moisture and groundwater. • Soil water movements were affected by land use and rainfall events. • Shallow groundwater variations depicted ecological water utilization in check dams. • Processes from rainfall to shallow groundwater were constructed in check dams. Stable regional water resource distribution is essential for ecosystems, yet soil water dynamics and groundwater evolutions of check dams remain many uncertainties under natural rainfall reduction in semi-arid areas. To explore these changeable hydrologic processes, continuous fixed-point observation and water balance models were introduced in nearly-four consecutive hydrological years (2018–2021). The results showed that soil water storage presented a downward fluctuation in each soil layer of all land uses. Moreover, the grassland profile moisture descended slowly and had deeper infiltration depths than others, which might be an ideal land-use type for the reservoir's sustainable utilization in check dams. The results also indicated that surface soil moisture (<50 cm) could rapidly respond to a single rainfall event > 10 mm d−1, whereas deep soil moisture (>50 cm) and shallow groundwater fluctuations were mainly affected by annual cumulative precipitation. Furthermore, a conceptual hydrological model of rainwater falling to the ground, percolating through soil profiles, and reaching groundwater through different vegetation covers in check dams has been proposed. Soil infiltration rates varied under different land use types and depths, ranging from 0.82 to 3.47 cm h−1. The groundwater recharge time from accumulated annual rainfall was 69–250 days, whereas the discharge time due to vegetation water consumption and groundwater lateral movement was 66–774 days. With a decrease in annual rainfall, the recharge time gradually increased, whereas the discharge time gradually decreased. These results inaugurate new perspectives for a deeper understanding of ecohydrological equilibrium in check dams and provide theoretical insights into ecological restoration in semi-arid areas. [ABSTRACT FROM AUTHOR]

• Developed computationally efficient three new variants of the CN model. • Introduced flexible initial abstraction to avoid sudden jumps in runoff estimation. • New weighted score-based statistical indicators for the models' evaluation. • The proposed models outperformed in almost all watersheds. The globally adopted and computationally efficient curve number (CN) model fills an active hydrological professional niche and has a well-documented history. However, it is structurally inconsistent and fails to reliably estimate runoff from rainfall. This is mainly due to the much-debated fixed initial abstraction (λ) and associated sudden jumps in runoff based on CN obtained from the documented tables. In this study, three new variants (M4, M5, M6) of the CN model are proposed that consider the hydrological imbalance between pre-storm soil moisture and initial abstraction after a rainfall event. A total of 1837 rainfall-runoff events were analyzed from 41 steep-slope watersheds in South Korea to test the robustness of the proposed CN models. The results were compared to the recently updated original CN model (M1) and two other recent variants (M2, M3) of this model. These models were evaluated using root mean squared error (RMSE), Nash-Sutcliffe efficiency (NSE), percent bias (PB), Kling-Gupta efficiency (KGE), a proposed overall weighted score, 1:1 line graph, and the FITEVAL tool. Using data from 41 watersheds, the lowest mean (median) RMSE of M5, M6, M4 [15.54(16.56), 15.84(11.45), 18.00(16.56)], PB for M4, M6, M5 [−1.28(−1.03), 1.29(0.03), −7.06(−7.27)]; the highest mean (median) NSE for M5, M6, M4 [0.86(0.87), 0.85(0.87), 0.81(0.83)], KGE for M6, M5, M4 [0.81(0.84), 0.79(0.81), 0.79(0.81)] and other graphical assessments show a better agreement between the observed and the runoff estimated by the proposed models. The corresponding mean (median) of RMSE, PB, NSE, and KGE statistics for M2 [19.26(17.69), 9.50(10.34), 0.78(0.80), 0.77(0.79)], and M3 [19.99(18.47), 05.56(7.17), 0.76(0.79), 0.77(0.79)] models show comparatively inferior results. Based on the same statistics, the M1 [24.60(22.48), 33.62(32.77), 0.63(0.68), 0.60(0.64)] model yields unrealistic results. It is inferred that both λ and CN should be kept flexible for a systematic and region-specific revision of the CN model to improve runoff estimation. In addition, a structurally consistent model with a stable soil moisture accounting (SMA) procedure is vital to get more reliable runoff estimates without compromising the simplicity and applicability to ungauged watersheds. [ABSTRACT FROM AUTHOR]

The accurate estimation of rainfall from remote sensing is of paramount importance for many applications as, for instance, the mitigation of natural hazards like floods, droughts, and landslides. Traditionally, microwave observations in the frequency between 10 and 183 GHz are used for estimating rainfall based on the direct interaction of radiation with the hydrometeors within precipitating clouds in a so-called top-down approach. Recently, a bottom-up approach was proposed that uses satellite soil moisture products derived from microwave observations (<10 GHz) for the estimation of accumulated rainfall amounts. The integration of the bottom-up and top-down approaches has large potential for providing high accurate rainfall estimates exploiting their different and complementary nature. In this study, we perform a long-term (3 years) assessment of different satellite rainfall products exploiting the full range of microwave frequencies over Italy. Specifically, the integration of two top-down algorithms (CDRD, Cloud Dynamics and Radiation Database, and PNPR, Passive microwave Neural network Precipitation Retrieval) for estimating rainfall from conically and cross-track scanning radiometers, and one bottom-up algorithm (SM2RAIN) applied to the Advanced SCATterometer soil moisture product is carried out. The performances of the products, individually and merged together, are assessed at daily time scale. The integration of top-down and bottom-up approaches provides the highest performance both in terms of continuous and categorical scores (i.e., median correlation coefficient and root mean square error values equal to 0.71 and 6.62 mm, respectively). In such a combination, the limitations of the two approaches are compensated allowing a better estimation of ground accumulated rainfall through SM2RAIN while, overcoming the limitations of rainfall estimation for intense events during wet conditions through CDRD-PNPR product. The accuracy and the reliability of the merged product open new possibilities for their testing in hydrological applications, such as the monitoring and prediction of floods and droughts over large areas, including regions where ground-based measurements are sparse or not available. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) is an essential climate variable of greater relevance in the monsoon scenario, hence validation and understanding of its spatio-temporal variability over the Indian region is of high significance. In the present study, five SM products are evaluated against in situ SM measurements conducted by India Meteorological Department and the selected data product is used for spatio-temporal characterization of SM in relation to monsoon rainfall. The data products evaluated are: European Space Agency’s merged satellite SM, Modern-Era Retrospective analysis for Research and Applications (MERRA) Land SM, ECMWF’s ERA interim SM, Climate Forecast System Reanalysis SM, and Global Land Data Assimilation System Noah Land Surface Model SM. Comparisons show that seasonal SM patterns in all products generally follow the characteristics of rainfall, even though there are certain differences in details. The statistical estimates indicate fairly good agreement between in situ and the five products, with some variations among them and over the homogeneous rainfall regions. On comparison, MERRA SM is found appropriate for further analyses on spatio-temporal characteristics, which are then carried out with the 20 year (1993–2012) SM data. Stability analyses revealed SM patterns indicative of relative SM variability as well as persistence. The spatial stability analysis depicts dry and wet patterns and their seasonal variations over different geographical locations in relation to all India spatial average. Large temporal variations are found over central, western and northern Indian regions caused by large intraseasonal variability in rainfall. In brief, intraseasonal and interannual soil moisture variations broadly follow the rainfall pattern, with long-term influences attributed to SM memory effects. The soil moisture persistence and dominant scales of variability are explored with autocorrelation and wavelet transform techniques. Seasonal persistence is large over regions receiving excessive rainfall, while drought years are noted to have large intraseasonal SM persistence compared to that of surplus year. Wavelet decomposition demonstrates that low periodicity (2–10 days) SM modes match that of rainfall during initial periods of monsoon. The occurrence of significant higher periodicity modes are dominant in drought years compared to surplus, which also vary with geographical locations. [ABSTRACT FROM AUTHOR]

Summary Landslides are frequent and widespread geomorphological phenomena causing loss of human life and damage to property. The main tool for assessing landslide risk relies on rainfall thresholds and thus, many countries established early warning systems aimed to landslide hazard assessment. The Umbria Region Civil Protection Centre developed an operational early warning system for landslide risk assessment, named PRESSCA, based on the soil saturation conditions to identify rainfall thresholds. These thresholds, currently used by the Civil Protection operators for the day-by-day landslide hazard assessment, provided satisfactory results with more than 86% of the landslides events correctly identified during the period 1990–2013. In this study, the PRESSCA system was employed for the assessment of climate change impact on landslide hazard in Central Italy. The outputs of five different Global Circulation Models (GCMs) were downscaled and weather generators were used for obtaining hourly rainfall and temperature time series from daily GCMs projection. Then, PRESSCA system was employed to estimate the number of landslide occurrence per year. By comparing results obtained for three different periods (1990–2013 (baseline), 2040–2069 and 2070–2099), for the Umbria territory a general increase in events occurrence was expected (up to more than 40%) in the future period, mainly during the winter season. The results also revealed that the effect of climate change on landslides was not straightforward to identify and the close interaction between rainfall magnitude/intensity, temperature and soil moisture should be analysed in depth. Overall, soil moisture was projected to decrease throughout the year but during the wet season the variations with respect to the present period were very small. Specifically, it was found that during the warm-dry season, due to the strong decrease of soil moisture, even for a sensible increase in rainfall intensity, the landslide occurrence was unchanged. Conversely, during the cold-wet season, the number of landslide events increased considerably if a positive variation in rainfall amount, more significant than rainfall intensity, was coupled with small negative variations in soil moisture. [ABSTRACT FROM AUTHOR]

Summary Lake Chad has recently been perceived to be completely desiccated and almost extinct due to insufficient published ground observations. Given the high spatial variability of rainfall in the region, and the fact that extreme climatic conditions (for example, droughts) could be intensifying in the Lake Chad basin (LCB) due to human activities, a spatio-temporal approach to drought analysis becomes essential. This study employed independent component analysis (ICA), a fourth-order cumulant statistics, to decompose standardised precipitation index (SPI), standardised soil moisture index (SSI), and terrestrial water storage (TWS) derived from Gravity Recovery and Climate Experiment (GRACE) into spatial and temporal patterns over the LCB. In addition, this study uses satellite altimetry data to estimate variations in the Lake Chad water levels, and further employs relevant climate teleconnection indices (El-Niño Southern Oscillation-ENSO, Atlantic Multi-decadal Oscillation-AMO, and Atlantic Meridional Mode-AMM) to examine their links to the observed drought temporal patterns over the basin. From the spatio-temporal drought analysis, temporal evolutions of SPI at 12 month aggregation show relatively wet conditions in the last two decades (although with marked alterations) with the 2012–2014 period being the wettest. In addition to the improved rainfall conditions during this period, there was a statistically significant increase of 0.04 m/yr in altimetry water levels observed over Lake Chad between 2008 and 2014, which confirms a shift in the hydrological conditions of the basin. Observed trend in TWS changes during the 2002–2014 period shows a statistically insignificant increase of 3.0 mm/yr at the centre of the basin, coinciding with soil moisture deficit indicated by the temporal evolutions of SSI at all monthly accumulations during the 2002–2003 and 2009–2012 periods. Further, SPI at 3 and 6 month scales indicated fluctuating drought conditions at the extreme south of the basin, coinciding with a statistically insignificant decline in TWS of about 4.5 mm/yr at the southern catchment of the basin. Finally, correlation analyses indicate that ENSO, AMO, and AMM are associated with extreme rainfall conditions in the basin, with AMO showing the strongest association (statistically significant correlation of 0.55) with SPI 12 month aggregation. Therefore, this study provides a framework that will support drought monitoring in the LCB. [ABSTRACT FROM AUTHOR]

Knowledge of soil water percolation below the rooting zone and its responses to the dynamic interactions of different factors are important for the control of non-point source pollution. Based on 3600 scenarios in Hydrus-1D simulation, this study revealed the integrated effects of rainfall characteristics (rainfall amount, maximum rainfall intensity or MRI, time distribution characteristics of rainfall or TDC), antecedent moisture and the season on deep percolation (DP) at a forest site in Taihu Lake Basin, China. Results showed that Hydrus-1D model can well simulate the soil water dynamics at this site. Antecedent moisture had the greatest relative contribution to DP (85.7%), followed by rainfall amount (10.9%) and MRI (3.4%). As the antecedent moisture increased, the relative contribution of the season on DP increased from 0.0% to 16.4%. In comparison, that of MRI decreased from 58.7% to 38.5% and that of rainfall amount followed a bell shape pattern (greatest when the antecedent moisture was 0.26 m 3 m −3 ). The relative contribution of antecedent moisture to DP in summer was the greatest (87.8%), while that of the rainfall was the least. The TDC influenced DP by affecting the responses of DP to other factors. When the rainfall amount was ⩾80 mm and the antecedent moisture content was ⩾0.34 m 3 m −3 , effect of TDC on DP could be observed. The DP of TDC_B (rainfall intensity linearly increased with time) was the lowest, while that of TDC_E (rainfall intensity kept constant with time) was the greatest. Findings of this study have practical significance for investigating the water and pollutant transport in vadose zone. [ABSTRACT FROM AUTHOR]

Summary This paper examines the combination of support vector machines (SVM) and the dual ensemble Kalman filter (EnKF) technique to estimate root zone soil moisture at different soil layers up to 100 cm depth. Multiple experiments are conducted in a data rich environment to construct and validate the SVM model and to explore the effectiveness and robustness of the EnKF technique. It was observed that the performance of SVM relies more on the initial length of training set than other factors (e.g., cost function, regularization parameter, and kernel parameters). The dual EnKF technique proved to be efficient to improve SVM with observed data either at each time step or at a flexible time steps. The EnKF technique can reach its maximum efficiency when the updating ensemble size approaches a certain threshold. It was observed that the SVM model performance for the multi-layer soil moisture estimation can be influenced by the rainfall magnitude (e.g., dry and wet spells). [ABSTRACT FROM AUTHOR]

• Global temperature change vs moisture deficit studied for number of hot days (NHD). • The area where deficient moisture impacts NHD more than rising temperature is larger. • Temperature-sensitive regions are located in mountain ranges, plateaus, and deserts. • Soil moisture deficit-sensitive regions have strong land–atmosphere coupling. • Wavelet decomposition improves GRACE TWS for examining moisture-temperature coupling. This study compares the relative importance of global temperature change and local moisture deficit in influencing the frequency of hot extremes on a global scale. For the first time, the wavelet decomposed GRACE terrestrial water storage is applied in examining the relationship between soil moisture (θ) and the number of hot days in the hottest month (NHD). It reveals stronger θ-NHD relationships over larger areas than the selected commonly used soil moisture proxies (i.e., standardised precipitation index and a GLDAS model-derived product). During 1985–2015, local moisture deficit played a more important role in influencing hot extreme occurrences in the regions with relatively flat topography, thick soil and where inter-annual rainfall variability is large. They cover an area 1.6 times larger than the areas (e.g., mountain ranges, deserts) where the global temperature change has posed a stronger influence. Under a continuing increase of greenhouse gas forcing, global actions in reducing emissions will support combating the expansion of hot extremes. However, this study shows that necessary attention should also be directed to mitigating the moisture deficit exacerbating hot extremes, e. g., through regional adaptive land management. [ABSTRACT FROM AUTHOR]

• Hydrologic functions of vegetation in karst regions still need to be enhanced. • Thinning alone increased SSWC and released water limitation on woody species. • We provided a testable path for enhancing hydrologic functions of karst vegetation. The use of plantations and natural restoration enhance vegetation coverage and contribute significantly to the hydrologic functions of degraded terrestrial ecosystems. Researchers have investigated the development and use of plantations, however, few studies looked at naturally-restored vegetation, especially for early successional areas. We applied a series of treatments and their impacts on water status and the dominant woody species were monitored. Our goal is to enhance the hydrologic functions of naturally-restored karst vegetation that stagnated as early successional shrubby-grassland. Our results show that vegetation on both the upper and lower slopes intercepted approximately 50 % of the rainfall because of the dense community structure. With more than 60 % of the community-level root biomass concentrated in the upper 20 cm soil depth, shallow soil water content (SSWC) decreased continuously even when there was scattered light rain events. On the lower slopes, competition-reducing oriented removal of non-woody species significantly reduced canopy interception of water, which contributed to the increase of SSWC and water availability for the remaining dominant woody species. Moreover, dominant woody species in the treated plot exhibited more negative leaf carbon isotope values than the same species in the control plot, indicating released water limitation on plant growth because of the treatment. On the contrary, this treatment exhibited negligible effects on SSWC on the upper slope, environmental water status could only be improved by improving soil water storage capacity. Our results highlight strong competition on SSWC for naturally-restored vegetation on karst hillslopes that stagnated during the early successional stages. In lower slope position where soil is relatively deep, competition-reducing oriented treatment alone can release water limitations on plant growth and provide opportunities for the settlement of species with different hydrologic niches, thus providing a path for enhancing hydrologic functions of naturally-restored karst vegetation. [ABSTRACT FROM AUTHOR]

• The PF contributed to the total infiltration was >50% • The control mechanisms of temporal and small-scale spatial characteristics on different types of preferential flow processes were clarified. • Environmental characteristics differed between two types of preferential flow. • The two types of preferential flow affected soil moisture parameters differently. The control mechanisms of temporal and small-scale spatial characteristics on different types of preferential flow (PF) processes during infiltration are still lacking. Two-year high-resolution in situ soil moisture profiles were used to investigate the controls of PF processes and its interaction with moisture and vegetation dynamics, which covers three hillslope positions (upslope–14˚, midslope–9˚, and downslope–4˚) and three vegetation treatments (bare ground, stubble grassland and natural grassland) in a typical semi-arid grassland of Eurasia. Two types of PF were identified. Non-sequential response (NSR) was taken as one indication of PF using the disordered response of soil moisture profiles to rainfall. Fast preferential flow in sequence response (PF-rate) was taken as another indicator when a measured maximum pore water rate higher than saturated hydraulic conductivity. The conditions for the occurrence of the two PFs were inconsistent and different from the studies which showed the higher probability of PFs under dryer conditions and with higher rainfall intensities. Small rainfall events with low rainfall intensity and relatively low soil moisture at most locations showed higher NSR frequency, which further highlight the strong dependence of NSR on hydrophobicity and macropore structure of the topsoil. Whereas a higher rainfall intensity increased PF-rate under wet conditions. Meanwhile, the occurrence of PF-rate was also significantly controlled by vegetation coverage, soil texture and saturated hydraulic conductivity of 5–10 cm soil layer. Furthermore, the frequency of PF was 15.9%–44.5%, and its contribution to the total infiltration was >50%. The water recession rate of NSR and PF was slower and faster than that of matrix flow, respectively. This demonstrates the importance of PF to water replenishment in scarce rain areas and the influence of combinations of spatial–temporal factors on different flow processes. [ABSTRACT FROM AUTHOR]

[Display omitted] • SM2RAIN-NWF is developed through substituting the net water flux model. • Performance of SM2RAIN-NWF algorithm was compared against SM2RAIN. • Results showed the better performance of SM2RAIN-NWF algorithm compared to SM2RAIN. • The quality of soil moisture data impact on the performance of the algorithm. Sparse distribution of rain gauge networks challenges the estimation of rainfall variability over space and time. The SM2RAIN algorithm was developed to estimate rainfall from the knowledge of soil moisture (SM) by inverting the soil‐water balance equation. The algorithm was simplified by neglecting the contribution of evapotranspiration and surface runoff rate during the rainfall event. A recent study developed an analytical model to estimate the net water flux (NWF) from SM data via inversion of analytical Warrick's equation. In this study, the SM2RAIN-NWF algorithm was developed by integrating the SM2RAIN algorithm and the NWF model to improve the accuracy of rainfall estimation. The applicability of the SM2RAIN-NWF algorithm was evaluated based on observed rainfall data in the Lake Urmia basin, Iran. Satellite SM data was obtained from the Advanced Microwave Scanning Radiometer 2 (AMSR2). The algorithm calibrated based on the data from July 3, 2012, to December 31, 2017, was then used to estimate rainfall for two years extending from January 2018 to December 2019. Estimated rainfall through SM2RAIN-NWF algorithm improved compared to SM2RAIN by 14% and 37.4% increase in the average values of correlation coefficient (R) and Nash–Sutcliffe (NS), and 11.5% decrease in the Percentage Root Mean Square Error (PRMSE) over the calibration period. Validating the estimated rainfall showed a considerable improvement in the performance of the SM2RAIN-NWF algorithm compared to the SM2RAIN algorithm by 8.6% and 30.4% increase in the average values of R and NS, and 13.4% decrease in the PRMSE. It was also found that the SM2RAIN-NWF algorithm contributes to the improvement of error indices in rainfall estimation and simulates the rainfall variation trend in a better fashion than the SM2RAIN algorithm. [ABSTRACT FROM AUTHOR]

Summary The response of soil moisture to rainfall events along hillslope transects is an important hydrologic process and a critical component of interactions between soil vegetation and the atmosphere. In this context, the research described in this article addresses the spatial distribution of soil moisture as a function of topography. In order to characterize the temporal variation in soil moisture on a steep mountainous hillside, a transfer function, including a model for noise, was introduced. Soil moisture time series with similar rainfall amounts, but different wetness gradients were measured in the spring and fall. Water flux near the soil moisture sensors was modeled and mathematical expressions were developed to provide a basis for input–output modeling of rainfall and soil moisture using hydrological processes such as infiltration, exfiltration and downslope lateral flow. The characteristics of soil moisture response can be expressed in terms of model structure. A seasonal comparison of models reveals differences in soil moisture response to rainfall, possibly associated with eco-hydrological process and evapotranspiration. Modeling results along the hillslope indicate that the spatial structure of the soil moisture response patterns mainly appears in deeper layers. Similarities between topographic attributes and stochastic model structures are spatially organized. The impact of temporal and spatial discretization scales on parameter expression is addressed in the context of modeling results that link rainfall events and soil moisture. [ABSTRACT FROM AUTHOR]