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• 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]

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]

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]

• 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]

Summary: Soil moisture is an important variable in the hydrological cycle and plays a vital role in agronomy, meteorology, and hydrology. It regulates the exchange of water and heat between land surface and atmosphere and thus plays an important role in the development of weather patterns. It is difficult to obtain a comprehensive spatio-temporal map of soil moisture because of expensive installation of soil moisture measuring instruments. In this paper, a model to estimate soil moisture (ms ) using Tropical Rainfall Measuring Mission Precipitation Radar (TRMMPR) backscatter (σ°) and Normalized Difference Vegetation Index (NDVI) is developed for the Southern United States. Soil moisture data from Soil and Climate Analysis Network (SCAN) stations is used to calibrate and validate the model. The estimated values of ms compare well with the ground measurements of soil moisture. The model works well for various landcovers but works best for low density vegetated areas (closed shrubland). All the soil moisture estimates in this landcover have an absolute error of less than 8%. The model performance deteriorates with increase in vegetation density (crops and forest). Overall, the model performance is satisfactory for all landcover types with RMSE less than 6.3% and absolute error of 10% or less for 90% of the estimates. Estimation of soil moisture over a large area with low error provides another use of TRMMPR data. [Copyright &y& Elsevier]

Summary: Large-scale vegetation restoration has been helpful to prevent serious soil erosion, but also has aggravated water scarcity and resulted in soil desiccation below a depth of 200cm in the Loess Plateau of China. To understand the dynamic mechanism of soil desiccation formation is very important for sustainable development of agriculture in the Loess Plateau. Based on natural and simulated rainfall, the characteristics of soil water cycle and water balance in the 0–400cm soil layer on a steep grassland hillslope in Changwu County of Shaanxi Loess Plateau were investigated from June to November in 2002, a drought year with annual rainfall of 460mm. It was similarly considered to represent a rainy year with annual rainfall of 850mm under simulated rainfall conditions. The results showed that the temporal variability of water contents would decrease in the upper 0–200cm soil layer with the increase in rainfall. The depth of soil affected by rainfall infiltration was 0–200cm in the drought year and 0–300cm in the rainy year. During the period of water consumption under natural conditions, the deepest layer of soil influenced by evapotranspiration (ET) rapidly reached a depth of 200cm on July 21, 2002, and soil water storage decreased by 48mm from the whole 0–200cm soil layer. However, during the same investigation period under simulated rainfall conditions, soil water storage in the 0–400cm soil layer increased by only 71mm, although the corresponding rainfall was about 640mm. The extra-simulated rainfall of 458mm from May 29 to August 10 did not result in the disappearance of soil desiccation in the 200–400cm deep soil layer. Most infiltrated rainwater retained in the top 0–200cm soil layer, and it was subsequently depleted by ET in the rainy season. Because very little water moved below the 200cm depth, there was desiccation in the deep soil layer in drought and normal rainfall years. [Copyright &y& Elsevier]

Summary: For many good and practical reasons, lumped rainfall–runoff models are widely used to represent a catchment’s response to rainfall. However, they have some acknowledged limitation, some of which are addressed here using a neuro-fuzzy model to combine, in an optimal way, a number of lumped-sub-models. For instance, to address temporal variation, one of the sub-models in the combination may perform well under flood conditions and another under drier conditions and the neuro-fuzzy system would combine their outputs for each time-step in a manner depending on the prevailing conditions. Similarly to address spatial variation, one of the sub-models may perform well for the upland parts of the catchment and another for the lowland parts and again the neuro-fuzzy system is expected to combine the different outputs appropriately. The proposed combination method can use any lumped catchment model, but has been tested here with the simple linear model (SLM) and the soil moisture and accounting routing (SMAR) models. Eleven catchments with different hydrological and meteorological conditions have been used to assess the models with respect to temporal variations in response while one catchment is used to address the effect of spatial variation. The neuro-fuzzy combined-sub-models of SLM and SMAR modelled the temporal and spatial variation in catchment response better than the lumped version of each model. Also the SMAR model significantly outperformed the SLM either as a lumped model or as a sub-model in any of the combinations. [Copyright &y& Elsevier]

Abstract: The first part of this two-part paper demonstrated the feasibility of the direct use of data from a high resolution (25km) Regional Climate Model (RCM) to provide inputs for a rainfall-runoff model, in order to obtain estimates of flood frequency. This paper uses data from a climate change experiment with the same RCM (HadRM3H) to provide estimates of change in flood frequency between the 1970s and 2080s, for 15 catchments across Great Britain. This experiment is a rerun, at twice the horizontal resolution, of one of those used by the UK Climate Impacts Programme (UKCIP) in the construction of its UKCIP02 climate change scenarios for the UK. It thus allows an exploration of the implication of these scenarios using a resolution more suited to the detailed hydrological application addressed in this paper. Despite decreases in annual average rainfall in all but one catchment, eight show an increase in flood frequency at most return periods whereas two show substantial decreases. As part I of this paper showed a distinct positive correlation between errors in annual rainfall and errors in flood frequency, the fact that flood frequency can increase despite an overall decrease in rainfall implies a marked change in the distribution of rainfall, either in terms of the probability of rainfall events and/or its seasonal cycle. Decreases in flood peaks are shown for a number of the catchments in the south and east of England, despite an increase in winter mean and extreme rainfall. Increased summer and autumn soil moisture deficits are thought to be the reason for this. Other catchments, further north or west, show an increase in flood peaks, in some cases of over 50% at the 50-year return period. Care needs to be taken when interpreting these results, as they are based on a single RCM experiment (using driving data from one GCM under a single emissions scenario). Other RCM experiments may give quite different results, and ensemble runs would ideally be required to limit sample error. [Copyright &y& Elsevier]

• Australian Landscape Water Balance model is used to evaluate hydrologic trends. • Trends in modelled streamflow are evaluated against observed streamflow. • Rainfall, soil moisture, and streamflow trends are consistent with tropical expansion. • Changes in flood and drought are linked to mean rainfall changes at continental scale. • Trends are more likely to be driven by local factors at the catchment scale. Changes in the hydrologic cycle have far reaching impacts on agricultural productivity, water resources availability, riverine ecosystems, and our ability to manage environmental assets, bushfire risk, and flood hazard. For example, declining rainfall in the southeast of Australia has led to a prolonged period of drought, with serious impacts on agriculture, the environment, and water supply to urban and rural towns. Here, using the continental wide Australian Water Resources Assessment Landscape model (AWRA-L), we evaluate historical trends from 1960 to 2017 in rainfall, soil moisture, evapotranspiration, and runoff to explain changing drought and flooding. Northern parts of Australia have experienced increasing annual rainfall totals, resulting in increased water availability in the tropics with increased soil moisture, evapotranspiration, and runoff, particularly during the hot, wet monsoon season. In contrast, the southwest and southeast coast of Australia have experienced declines in rainfall, particularly in the colder months, corresponding with decreasing evapotranspiration, soil moisture, and runoff. Trends in flooding are aligned with runoff trends, and closely follow trends in rainfall, with changes in soil moisture of secondary influence. Streamflow droughts, measured by the standardised runoff index, are increasing across large parts of Australia, with these increases more widespread than changes in rainfall alone. Increases in rainfall in the tropics of northern Australia appear to be related to decreasing drought occurrence and extent, but this trend is not universal, suggesting changes in rainfall alone are not an indicator of changing drought conditions. [ABSTRACT FROM AUTHOR]

• Infiltration is directly affected by soil moisture, rather than rainfall duration. • Horton infiltration equation is improved by adopting soil moisture variation. • Improved equation is better in simulation performance and uncertainty intervals. Soil water infiltration simulation is a subject receiving great interest in hydrological cycle modelling. The traditional Horton equation is based on the curve of infiltration capacity-rainfall duration time. However, the infiltration process is directly affected by soil moisture content, rather than rainfall duration. The objective of this study was to determine a relationship between infiltration capacity and soil moisture content in order to improve the Horton infiltration equation. Artificial rainfall-infiltration experiments were used to determine a series of power functions. The improved equation was cross-validated with observations from 32 experiments of multiple rainfall intensities and antecedent soil moisture. The simulation performance and uncertainty of the improved equation were compared with those of the original Horton equation to verify its accuracy. The results showed that infiltration rate decreases nonlinearly as soil moisture increases, and finally approaches a stable infiltration rate when the soil is saturated. Overland flow simulations by the improved Horton equation closely matched the observations from all 32 experiments over a soil moisture range of 0.222–0.349 m3/m3. The simulation performance was rated as good for most of the experiments for both the calibration and validation data sets. Compared with the original Horton equation, the simulation performance of the improved equation clearly improved estimation of infiltration, particularly as quantified by the Nash-Sutcliffe efficiency coefficient (NSE) and the coefficient of determination (R 2). The number of simulations with NSE values greater than 0.65 increased 11.59% and 2.50% for the calibration and validation data sets, respectively. The number of simulations with R2 values greater than 0.90 increased 31.14% and 22.50%, respectively. The uncertainty intervals of the improved Horton equation became a little greater than those of the original Horton equation. For all 32 experimental simulations, the average relative length of the uncertainty interval at the 95% confidence level increased from 40.52% with the original Horton equation to 49.17% with the improved Horton equation. The number of observations falling within the 95% confidence interval increased from 92.13% to 95.94% with the improved Horton equation. Most of the observations were accurately simulated using the improved Horton equation. The greatest improvements in simulating overland flow were seen for the experiments with low flow simulations. The study results provide insights into soil infiltration mechanisms, and also provide references to support improved infiltration simulation by considering soil moisture variation. [ABSTRACT FROM AUTHOR]

• Subsurface runoff was generated by the "fill and spill" mechanism. • Overland flow generation via an "infiltration-excess and saturation-excess" mechanism. • Steady infiltration rate of the epikarst was determined (40 mm/h). • A conceptual model to describe the runoff generation on karst slope was developed. Southwest China receives abundant rainfall with a mean annual precipitation of 1450 mm (1960–2013) but surface runoff is small, whereas subsurface runoff is relatively large on karst hillslopes. However, not enough studies have been done to investigate the mechanisms of surface and subsurface runoff generation in subtropical karst landscapes. Here we report the dynamics of soil water content (SWC), instantaneous water levels at the soil-epikarst interface (SEI), and runoff characteristics related to the mechanisms of near-surface runoff generation at the slope scale (5 m × 20 m). Four field rainfall simulation experiments were conducted with rainfall intensities ranging from 35 to 136 mm h - 1 . Subsurface saturation started first at the relatively flat lower slope, and then extended up slope. Subsurface runoff began after subsurface saturated areas connected to each other, representing a "fill-and-spill" mechanism. Surface runoff, which mainly developed after instantaneous water levels reached near the surface, represents an " infiltration-excess and saturation-excess " runoff mechanism, where two thresholds must be attained: rainfall amount and intensity. The rainfall amount threshold is dependent on soil water deficit, water capacity of the epikarst-surface depression at the SEI, and deep percolation from SEI. The rainfall intensity threshold must be larger than the steady infiltration rate of SEI, which is the prerequisite for the saturation of the epikarst-surface depression and soil layer. Steady SEI infiltration rate was estimated (40 mm h - 1 ) according to the surface runoff generation mechanism. This parameter is important as it represents the lower boundary condition in modeling hillslope hydrological processes. Rainfall-runoff thresholds for surface and subsurface runoff decrease with increasing rainfall intensity. Overall, our results show that epikarst permeability along karst hillslopes is relatively high, being the main factor controlling surface and subsurface runoff generation. Therefore, epikarst permeability significantly affects near-surface hydrological processes in karst landscapes. Our data contribute to a more comprehensive understanding of runoff generation processes and water cycle in the critical zone. [ABSTRACT FROM AUTHOR]