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A stochastic model of rainfall rate is used to examine the temporal variability of rainfall during heavy convective rain periods. The model represents the microstructure of rainfall rate at time scales that are important for land surface processes associated with infiltration and runoff production. The representation of rainfall rate is based on a marked point process model of raindrop size distributions, which yields a gamma raindrop spectrum with parameters that are time-varying stochastic processes. Raindrop size distribution observations from a Joss-Waldvogel disdrometer in Princeton, New Jersey, during the period May-October 2006 are used along with the stochastic model to examine rainfall rate variability. Analyses focus on a sample of 60-min time periods in which heavy convective rainfall occurred. Central elements of the analyses entail examination of the relationships between rainfall rate and the time-varying model parameters that characterize the raindrop size distribution. We also examine the dependence structure among these processes. 'Scaling law' formulations of raindrop size distributions are used to examine variability of raindrop size distributions. Analyses of the Princeton heavy rainfall periods also point to seasonal and diurnal heterogeneities as important elements of the distribution of extreme rainfall rates. Convective intensity, as reflected in cloud-to-ground lightning observations, plays an important role in the distribution of extreme rainfall rates and the evolution of raindrop size distributions associated with heavy rainfall. [ABSTRACT FROM AUTHOR]

The temporal variability of rainfall and raindrop processes is examined at time scales ranging from less than 1 min to 1 hour. Raindrop processes are represented in terms of drop arrival rate, mean diameter, and coefficient of variation of drop diameter and modeled as time-varying stochastic processes. It is shown that rainfall rate and accumulated rainfall have simple and accurate representations in terms of raindrop processes. Using these results the temporal variability of rainfall rate is examined in terms of temporal variability of raindrop processes. It is shown that the temporal variability of rainfall rate varies systematically across a range of climatic settings and, more importantly, that these climatic contrasts in rainfall rate can be related to contrasting properties of raindrop processes. Two statistical models of rainfall rate and raindrop processes are examined in detail: a lognormal model with fixed parameters and a lognormal model with parameters that vary from storm to storm. Temporal correlation structure of rainfall rate exhibits qualitatively different behaviour under the two models. Lognormal models of rainfall rate are extended to models in which dependence on the averaging time interval is explicitly represented. Scale properties of rainfall rate are examined empirically for averaging time intervals ranging from 1 min to 30 min. Empirical analyses are based on drop-size data from North Carolina, New Jersey, Oregon, Alaska, and the Marshall Islands. [ABSTRACT FROM AUTHOR]

Rainfall is an important driver of erosion processes. The mean rainfall rate is often used to account for the erosive impact of a particular climate. However, for some erosion processes, erosion rate is a nonlinear function of rainfall, e.g., due to a threshold for erosion. When this is the case, it is important to take into account the full distribution of rainfall, instead of just the mean. In light of this, we have characterized the variability of daily rainfall over the Himalayan orogen using high spatial and temporal resolution rainfall data sets. We find significant variations in rainfall variability over the Himalayan orogen, with increasing rainfall variability to the west and north of the orogen. By taking into account variability of rainfall in addition to mean rainfall rate, we find a pattern of rainfall that, from a geomorphological perspective, is significantly different from mean rainfall rate alone. Using these findings, we argue that short-term rainfall variability may help explain observed short and long-term erosion rates in the Himalayan orogen. [ABSTRACT FROM AUTHOR]

A 29-storm sample of 1-minute rainfall rates was obtained with an Illinois network of 50 recording gages in 100 square miles during the warm seasons of 1952 and 1953. These gages were equipped with enlarged orifices and 6-hour charts to provide nearly instantaneous spatial patterns of rainfall intensity on the network. The data were used to determine quantitative estimates of rainfall rate gradients, sampling errors in the measurement of mean areal rates, and spatial correlation patterns. The derived relations are considered first approximations for midwestern warm-season storms. It was concluded that the spatial variability of rainfall rates is frequently so great within and between convective storms that the rain gaging equipment and operational requirements for accurate rate measurements may be prohibitive for most users when sampling areas are 100 square miles or greater. Consequently it is recommended that the use of radar in combination with recording gages be investigated as a possible solution to the measurement problem. [ABSTRACT FROM AUTHOR]

Estimates of 'macropore' soil water phenomena are calculated from a simple stochastic model of infiltration. Probability density functions (pdf) for cumulative infiltration ( I), infiltration rate ( I′), and infiltrating-water flux (ν) are proposed. Cumulative infiltration is defined here as the maximum quantity of water the soil can accept from unponded water supplied at a given location on the soil surface. Similarly, infiltration rate is defined as the maximum rate at which unponded water can enter the soil. The pdfs for cumulative infiltration ( fI) and infiltration rate ( fI′) are derived by assuming that the saturated hydraulic conductivity ( Ks) is a lognormal-distributed random variable. The actual infiltrating-water flux will depend on I′, rainfall rate ( R0), slope, and surface roughness. For a flat and smooth soil surface the pdf for infiltrating-water flux fν is derived from f I′, by assuming that water failing to infiltrate into portions of the soil with lower infiltration rates will flow over the soil surface, eventually being accepted by areas with higher infiltration rates. The pdf fν predicts that macropore soil water flow phenomena will become more pronounced as the rainfall rate approaches the mean infiltration rate, when macropore flux predicted by fν, is many times the rainfall rate. These results indicate that stochastic description of soil hydraulic properties shows promise in describing macropore soil water phenomena. Models of the field-scale effects of macropore soil water flow should include infiltration rate variability and runoff contributions to infiltrating-water flux. [ABSTRACT FROM AUTHOR]

Commercial microwave links (CMLs) have proven useful for providing rainfall information close to the ground surface. However, large uncertainties are associated with these retrievals, partly due to challenges in the type of data collection and processing. In particular, the most common case is when only minimum and maximum received signal levels (RSLs) over a given time interval (hereafter 15 min) are stored by mobile network operators. The average attenuation and the corresponding rainfall rate are then calculated based on a weighted average method using the minimum and maximum attenuation. In this study, an alternative to using a constant weighted average method is explored, based on a machine learning model trained to produce actual attenuation from minimum/maximum values. A rainfall retrieval deep learning model was designed based on a long short‐term memory (LSTM) model architecture and trained with disdrometer data in a form that is comparable to the data provided by mobile network operators. A first evaluation used only disdrometer data to mimic both attenuation from a CML and corresponding rainfall rates. For the test data set, the relative bias was reduced from 5.99% to 2.84% and the coefficient of determination (R2) increased from 0.86 to 0.97. The second evaluation used this disdrometer‐trained LSTM to retrieve rainfall rates from an actual CML located nearby the disdrometer. A significant improvement in the overall rainfall estimation compared to existing microwave link attenuation models was observed. The relative bias reduced from 7.39% to −1.14% and the R2 improved from 0.71 to 0.82. Plain Language Summary: A deep learning model was designed and trained using a disdrometer‐derived data set and further applied to retrieve rainfall from commercial microwave link data. This model showed significant improvements in rainfall estimation over a constant weighted average method. Key Points: A novel approach is proposed to estimate rainfall from only maximum and minimum attenuation data from microwave links using a deep learningThe RNN model trained and tested using disdrometer data outperformed existing rainfall estimation methods from microwave link attenuationThis disdrometer‐trained model also outperformed rainfall estimation methods when applied to Commercial Microwave Link data [ABSTRACT FROM AUTHOR]

We analyze flash flooding in small urban watersheds, with special focus on the roles of rainfall variability, antecedent soil moisture, and urban storm water management infrastructure in storm event hydrologic response. Our results are based on empirical analyses of high-resolution rainfall and discharge observations over Harry's Brook watershed in Princeton, New Jersey, during 2005-2006, as well as numerical experiments with the Gridded Surface Subsurface Hydrologic Analysis (GSSHA) model. We focus on two subwatersheds of Harry's Brook, a 1.1 km2 subwatershed which was developed prior to modern storm water management regulations, and a 0.5 km2 subwatershed with an extensive network of storm water detention ponds. The watershed developed prior to modern storm water regulations is an 'end-member' in urban flood response, exhibiting a frequency of flood peaks (with unit discharge exceeding 1 m3 s−1 km−2) that is comparable to the 'flashiest' watersheds in the conterminous U.S. Observational analyses show that variability in storm event water balance is strongly linked to peak rain rates at time intervals of less than 30 min and only weakly linked to antecedent soil moisture conditions. Peak discharge for both the 1.1 and 0.5 km2 subwatersheds are strongly correlated with rainfall rate averaged over 1-30 min. Hydrologic modeling analyses indicate that the sensitivity of storm event hydrologic response to spatial rainfall variability decreases with storm intensity. Temporal rainfall variability is relatively more important than spatial rainfall variability in representing urban flood response, especially for extreme storm events. [ABSTRACT FROM AUTHOR]

The current study investigates the variability of vertical structure of precipitation in the Huaihe River Basin (HRB) of China. The precipitation characteristics have been revealed by the long-term observations of vertical profile of reflectivity (VPR) from the first spaceborne precipitation radar (PR) onboard the National Aeronautics and Space Administration (NASA)'s Tropical Rainfall Measuring Mission (TRMM) satellite. This study has statistically analyzed the latest TRMM 2A-23 and 2A-25 products (version 7, released in 2012) with ∼15 years time span (from 11 December 1997 to 19 August 2012). First, the spatial and seasonal variations of storm height and freezing level have been investigated. The results show a climatological relation connecting the storm height with the rainfall rate in HRB. Second, mean VPRs have been studied for the stratiform and convective precipitation. The VPR variability has been analyzed for different seasons and rain intensities. Third, the characteristics of rain intensification and weakening in the vertical direction have been examined by the statistical analysis of VPR slope below the melting layer. The results show that the rainfall tends to be reduced (or intensified) with the height changing downward in the light (or moderate and heavy) precipitating clouds, no matter stratiform or convection. Finally, the S-band climatological VPRs have been characterized by converting the VPR from Ku-band to S-band. Considering the wide application of national radar network for weather surveillance in China, the developed S-band climatological VPRs can be potentially applied in a VPR correction scheme to improve the ground radar-based quantitative precipitation estimation (QPE) in this river basin. [ABSTRACT FROM AUTHOR]

Shrink‐swell soils possess dynamic hydraulic properties, which may limit the applicability of traditional models for simulating infiltration and overland flow. This study incorporates Green‐Ampt infiltration concepts into a multidomain porosity framework to account for variations in pore size distributions and saturated hydraulic conductivities caused by soil shrinkage and swelling. The model requires three input variables (initial water content, rainfall rate, and time) and up to 15 parameters to simulate infiltration and overland flow, though most of the parameters are universal constants or can be estimated from auxiliary measurements. In comparison, the classic Green‐Ampt model, which assumes constant hydraulic properties and a single domain, requires the same three inputs and up to seven parameters to use. Performance of the proposed multidomain model was verified with two data sets. The first came from a study in Mexico where time to ponding and soil matrix infiltration were quantified under simulated rainfall, and the second came from a study in Chile where overland flow was measured during irrigation experiments on runoff plots. By tuning two (Chile) or three (Mexico) parameters, the multidomain model provided accurate estimations of infiltration/runoff partitioning at multiple scales. Compared to the classic single‐domain model, the multidomain model had lower root‐mean‐square deviations (reducing simulated infiltration errors by 2–3 times) and Akaike Information Criterion (AIC) scores (ΔAIC ~100), thus providing better simulations of infiltration, ponding, and runoff. These results demonstrate that modeling hydrological processes in shrink‐swell soils necessitates separating soil properties mediated by the matrix from those associated with interblock shrinkage cracks. Plain Language Summary: Many soils develop cracks as they dry. During rainstorms and irrigation events, these cracks permit water to move rapidly, but we do not currently possess appropriate tools to simulate water movement in such conditions. This study proposes a mathematical model that calculates water infiltration into such soils by explicitly accounting for properties of cracks versus those of the surrounding soil. The model was verified using field observations from two locations, which demonstrated that the model can accurately simulate water infiltration, ponding on the soil surface, and surface runoff in soils containing cracks. Key Points: This model incorporates Green‐Ampt infiltration concepts into a dynamic multidomain porosity frameworkModel was verified on two soils, improving estimates of infiltration and ponding compared to the classic Green‐Ampt modelMost model parameters can be constrained using universal constants or auxiliary measurements [ABSTRACT FROM AUTHOR]

We used the frameworks of queuing theory and connectivity to study the runoff generated under constant rainfall on a one-dimensional slope with randomly distributed infiltrability. The equivalence between the stationary runoff-runon equation and the customers waiting time in a single server queue provides a theoretical link between the statistical description of infiltrability and that of runoff flow rate. Five distributions of infiltrability, representing soil heterogeneities at different scales, are considered: four uncorrelated (exponential, bimodal, lognormal, uniform) and one autocorrelated (lognormal, with or without a nugget). The existing theoretical results are adapted to the hydrological framework for the exponential case, and new theoretical developments are proposed for the bimodal law. Numerical simulations validate these results and improve our understanding of runoff-runon for all of the distributions. The quantities describing runoff generation (runoff one-point statistics) and its organization into patterns (patterns statistics and connectivity) are studied as functions of rainfall rate. The variables describing the wet areas are also compared to those describing the rainfall excess areas, i.e., the areas where rainfall exceeds infiltrability. Preliminary results concerning the structural and functional connectivity functions are provided, as well as a discussion about the origin of scale effects in such a system. We suggest that the upslope no-flow boundary condition may be responsible for the dependence of the runoff coefficient on the scale of observation. Queuing theory appears to be a promising framework for runoff-runon modeling and hydrological connectivity problems. [ABSTRACT FROM AUTHOR]

Both rainfall intensity and duration take part in determining the hydrologic conditions favorable to the occurrence of shallow landslides. Hydrogeomorphic models of slope stability generally account for the dependence of landsliding on soil mechanical and topographic factors, while the role of rainfall duration is seldom considered within a process-based approach. To investigate the effect of different climate drivers on slope stability, we developed a modeling framework that accounts for the variability of extreme rainfall rate with the duration of rainfall events. The slope stability component includes the key characteristics of the soil mantle, i.e., angle of shearing resistance, void ratio, and specific gravity of solids. Hillslope hydrology is modeled by coupling the conservation of mass of soil water with the Darcy's law used to describe seepage flow. This yields a simple analytical model capable of describing combined effect of duration and intensity of a precipitation episode in triggering shallow landslides. Dimensionless variables are introduced to investigate model sensitivity. Finally, coupling this model with the simple scaling model for the frequency of storm precipitation can help in understanding the climate control on landscape evolution. This leads to predict the temporal scale of hillslope evolution associated with the occurrence of shallow landslides. Model application is shown for the Mettman Ridge study area in Oregon, United States. [ABSTRACT FROM AUTHOR]

Prediction of saturated area formation is important for hydrologic modeling of watersheds with shallow, highly pervious soils. This simulation study examines the relative importance of hillslope properties and rainfall rate on the evolution of saturated source areas during wetting. The study focuses on homogeneous, nonconvergent hillslope topography with constant slope. The two-dimensional, variably saturated groundwater model VS2D [ Healy, 1990; Lappala et al. 1993] is used to simulate saturated area formation under the action of steady uniform rainfall. The study methodology systematically varies four hillslope properties, depth to impervious layer, slope length, slope angle, and average saturated hydraulic conductivity, and the rainfall rate. Results indicate that the fraction of the hillslope length that is saturated at equilibrium is a function of a parameter Φ, which is defined as the rainfall rate multiplied by the slope length, divided by the slope angle, soil thickness, and saturated hydraulic conductivity. The temporal evolution of saturated area is analyzed in terms of the equilibrium time. Nonlinearity in the unsaturated zone and differences in hillslope properties result in a nonunique time to equilibrium relation. The time to equilibrium is maximum when factors that tend to cause surface saturation are in approximate balance with those that tend to dissipate surface saturation. The temporal evolution of surface saturation during wetting follows a wide variety of trajectories. Equivalent hillslope soil water storage ratios on slopes with different properties can result in a wide range of surface saturation conditions. Hillslopes with shallower soils and smaller slope angles are most susceptible to saturated area formation. However, sudden changes in surface saturation are possible on steep hillslopes when 1 < Φ < 6. [ABSTRACT FROM AUTHOR]

The role of overland flow dynamics on the dissolved chemical transport toward an outlet is studied herein using the solutions of the mass conservation equations for overland flow and transport. Some simplifying conditions are considered, to develop an analytical solution for both equations. The rainfall rate ƒ, the infiltration rate i ,the mass transfer coefficient k, and the soil surface concentration cs are assumed constant. The solution, which is analytical, is based on the characteristics method for the two main stages of overland flow, namely, the rising and falling stages. The first stage occurs from ponding time to the time when rainfall ceases, at which point the second stage begins. During the second stage the slope drains, and overland flow depth gradually becomes zero. Although the initial water depth for the kinematic wave equation, h0, could be chosen arbitrarily, its combination with the solute equation induces that h0 should be greater than zero, since a singularity is obtained for h0 = 0. Therefore the solution for the overland flow is developed for a general constant initial water depth, but in order to meet real initial conditions, h0 is chosen to be very small. As an initial condition for the solute equation, c( x, 0) = cs is taken. This is based on the postulation that some mixing occurs with the impact of the raindrops during the first stage of water depth buildup. The initial condition also implies that k → ∞ which, according to the convective mass transfer theory, is obtained for h → 0. An analytical solution is obtained by the characteristics method. As a result, different solutions are obtained for each subzone that composes the domain. In one subzone that belongs to the falling stage, the characteristic curve is solved by Euler's method. The concentration hydrograph decreases rapidly during the rising stage of overland flow to a constant value. During the falling stage of overland flow the concentration hydrograph increases gradually to a value larger than cs, which depends on the ratio k/( k − i). Therefore at the time of ponding and during the final period of overland flow recession, the assumption of constant k is not valid, and, although mathematically correct, physically erroneous results are obtained. [ABSTRACT FROM AUTHOR]

Broadbridge et al. (1988) studied constant rainfall infiltration into bounded profiles and, in particular, the dependence on profile depth Z* of Rcrit/ K1. K1 is saturated hydraulic conductivity and Rcrit is the critical rainfall rate for which surface ponding and profile base saturation occur simultaneously. They found for the linear soil that for lim z* →0 Rcrit/ K1 ≈ 2.004. The correct value is in fact exactly 2. In the present work a shallow profile flow equation is established and used (1) to prove this result holds exactly for soils with moisture diffusivity D and hydraulic conductivity K quasi-linearly connected but otherwise arbitrary functions of volumetric moisture content θ; and (2) to develop a physical argument indicating the result is exact in the fully general case with D(θ) and K(θ) unconnected. [ABSTRACT FROM AUTHOR]

An analytic expression for time to ponding is introduced using the nonlinear model of Broadbridge and White (1987). The hydraulic properties of this model can encompass properties ranging from those of a highly nonlinear Green-Ampt-like soil to those satisfying the weakly nonlinear Burgers' equation. Because of its versatility, this analytic solution is used as a benchmark against which extant analytic, quasi-analytic, and approximate expressions are compared. Time to ponding is parameterized here in terms of the readily measured field properties, sorptivity and hydraulic conductivity. In the limit of Green-Ampt-like properties the analytic solution reduces exactly to the Parlange and Smith (1976) approximation. A similar functional dependence of time to ponding on rainfall rate is found from quasi-analytic approximations. Based on this, a modified approximation is suggested which should give time to ponding for most soils to within ±10%. Some existing approximations are found to have unacceptable deviations from the analytic solution, and their continued use appears unwarranted. Finally, we address the field problem of predicting time to ponding at any antecedent water content, given sorptivity measured at only one initial water content. [ABSTRACT FROM AUTHOR]

Data from a 50-storm sample on two dense networks in Illinois were used to investigate the time distribution of 1-minute rainfall rates in warm-season storms. Absolute and relative variability were analyzed for point and mean rates on areas from 25 to 100 square miles. Several variability measures were employed including sequential variability that uses both the magnitude and the sequence of rates in characterizing the time distribution. Since the variability parameters were found to fit closely a log normal distribution, probability distributions were constructed to define interstorm variability relations. Both absolute and relative variability showed a wide range within and between storms, and between areas of different size. Little difference in variability properties was noted between rain and synoptic weather types associated most frequently with warm-season storms. No evidence of regular oscillations in the time distribution of rainfall rates in convective storms was shown by lag correlation analyses. [ABSTRACT FROM AUTHOR]

The demand for accurate satellite rainfall products is increasing particularly in Africa where ground-based data are mostly unavailable, timely inaccessible, and unreliable. In this study, the accuracy of three widely used, near-global, high-resolution satellite rainfall products (CMORPH, TMPA-RT v7, TMPA-RP v7), with a spatial resolution of 0.25° and a temporal resolution of 3 h, is assessed over the Blue Nile River Basin, a basin characterized by complex terrain and tropical monsoon. The assessment is made using relatively dense experimental networks of rain gauges deployed at two, 0.25° × 0.25°, sites that represent contrasting topographic features: lowland plain (mean elevation of 719 m.a.s.l.) and highland mountain (mean elevation of 2268 m.a.s.l.). The investigation period covers the summer seasons of 2012 and 2013. Compared to the highland mountain site, the lowland plain site exhibits marked extremes of rain intensity, higher mean rain intensity when it rains, lower frequency of rain occurrence, and smaller seasonal rainfall accumulation. All the satellite products considered tend to overestimate the mean rainfall rate at the lowland plain site, but underestimate it at the highland mountain site. The satellite products miss more rainfall at the highland mountain site than at the lowland plain site, and underestimate the heavy rain rates at both sites. Both sites have uncertainty (root mean square error) values greater than 100% for 3 h accumulations of <5 mm, or daily accumulations of <10 mm, and the uncertainty values decrease with increasing rainfall accumulation. Among the satellite products, CMORPH suffers from a large positive bias at the lowland plain site, and TMPA-RP and TMPA-RT miss a large number of rainfall events that contribute nearly half of the total rainfall at the highland mountain. [ABSTRACT FROM AUTHOR]

Model studies suggest that semiarid ecosystems with patterned vegetation can respond in a nonlinear way to climate change. This means that gradual changes can result in a rapid transition to a desertified state. Previous model studies focused on the response of patterned semiarid ecosystems to changes in mean annual rainfall. The intensity of rain events, however, is projected to change as well in the coming decades. In this paper, we study the effect of changes in rainfall intensity on the functioning of patterned semiarid ecosystems with a spatially explicit model that captures rainwater partitioning and runoff-runon processes with simple event-based process descriptions. Analytical and numerical analyses of the model revealed that rainfall intensity is a key parameter in explaining patterning of vegetation in semiarid ecosystems as low mean rainfall intensities do not allow for vegetation patterning to occur. Surprisingly, we found that, for a constant annual rainfall rate, both an increase and a decrease in mean rainfall intensity can trigger desertification. An increase negatively affects productivity as a greater fraction of the rainwater is lost as runoff. This can result in a shift to a bare desert state only if the mean rainfall intensity exceeds the infiltration capacity of bare soil. On the other hand, a decrease in mean rainfall intensity leads to an increased fraction of rainwater infiltrating in bare soils, remaining unavailable to plants. Our findings suggest that considering rainfall intensity as a variable may help in assessing the proximity to regime shifts in patterned semiarid ecosystems and that monitoring losses of resource through runoff and bare soil infiltration could be used to determine ecosystem resilience. [ABSTRACT FROM AUTHOR]

The literature contains contradictory conclusions regarding the relative effects of urbanization on peak flood flows due to increases in impervious area, drainage density and width function, and the addition of subsurface storm drains. We used data from an urbanized catchment, the 14.3 km2 Dead Run watershed near Baltimore, Maryland, USA, and the physics-based gridded surface/subsurface hydrologic analysis (GSSHA) model to examine the relative effect of each of these factors on flood peaks, runoff volumes, and runoff production efficiencies. GSSHA was used because the model explicitly includes the spatial variability of land-surface and hydrodynamic parameters, including subsurface storm drains. Results indicate that increases in drainage density, particularly increases in density from low values, produce significant increases in the flood peaks. For a fixed land-use and rainfall input, the flood magnitude approaches an upper limit regardless of the increase in the channel drainage density. Changes in imperviousness can have a significant effect on flood peaks for both moderately extreme and extreme storms. For an extreme rainfall event with a recurrence interval in excess of 100 years, imperviousness is relatively unimportant in terms of runoff efficiency and volume, but can affect the peak flow depending on rainfall rate. Changes to the width function affect flood peaks much more than runoff efficiency, primarily in the case of lower density drainage networks with less impermeable area. Storm drains increase flood peaks, but are overwhelmed during extreme rainfall events when they have a negligible effect. Runoff in urbanized watersheds with considerable impervious area shows a marked sensitivity to rainfall rate. This sensitivity explains some of the contradictory findings in the literature. [ABSTRACT FROM AUTHOR]

An experimental investigation was undertaken to study the ability of Spectral Induced Polarization (SIP) to monitor water infiltration in a silty clay loam soil. It was based on the coupled acquisition of tensiometer data and Spectral Induced Polarization (SIP) spectra (1.46 Hz to 12 kHz) during the infiltration event created by an artificial constant rainfall rate of about 15 mm/h. The approach, which was applied both in the field and in a soil column, confirms the existence of a significant phase drop in the high-frequency domain (typically greater than 1 kHz) during the first infiltration cycles. The interpretation of the tensiometer and SIP data show that this phase drop is correlated with the water filling of pores in the [30-85] μm diameter range. The phase drop is qualitatively and quantitatively interpreted as a Maxwell-Wagner effect associated with the electrical heterogeneity of the soil. It could correspond to the transition between two physical states. In the first state before the arrival of the wetting front, highly polarized and wet aggregates are embedded in an electrically isolating phase, i.e., air. In the second state after the arrival of the wetting front, structural pores between the aggregates are filled with a connected and conducting phase, i.e., water, leading macroscopically to a decrease in bulk soil polarizability. The experimental and theoretical results of this study suggest strongly that the SIP method can be used to monitor the water filling of structural or draining pores in the field. This original result requires validation in other sites. [ABSTRACT FROM AUTHOR]

The focus of this study is on the role of precipitation uncertainty in the estimation of soil texture and soil hydraulic properties for application to land-atmosphere modeling systems. This work extends a recent study by Santanello et al. (2007) in which it was shown that soil texture and related physical parameters may be estimated using a combination of multitemporal microwave remote sensing, land surface modeling, and parameter estimation methods. As in the previous study, the NASA-GSFC Land Information System modeling framework, including the community Noah land surface model constrained with pedotransfer functions (PTF) for use with the Parameter Estimation Tool, is applied to several sites in the Walnut Gulch Experimental Watershed (WGEW) in southeastern Arizona during the Monsoon '90 experiment period. It is demonstrated that the application of PTF constraints in the estimation process for hydraulic parameters provides accuracy similar to direct hydrologic parameter estimation, with the additional benefit of simultaneously estimated soil texture. Precipitation uncertainty is then represented with systematically varying sources, from the high-density precipitation gauge network in WGEW to lower quality sources, including spatially averaged precipitation, single gauges in and near the watershed, and results from the continental-scale North American Regional Reanalysis data set. It is demonstrated that the quality of the input precipitation data set, and particularly the accuracy of the data set, in both detection of convective (heavy) rainfall events and reproduction of the observed rainfall rate probabilities, is a critical determinant in the use of successive remote sensing results in order to establish and refine estimates of soil texture and hydraulic properties. [ABSTRACT FROM AUTHOR]

The purpose of this study was to determine the effects of single-storm rainfall variability on the timing of the unsaturated zone soil water content response. To investigate this, we monitored rainfall rate and soil water content at three soil profiles about 8 m apart along a downslope transect on a sandy forested hillslope. We also conducted one-dimensional numerical simulations of soil water content response in order to compare observed and expected wetting velocities. Results show that during relatively low intensity storms, wetting rates were comparable in each soil profile and were adequately represented in the numerical results. However, storms with highly variable, high-intensity rainfall rates produced an increase in wetting velocity with soil depth in two of three soil profiles, and the numerical simulations did not adequately replicate this response. Therefore it appears that variability in rainfall intensity, and in particular the sequence of rainfall variability, may cause all or part of the soil profile undergoing wetting to switch from a slow displacement process to a much faster accelerating process. We speculate that this transition is related to the initiation of preferential flow. This switching process may help reconcile the disparate findings of old versus new water in stormflow reported by Mosley (1979, 1982), Pearce et al. (1986), and Sklash et al. (1986), and it may help explain the rapid development of high pore pressures that lead to slope instability (e.g., Montgomery et al., 2002; Iverson, 2000). [ABSTRACT FROM AUTHOR]

The channel head represents an important transition point from hillslope to fluvial processes. There is a nonlinear threshold transition across the channel head with sediment transport much larger in channels than on hillslopes. Deterministic specific catchment area, a, thresholds for channel initiation, sometimes dependent on slope, S, in the form of aSα ≥ C, have been suggested. In this paper the channel initiation problem is viewed probabilistically with a spatially variable probability of channel initiation that depends on slope, specific catchment area, and the probability distributions of median grain size, surface roughness, and excess rainfall rate. The channel initiation threshold C is cast as a random variable to characterize the variability of aSα at channel heads. Using field measurements from the Idaho Batholith, we show that median grain size measurements at each channel head explain a significant part of the observed variability of aSα. We then characterize the variability of model inputs (median grain size, roughness, and excess rainfall) using probability distributions and show that the probability distribution of area-slope threshold derived from these inputs matches the probability distribution of area-slope thresholds measured at field channel head locations. A gamma probability distribution provides a reasonable match to the distributions of area-slope threshold measured and modeled at channel heads in our study area and in other published channel head data. [ABSTRACT FROM AUTHOR]

Shifts in water fluxes and chemical heterogeneity through catchments combine to dictate stream solute export from the Critical Zone. The ways in which these factors emerge in resultant concentration‐discharge (C‐Q) relationships remain obscure, particularly at the timescale of individual precipitation and discharge events. Here we take advantage of a new high‐frequency, multi‐element and multi‐event stream C‐Q data set. The stream solute concentrations of seven major ions were recorded every 40 min over five flood events spanning one hydrologic year in a French agricultural watershed (Orgeval) using a lab‐in‐the‐field deployment we refer to as a "River Lab." We focus attention on the recession periods of these events to consider how geochemical heterogeneity within the catchment translates into dynamic stream solute concentrations during shifts in water storage. We first show that for C‐Q relationships resulting from data acquisition over multiple flood events, lumping all trends together can lead to biases in characteristic C‐Q parameters. We then reframe C‐Q relationships using a simple recession curve analysis to consider how hydrological processes produce chemical mixing of distinct solute pools immediately following discharge events. We find three distinct classes of behavior among the major solutes, none of which can be interpreted based on water storage changes alone. The shape of C‐Q relationships for each solute can then be related to their vertical zonation in the subsurface of Orgeval, and to the capacity for subcomponents of these distributions to be readily mobilized during a discharge event. Key Points: We combine high‐frequency (every 40 min) stream chemistry data and stream discharge recession analysisWe propose a conceptual model for the relationship between water storage and solute export at the Orgeval Critical Zone Observatory (CZO), FranceThree classes of solute behavior are identified at the Orgeval CZO, related to the role of rock dissolution and amendments in their budget [ABSTRACT FROM AUTHOR]

Tracer studies during catchment-scale sprinkler experiments illuminate the pathways of subsurface flow in a small, steep catchment in the Oregon Coast Range. Bromide point injections into saturated materials showed rapid flow in bedrock to the catchment outlet. Bedrock flow returned to the colluvium, sustaining shallow subsurface flow there. The bromide peak velocity of ∼10−3 m s−1 exceeded the saturated hydraulic conductivity of intact bedrock. This, and the peak shapes, verify that fractures provide important avenues for saturated flow in the catchment. Deuterium added to the sprinkler water moved through the vadose zone as plug flow controlled by rainfall rate and water content. Ninety-two percent of the labeled water remained in the vadose zone after 3 days (∼140mm) of sprinkling. Preferential flow of new water was not observed during either low-intensity irrigation or natural storms; however, labeled preevent water was mobile in shallow colluvium during a storm following our spiking experiment. In response to rainfall, waters from the deeper bedrock pathway, which have traveled through the catchment, exfiltrate into the colluvium mantle and mix with relatively young vadose zone water, derived locally, creating an area of subsurface saturation near the channel head. This effectively becomes a subsurface variable source area, which, depending on its size and the delivery of water from the vadose zone, dictates the apportioning of old and new water in the runoff and, correspondingly, the runoff chemistry. The slow movement of water through the vadose zone allows for chemical modification and limits the amount of new water in the runoff. Moreover, it suggests that travel time of new rain water does not control the timing of runoff generation. [ABSTRACT FROM AUTHOR]

The main physical aspects of soil surface seal formation caused by rainfall are modeled. The proposed model relates the surface sealing to the specific hydraulic and mechanical properties of the initially undisturbed soil as well as the physical characteristics of the rainfall applied, under given initial and boundary conditions defining the flow system. The soil disturbance resulting from the raindrop impacts is expressed in terms of an increase of the initial soil bulk density. The dynamics of seal formation at the soil surface are found to be related to the following variables: the rainfall intensity, the second moment of the drop-size density distribution, the maximal drop diameter, the compaction limit of the given soil, and its initial shear strength, which depends upon the initial soil bulk density and water content. Following Mualem and Assouline [1989], a nonuniform seal is considered, represented by an exponentially decreasing function of the bulk density with depth. The seal thickness is assumed to be dependent upon the rainfall rate. Its steady state value is assumed to be reached shortly after the beginning of rainfall so that it might be considered as constant during the stage of formation. A calibration procedure is presented on the basis of measured infiltration under sealing conditions. The results show that the proposed model addresses the main factors affecting soil sealing formation and is able to simulate the process of infiltration through sealing soils under saturated as well as unsaturated flow conditions. [ABSTRACT FROM AUTHOR]

Macropore flow at the groundwater/surface water interface to a humic lake and the seepage fluxes through the lake bottom were measured, as well as was the groundwater chemistry. With a 100-fold difference in discharge from the lake, the seepage rates through the lake bottom differed by only 15%, indicating that macropores provided a major part of the inflow during high-flow events. Two larger macropores had flow rates between 0.3 and 0.7 L s−1, corresponding to velocities of 1-3 m min−1. The flow rates of four smaller macropores were recorded to only 0.02-0.1 × 10−4 L s−1. One of the larger macropores had water with high concentration of alkalinity, Ca and Si in dry periods, whereas during wet periods dissolved organic carbon was elevated and pH was depressed. This is a indication of different source areas depending on the rainfall rate. As the alkalinity/chloride ratios were lower in the macropores than in the peat water, acid groundwater seemed to find a shortcut directly into the lake. [ABSTRACT FROM AUTHOR]

In a hydrologic basin where precipitation rates have strong seasonal characteristics, simple seasonal forecasts of rainfall along with regression analysis on a few related meteorological observations can be used to obtain an estimate of the anticipated rainfall rate one day in advance. In this paper a model for forecasting daily rainfall with one day lead time is presented. The model uses smoothed normal daily rainfall rates as seasonal forecasts and a linear regression model on deviations of atmospheric pressure, temperature, and humidity from their seasonal mean values for estimating departures from seasonal rainfall forecasts. The model has been applied to and tested with daily rainfall data of Dhaka (Dacca) city in Bangladesh. [ABSTRACT FROM AUTHOR]

A solution to the kinematic wave equations for overland flow routing where the lateral inflow term is determined from a constant rainfall rate and the infiltration model of Philip is presented. The solution utilizes the method of characteristics, and while it is not completely analytical, it is reduced to a simple numerical procedure which does not require the use of finite differences. The analysis presented deals with both the rising and falling stages. Example calculations, water surface profiles, and hydrographs are shown. [ABSTRACT FROM AUTHOR]

There is no apparent relationship between elevation and the intensity of spring and summer rainfall in a 93-square-mile area with a range of 3500 feet in elevation in semiarid southwestern Idaho. Analysis covered four years' data from recording rain gages with an average density of 1 per square mile. Rainfall bursts amounting to 0.10 inch or more were considered. The maximum intensity recorded was 0.49 inch falling at 9.8 inches per hour. Rainfall in excess of 0.8 inch per hour occurred an average of once a year. The logarithm of the amount of rain falling in excess of a given intensity plots as a straight line against intensity. There is no difference in this relationship when the data are separated by elevation classes. The amount of rainfall decreases by about one-half with each 1-inch-per-hour increase in rainfall rate. This ratio may be a characteristic of the regional climate. It is suggested that data from accessible valley stations can be used to estimate the relative frequency of high intensity rains throughout an area of appreciable range in elevation. [ABSTRACT FROM AUTHOR]

Studies have been made of the relationship between the rainout of radioactivity in convective storms and three rainfall factors: rainfall volume, storm duration, and rainfall rate. Data were used from four densely gaged sampling networks operated during the spring and summer of 1962-1964 in central Illinois. The network areas ranged from 10 to 6000 mi2 and provided data on both microscale and mesoscale relationships. Analyses of spatial variability showed a trend for the relative variability of radioactive rainout to (1) exceed the storm rainfall variability, (2) decrease with increasing rainfall volume and storm duration, and (3) increase with increasing network size. Investigation of the point representativeness of single measurements of radioactive rainout in a 15-storm sample indicated that an average error of 20-25% is introduced when a single observation is assumed to represent the mean rainout over areas of 10-12 mi2. Correlation analyses indicated that the rainfall at a given point is not strongly related to the radioactive rainout at that point. However, when areal patterns of rainfall and rainout are compared and allowance is made for displacement of high and low centers due to various meteorological influences, a strong association is indicated between the major features of the patterns in most storms. [ABSTRACT FROM AUTHOR]

Urbanization introduces new and alters the existing hydrological processes. Projecting the direction and magnitude of change of evapotranspiration (ET), often a large existing process, in humid subtropical climates is difficult due to the lack of land‐cover specific estimates of ET. This research aims to improve our fundamental understanding of ET in urban areas by focusing on ET specific to land‐cover classes of the National Land Cover Database (NLCD). Using multiple physically based models along with ET from reference watersheds, this study estimates ET—within the Atlanta, GA, USA region—for NLCD classes. ET also is estimated for urban watersheds—both in the Atlanta region and in areas with humid subtropical climate types—for which published ET estimates exist. There are major differences in land cover among the four developed classes: high‐intensity developed land is 92% impervious surfaces, while open‐space developed land—the least intensively developed land—is only 8% impervious surfaces. Consequently, open‐space developed land has an ET total that is over four times that of high‐intensity developed land. Due to a high percentage of impervious cover and substantial evaporation of water from impervious surfaces throughout the year, there is little intra‐annual variation in ET for the high‐intensity developed class. The land‐cover ET totals aggregate to reliable estimates for urban watersheds. The largest source of uncertainty for ET estimates in urban areas is likely the evaporation magnitude associated with impervious surfaces; therefore, more work is needed in determining those magnitudes for humid subtropical climates. Key Points: Evapotranspiration (ET) varies greatly among developed land‐cover classes in a humid subtropical climateET totals specific to land‐cover classes aggregate to reliable estimates for urban watershedsThe largest source of uncertainty for urban ET estimates is likely the magnitude of evaporation from impervious surfaces [ABSTRACT FROM AUTHOR]

In our era, the rapid increase of parallel programming coupled with high‐performance computing (HPC) facilities allows for the use of two‐dimensional shallow water equation (2D‐SWE) algorithms for simulating floods at the "hydrological" catchment scale, rather than just at the "hydraulic" fluvial scale. This approach paves the way for the development of new operational systems focused on impact‐based flash‐floods nowcasting, wherein hydrodynamic simulations directly model the spatial and temporal variability of measured or predicted rainfall on impacts even at a street scale. Specifically, the main goal of this research is to make a step to move toward the implementation of an effective flash flood nowcasting system in which timely and accurate impact warnings are provided by including weather radar products in the HPC 2D‐SWEs modelling framework able to integrate watershed hydrology, flow hydrodynamics, and river urban flooding in just one model. The timing, location, and intensity of the street‐level evolution of some key elements at risk (people, vehicles, and infrastructures) are also discussed considering both calibration issues and the role played by the spatial and temporal rainfall resolution. All these issues are analyzed and discussed having as a starting point the flood event which hit the Mandra town (Athens, Greece) on the 15 November 2017, highlighting the feasibility and the accuracy of the overall approach and providing new insights for the research in this field. Plain Language Summary: In this study, we try to investigate if there is a potentiality for using a flood simulator, which usually requires a lot of time to give the final results, in order to predict, in real‐time, the flood hazard at the roads of a city. For this reason, we exploited the use of supercomputers, which significantly quickened the simulations and the meteorological forecasting given by a weather radar. According to our findings, there is merit for the proposed approach which can shift the flood awareness from generic instructions to more specific predictions, regarding the place and the time of the flood peak. Key Points: The potential of radar data and high‐performance computing two‐dimensional shallow water equation solvers at the watershed scale for impact‐based flash‐flood nowcasting system is highlightedReliable prediction of water depths within the urban area, with run time 30 times faster than real‐time using a high‐resolution gridRain resolution can affect simulated arrival times, peak and time‐to‐peak values, and street‐level prediction of the effects on a specific target [ABSTRACT FROM AUTHOR]

The Yarlung Zangbo River (YZR) is the largest river in the northern Himalayas, providing crucial water resources for downstream. A full understanding of the streamflow dynamics and regional water budget is critical to secure water security of the Himalayan water tower. Here we establish a comprehensive hydrological model to simulate the precipitation‐runoff‐evapotranspiration‐groundwater‐streamflow complex in the YZR basin. We decipher contributions of different water sources (e.g., precipitation, meltwater, groundwater) to YZR's streamflow and estimate that groundwater sustains ∼36% of annual streamflow in the YZR, while precipitation and melt surface runoff contribute 40% and 24%, respectively. Combining modeling, observation and reanalysis data, our results reveal a water "imbalance" that ∼31% of annual precipitation and meltwater (∼333 mm yr−1 or ∼85 km3 yr−1) is unaccounted for in the YZR basin. We propose that the "excess water" discharges to deep fractured bedrock aquifers, which is promoted by widespread permeable active structures (e.g., faults, fractures). This hypothesis is supported by groundwater storage (GWS) estimates where inclusion of the deep groundwater bridges the discrepancy between baseflow‐derived (shallow) GWS and those derived from the Gravity Recovery and Climate Experiment satellite data. The deep groundwater most likely flows across basins, bypasses streams, and finally discharges to downstream aquifers in the Indo‐Gangetic Plain as mountain block recharge. This study not only provides a comprehensive analysis of the streamflow composition in the YZR, but also contributes to shaping a more complete picture of the functionality of the Himalayan water tower, highlighting the importance of groundwater in regional water transfers. Plain Language Summary: Understanding the streamflow dynamics and components feeding the Yarlung Zangbo River (YZR), the largest river in the northern Himalayas, is critical for quantifying regional water resources. Here we show that shallow groundwater sustains ∼36% of the annual streamflow in the YZR, while the contribution of precipitation and melt surface runoff is 40% and 24%, respectively. Regional water balance indicates that ∼31% of precipitation and meltwater, corresponding to ∼333 mm yr−1 and ∼85 km3 yr−1, is unaccounted for in the YZR basin. This component of water "imbalance" is hypothesized to recharge deep fractured bedrock aquifers (promoted by widespread faults and fractures) and flow out of the basin bypassing surface streams. This hypothesis is supported by satellite‐based groundwater estimates. The study yields new insights into streamflow components of the YZR and highlights the significant role of deep groundwater in the water budget of the Himalayan water tower. Key Points: Groundwater, precipitation and snow/glacier melt runoff contribute 36%, 40%, and 24% to annual streamflow in the Yarlung Zangbo River (YZR)∼31% annual meteoric water (∼333 mm yr−1) in YZR basin discharges to deep fractured bedrock and forms inter basin flow that bypasses streamsGRACE‐derived groundwater storage observations support the hypothesis of inter basin deep groundwater pathways [ABSTRACT FROM AUTHOR]

Wildfires naturally occur in many landscapes, however they are undergoing rapid regime shifts. Despite the emphasis in the literature on the most severe hydrological responses to wildfire, there remains a knowledge gap on the thresholds of wildfire (i.e., burned area/drainage area ratio, BAR) required to initiate hydrological responses. We investigated hydrological changes in the Russian River Watershed (RRW) in California, a coastal, Mediterranean, drought‐prone, wildfire‐adapted ecosystem, following ten wildfires that burned 30% of the watershed. Our findings suggest that sub‐watersheds of the RRW have not burned beyond an intrinsic, unknown, threshold required to initiate change. Using paired watersheds, we examined spatiotemporal patterns of pre‐and‐post wildfire hydrology with a rainfall‐runoff hydrological model. Even though these successive wildfires burned 1%–50% of each sub‐watershed (1%–30% at moderate/high severity), we found little evidence of wildfire‐related shifts in hydrology. As a function of BAR, wildfire imposed limited effects on runoff ratios (runoff/precipitation) and runoff residuals (observations—model simulations). Our findings that post‐wildfire runoff enhancements asymptote beyond 30% burn indicate that when a watershed is burned beyond a certain threshold, the magnitude of the hydrologic response no longer increases. Drought and storm conditions explained much of the variability observed in streamflow, whereas wildfire explained only moderate variability in streamflow even when wildfire accounted for >45% BAR. While the BAR in the RRW was sufficiently beyond previously reported minimum disturbance thresholds (>20% burned forest), the lack of hydrological response is attributed to buffering effects of wildfire adaptation and drought factors that are unique to Mediterranean ecoregions. Plain Language Summary: Western United States water resources are vulnerable to changes caused by wildfires. While many studies indicate that streamflow may increase during post‐wildfire years, the compounding factors of drought and wildfire‐adapted landscapes challenge our ability to predict and prepare for coming changes in streamflow. Our current knowledge cannot answer the question "How much wildfire is required for river water flows to change?" Our study results show that drought can buffer the hydrological response to wildfire. While the drought can mitigate post‐wildfire flood potential, effects of the wildfire could emerge years later when high intensity rain events return. Key Points: Little evidence of wildfire‐related shifts in hydrology in drought‐prone Northern California coastal region having a Mediterranean climateWhen the percent of burned area increased beyond 30% of the watershed, the magnitude of the runoff response asymptotesPost‐wildfire hydrological variability did not extend outside of pre‐wildfire streamflow conditions [ABSTRACT FROM AUTHOR]

When precipitation happens in summer, the thermal runoff from impervious surfaces flow into urban lakes, causing the rise of the surface water temperature. Such a process eventually leads to the short‐term effects of cyanobacteria blooms in eutrophic lakes and the long‐term effects of changes in the structure and quantity of lake species. It is of great scientific significance to understand the heat exchange process between surface air, underlying surface, and surface runoff and reveal the thermal runoff formation mechanism. In this study, the heat transfer models between land, surface‐air, and surface‐water were implemented, aiming to quantify the heating process of surface runoff caused by surface heat load under real conditions. The results show that the two established models can accurately simulate the heat exchange process. Based on our model simulations and field measurements, we analyzed the impact of weather conditions, hydrological conditions, and underlying surface types on runoff temperature. The study finds that the initial surface temperature, wind speed, rainfall intensity, thermal conductivity, and the underlying surface's water permeability can explain 95.4% and 91.9% of the observed differences in surface runoff heating and temperature increase rate, respectively. The initial surface temperature is the most critical factor in the heat exchange process. The reduction of urban ventilation will aggravate the heat effect of surface runoff. Compared with the underlying permeable surface, the impervious surface is the main driving force for the formation of surface thermal runoff pollution. [ABSTRACT FROM AUTHOR]

On 1 September 2021, the remnants of Hurricane Ida transformed into a lethal variant of tropical cyclone in which unprecedented short‐duration rainfall from clusters of supercells produced catastrophic flooding in watersheds of the Northeastern US. Short‐duration rainfall extremes from Ida are examined through analyses of polarimetric radar fields and rain gauge observations. Rainfall estimates are constructed from a polarimetric rainfall algorithm that is grounded in specific differential phase shift (KDP) fields. Rainfall accumulations at multiple locations exceed 1000‐year values for 1–3 hr time scales. Radar observations show that supercells are the principal agents of rainfall extremes. Record flood peaks occurred throughout the eastern Pennsylvania—New Jersey region; the peak discharge of the Elizabeth River is one of the most extreme in the eastern US, based on the ratio of the peak discharge to the sample 10‐year flood at the gaging station. As with other tropical cyclones that have produced record flooding in the Northeastern US, Extratropical Transition was a key element of extreme rainfall and flooding from Ida. Tropical and extratropical elements of the storm system contributed to extremes of atmospheric water balance variables and Convective Available Potential Energy, providing the environment for extreme short‐duration rainfall from supercells. Key Points: Remnants of Hurricane Ida produced unprecedented short‐duration rainfall extremes at 1–3 hr time scaleSupercells were the principal agents of extreme rainfall and floodingExtratropical Transition of Ida contributed to the environment of record short‐duration rainfall [ABSTRACT FROM AUTHOR]

Numerous studies have evaluated the reliability and hydrologic utility of various rainfall data sets through hydrological modeling. However, the calibration of hydrological models compensates for errors in rainfall inputs. The drivers, conditions, and factors affecting the calibration of hydrological models given the accuracy of rainfall inputs are not well understood. Here, we explore hydrological model adaptability to rainfall inputs of varied quality and its potential mechanisms. Twenty‐eight rainfall products from multiple sources are collected for a headwater catchment in the Southern United States. These rainfall data sets include measurements from rain gauges, weather radars, satellites, reanalysis products, and Weather Research and Forecasting model simulations. Such rainfall data sets with varied errors are used to independently calibrate a widely used conceptual Xin'anjiang (XAJ) hydrological model. Results suggest that the hydrological model can often adapt well to two scenarios of inaccurate rainfall inputs producing high‐performance streamflow simulations. This adaptive ability is controlled by an adaptable threshold of the overall bias of the rainfall inputs. Moreover, hydrological model adaptability to rainfall inputs is further influenced by how event‐based rainfall bias shapes the overall rainfall bias, especially from those of heavy rainstorms. The hydrological model can adapt to those rainfall inputs that contain important information content for model calibration. Notably, the adaptability to rainfall inputs of the XAJ model is mainly controlled by a bias reduction through adjustment of evapotranspiration and soil moisture storage, yielding satisfactory effective rainfall. The study quantitatively sheds new light on hydrological model adaptability to rainfall input quality. Plain Language Summary: Accurate rainfall is an ideal input for the hydrological model to simulate streamflow reliably. However, some inaccurate rainfall data sets can be compensated by hydrological model calibration to generate good streamflow. It is still unclear what kind of rainfall inputs the model calibration can and cannot adapt to. Here, we explore a large number of rainfall data sets from different sources and their corresponding streamflow simulation performance after independent model calibrations. It is found that the hydrological model can adapt well to two scenarios of inaccurate rainfall data. The adaptive ability of the hydrological model calibration to rainfall inputs is not only affected by the accuracy over the entire period but also by the accuracy of individual rainfall events, especially those of the most severe rainstorms. Therefore, a good hydrological simulation does not always mean its rainfall input data are reliable. This study enhances a quantitative understanding of how the model calibration adapts to the errors in rainfall input data. The findings are expected to provide quantitative guidance for bias correction and data fusion of rainfall products. Key Points: Two scenarios of inaccurate rainfall inputs and a threshold of overall rainfall bias are identified for hydrological model adaptabilityHydrological model adaptability is further influenced by how event‐based bias of individual rainstorms shapes the overall rainfall biasHydrological model adaptability is mainly controlled by a bias reduction through adjustment of evapotranspiration and soil moisture storage [ABSTRACT FROM AUTHOR]