On the nonuniqueness of sediment yield at the catchment scale: The effects of soil antecedent conditions and surface shield

The understanding of reasons leading to nonuniqueness of soil erosion susceptibility is still inadequate, yet indispensable for establishing general relations between runoff volume and sediment yield. To obtain relevant insights, we performed a series of numerical simulations with a detailed hydrodynamic model using synthetic storms of varying intensity, duration, and lag time between events as representations of different hydrologic response conditions in a zero‐order catchment. The design targeted to generate surface flow and “perturb” soil substrate by a first rainfall event, creating a set of initial conditions in terms of flow and deposited sediment prior to the onset of a subsequent rainfall event. Due to the differential effect of (re)detachment and (re)entrainment processes on soil particles of varying sizes, the deposited sediment mass formed shielding layer. One of the essential results is that unless the initial condition of flow and sediment is identical, the same volume of runoff can generate different total sediment yields and their variation can reach up to ∼200%. The effect is attributed to two major conflicting effects exerted by the deposited “initialization” (soil antecedent condition) sediment mass: erosion enhancement, because of supply of highly erodible sediment, and erosion impediment, because of constrain on the availability of lighter particles by heavier sediment. Consistently with this inference, long‐term simulations with continuous rainfall show that a peculiar feature of sediment yield series is the existence of maximum before the steady state is reached. The two characteristic time scales, the time to peak and the time to steady state, separate three characteristic periods that correspond to flow‐limited, source‐limited, and steady‐state regimes. These time scales are log linearly and negatively related to the spatially averaged Shields parameter: the smaller the rainfall input and the heavier a given particle is, the larger the two scales are. The results provide insights on how the existence of shield operates on erosion processes, possibly implying that accurate short‐term predictions of geomorphic events from headwater areas may never become a tractable problem: the latter would require a detailed spatial characterization of particle size distribution prior to precipitation events. Key Points The same volume of runoff can generate different total sediment yields (∼200%) Erosion enhancement or impediment effects exerted by the shielding layer Two time scales and three characteristic regimesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/106740/1/wrcr20739-sup-0002-suppinfo2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/106740/2/wrcr20739.pd

Modeling erosion and sedimentation coupled with hydrological and overland flow processes at the watershed scale

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/100271/1/wrcr20373-sup-0001-suppinfo1.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/100271/2/wrcr20373-sup-0002-suppinfo2.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/100271/3/wrcr20373.pd

A weather generator for hydrological, ecological, and agricultural applications

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95112/1/wrcr11029.pd

A Novel Modeling Framework for Computationally Efficient and Accurate Real‐Time Ensemble Flood Forecasting With Uncertainty Quantification

A novel modeling framework that simultaneously improves accuracy, predictability, and computational efficiency is presented. It embraces the benefits of three modeling techniques integrated together for the first time: surrogate modeling, parameter inference, and data assimilation. The use of polynomial chaos expansion (PCE) surrogates significantly decreases computational time. Parameter inference allows for model faster convergence, reduced uncertainty, and superior accuracy of simulated results. Ensemble Kalman filters assimilate errors that occur during forecasting. To examine the applicability and effectiveness of the integrated framework, we developed 18 approaches according to how surrogate models are constructed, what type of parameter distributions are used as model inputs, and whether model parameters are updated during the data assimilation procedure. We conclude that (1) PCE must be built over various forcing and flow conditions, and in contrast to previous studies, it does not need to be rebuilt at each time step; (2) model parameter specification that relies on constrained, posterior information of parameters (so‐called Selected specification) can significantly improve forecasting performance and reduce uncertainty bounds compared to Random specification using prior information of parameters; and (3) no substantial differences in results exist between single and dual ensemble Kalman filters, but the latter better simulates flood peaks. The use of PCE effectively compensates for the computational load added by the parameter inference and data assimilation (up to ~80 times faster). Therefore, the presented approach contributes to a shift in modeling paradigm arguing that complex, high‐fidelity hydrologic and hydraulic models should be increasingly adopted for real‐time and ensemble flood forecasting.Key PointsA surrogate model must be built over various forcing and flow conditions and it does not need to be rebuilt at each time stepModel parameter specification for data assimilation can significantly improve forecasting performance and reduce uncertainty boundsNo substantial differences in results exists between single and dual EnKFs, but the latter better simulates flood peaksPeer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154302/1/wrcr24506_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/154302/2/wrcr24506.pd

Hysteresis of soil moisture spatial heterogeneity and the “homogenizing” effect of vegetation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/94935/1/wrcr12475.pd

Uncertainty partition challenges the predictability of vital details of climate change

Decision makers and consultants are particularly interested in “detailed” information on future climate to prepare adaptation strategies and adjust design criteria. Projections of future climate at local spatial scales and fine temporal resolutions are subject to the same uncertainties as those at the global scale but the partition among uncertainty sources (emission scenarios, climate models, and internal climate variability) remains largely unquantified. At the local scale, the uncertainty of the mean and extremes of precipitation is shown to be irreducible for mid and end‐of‐century projections because it is almost entirely caused by internal climate variability (stochasticity). Conversely, projected changes in mean air temperature and other meteorological variables can be largely constrained, even at local scales, if more accurate emission scenarios can be developed. The results were obtained by applying a comprehensive stochastic downscaling technique to climate model outputs for three exemplary locations. In contrast with earlier studies, the three sources of uncertainty are considered as dependent and, therefore, non‐additive. The evidence of the predominant role of internal climate variability leaves little room for uncertainty reduction in precipitation projections; however, the inference is not necessarily negative, because the uncertainty of historic observations is almost as large as that for future projections with direct implications for climate change adaptation measures.Key PointsUncertainties of climate change projections at high spatial and temporal resolution are analyzedUncertainty cannot be reduced in precipitation projections and for extremesUncertainty in air temperature can be potentially constrained with refined emission scenariosPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/122428/1/eft2122_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/122428/2/eft2122.pd

Species‐specific transpiration responses to intermediate disturbance in a northern hardwood forest

Intermediate disturbances shape forest structure and composition, which may in turn alter carbon, nitrogen, and water cycling. We used a large‐scale experiment in a forest in northern lower Michigan where we prescribed an intermediate disturbance by stem girdling all canopy‐dominant early successional trees to simulate an accelerated age‐related senescence associated with natural succession. Using 3 years of eddy covariance and sap flux measurements in the disturbed area and an adjacent control plot, we analyzed disturbance‐induced changes to plot level and species‐specific transpiration and stomatal conductance. We found transpiration to be ~15% lower in disturbed plots than in unmanipulated control plots. However, species‐specific responses to changes in microclimate varied. While red oak and white pine showed increases in stomatal conductance during postdisturbance (62.5 and 132.2%, respectively), red maple reduced stomatal conductance by 36.8%. We used the hysteresis between sap flux and vapor pressure deficit to quantify diurnal hydraulic stress incurred by each species in both plots. Red oak, a ring porous anisohydric species, demonstrated the largest mean relative hysteresis, while red maple, bigtooth aspen, and paper birch, all diffuse porous species, had the lowest relative hysteresis. We employed the Penman‐Monteith model for LE to demonstrate that these species‐specific responses to disturbance are not well captured using current modeling strategies and that accounting for changes to leaf area index and plot microclimate are insufficient to fully describe the effects of disturbance on transpiration.Key PointsPlot level scaling of evaporation from sap flux evaluated with eddy fluxDisturbance changes intradaily transpiration dynamicsHydraulic strategy causes species‐specific transpiration differencesPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/110637/1/jgrg20315.pd

Characterizing the diurnal patterns of errors in the prediction of evapotranspiration by several land‐surface models: An NACP analysis

Land‐surface models use different formulations of stomatal conductance and plant hydraulics, and it is unclear which type of model best matches the observed surface‐atmosphere water flux. We use the North American Carbon Program data set of latent heat flux (LE) measurements from 25 sites and predictions from 9 models to evaluate models' ability to resolve subdaily dynamics of transpiration. Despite overall good forecast at the seasonal scale, the models have difficulty resolving the dynamics of intradaily hysteresis. The majority of models tend to underestimate LE in the prenoon hours and overestimate in the evening. We hypothesize that this is a result of unresolved afternoon stomatal closure due to hydrodynamic stresses. Although no model or stomata parameterization was consistently best or worst in terms of ability to predict LE, errors in model‐simulated LE were consistently largest and most variable when soil moisture was moderate and vapor pressure deficit was moderate to limiting. Nearly all models demonstrate a tendency to underestimate the degree of maximum hysteresis which, across all sites studied, is most pronounced during moisture‐limited conditions. These diurnal error patterns are consistent with models' diminished ability to accurately simulate the natural hysteresis of transpiration. We propose that the lack of representation of plant hydrodynamics is, in part, responsible for these error patterns. Key Points Land‐surface models produce subdaily patterns of latent heat flux error Error patterns are characterized by the stomatal conductance formulation used Current models lack a mechanism to simulate hysteretic transpirationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108341/1/jgrg20246.pd

Vegetation‐hydrology dynamics in complex terrain of semiarid areas: 2. Energy‐water controls of vegetation spatiotemporal dynamics and topographic niches of favorability

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95632/1/wrcr11124.pd

Vegetation‐hydrology dynamics in complex terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/95225/1/wrcr11121.pd