Valeriy Y. Ivanov

Surface‐subsurface model intercomparison: A first set of benchmark results to diagnose integrated hydrology and feedbacks

There are a growing number of large-scale, complex hydrologic models that are capable of simulating integrated surface and subsurface flow. Many are coupled to land-surface energy balance models, biogeochemical and ecological process models, and atmospheric models. Although they are being increasingly applied for hydrologic prediction and environmental understanding, very little formal verification and/or benchmarking of these models has been performed. Here we present the results of an intercomparison study of seven coupled surface-subsurface models based on a series of benchmark problems. All the models simultaneously solve adapted forms of the Richards and shallow water equations, based on fully 3-D or mixed (1-D vadose zone and 2-D groundwater) formulations for subsurface flow and 1-D (rill flow) or 2-D (sheet flow) conceptualizations for surface routing. A range of approaches is used for the solution of the coupled equations, including global implicit, sequential iterative, and asynchronous linking, and various strategies are used to enforce flux and pressure continuity at the surface-subsurface interface. The simulation results show good agreement for the simpler test cases, while the more complicated test cases bring out some of the differences in physical process representations and numerical solution approaches between the models. Benchmarks with more traditional runoff generating mechanisms, such as excess infiltration and saturation, demonstrate more agreement between models, while benchmarks with heterogeneity and complex water table dynamics highlight differences in model formulation. In general, all the models demonstrate the same qualitative behavior, thus building confidence in their use for hydrologic applications.

Extending the Predictability of Hydrometeorological Flood Events Using Radar Rainfall Nowcasting

Abstract The predictability of hydrometeorological flood events is investigated through the combined use of radar nowcasting and distributed hydrologic modeling. Nowcasting of radar-derived rainfall fields can extend the lead time for issuing flood and flash flood forecasts based on a physically based hydrologic model that explicitly accounts for spatial variations in topography, surface characteristics, and meteorological forcing. Through comparisons to discharge observations at multiple gauges (at the basin outlet and interior points), flood predictability is assessed as a function of forecast lead time, catchment scale, and rainfall spatial variability in a simulated real-time operation. The forecast experiments are carried out at temporal and spatial scales relevant for operational hydrologic forecasting. Two modes for temporal coupling of the radar nowcasting and distributed hydrologic models (interpolation and extended-lead forecasting) are proposed and evaluated for flood events within a set of nes...

Assessment of a stochastic downscaling methodology in generating an ensemble of hourly future climate time series

This study extends a stochastic downscaling methodology to generation of an ensemble of hourly time series of meteorological variables that express possible future climate conditions at a point-scale. The stochastic downscaling uses general circulation model (GCM) realizations and an hourly weather generator, the Advanced WEather GENerator (AWE-GEN). Marginal distributions of factors of change are computed for several climate statistics using a Bayesian methodology that can weight GCM realizations based on the model relative performance with respect to a historical climate and a degree of disagreement in projecting future conditions. A Monte Carlo technique is used to sample the factors of change from their respective marginal distributions. As a comparison with traditional approaches, factors of change are also estimated by averaging GCM realizations. With either approach, the derived factors of change are applied to the climate statistics inferred from historical observations to re-evaluate parameters of the weather generator. The re-parameterized generator yields hourly time series of meteorological variables that can be considered to be representative of future climate conditions. In this study, the time series are generated in an ensemble mode to fully reflect the uncertainty of GCM projections, climate stochasticity, as well as uncertainties of the downscaling procedure. Applications of the methodology in reproducing future climate conditions for the periods of 2000–2009, 2046–2065 and 2081–2100, using the period of 1962–1992 as the historical baseline are discussed for the location of Firenze (Italy). The inferences of the methodology for the period of 2000–2009 are tested against observations to assess reliability of the stochastic downscaling procedure in reproducing statistics of meteorological variables at different time scales.

Interannual variability of evapotranspiration and vegetation productivity

Interannual variability of precipitation can influence components of the hydrological budget, affecting them directly and indirectly through adjustments in vegetation structure and function. We investigate the effects of fluctuations of annual precipitation on ecohydrological dynamics. Specifically, we use the advanced weather generator, AWE-GEN, to simulate 200 years of hourly meteorological forcing obtained by imposing four types of precipitation annual process with identical long-term mean. The generated time series force a mechanistic ecohydrological model, Tethys-Chloris. Simulations with perturbed precipitation variability are performed for four locations characterized by different vegetation cover and climate. The results indicate that long-term transpiration (T) and evapotranspiration (ET) fluxes as well as vegetation productivity expressed as Gross Primary Production (GPP) and Aboveground Net Primary Production (ANPP) are essentially unaffected by the imposed climate fluctuations. This finding supports the hypothesis of a relative insensitivity, except for water-limited environments, of interannual evapotranspiration and vegetation productivity to annual climatic fluctuations, which are mostly reflected in the fluxes of deep leakage and runoff. The occurrence of short periods of favorable meteorological conditions randomly taking place within the year was found to be a better explanatory variable for interannual variability of ET and ANPP than average annual or growing season conditions. The results indicated that local, single-site sensitivities are considerably smaller than those observed across climatic and vegetation spatial gradients and thus an important role of ecosystem reorganization in modifying ANPP and ET sensitivity in a changing climate is recognized.

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.

Embedding landscape processes into triangulated terrain models

Triangulated irregular networks (TIN) can form the basis for multiple‐resolution representations in distributed hydrogeomorphic simulations over complex basins. Current methods for deriving TIN meshes depend primarily on surface slope without considering other terrain attributes significant to the watershed response such as the specific basin area. As an alternative, we present a methodology for combining a hydrogeomorphic or landscape index with an unstructured triangulated mesh. Landscape indices provide a concise method for describing steady‐state terrain processes by isolating the dominant physical factors. The mesh‐generation algorithm results in an adaptive discretization that resembles the spatial pattern of the landscape index with a high resolution retained in areas expected to impact the basin response. We compare the proposed algorithm with a slope‐preserving method as a means for initializing the terrain representation in two TIN‐based hydrogeomorphic models. Through three case studies in saturation‐excess runoff, transport‐limited soil erosion and shallow landslide simulation, we assess the distributed model sensitivity to the triangulated terrain algorithm. Model comparisons reveal that the process‐based triangulations focus the distributed simulation in regions anticipated via a steady‐state index to affect the transient watershed response.

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.

Impact of Hillslope-Scale Organization of Topography, Soil Moisture, Soil Temperature, and Vegetation on Modeling Surface Microwave Radiation Emission

Microwave radiometry will emerge as an important tool for global remote sensing of near-surface soil moisture in the coming decade. In this modeling study, we find that hillslope-scale topography (tens of meters) influences microwave brightness temperatures in a way that produces bias at coarser scales (kilometers). The physics underlying soil moisture remote sensing suggests that the effects of topography on brightness temperature observations are twofold: 1) the spatial distribution of vegetation, moisture, and surface and canopy temperature depends on topography and 2) topography determines the incidence angle and polarization rotation that the observing sensor makes with the local land surface. Here, we incorporate the important correlations between factors that affect emission (e.g., moisture, temperature, and vegetation) and topographic slope and aspect. Inputs to the radiative transfer model are obtained at hillslope scales from a mass-, energy-, and carbon-balance-resolving ecohydrology model. Local incidence and polarization rotation angles are explicitly computed, with knowledge of the local terrain slope and aspect as well as the sky position of the sensor. We investigate both the spatial organization of hillslope-scale brightness temperatures and the sensitivity of spatially aggregated brightness temperatures to satellite sky position. For one computational domain considered, hillslope-scale brightness temperatures vary from approximately 121 to 317 K in the horizontal polarization and from approximately 117 to 320 K in the vertical polarization. Including hillslope-scale heterogeneity in factors effecting emission can change watershed-aggregated brightness temperature by more than 2 K, depending on topographic ruggedness. These findings have implications for soil moisture data assimilation and disaggregation of brightness temperature observations to hillslope scales.

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 due to 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, since the uncertainty of historic observations is almost as large as that for future projections with direct implications for climate change adaptation measures.

Abiotic and biotic controls of soil moisture spatiotemporal variability and the occurrence of hysteresis

An expression that separates biotic and abiotic controls on the temporal dynamics of the soil moisture spatial coefficient of variation Cv(?) was explored via numerical simulations using a mechanistic ecohydrological model, Tethys-Chloris. Continuous soil moisture spatiotemporal dynamics at an exemplary hillslope domain were computed for six case studies characterized by different climate and vegetation cover and for three configurations of soil properties. It was shown that abiotic controls largely exceed their biotic counterparts in wet climates. Biotic controls on Cv(?) were found to be more pronounced in Mediterranean climates. The relation between Cv(?) and spatial mean soil moisture inline image was found to be unique in wet locations, regardless of the soil properties. For the case of homogeneous soil texture, hysteretic cycles between Cv(?) and inline image were observed in all Mediterranean climate locations considered here and to a lesser extent in a deciduous temperate forest. Heterogeneity in soil properties increased Cv(?) to values commensurate with field observations and weakened signatures of hysteresis at all of the studied locations. This finding highlights the role of site-specific heterogeneities in hiding or even eliminating the signature of climatic and biotic controls on Cv(?), thereby offering a new perspective on causes of confounding results reported across field experiments.