Stefano Orlandini

Surface-subsurface flow modeling with path-based runoff routing, boundary condition-based coupling, and assimilation of multisource observation data

Received 21 October 2008; revised 2 September 2009; accepted 16 September 2009; published 13 February 2010. [1] A distributed physically based model incorporating novel approaches for the representation of surface-subsurface processes and interactions is presented. A path-based description of surface flow across the drainage basin is used, with several options for identifying flow directions, for separating channel cells from hillslope cells, and for representing stream channel hydraulic geometry. Lakes and other topographic depressions are identified and specially treated as part of the preprocessing procedures applied to the digital elevation data for the catchment. Threshold-based boundary condition switching is used to partition potential (atmospheric) fluxes into actual fluxes across the land surface and changes in surface storage, thus resolving the exchange fluxes, or coupling, between the surface and subsurface modules. Nested time stepping allows smaller steps to be taken for typically faster and explicitly solved surface runoff routing, while a mesh coarsening option allows larger grid elements to be used for typically slower and more compute-intensive subsurface flow. Sequential data assimilation schemes allow the model predictions to be updated with spatiotemporal observation data of surface and subsurface variables. These approaches are discussed in detail, and the physical and numerical behavior of the model is illustrated over catchment scales ranging from 0.0027 to 356 km 2 , addressing different hydrological processes and highlighting the importance of describing coupled surfacesubsurface flow.

LOCAL CONTRIBUTIONS TO INFILTRATION EXCESS RUNOFF FOR A CONCEPTUAL CATCHMENT SCALE MODEL

The response of a conceptual soil water balance model to storm events is compared to a detailed finite element solution of the one-dimensional Richards equation in order to test the capabilities of the former in calculating the local contributions to infiltration excess runoff in a distributed catchment scale model. Local infiltration excess runoff is computed from ground level precipitation using the time compression approximation and a Philip infiltration capacity curve with Brooks-Corey constitutive equations. The validity of applying the conceptual model for local runoff and soil water balance calculations is investigated by performing numerical experiments over a range of soil types, control volume depths, and initial soil moisture conditions. We find that a good agreement between the conceptual and detailed models is obtained when the gravitational infiltration rate in Philips formula is set to the saturated hydraulic conductivity, and when percolation from the control volume is updated as a function of the soil moisture content in a stepwise fashion. The comparison between these two models suggests that the simpler (and much less computer-intensive) conceptual water balance technique could be incorporated into distributed models for large scale complex terrains as an efficient means of retaining consideration of spatial variability effects in catchment scale hydrologie simulations. This is illustrated in an application to the Rio Missiaga catchment in the eastern Italian Alps, where the local contributions to surface and subsurface runoff are routed onto a digital elevation model-based conceptual transport network via a simple numerical scheme based on the Muskingum-Cunge method.

Artificial neural network estimation of rainfall intensity from radar observations

Volumetric scans of radar reflectivity Z and gage measurements of rainfall intensity R are used to explore the capabilities of three artificial neural networks to identify and reproduce the functional relationship between Z and R. The three networks are a multilayer perceptron, a Bayesian network, and a radial basis function network. For each of them, numerical experiments are conducted incorporating in the network inputs different descriptions of the space-time variability of Z. Space variability refers to the observations of Z along the vertical atmospheric profile, at 11 constant altitude plan position indicator levels, namely ZT = (Z1,…,Z11). Time variability refers to the observations of Z at the time intervals prior to that for which the estimate of R is provided. Space variability is evaluated by performing a principal component analysis over standardized values of Z, namely Z˜, and the first two principal components of Z˜ (which describe 91% of the original variance) are used to synthesize the elements of Z into fewer orthogonal inputs for the networks. Network predictions significantly improve when the models are trained with the two principal components of Z˜ with respect to the case in which only Z1 is used. Increasing the time horizon further improves the performances of the Bayesian network but is found to worsen the performances of the other two networks.

Evidence of an emerging levee failure mechanism causing disastrous floods in Italy

A levee failure occurred along the Secchia River, Northern Italy, on 19 January 2014, resulting in flood damage in excess of

On the storm flow response of upland Alpine catchments

500 million. In response to this failure, immediate surveillance of other levees in the region led to the identification of a second breach developing on the neighboring Panaro River, where rapid mitigation efforts were successful in averting a full levee failure. The paired breach events that occurred along the Secchia and Panaro Rivers provided an excellent window on an emerging levee failure mechanism. In the Secchia River, by combining the information content of photographs taken from helicopters in the early stage of breach development and 10 cm resolution aerial photographs taken in 2010 and 2012, animal burrows were found to exist in the precise levee location where the breach originated. In the Panaro River, internal erosion was observed to occur at a location where a crested porcupine den was known to exist and this erosion led to the collapse of the levee top. This paper uses detailed numerical modeling of rainfall, river flow, and variably saturated flow in the levee to explore the hydraulic and geotechnical mechanisms that were triggered along the Secchia and Panaro Rivers by activities of burrowing animals leading to levee failures. As habitats become more fragmented and constrained along river corridors, it is possible that this failure mechanism could become more prevalent and, therefore, will demand greater attention in both the design and maintenance of earthen hydraulic structures as well as in wildlife management.

Comment on “Global search algorithm for nondispersive flow path extraction” by Kyungrock Paik

Detailed measurements of near-surface soil hydraulic conductivity, Ks, across the Bracciasco catchment (Central Italian Alps) are incorporated into a distributed, digital elevation model-based hydrological model to evaluate the effect of soil heterogeneity on catchment storm flow response. Surface and subsurface storm flow components are simulated for different distributions of Ks, including that obtained directly from measurements, that obtained by averaging measured data and others obtained on the basis of a simple functional parameter model. The reproduction of the catchment storm flow responses obtained using distributions of Ks based on measurements is satisfactory although an adjustment of such distributions is suggested to reproduce the hydrograph peaks owing to rapid surface runoff concentration and to improve the description of recession limbs at the same time. Numerical experiments indicate that the simulated storm flow response of the study catchment is substantially insensitive to near-surface soil heterogeneity in as far as the predominant mechanism of channel storm flow generation is subsurface flow. However, Ks is found to play an important role in the generation of overland flow during intense rainfall and, under these circumstances, monitoring of near-surface heterogeneity may be important to provide accurate descriptions of both surface and subsurface storm flow components. Copyright

On the control volume modelling of near-surface soil drying

] Paik [2008] presents a new algorithm for the extrac-tion of surface flow paths from gridded elevation data,arguing that ‘‘significant improvement over the limitationof D8 and D8-LTD [methods] can be achieved using a newand simple idea without introducing any model parameter’’[Paik, 2008, paragraph 9]. However, all Paik’s [2008]arguments against Orlandini et al.’s [2003] D8-LTD methodcan be shown to be unsubstantial merely on the basis ofgeometrical considerations. The purpose of the presentcomment is to point out that (1) an analytical backgroundto support the decision to set the dampening factor l equalto 1 in the D8-LTD method does exist and (2) resultsobtained from incorrect implementations of the D8-LTDmethod are used in the investigation of Paik [2008]. Furtherconsiderations on Paik’s [2008] analysis of the D8-LTDmethod are also provided.[

Control of coupling mass balance error in a process-based numerical model of surface-subsurface flow interaction

Abstract The problem of simulating the topsoil water dynamics in response to atmospheric evaporative events is considered in the present paper. It is emphasised how the assumption that soil moisture profiles approximately preserve similarity during simultaneous atmospheric drying and gravity drainage may be required in order to incorporate the effects of deep soil layers in the near-surface soil control volume hydrologic modelling. The reliability of the proposed formulation is evaluated with rates of evaporation calculated from measurements of the Bower ratio and soil moisture data obtained from time domain reflectometry measurements for a bare soil field in the Zwalmbeek catchment (Belgium).

Copula‐Based Modeling of Flood Control Reservoirs

A process-based numerical model of integrated surface-subsurface flow is analyzed in order to identify, track, and reduce the mass balance errors affiliated with the models coupling scheme. The sources of coupling error include a surface-subsurface grid interface that requires node-to-cell and cell-to-node interpolation of exchange fluxes and ponding heads, and a sequential iterative time matching procedure that includes a time lag in these same exchange terms. Based on numerical experiments carried out for two synthetic test cases and for a complex drainage basin in northern Italy, it is shown that the coupling mass balance error increases during the flood recession limb when the rate of change in the fluxes exchanged between the surface and subsurface is highest. A dimensionless index that quantifies the degree of coupling and a saturated area index are introduced to monitor the sensitivity of the model to coupling error. Error reduction is achieved through improvements to the heuristic procedure used to control and adapt the time step interval and to the interpolation algorithm used to pass exchange variables from nodes to cells. The analysis presented illustrates the trade-offs between a flexible description of surface and subsurface flow processes and the numerical errors inherent in sequential iterative coupling with staggered nodal points at the land surface interface, and it reveals mitigation strategies that are applicable to all integrated models sharing this coupling and discretization approach.

Relation between grid, channel, and Peano networks in high‐resolution digital elevation models

Copulas are shown in this paper to provide an effective strategy to describe the statistical dependence between peak flow discharge and flood volume featuring hydrographs forcing a flood control reservoir. A 52 year time series of flow discharges observed in the Panaro River (Northern Italian Apennines) is used to fit an event-based bivariate distribution and to support time-continuous modeling of a flood control reservoir, located online along the river system. With regard to reservoir performances, a method aimed at estimating the bivariate return period is analytically developed, by exploiting the derived distribution theory and a simplified routing scheme. In this approach, the return period is that of the peak flow discharge released downstream from the reservoir. Therefore, in order to verify the reliability of the proposed method, a nonparametric version of its frequency distribution is assessed by means of continuous simulation statistics. Copula derived and nonparametric distributions of the downstream peak flow discharge are found to be in satisfactory agreement. Finally, a comparison of bivariate return period estimates carried out by using alternative approaches is illustrated.