1,721,006 research outputs found
Influence of spatial precipitation sampling on hydrological response at catchment scale
Full text linkRetrieving precipitation data from raingauge network is a classical and common practice in hydrology and climatology. These data represent the key input in hydrological modeling to reproduce, for example, the characteristics of a flood phenomenon. The accuracy of the model results is strongly dependent on the consistency of the monitoring network in terms of spatial scale, i.e. network density and location of raingauges, and time resolution. In this context, several studies have been carried out to analyze how the rainfall sampling influences the estimation of total runoff volume.
The aim of this paper is to use a physically based and distributed-parameter hydrologic model to investigate how the number and the spatial distribution of a raingauge network influence the estimation of the hydrograph and its characteristics, in conjunction with different spatial and temporal characteristics of rainfall forcing and different soil type characteristics. The tRIBS hydrologic model was used to simulate hydrologic response at Baron Fork basin, Oklahoma. Downscaled NEXRAD radar measurements were assumed to represent the true precipitation distribution over the basin. Additional precipitation fields have been derived from interpolation of eight fictitious raingauges randomly placed in the area. The hydrological response from tRIBS that is driven by these precipitation fields has been compared with the response of the model forced with NEXRAD precipitation. The analysis has been carried out assuming first simplified spatial distributions of soil characteristics, and then the real soil-type distribution. Results have shown the dependence of the best raingauges configuration for the estimation of runoff on the spatiotemporal characteristics of storm events and the soil-type distribution
Budyko’s Based Method for Annual Runoff Characterization across Different Climatic Areas: an Application to United States
No full textRunoff data knowledge is of fundamental importance for a wide range of hydrological, ecological, and socioeconomic applications. The reconstruction of annual runoff is a fundamental task for several activities related to water resources management, especially for ungauged basins. At catchment scales, the Budyko’s framework provides an extremely useful and, in some cases, accurate estimation of the long-term partitioning of precipitation into evapotranspiration and runoff as a function of the prevailing climatic conditions. Recently the same long-term partitioning rules have been successfully used to describe water partitioning also at the annual scale and calculate the annual runoff distribution within a simple analytic framework in arid and semi-arid basins. One of the main advantages of the latter method is that only annual precipitation and potential evapotranspiration statistics, and the Fu’s equation parameter ω are required to obtain the annual runoff probability distribution. The aim of this study is to test the limit and potentialities of the aforementioned method under different climatic conditions. To this aim, the model is applied to more than four hundred basins located in the United States. Catchments were grouped into five different samples, following the subdivision of the continental region in five homogeneous climatic zones according to Köppen-Geiger classification. The theoretical probability distribution of annual runoff at each basin has been compared with that derived from historical observations. The results confirm the capability of the tested technique to reproduce the empirical annual runoff distributions with similar and satisfactory performances across different areas, revealing a good option also in cases characterized by climate and hydrological conditions very different from those hypothesized during the original analytical model design, thus extending the geographical and conceptual limits of applicability of the framework
Derivation of critical rainfall thresholds for landslide in Sicily
Full text linkRainfall is the primary trigger of shallow landslides that can cause fatalities, damage to properties and economic
losses in many areas of the world. For this reason, determining the rainfall amount/intensity responsible for
landslide occurrence is important, and may contribute to mitigate the related risk and save lives. Efforts have
been made in different countries to investigate triggering conditions in order to define landslide-triggering rainfall
thresholds. The rainfall thresholds are generally described by a functional relationship of power in terms of
cumulated or intensity event rainfall-duration, whose parameters are estimated empirically from the analysis of
historical rainfall events that triggered landslides.
The aim of this paper is the derivation of critical rainfall thresholds for landslide occurrence in Sicily, southern
Italy, by focusing particularly on the role of the antecedent wet conditions. The creation of the appropriate
landslide-rainfall database likely represents one of main efforts in this type of analysis. For this work, historical
landslide events occurred in Sicily from 1919 to 2001 were selected from the archive of the Sistema Informativo
sulle Catastrofi Idrogeologiche, developed under the project Aree Vulnerabili Italiane. The corresponding
triggering precipitations were screened from the raingauges network in Sicily, maintained by the Osservatorio
delle Acque - Agenzia Regionale per i Rifiuti e le Acque. In particular, a detailed analysis was carried out to
identify and reconstruct the hourly rainfall events that caused the selected landslides.
A bootstrapping statistical technique has been used to determine the uncertainties associated with the threshold
parameters. The rainfall thresholds at different exceedance probability levels, from 1% to 10%, were defined in
terms of cumulated event rainfall, E, and rainfall duration, D. The role of rainfall prior to the damaging events
was taken into account by including in the analysis the rainfall fallen 6, 15 and 30 days before each landslide. The
antecedent rainfall turned out to be particularly important in triggering landslides. The rainfall thresholds obtained
for the Sicily were compared with the regional curves proposed by various authors confirming a good agreement
with these
Analytical estimation of annual runoff distribution in ungauged seasonally dry basins based on a first order Taylor expansion of the Fu's equation
No full textThe assessment of the mean annual runoff and its interannual variability in a basin is the first and fundamental task for several activities related to water resources management and water quality analysis. The scarcity of observed runoff data is a common problem worldwide so that the runoff estimation in ungauged basins is still an open question. In this context, the main aim of this work is to propose and test a simple tool able to estimate the probability distribution of the annual surface runoff in ungauged river basins in arid and semi-arid areas using a simplified Fu's parameterization of the Budyko's curve at regional scale. Starting from a method recently developed to derive the distribution of annual runoff, under the assumption of negligible inter-annual change in basin water storage, we here generalize the application to any catchment where the parameter of the Fu's curve is known. Specifically, we provide a closed-form expression of the annual runoff distribution as a function of the mean and standard deviation of annual rainfall and potential evapotranspiration, and the Fu's parameter. The proposed method is based on a first order Taylor expansion of the Fu's equation and allows calculating the probability density function of annual runoff in seasonally dry arid and semi-arid geographic context around the world by taking advantage of simple easy-to-find climatic data and the many studies with estimates of the Fu's parameter worldwide. The computational simplicity of the proposed tool makes it a valuable supporting tool in the field of water resources assessment for practitioners, regional agencies and authorities
INFLUENCE OF RAINFALL OBSERVATION NETWORK ON MODELED HYDROLOGICAL RESPONSE
Full text linkPrecipitation data, one of the most important input required in hydrological modeling and forecasting, are usually recorded using raingauges which are classical and fundamental tools able to provide an estimate of rainfall at a point. The consistency of precipitation monitoring network in terms of spatial scale (network density and location of raingauges) and time resolution has to be capable to reproduce, with acceptable accuracy, the characteristics of the flood phenomenon. In this context, over the last thirty years, several studies concerning the influence of point measurement of rainfall for the estimation of total runoff volume have been carried out. Aim of this paper is using a physically based and distributed-parameter hydrologic model in order to investigate the influence of the raingauges network configuration, in terms of number and spatial distribution, on the estimation of hydrograph peak discharge considering also the spatial distribution of soil types in the basin. The hydrologic model has been applied to the catchment of Baron Fork located in Oklahoma. The radar measurements, available in the area, have been assumed as representative of the “real” distribution of precipitation. Its hydrological response is compared with that obtained from interpolated precipitation fields, which, in turn, are obtained by varying the distribution of the raingauges network. The analysis has been first carried out assuming a simplified spatial distribution of soil characteristics and then considering the real spatial distribution of soil types
A physically-based and distributed tool for modeling the hydrological and mechanical processes of shallow landslides
No full textThis work presents the capabilities of a model, i.e. the tRIBS-VEGGIE-Landslide, in two different versions, i.e. developed within a probabilistic framework and coupled with a root cohesion module. The probabilistic model treats geotechnical and soil retention curve parameters as random variables across the basin and estimates theoretical probability distributions of slope stability and the associated “factor of safety” commonly used to describe the occurrence of shallow landslides. The derived distributions are used to obtain the spatiotemporal dynamics of probability of failure, conditioned on soil moisture dynamics at each watershed location. The framework has been tested in the Luquillo Experimental Forest (Puerto Rico) where shallow landslides are common. In particular, the methodology was used to evaluate how the spatial and temporal patterns of precipitation, whose variability is significant over the basin, affect the distribution of probability of failure.
Another version of the model accounts for the additional cohesion exerted by vegetation roots. The approach is to use the Fiber Bundle Model (FBM) framework that allows for the evaluation of the root strength as a function of the stress-strain relationships of bundles of fibers. The model requires the knowledge of the root architecture to evaluate the additional reinforcement from each root diameter class. The root architecture is represented with a branching topology model based on Leonardo’s rule.
The methodology has been tested on a simple case study to explore the role of both hydrological and mechanical root effects. Results demonstrate that the effects of root water uptake can at times be more significant than the mechanical reinforcement; and that the additional resistance provided by roots depends heavily on the vegetation root structure and length
Assessing the hydrological changes due to land use alterations
Full text linkThe increase of urbanized areas and, consequently, of the impervious surfaces in land-use distributions may have important implications on the basin hydrological response. As a direct impact, the increase of cemented areas reduces the available storage volume for water in the watershed, which in turn exacerbates the runoff generation. Additionally, drainage pathways can be altered and the travel time to the watershed outlet considerably speeded up, with impacts on the hydrograph characteristics. The complex interactions among different hydrological processes make the estimations of the hydrological changes highly non linear.
The aim of this work is using an advanced physically-based and distributed model, i.e. tRIBS (TIN-based real-time integrated basin simulator), to evaluate how the changes in the hydrological properties affect the watershed response not only in terms of outlet discharge but also in terms of spatial distribution of the main hydrological variables (e.g., soil moisture patterns, groundwater level, etc...).
Moreover, we evaluate whether and how the spatial pattern of the impervious areas increase affects the change in the hydrological response.
The work has been carried out on the Baron Fork watershed, located in OK (USA), characterized by an area of about 800 km2 and for which the tRIBS model was successfully calibrated in the past. Specifically, we eval- uate the hydrological response for different extreme events typical of the area and different land-use configurations
Hydrological and mechanical effects of roots in shallow landslide analysis: A physically-based approach
No full textThis study provides the first insights of a methodology for estimating the additional cohesion exercised by vegetation roots in a hillslope landslide analysis within a coupled ecohydrological-stability model. The existing coupled system is able to simulate the spatial distribution and temporal dynamics of Factor of Safety (FS) as a function of soil moisture dynamics. The model takes into account the hydrological effects of vegetation which, through the root water uptaking, contributes in reducing the soil water content and, thus, in increasing the slope stability. The additional mechanical root cohesion is estimated in a Fiber Bundle Model (FBM) framework that allows for the evaluation of the root strength as a function of stress-strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture to evaluate the additional reinforcement from each root diameter class. In order to reproduce such characteristics, we adopted a branching topology model based on the Leonardo’s rule that gives an estimation of the amount of root and the diameters distribution with depth at particular stage of plant life. The methodology has been tested in a simple synthetic hillslope with different configurations of vegetation types, i.e. tree and shrubs. The topological model has been calibrated using observed root area (AR) profiles of two considered vegetation types
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
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