scholarly journals A hydrography upscaling method for scale-invariant parametrization of distributed hydrological models

2021 ◽  
Vol 25 (9) ◽  
pp. 5287-5313
Author(s):  
Dirk Eilander ◽  
Willem van Verseveld ◽  
Dai Yamazaki ◽  
Albrecht Weerts ◽  
Hessel C. Winsemius ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Flow Direction ◽  
Hydrological Models ◽  
Scale Invariant ◽  
Distributed Hydrological Models ◽  
Relationship Of ◽  
Improved Accuracy ◽  
Basin Boundaries ◽  
Independent Model

Abstract. Distributed hydrological models rely on hydrography data such as flow direction, river length, slope and width. For large-scale applications, many of these models still rely on a few flow direction datasets, which are often manually derived. We propose the Iterative Hydrography Upscaling (IHU) method to upscale high-resolution flow direction data to the typically coarser resolutions of distributed hydrological models. The IHU aims to preserve the upstream–downstream relationship of river structure, including basin boundaries, river meanders and confluences, in the D8 format, which is commonly used to describe river networks in models. Additionally, it derives representative sub-grid river length and slope parameters, which are required for resolution-independent model results. We derived the multi-resolution MERIT Hydro IHU dataset at resolutions of 30 arcsec (∼ 1 km), 5 arcmin (∼ 10 km) and 15 arcmin (∼ 30 km) by applying IHU to the recently published 3 arcsec MERIT Hydro data. Results indicate improved accuracy of IHU at all resolutions studied compared to other often-applied upscaling methods. Furthermore, we show that MERIT Hydro IHU minimizes the errors made in the timing and magnitude of simulated peak discharge throughout the Rhine basin compared to simulations at the native data resolutions. As the method is open source and fully automated, it can be applied to other high-resolution hydrography datasets to increase the accuracy and enhance the uptake of new datasets in distributed hydrological models in the future.

scholarly journals A hydrography upscaling method for scale invariant parametrization of distributed hydrological models

2020 ◽  
Author(s):  
Dirk Eilander ◽  
Willem van Verseveld ◽  
Dai Yamazaki ◽  
Albrecht Weerts ◽  
Hessel C. Winsemius ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Flow Direction ◽  
Hydrological Models ◽  
Scale Invariant ◽  
Distributed Hydrological Models ◽  
Relationship Of ◽  
Improved Accuracy ◽  
Basin Boundaries ◽  
Made In

Abstract. Distributed hydrological models rely on hydrography data such as flow direction, river length, slope and width. For large-scale applications, many of these models still rely on a few flow-direction datasets, which are often manually derived. We propose the Iterative Hydrography Upscaling (IHU) method to upscale high-resolution flow direction data to the typically coarser resolutions of distributed hydrological models. The IHU aims to preserve the upstream-downstream relationship of river structure, including basin boundaries, river meanders and confluences, in the D8 format, which is commonly used to describe river networks in models. Additionally, it derives sub-grid river attributes such as drainage area, river length, slope and width. We derived the multi-resolution MERIT Hydro IHU dataset at resolutions of 30 arcsec (~1 km), 5 arcmin (~10 km) and 15 arcmin (~30 km) by applying IHU to the recently published 3 arcsec MERIT Hydro data. Results indicate improved accuracy of IHU at all resolutions studied compared to other often applied methods. Furthermore, we show that using IHU-derived hydrography data minimizes the errors made in timing and magnitude of simulated peak discharge throughout the Rhine basin compared to simulations at the native data resolutions. As the method is fully automated, it can be applied to other high-resolution hydrography datasets to increase the accuracy and enhance the uptake of new datasets in distributed hydrological models in the future.

Global scale hydrological modelling at 100 m, 1 h resolution, in Python

2021 ◽  
Author(s):  
Kor de Jong ◽  
Marc van Kreveld ◽  
Debabrata Panja ◽  
Oliver Schmitz ◽  
Derek Karssenberg
Keyword(s):  
Large Scale ◽  
Model Building ◽  
Flow Direction ◽  
Building Blocks ◽  
Global Scale ◽  
Data Availability ◽  
Hydrological Models ◽  
Continental Scale ◽  
Modelling Framework ◽  
Scale Models

<p>Data availability at global scale is increasing exponentially. Although considerable challenges remain regarding the identification of model structure and parameters of continental scale hydrological models, we will soon reach the situation that global scale models could be defined at very high resolutions close to 100 m or less. One of the key challenges is how to make simulations of these ultra-high resolution models tractable ([1]).</p><p>Our research contributes by the development of a model building framework that is specifically designed to distribute calculations over multiple cluster nodes. This framework enables domain experts like hydrologists to develop their own large scale models, using a scripting language like Python, without the need to acquire the skills to develop low-level computer code for parallel and distributed computing.</p><p>We present the design and implementation of this software framework and illustrate its use with a prototype 100 m, 1 h continental scale hydrological model. Our modelling framework ensures that any model built with it is parallelized. This is made possible by providing the model builder with a set of building blocks of models, which are coded in such a manner that parallelization of calculations occurs within and across these building blocks, for any combination of building blocks. There is thus full flexibility on the side of the modeller, without losing performance.</p><p>This breakthrough is made possible by applying a novel approach to the implementation of the model building framework, called asynchronous many-tasks, provided by the HPX C++ software library ([3]). The code in the model building framework expresses spatial operations as large collections of interdependent tasks that can be executed efficiently on individual laptops as well as computer clusters ([2]). Our framework currently includes the most essential operations for building large scale hydrological models, including those for simulating transport of material through a flow direction network. By combining these operations, we rebuilt an existing 100 m, 1 h resolution model, thus far used for simulations of small catchments, requiring limited coding as we only had to replace the computational back end of the existing model. Runs at continental scale on a computer cluster show acceptable strong and weak scaling providing a strong indication that global simulations at this resolution will soon be possible, technically speaking.</p><p>Future work will focus on extending the set of modelling operations and adding scalable I/O, after which existing models that are currently limited in their ability to use the computational resources available to them can be ported to this new environment.</p><p>More information about our modelling framework is at https://lue.computationalgeography.org.</p><p><strong>References</strong></p><p>[1] M. Bierkens. Global hydrology 2015: State, trends, and directions. Water Resources Research, 51(7):4923–4947, 2015.<br>[2] K. de Jong, et al. An environmental modelling framework based on asynchronous many-tasks: scalability and usability. Submitted.<br>[3] H. Kaiser, et al. HPX - The C++ standard library for parallelism and concurrency. Journal of Open Source Software, 5(53):2352, 2020.</p>

scholarly journals Fractal analysis of urban catchments and their representation in semi-distributed models: imperviousness and sewer system

2016 ◽  
Author(s):  
Auguste Gires ◽  
Ioulia Tchiguirinskaia ◽  
Daniel Schertzer ◽  
Susana Ochoa Rodriguez ◽  
Patrick Willems ◽  
...  
Keyword(s):  
Fractal Dimension ◽  
Fractal Analysis ◽  
Fractal Dimensions ◽  
Hydrological Models ◽  
Scale Invariant ◽  
Sewer System ◽  
Distributed Models ◽  
Urban Catchments ◽  
Distributed Hydrological Models ◽  
Dimension Characteristic

Abstract. Fractal analysis relies on scale invariance and the concept of fractal dimension enables to characterise and quantify the space filled by a geometrical set exhibiting complex and tortuous patterns. Fractal tools have been widely used in hydrology but seldom in the specific context of urban hydrology. In this paper fractal tools are used to analyse surface and sewer data from 10 urban or peri-urban catchments located in 5 European countries. The aim was to characterise urban catchment properties accounting for the complexity and inhomogeneity typical of urban water systems. Sewer system density and imperviousness (roads or buildings), represented in rasterized maps of 2 m × 2 m pixels, were analysed to quantify their fractal dimension, characteristic of scaling invariance. The results showed that both sewer density and imperviousness exhibit scale invariant features and can be characterized with the help of fractal dimensions ranging from 1.6 to 2, depending on the catchment. In a given area consistent results were found for the two geometrical features, yielding a robust and innovative way of quantifying the level of urbanization. The representation of imperviousness in operational semi-distributed hydrological models for these catchments was also investigated by computing fractal dimensions of the geometrical sets made up of the sub-catchments with coefficients of imperviousness greater than a range of thresholds. It enabled to quantify how well spatial structures of imperviousness were represented in the urban hydrological models.

Wormholing in anisotropic media: Pore orientation effect on large-scale patterns

2020 ◽  
Author(s):  
Roi Roded ◽  
Piotr Szymczak ◽  
Ran Holtzman
Keyword(s):  
Large Scale ◽  
Flow Direction ◽  
Hierarchical Structures ◽  
Anisotropic Media ◽  
Viscous Fingering ◽  
Reactive Flow ◽  
Small Scale ◽  
Microfluidic Channels ◽  
Permeability Evolution ◽  
Scale Invariant

<p>The dissolution of fractured or porous media by reactive flow is often occurring preferentially, forming highly conductive channels, so-called “wormholes”. Wormhole formation prevails in subsurface karst where it can form extensive speleological systems, and is also significant for a large range of applications, e.g. well acidizing or CO<sub>2</sub> geo-sequestration. The underlying mechanism involves positive feedback between reaction and transport— the flow pathways that focus the reactive flow dissolve preferentially and increase their conductivity, and in turn their flow. An increased pressure ahead of the longer wormholes screens off the shorter ones, which ultimately cease to grow. Over time, the characteristic spacing between active (growing) wormholes increases, while their number declines, which results in a hierarchical scale-invariant distribution of wormhole lengths. Interestingly, a variety of other pattern-forming processes in nature show a similar competitive dynamics and emergent of hierarchical structures, with examples ranging from viscous fingering to crack propagation in brittle solids and side-branches growth in crystallization [1].</p><p>The importance of wormholing and its intriguing dynamics motivated intensive research, including on the emergence of reactive-infiltration instabilities [2], as well as on the effects of medium heterogeneity on the wormhole growth. Here, we study wormholing in anisotropic media using a network model of regular geometry— longitudinal channels (aligned along the main flow direction) and transverse ones, of a different average cross-section. Our simulations show that anisotropy substantially affects wormholing, controlling the characteristic spacing between the wormholes and the overall permeability evolution. In the case of wider transverse channels, wormhole interaction via the pressure field is enhanced, resulting in stronger wormhole competition and hence larger spacing. Conversely, in the extreme case of very narrow transverse channels, spacing becomes minimal and neighboring wormholes tend to merge. Simulations further reveal that narrow transverse channels promote the emergence of thinner and more conical wormholes with several side-branches.</p><p>Additionally, we discuss the relation between the wormhole development in an anisotropic medium and viscous fingering phenomena in a network of microfluidic channels [3]. Despite many similarities between these systems we also find important differences— while the spacing between viscous fingers increases linearly with anisotropy, the corresponding relation for wormholes turns out to be nonlinear. This nonlinearity could be attributed to the effect of anisotropy on wormhole shape and advancement velocity and is of interest for future investigation. Our findings contribute to the understanding of wormholing in geological systems and demonstrate how the small-scale features can fundamentally affect the resulting large-scale morphologies.</p><p>[1] Krug, J., Adv. Phys., 46, 139, 1997</p><p>[2] Ortoleva, P. et al, Amer. J. Sci., 287, 1008, 1987</p><p>[3] Budek, A. et al, Phys. Fluids, 27, 112109, 2015</p>

scholarly journals High-resolution meteorological forcing data for hydrological modelling and climate change impact analysis in the Mackenzie River Basin

2020 ◽  
Vol 12 (1) ◽  
pp. 629-645 ◽  
Author(s):  
Zilefac Elvis Asong ◽  
Mohamed Ezzat Elshamy ◽  
Daniel Princz ◽  
Howard Simon Wheater ◽  
John Willard Pomeroy ◽  
...  
Keyword(s):  
Climate Change ◽  
High Resolution ◽  
Impact Assessment ◽  
River Basin ◽  
Climate Change Impact ◽  
Large Scale ◽  
Historical Record ◽  
Hydrological Models ◽  
Climate Change Impact Assessment ◽  
Change Impact

Abstract. Cold region hydrology is very sensitive to the impacts of climate warming. Impacts of warming over recent decades in western Canada include glacier retreat, permafrost thaw, and changing patterns of precipitation, with an increased proportion of winter precipitation falling as rainfall and shorter durations of snow cover, as well as consequent changes in flow regimes. Future warming is expected to continue along these lines. Physically realistic and sophisticated hydrological models driven by reliable climate forcing can provide the capability to assess hydrological responses to climate change. However, the provision of reliable forcing data remains problematic, particularly in data-sparse regions. Hydrological processes in cold regions involve complex phase changes and so are very sensitive to small biases in the driving meteorology, particularly in temperature and precipitation, including precipitation phase. Cold regions often have sparse surface observations, particularly at high elevations that generate a large amount of runoff. This paper aims to provide an improved set of forcing data for large-scale hydrological models for climate change impact assessment. The best available gridded data in Canada are from the high-resolution forecasts of the Global Environmental Multiscale (GEM) atmospheric model and outputs of the Canadian Precipitation Analysis (CaPA), but these datasets have a short historical record. The EU WATCH ERA-Interim reanalysis (WFDEI) has a longer historical record but has often been found to be biased relative to observations over Canada. The aim of this study, therefore, is to blend the strengths of both datasets (GEM-CaPA and WFDEI) to produce a less-biased long-record product (WFDEI-GEM-CaPA) for hydrological modelling and climate change impact assessment over the Mackenzie River Basin. First, a multivariate generalization of the quantile mapping technique was implemented to bias-correct WFDEI against GEM-CaPA at 3 h ×0.125∘ resolution during the 2005–2016 overlap period, followed by a hindcast of WFDEI-GEM-CaPA from 1979. The derived WFDEI-GEM-CaPA data are validated against station observations as a preliminary step to assess their added value. This product is then used to bias-correct climate projections from the Canadian Centre for Climate Modelling and Analysis Canadian Regional Climate Model (CanRCM4) between 1950 and 2100 under RCP8.5, and an analysis of the datasets shows that the biases in the original WFDEI product have been removed and the climate change signals in CanRCM4 are preserved. The resulting bias-corrected datasets are a consistent set of historical and climate projection data suitable for large-scale modelling and future climate scenario analysis. The final historical product (WFDEI-GEM-CaPA, 1979–2016) is freely available at the Federated Research Data Repository at https://doi.org/10.20383/101.0111 (Asong et al., 2018), while the original and corrected CanRCM4 data are available at https://doi.org/10.20383/101.0162 (Asong et al., 2019).

scholarly journals River network and hydro-geomorphology parametrization for global river routing modelling at 1/12° resolution

2021 ◽  
Author(s):  
Simon Munier ◽  
Bertrand Decharme
Keyword(s):  
High Resolution ◽  
Water Resources ◽  
Spatial Resolution ◽  
Large Scale ◽  
Flow Direction ◽  
Global Scale ◽  
River Network ◽  
Added Value ◽  
The Impact ◽  
River Routing

Abstract. Global scale river routing models (RRMs) are commonly used in a variety of studies, including studies on the impact of climate change on extreme flows (floods and droughts), water resources monitoring or large scale flood forecasting. Over the last two decades, the increasing number of observational datasets, mainly from satellite missions, and the increasing computing capacities, have allowed better performances of RRMs, namely by increasing their spatial resolution. The spatial resolution of a RRM corresponds to the spatial resolution of its river network, which provides flow direction of all grid cells. River networks may be derived at various spatial resolution by upscaling high resolution hydrography data. This paper presents a new global scale river network at 1/12° derived from the MERIT-Hydro dataset. The river network is generated automatically using an adaptation of the Hierarchical Dominant River Tracing (DRT) algorithm, and its quality is assessed over the 70 largest basins of the world. Although this new river network may be used for a variety of hydrology-related studies, it is here provided with a set of hydro-geomorphological parameters at the same spatial resolution. These parameters are derived during the generation of the river network and are based on the same high resolution dataset, so that the consistency between the river network and the parameters is ensured. The set of parameters includes a description of river stretches (length, slope, width, roughness, bankfull depth), floodplains (roughness, sub-grid topography) and aquifers (transmissivity, porosity, sub-grid topography). The new river network and parameters are assessed by comparing the performances of two global scale simulations with the CTRIP model, one with the current spatial resolution (1/2°) and the other with the new spatial resolution (1/12°). It is shown that CTRIP at 1/12° overall outperforms CTRIP at 1/2°, demonstrating the added value of the spatial resolution increase. The new river network and the consistent hydro-geomorphology parameters may be useful for the scientific community, especially for hydrology and hydro-geology modelling, water resources monitoring or climate studies.

scholarly journals Which spatial discretization for distributed hydrological models? Proposition of a methodology and illustration for medium to large-scale catchments

2008 ◽  
Vol 12 (3) ◽  
pp. 769-796 ◽  
Author(s):  
J. Dehotin ◽  
I. Braud
Keyword(s):  
Land Use ◽  
Large Scale ◽  
Landscape Heterogeneity ◽  
Data Availability ◽  
Hydrological Processes ◽  
Hydrological Models ◽  
Spatial Discretization ◽  
General Methodology ◽  
Distributed Hydrological Models ◽  
Landscape Units

Abstract. Distributed hydrological models are valuable tools to derive distributed estimation of water balance components or to study the impact of land-use or climate change on water resources and water quality. In these models, the choice of an appropriate spatial discretization is a crucial issue. It is obviously linked to the available data, their spatial resolution and the dominant hydrological processes. For a given catchment and a given data set, the "optimal" spatial discretization should be adapted to the modelling objectives, as the latter determine the dominant hydrological processes considered in the modelling. For small catchments, landscape heterogeneity can be represented explicitly, whereas for large catchments such fine representation is not feasible and simplification is needed. The question is thus: is it possible to design a flexible methodology to represent landscape heterogeneity efficiently, according to the problem to be solved? This methodology should allow a controlled and objective trade-off between available data, the scale of the dominant water cycle components and the modelling objectives. In this paper, we propose a general methodology for such catchment discretization. It is based on the use of nested discretizations. The first level of discretization is composed of the sub-catchments, organised by the river network topology. The sub-catchment variability can be described using a second level of discretizations, which is called hydro-landscape units. This level of discretization is only performed if it is consistent with the modelling objectives, the active hydrological processes and data availability. The hydro-landscapes take into account different geophysical factors such as topography, land-use, pedology, but also suitable hydrological discontinuities such as ditches, hedges, dams, etc. For numerical reasons these hydro-landscapes can be further subdivided into smaller elements that will constitute the modelling units (third level of discretization). The first part of the paper presents a review about catchment discretization in hydrological models from which we derived the principles of our general methodology. The second part of the paper focuses on the derivation of hydro-landscape units for medium to large scale catchments. For this sub-catchment discretization, we propose the use of principles borrowed from landscape classification. These principles are independent of the catchment size. They allow retaining suitable features required in the catchment description in order to fulfil a specific modelling objective. The method leads to unstructured and homogeneous areas within the sub-catchments, which can be used to derive modelling meshes. It avoids map smoothing by suppressing the smallest units, the role of which can be very important in hydrology, and provides a confidence map (the distance map) for the classification. The confidence map can be used for further uncertainty analysis of modelling results. The final discretization remains consistent with the resolution of input data and that of the source maps. The last part of the paper illustrates the method using available data for the upper Saône catchment in France. The interest of the method for an efficient representation of landscape heterogeneity is illustrated by a comparison with more traditional mapping approaches. Examples of possible models, which can be built on this spatial discretization, are finally given as perspectives for the work.

scholarly journals Calibration and uncertainty issues of a hydrological model (SWAT) applied to West Africa

2006 ◽  
Vol 9 ◽  
pp. 137-143 ◽  
Author(s):  
J. Schuol ◽  
K. C. Abbaspour
Keyword(s):  
West Africa ◽  
Model Calibration ◽  
Large Scale ◽  
Assessment Tool ◽  
Hydrological Models ◽  
Scale Models ◽  
Distributed Hydrological Models ◽  
Water Assessment ◽  
River Niger

Abstract. Distributed hydrological models like SWAT (Soil and Water Assessment Tool) are often highly over-parameterized, making parameter specification and parameter estimation inevitable steps in model calibration. Manual calibration is almost infeasible due to the complexity of large-scale models with many objectives. Therefore we used a multi-site semi-automated inverse modelling routine (SUFI-2) for calibration and uncertainty analysis. Nevertheless, the question of when a model is sufficiently calibrated remains open, and requires a project dependent definition. Due to the non-uniqueness of effective parameter sets, parameter calibration and prediction uncertainty of a model are intimately related. We address some calibration and uncertainty issues using SWAT to model a four million km2 area in West Africa, including mainly the basins of the river Niger, Volta and Senegal. This model is a case study in a larger project with the goal of quantifying the amount of global country-based available freshwater. Annual and monthly simulations with the "calibrated" model for West Africa show promising results in respect of the freshwater quantification but also point out the importance of evaluating the conceptual model uncertainty as well as the parameter uncertainty.

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