scholarly journals Deriving a global river network map at flexible resolutions from a fine-resolution flow direction map with explicit representation of topographical characteristics in sub-grid scale

2009 ◽  
Vol 6 (4) ◽  
pp. 5019-5046
Author(s):  
D. Yamazaki ◽  
T. Oki ◽  
S. Kanae

Abstract. This paper proposes an improved method to convert a fine-resolution flow direction map into a coarse-resolution river network map for the use in global river routing models. The proposed method attempts to preserve the river network structure of an original fine-resolution map in upscaling procedures, which has not been achieved by previous methods. It is found that the problem in previous methods is mainly due to the traditional way of describing downstream cells of a river network map with a direction toward one of the eight neighboring cells. Instead in the improved method, the downstream cell can be flexibly located onto any cells in the river network map. The improved method is applied to derive global river network maps at various resolutions. It succeeded to preserve the river network structure of the original flow direction map, and consequently realizes automatic construction of river network maps at any resolutions. This enables both higher-resolution approach in global river routing models and inclusion of sub-grid scale topographic features, such as realistic river meanderings and catchment boundaries. Those advantages of the proposed method are expected to enhance ability of global river routing models, providing ways to represent surface water storage and movement such as river discharge and inundated area extent in much finer-scale than ever modeled.

2009 ◽  
Vol 13 (11) ◽  
pp. 2241-2251 ◽  
Author(s):  
D. Yamazaki ◽  
T. Oki ◽  
S. Kanae

Abstract. This paper proposes an improved method for converting a fine-resolution flow direction map into a coarse-resolution river network map for use in global river routing models. The proposed method attempts to preserve the river network structure of an original fine-resolution map in the upscaling procedure, as this has not been achieved with previous upscaling methods. We describe an improved method in which a downstream cell can be flexibly located on any cell in the river network map. The improved method preserves the river network structure of the original flow direction map and allows automated construction of river network maps at any resolution. Automated construction of a river network map is helpful for attaching sub-grid topographic information, such as realistic river meanderings and drainage boundaries, onto the upscaled river network map. The advantages of the proposed method are expected to enhance the ability of global river routing models by providing ways to more precisely represent surface water storage and movement.


2021 ◽  
Author(s):  
Simon Munier ◽  
Bertrand Decharme

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.


2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Peirong Lin ◽  
Ming Pan ◽  
Eric F. Wood ◽  
Dai Yamazaki ◽  
George H. Allen

AbstractSpatial variability of river network drainage density (Dd) is a key feature of river systems, yet few existing global hydrography datasets have properly accounted for it. Here, we present a new vector-based global hydrography that reasonably estimates the spatial variability of Dd worldwide. It is built by delineating channels from the latest 90-m Multi-Error-Removed Improved Terrain (MERIT) digital elevation model and flow direction/accumulation. A machine learning approach is developed to estimate Dd based on the global watershed-level climatic, topographic, hydrologic, and geologic conditions, where relationships between hydroclimate factors and Dd are trained using the high-quality National Hydrography Dataset Plus (NHDPlusV2) data. By benchmarking our dataset against HydroSHEDS and several regional hydrography datasets, we show the new river flowlines are in much better agreement with Landsat-derived centerlines, and improved Dd patterns of river networks (totaling ~75 million kilometers in length) are obtained. Basins and estimates of intermittent stream fraction are also delineated to support water resources management. This new dataset (MERIT Hydro–Vector) should enable full global modeling of river system processes at fine spatial resolutions.


2019 ◽  
Vol 221 ◽  
pp. 377-388 ◽  
Author(s):  
Song Song ◽  
Lin Zeng ◽  
Yuefeng Wang ◽  
Guang Li ◽  
Xiaojun Deng

1992 ◽  
Vol 38 (128) ◽  
pp. 3-8 ◽  
Author(s):  
Peter G. Knight

AbstractThis paper describes fine-resolution measurements of glacier surface strain rates very close to the margin of Russell Glacier, West Greenland. Measurements at a small scale make possible detailed analysis of strain patterns close to the glacier margin, and suggest that strain rates vary over small areas. The strain pattern is determined by ice flexure over subglacial obstacles as well as by seasonally variable marginal retardation and by the orientation of the ice margin relative to the flow direction.


2003 ◽  
Vol 20 (7) ◽  
pp. 1060-1068 ◽  
Author(s):  
Igor Shulman ◽  
Steven H. D. Haddock ◽  
Dennis J. McGillicuddy ◽  
Jeffrey D. Paduan ◽  
W. Paul Bissett

Abstract Bioluminescence (BL) predictability experiments (predictions of the intensity, depth, and distance offshore of the BL maximum) were conducted using an advective–diffusive tracer model with velocities and diffusivities from a fine-resolution model of the Monterey Bay, California, area. For tracer initialization, observations were assimilated into the tracer model while velocities and diffusivities were taken from the hydrodynamic model and kept unchanged during the initialization process. This dynamic initialization procedure provides an equilibrium tracer distribution that is balanced with the velocity and diffusivity fields from the hydrodynamic model. This equilibrium BL distribution was used as the initial BL field for 3 days of prognostic calculations. Two cross-shore surveys of bioluminescence data conducted at two locations (north of the bay and inside the bay) were used in four numerical experiments designed to estimate the limits of bioluminescence predictions by tracers. The cross-shore sections extended to around 25 km offshore, they were around 30 m deep, and on average they were approximately 35 km apart from each other. Bioluminescence predictability experiments demonstrated a strong utility of the tracer model (combined with limited bioluminescence observations and with the output from a circulation model) in predicting (over a 72-h period and over 25–35-km distances) the location and intensity of the BL maximum. Analysis of the model velocity fields and observed and model-predicted bioluminesence fields shows that the BL maximum is located in the frontal area representing a strong reversal of flow direction.


2018 ◽  
Vol 30 (6) ◽  
pp. 1722-1731
Author(s):  
LIN Zhixin ◽  
◽  
XU Youpeng ◽  
DAI Xiaoying ◽  
WANG Qiang ◽  
...  

2015 ◽  
Vol 26 (05) ◽  
pp. 1550059 ◽  
Author(s):  
Xiao-Lei Tong ◽  
Jian-Guo Liu ◽  
Jiang-Pan Wang ◽  
Qiang Guo ◽  
Jing Ni

Ranking nodes by their spreading ability in complex networks is of vital significance to better understand the network structure and more efficiently spread information. The k-shell decomposition method could identify the most influential nodes, namely network core, with the same ks values regardless to their different spreading influence. In this paper, we present an improved method based on the k-shell decomposition method and closeness centrality (CC) to rank the node spreading influence of the network core. Experiment results on the data from the scientific collaboration network and U.S. aviation network show that the accuracy of the presented method could be increased by 31% and 45% than the one obtained by the degree k, 32% and 31% than the one by the betweenness.


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