scholarly journals Hydroinformatics advances for operational river forecasting: using graphs for drainage network descriptions

2010 ◽  
Vol 13 (2) ◽  
pp. 181-197 ◽  
Author(s):  
Zhengtao Cui ◽  
Victor Koren ◽  
Neftali Cajina ◽  
Andreas Voellmy ◽  
Fekadu Moreda
Keyword(s):  
Parallel Algorithm ◽  
Routing Algorithm ◽  
Computer Code ◽  
Illinois River ◽  
Distributed Model ◽  
Drainage Network ◽  
Grid Cells ◽  
Drainage Networks ◽  
Streamflow Forecasts ◽  
Illinois River Basin

Distributed hydrologic models provide accurate river streamflow forecasts and a multitude of spatially varied products on basin scales. The distributed elements of the basins are pieced together using drainage networks. An efficient representation of drainage networks in computer code is necessary. Graph theory has long been applied in many engineering areas to solve network problems. In this paper we demonstrate that adjacent list graph is the most efficient way of presenting the drainage network in terms of development and execution. The authors have implemented drainage networks using the adjacency-list structure in both the research and operational versions of the US National Weather Service (NWS) distributed model. A parallel routing algorithm based on Dijsktra's shortest path algorithm was also developed using the MPI library, which was tested on a cluster using the Oklahoma Illinois River basin dataset. Theoretical analysis and test results show that inter-processor communication and unbalanced workload among the processors limit the scalability of the parallel algorithm. The parallel algorithm is more applicable to computers with high inter-processor bandwidth, and to basins where the number of grid cells is large and the maximum distance of the grid cells to the outlet is short.

Research for Combined Drainage Networks in Chuanfang River Basin of Kunming City Based on SWMM

2012 ◽  
Vol 170-173 ◽  
pp. 2380-2385
Author(s):  
Xiao Min Zhu ◽  
Bing Huang ◽  
Shu Dong Wang ◽  
Jin Long Zheng ◽  
Bo Yao ◽  
...  
Keyword(s):  
River Basin ◽  
Drainage System ◽  
Sewage Water ◽  
Management Model ◽  
Peak Time ◽  
Drainage Network ◽  
Efficiency Coefficient ◽  
Storm Water Management Model ◽  
Drainage Networks ◽  
Water Base

A model for simulating combined drainage networks in Chuangfang river basin of Kunming City based on the Storm Water Management Model was established. The type and period of using water base on residential area, marketplace, school area, and guesthouse area Kunming city were introduced into the model, and their infection for drainage system was research. The results show that simulation results of two outlets flow have coherence with monitoring data based two typical rainfall in Kunming, the Nash-Sutcliffe efficiency coefficient is 0.71-0.82. And the model can be using analyze ‘bottleneck’ nodes and restricting conduits, simulating the running status of drainage network of combined drainage at raining and draining peak time of sewage water. The research provide strong technical support for rebuild drainage network in Kunming or other city.

Progress in the use of drainage network indices for rainfall-runoff modelling and runoff prediction

1994 ◽  
Vol 18 (4) ◽  
pp. 539-557 ◽  
Author(s):  
Geraldene Wharton
Keyword(s):  
Drainage Basin ◽  
Dynamic Network ◽  
Network Routing ◽  
Future Research ◽  
Drainage Network ◽  
Rainfall Runoff ◽  
Widespread Application ◽  
Digital Format ◽  
Drainage Networks ◽  
Runoff Prediction

Traditional catchment-based approaches to runoff prediction suffer from the problem that it is difficult to interpret the collective physical significance of a large number of intercorrelated drainage basin variables. This has highlighted the need for a sensitive and meaningful index to relate the basin character to the discharge produced. Network routing models also require an appropriate descriptor of drainage basin form to relate to hydrologic response characteristics. An index of the drainage network is potentially the most valuable because it responds to precipitation, reflects the characteristics of the basin and affects runoff. Although a large number of drainage network indices have been developed they have proved inadequate in their failure to describe the dynamic nature of drainage networks. Future research into the use of drainage networks for rainfall- runoff modelling and runoff prediction needs to have as its central aim the development of a dynamic network index which has physical meaning for drainage basins of all sizes and which is quick and easy to calculate from data that are rapidly obtainable. Despite the improved resolution of satellite imagery its high cost still prevents the widespread application of satellite remote sensing techniques to monitoring storm-specific drainage network changes. However, the increased availability of topographic data in digital format and the recent developments in digital elevation models (DEMs) have demonstrated the potential for the rapid derivation of both perennial and extended drainage networks from which network expansion potential can be calculated.

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