ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
Publications Copernicus
Articles | Volume III-2
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 109–112, 2016
ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., III-2, 109–112, 2016

  02 Jun 2016

02 Jun 2016


Fangli Zhang1,2, Qiming Zhou2, Qingquan Li1, Guofeng Wu1, and Jun Liu3 Fangli Zhang et al.
  • 1Key Laboratory for Geo-Environmental Monitoring of Coastal Zone of the National Administration of Surveying, Mapping and GeoInformation & Shenzhen Key Laboratory of Spatial-temporal Smart Sensing and Services, Shenzhen University, Shenzhen, China
  • 2Department of Geography, Hong Kong Baptist University, Kowloon, Hong Kong, China
  • 3Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China

Keywords: Hydrologic Model, Rainfall Runoff Process, Flow Path Network, Particle System, Parallel Computing

Abstract. The simulation of rainfall-runoff process is essential for disaster emergency and sustainable development. One common disadvantage of the existing conceptual hydrological models is that they are highly dependent upon specific spatial-temporal contexts. Meanwhile, due to the inter-dependence of adjacent flow paths, it is still difficult for the RS or GIS supported distributed hydrological models to achieve high-performance application in real world applications. As an attempt to improve the performance efficiencies of those models, this study presents a high-performance rainfall-runoff simulating framework based on the flow path network and a separate particle system. The vector-based flow path lines are topologically linked to constrain the movements of independent rain drop particles. A separate particle system, representing surface runoff, is involved to model the precipitation process and simulate surface flow dynamics. The trajectory of each particle is constrained by the flow path network and can be tracked by concurrent processors in a parallel cluster system. The result of speedup experiment shows that the proposed framework can significantly improve the simulating performance just by adding independent processors. By separating the catchment elements and the accumulated water, this study provides an extensible solution for improving the existing distributed hydrological models. Further, a parallel modeling and simulating platform needs to be developed and validate to be applied in monitoring real world hydrologic processes.