Name
Abstract | ||
|---|---|---|
In the solution of streamflow problems, fully distributed hydrologic models (DHMs), which are based directly on governing equations, offer distinct advantages over conceptual rainfall-runoff models, which are derived from empirical observations. However, the primary problem associated with DHMs is that they consume more computational resources than other models, and as a result, they have not been as popular as their capabilities would imply. A parallel DHM software system for solving streamflow prediction problems has been implemented and analysed, and an investigation has been conducted of: the efficiency and scalability of the algorithm; load balancing among processors; interprocessor communication; disk performance. The load balancing algorithms show great promise for the kind of problem addressed. The software exhibits substantial parallel speedup, but the degree of speedup is limited by I/O costs. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1504/IJCAT.2005.006802 | IJCAT |
Keywords | Field | DocType |
conceptual rainfall-runoff model,substantial parallel speedup,load balancing,computational resource,streamflow problem,disk performance,parallel dhm software system,hydrologic model,o cost,streamflow prediction problem,primary problem,flood forecasting,message passing,hydrological modelling | Hydrological modelling,Flood forecasting,Load balancing (computing),Computer science,Software system,Software,Message passing,Distributed computing,Speedup,Scalability | Journal |
Volume | Issue | ISSN |
22 | 1 | 0952-8091 |
Citations | PageRank | References |
6 | 0.84 | 4 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Zhengtao Cui | 1 | 6 | 0.84 |
| Baxter E. Vieux | 2 | 6 | 1.18 |
| Henry Neeman | 3 | 49 | 12.90 |
| Fekadu Moreda | 4 | 6 | 0.84 |