Error assessment of grid-based flow routing algorithms used in hydrological models

Zhou, Qiming; Liu, Xuejun

doi:10.1080/13658810210149425

Cited by 98 publications

(124 citation statements)

References 28 publications

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“…However, it is no doubt that measured data are always unsatisfactory. This leads to unknown errors inherent in measured data (Zhou & Liu, 2002 (Hosseini et al, 1993;Gotway et al, 1996;Zimmerman et al 1999;Erxleben et al, 2002;Vicente-Serrano et al, 2003;Attorre et al, 2007;Piazza et al, 2011) found that Kriging is the best one among all the existing interpolation models. Another phenomenon should be mentioned is that the frequency of interpolation methods compared varies considerably among methods and different studies have compared a suite of different methods, which makes it difficult to draw general conclusions.…”

Section: Comparison Results: Most Commonly Used Methods For Evaluatiomentioning

confidence: 99%

“…In this study, we took the similar approach as reported by Zhou and Liu (2002 by employing pre-defined standard surfaces for testing and comparing selected algorithms. As a result, the 'true' attribute value of any point on the standard surfaces which are pre-defined by known mathematical formulas can be acquired without errors.…”

Section: Design Of Mathematical Surfacesmentioning

confidence: 99%

See 1 more Smart Citation

Quantitative Evaluation of Spatial Interpolation Models Based on a Data-Independent Method

Liu¹,

Hu²,

Ma³

2011

Advances in Data, Methods, Models and Their Applications in Geoscience

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Section: Comparison Results: Most Commonly Used Methods For Evaluatiomentioning

confidence: 99%

Section: Design Of Mathematical Surfacesmentioning

confidence: 99%

Quantitative Evaluation of Spatial Interpolation Models Based on a Data-Independent Method

Liu¹,

Hu²,

Ma³

2011

Advances in Data, Methods, Models and Their Applications in Geoscience

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“…The root mean square error (RMSE) between the IFBFD result and the mathematical solution is presented for a number of different x values. For a detailed description of the test and the creation of the mathematical results and generated surfaces (see [13]). Based on the test, an x value of 1.4 was selected, judged to be most appropriate for convex surfaces.…”

Section: Resultsmentioning

confidence: 99%

Estimating surface flow over digital elevation models using a new improved form-based algorithm

Hasan

Pilesjö

Persson

2011

WIT Transactions on Ecology and the Environment

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This paper discusses new improvements of a form-based algorithm, which is used to estimate flow distribution over a continuous surface. In the new formbased algorithm (IFBFD), cells in a DEM are classified into five different classes. The classes are Peaks, Complicated, Sinks, Flats and Undisturbed cells. The method of how to estimate the flow distribution from each cell depends on its class. Estimating the flow distribution over flat area cells and sinks is done in an innovative way. The flow over a flat area can be either flow-out or flow-in. Flow-out occurs when one or more cells on the flat area border has an elevation lower than the flat area cells. The flat area is classified as 'flow-in' when all cells on the border of flat area have elevations higher than the flat area cells. The result is that the flow will be converged in the center of the flat area, and that cells will have no outflow (sink). Additionally, a culvert function is added to the new algorithm to enable the user to deal with man-made flow barriers like roads and railway lines. The new culvert function breaches the barrier and connects the flow between two defined points on both sides of it.The new algorithm is tested using the number of mathematical surfaces, as well as on a real DEM derived from LIDAR data. The results of comparing our new algorithm with some well-known algorithm used in most GIS programs shows that the IFBFD algorithm produces more realistic results than other algorithms. Tests show the capability of the new IFBFD algorithm to deal with different terrain types, flat areas and sinks, making it suitable for simulating the real flow distribution over any DEM without the need to e.g. fill sinks. Moreover, the IFBFD algorithm produces a convincing result when deriving the drainage network.

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“…Since water flow from several upslope cells may accumulate into a cell but only drains out to a single cell, this method can model convergent flow in valleys. However, it fails to model the flow divergence near ridge or hillslope areas (Zhou and Liu, 2002). To accommodate flow divergence, multiple flow directions (FD8) is then proposed by Freeman et al (1991).…”

Section: Methodsmentioning

confidence: 99%

“…Differences in algorithm-derived SCA have well been compared on ideal surface (e.g. Zhou and Liu, 2002;Florinsky, 1998;Wilson et al, 2000) or on hydrological simulation (Holmgren 1994;Quinn et al, 1995). However effects of algorithm-derived SCA on predicting slope failure have yet to be examined, particularly in subtropical mountainous watersheds with high rainfall and steep slope.…”

Section: Introductionmentioning

confidence: 99%

Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling

Huang

Kao

Hsu

et al. 2007

Nat. Hazards Earth Syst. Sci.

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Abstract. This study anatomized algorithm effects of specific contributing area (SCA) on soil wetness estimation, consequently landslide prediction, in SHALSTAB. A subtropical mountainous catchment during three typhoon invasions is targeted. The peak 2-day rainfall intensity of the three typhoons: Haitang, Mindulle and Herb are 144, 248 and 327 mm/day, respectively. We use modified success rate (MSR) to retrieve the most satisfying mean condition for model parameters in SHALSTAB at three rainfall intensities and respective pre-typhoon NDVI themes. Simulation indicates that algorithm affects the prediction of landslide susceptibility (i.e. FS, Factor of Safety) significantly.Based on fixed NDVI and the mean condition, we simulate by using full scale rainfall intensity from 0 to 1200 mm/day. Simulations show that predicted unstable area coverage increases non-linearly as rainfall intensity increases for all algorithms yet with different increasing trends. Compared to Dinf, D8 always gives lower coverage of predicted unstable area during three typhoons. By contrast, FD8 gives higher coverage areas. The absolute difference (compared to Dinf) in predicted unstable area ranges from ∼−3% to +4% (percent watershed area). The relative difference (compared to Dinf) ranges from −15% to as high as +40%. The maximum absolute and relative differences in unstable area prediction occur around the condition of 100-300 mm/day, which is common in subtropical mountainous region.Theoretical relationship among slope, rainfall intensity, SCA and FS value was derived in which FS values are very sensitive to algorithms in the field of slope from 37 to 52de-gree. Results imply any comparison among SCA-related landslide models or engineering application of rainfall return period analysis must base on the same algorithm to obtain comparable results. This study clarifies the SCA algorithm effect on FS prediction and deepens our understanding on landslide modeling.

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Error assessment of grid-based flow routing algorithms used in hydrological models

Cited by 98 publications

References 28 publications

Quantitative Evaluation of Spatial Interpolation Models Based on a Data-Independent Method

Quantitative Evaluation of Spatial Interpolation Models Based on a Data-Independent Method

Estimating surface flow over digital elevation models using a new improved form-based algorithm

Influence of Specific Contributing Area algorithms on slope failure prediction in landslide modeling

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