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An integrated method for calculating DEM-based RUSLE LS

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Abstract

The improvement of resolution of digital elevation models (DEMs) and the increasing application of the Revised Universal Soil Loss Equation (RUSLE) over large areas have created problems for the efficiency of calculating the LS factor for large data sets. The pretreatment for flat areas, flow accumulation, and slope-length calculation have traditionally been the most time-consuming steps. However, obtaining these features are generally usually considered as separate steps, and calculations still tend to be time-consuming. We developed an integrated method to improve the efficiency of calculating the LS factor. The calculation model contains algorithms for calculating flow direction, flow accumulation, slope length, and the LS factor. We used the Deterministic 8 method to develop flow-direction octrees (FDOTs), flat matrices (FMs) and first-in-first-out queues (FIFOQs) tracing the flow path. These data structures were much more time-efficient for calculating the slope length inside the flats, the flow accumulation, and the slope length linearly by traversing the FDOTs from their leaves to their roots, which can reduce the search scope and data swapping. We evaluated the accuracy and effectiveness of this integrated algorithm by calculating the LS factor for three areas of the Loess Plateau in China and SRTM DEM of China. The results indicated that this tool could substantially improve the efficiency of LS-factor calculations over large areas without reducing accuracy.

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References

  • Appels WM, Bogaart PW, Zee SEATMvd (2016) Surface runoff in flat terrain: How field topography and runoff generating processes control hydrological connectivity. J Hydrol 534:493–504

    Article  Google Scholar 

  • Bai R, Li T, Huang Y, Li J, Wang G (2015) An efficient and comprehensive method for drainage network extraction from DEM with billions of pixels using a size-balanced binary search tree. Geomorphology 238:56–67

    Article  Google Scholar 

  • Barnes R, Lehman C, Mulla D (2014) An efficient assignment of drainage direction over flat surfaces in raster digital elevation models. Pergamon Press, Inc, Oxford

    Google Scholar 

  • Byun J, Seong YB (2015) An algorithm to extract more accurate stream longitudinal profiles from unfilled DEMs. Geomorphology 242:38–48

    Article  Google Scholar 

  • Do HT, Limet S, Melin E (2011) Parallel computing flow accumulation in large digital elevation models. Procedia Comput Sci 4:2277–2286

    Article  Google Scholar 

  • Fatih G (2010) A new algorithm for extraction of continuous channel networks without problematic parallels from hydrologically corrected. DEMs Boletim De Ciencias Geodesicas 16:20–38

    Google Scholar 

  • Garbrecht J, Martz LW (1997) The assignment of drainage direction over flat surfaces in raster digital elevation models. J Hydrol 193:204–213

    Article  Google Scholar 

  • Govers G, Desmet PJJ (1995) A procedure for the calculation of the LS-factor for USLE-type models on topographically complex landscape units. J Clin Pathol 14:305–308

    Google Scholar 

  • Hickey R (2000) Slope Angle and Slope Length Solutions for GIS Cartography 29:1–8

    Article  Google Scholar 

  • Hickey R, Smith A, Jankowski P (1994) Slope length calculations from a DEM within ARC/INFO grid. Comput Environ Urban Syst 18:365–380

    Article  Google Scholar 

  • Hua Z, Huang GH (2009) Building channel networks for flat regions in digital elevation models. Hydrol Process 23:2879– 2887

    Article  Google Scholar 

  • Koo JY, Yoon DS, Dong JL, Han JH, Jung Y, Yang JE, Lim KJ (2016) Effect of DEM Resolution in USLE LS Factor. Journal of Korean Society on Water Environment 32:89–97

    Article  Google Scholar 

  • Liu K, Tang G, Jiang L, Zhu AX, Yang J, Song X (2015) Regional-scale calculation of the LS factor using parallel processing. Comput Geosci 78:110–122

    Article  Google Scholar 

  • Mccool DK, Foster GR, Mutchler CK, Meyer LD (1989) Revised slope length factor for the universal soil loss equation. Trans Asae 30:1387–1396

    Article  Google Scholar 

  • Moore ID, Wilson JP (1992) Length-slope factors for the revised universal soil loss equation: Simplified method of estimation. In: Journal of Soil & Water Conservation, pp 423-428

  • O’Callaghan JF, Mark DM (1984) The extraction of drainage networks from digital elevation data. Comput Vis Graph Image Process 28:323–344

    Article  Google Scholar 

  • Qin CZ, Zhan L (2012) Parallelizing flow-accumulation calculations on graphics processing units-From iterative DEM preprocessing algorithm to recursive multiple-flow-direction algorithm. Pergamon Press, Inc, Oxford

    Google Scholar 

  • Remortel RDV, Maichle RW, Hickey RJ (2004) Computing the LS factor for the Revised Universal Soil Loss Equation through array-based slope processing of digital elevation data using a C++ executable. Comput Geosci 30:1043–1053

    Article  Google Scholar 

  • Renard KG, Foster GR, Weesies GA, Mccool DK, Yoder DC (1997) Predicting soil erosion by water: a guide to conservation planning with the revised universal soil loss equation (RUSLE) agriculture handbook

  • Su C, Feng C, Wang X, Huang Z, Zhang X (2016) An efficient algorithm for assignment of flow direction over flat surfaces in raster DEMs based on distance transform. Earth Sci Inf 9:225–233

    Article  Google Scholar 

  • Wang H, Fu X, Wang G (2013) Multi-tree Coding Method (MCM) for drainage networks supporting high-efficient search. Comput Geosci 52:300–306

    Article  Google Scholar 

  • Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses - a guide to conservation planning United Statesdeptof Agricultureagriculture Handbook 537

  • Yang QK, Mcvicar TR, Niel TGV, Hutchinson MF, Li LT, Zhang XP (2007) Improving a digital elevation model by reducing source data errors and optimising interpolation algorithm parameters: An example in the Loess Plateau. China Int J Appl Earth Obs Geoinf 9:235–246

    Article  Google Scholar 

  • Zhang H et al (2013) Extension of a GIS procedure for calculating the RUSLE equation LS factor. Comput Geosci 52:177–188

    Article  Google Scholar 

  • Zhang H et al (2017) An integrated algorithm to evaluate flow direction and flow accumulation in flat regions of hydrologically corrected. DEMs Catena 151:174–181

    Article  Google Scholar 

  • Zhang H, Yang Q, Rui L, Liu Q (2012) Estimation methods of slope steepness and slope length in watershed based on GIS and multiple flow direction algorithm. Trans Chinese Soc Agric Eng 28:159–164

    Google Scholar 

Download references

Acknowledgements

This work was financially supported by Major Project of Chinese National Natural Science Foundation (41771315, 41301283, 41371274, 61402374), National Key R & D Plan from the MOST of China (2017YFC0403203) and EU Horizon 2020 research and innovation programme (ISQAPER: 635750). Sincere thanks to Yuping Li, Shuai Wang, Tong Wang’s help for source code modification. Thanks to Dr. William Blackhall for language edition. Thanks also to the anonymous reviewers and who all made valuable comments that improved our paper.

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Authors and Affiliations

  1. Northwest A&F University, College of Information Engineering, Yangling, Shaanxi, 712100, China

    Meng Wang, Hongming Zhang, Shuqin Li, Jiangtao Yang, Cheng Cai & Meili Wang

  2. Wageningen University, Soil Physics and Land Management Group, Droevendaalsesteeg 4,6708 PB, Wageningen, The Netherlands

    Jantiene E. M. Baartman, Coen J. Ritsema & Violette Geissen

  3. Department of Urbanology and Resource Science, Northwest University, Xi’an, Shaanxi, 710069, China

    Qinke Yang

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  1. Meng Wang
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  2. Jantiene E. M. Baartman
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  3. Hongming Zhang
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  4. Qinke Yang
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  5. Shuqin Li
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  6. Jiangtao Yang
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  7. Cheng Cai
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  8. Meili Wang
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  9. Coen J. Ritsema
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Correspondence to Hongming Zhang.

Additional information

Communicated by: H. A. Babaie

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Wang, M., Baartman, J.E.M., Zhang, H. et al. An integrated method for calculating DEM-based RUSLE LS. Earth Sci Inform 11, 579–590 (2018). https://doi.org/10.1007/s12145-018-0349-3

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  • DOI: https://doi.org/10.1007/s12145-018-0349-3

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