An integrated method for calculating DEM-based RUSLE LS
- 93 Downloads
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.
KeywordsLS factor Revised universal soil loss equation (RUSLE) Soil erosion Geographic information system (GIS)
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.
- Barnes R, Lehman C, Mulla D (2014) An efficient assignment of drainage direction over flat surfaces in raster digital elevation models. Pergamon Press, Inc, OxfordGoogle Scholar
- Fatih G (2010) A new algorithm for extraction of continuous channel networks without problematic parallels from hydrologically corrected. DEMs Boletim De Ciencias Geodesicas 16:20–38Google 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 14:305–308Google 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 423-428Google 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, OxfordGoogle 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 handbookGoogle Scholar
- Wischmeier WH, Smith DD (1978) Predicting rainfall erosion losses - a guide to conservation planning United Statesdeptof Agricultureagriculture Handbook 537Google 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 28:159–164Google Scholar