Abstract
As an important topographic attribute widely-used in precision agriculture, topographic wetness index (TWI) is designed to quantify the effect of local topography on hydrological processes and for modeling the spatial distribution of soil moisture and surface saturation. This index is formulated as TWI = ln(a/tanβ), where a is the upslope contributing area per unit contour length (or Specific Catchment Area, SCA) and tanβ is the local slope gradient for estimating a hydraulic gradient. The computation of both a and tanβ need to reflect impacts of local terrain on local drainage. Many of the existing flow direction algorithms for computing a use global parameters, which lead to unrealistic partitioning of flow. β is often approximated by slope gradient around the pixel. In fact, the downslope gradient of the pixel is a better approximation of β. This paper examines how TWI is impacted by a multiple flow routing algorithm adaptive to local terrain and the employment of maximum downslope gradient as β. The adaptive multiple flow routing algorithm partitions flow by altering the flow partition parameter based on local maximum downslope gradient. The proposed approach for computing TWI is quantitatively evaluated using four types of artificial terrains constructed as DEMs with a series of resolutions (1, 5, 10, 20, and 30 m), respectively. The result shows that the error of TWI computed using the proposed approach is generally lower than that of TWI by the widely used approach. The new approach was applied to a low-relief agricultural catchment (about 60 km2) in the Nenjiang watershed, Northeastern China. The results of this application show that the distribution of TWI by the proposed approach reflects local terrain conditions better.
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Acknowledgements
This study was supported by the National Natural Science Foundation of China (40501056; 40971235), the National Basic Research Program of China (2007CB407207), the National Key Technology R&D Program of China (2007BAC15B01), and the Knowledge Innovation Programs of the Chinese Academy of Sciences (KZCX2-YW-Q10-1-5). Supports from the Institute of Geographical Sciences and Natural Resources Research, the State Key Laboratory of Resources and Environmental Information Systems, and the University of Wisconsin-Madison (through its Vilas Associate Program and the Hamel Faculty Fellow Program) are also appreciated. We thank the anonymous reviewers and the editor for their constructive comments on an earlier version of this paper. We thank Dr. Yuxin Miao for kindly sharing the literatures in the 9th International Conference on Precision Agriculture.
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Qin, CZ., Zhu, AX., Pei, T. et al. An approach to computing topographic wetness index based on maximum downslope gradient. Precision Agric 12, 32–43 (2011). https://doi.org/10.1007/s11119-009-9152-y
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DOI: https://doi.org/10.1007/s11119-009-9152-y