期刊
PRECISION AGRICULTURE
卷 12, 期 1, 页码 32-43出版社
SPRINGER
DOI: 10.1007/s11119-009-9152-y
关键词
Topographic wetness index (TWI); Multiple flow direction algorithm (MFD); Digital terrain analysis; Digital elevation model (DEM); Resolution
资金
- National Natural Science Foundation of China [40501056, 40971235]
- National Basic Research Program of China [2007CB407207]
- National Key Technology R&D Program of China [2007BAC15B01]
- Chinese Academy of Sciences [KZCX2-YW-Q10-1-5]
- Institute of Geographical Sciences and Natural Resources Research
- State Key Laboratory of Resources and Environmental Information Systems
- University of Wisconsin-Madison
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/tan beta), where a is the upslope contributing area per unit contour length (or Specific Catchment Area, SCA) and tan beta is the local slope gradient for estimating a hydraulic gradient. The computation of both a and tan beta 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. beta is often approximated by slope gradient around the pixel. In fact, the downslope gradient of the pixel is a better approximation of beta. 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 beta. 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 km(2)) 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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