Application of remote sensing information about land use-land cover in flood forecasting with the Xinlanjiang model

被引:3
|
作者
Ren, LL [1 ]
An, R
Jiang, HM
Yuan, F
Wang, MR
机构
[1] Hohai Univ, Key Lab Water Resources Dev, Minist Educ, Coll Water Resources & Environm, Nanjing 210098, Peoples R China
[2] Beijing Bur Hydrol, Beijing 100039, Peoples R China
基金
中国国家自然科学基金;
关键词
D O I
10.5589/m04-034
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
摘要
Grid-based digital elevation data with a spatial resolution of 30 s of latitude or longitude, covering the Hanjiang River basin, were matched spatially with a 1 km x 1 km grid of land use - land cover data generated from remotely sensed data. The ratio of impervious area to subcatchment area (denoted IMP), a parameter in the Xin'anjiang model, can then be extracted directly from the land use - land cover data. Soil free water storage capacity (SM), a sensitive parameter in the Xin'aniiang model, can be obtained for the subcatchment by the relation between SM and the ratio of forest land area to subcatchment area. Thus, in the proposed semidistributed hydrological model, the spatial variability of land surface characteristics is taken into consideration. As a result, the physical meanings of model parameters are so clear that they can be extended from gauged catchments to ungauged catchments according to the land surface characteristics over the catchments. The accuracy of flood forecasting is improved as well. A case study of 24 flood events within the Baohe River, the upper tributary of the Hanjiang River, has shown that constructing the relationship between model parameters and land surface characteristics is an effective way to reduce errors in flood forecasting. In concrete terms, if the result computed by the semidistributed algorithm is compared with the result obtained by the lumped subcatchment algorithm, the Nash-Sutcliffe coefficients of 15 flood events increase, and the relative errors of 22 flood peaks decrease markedly. Also, the sensitivity of SM to flood peak discharge is greater than its sensitivity to the Nash-Sutcliffe coefficient. The semidistributed hydrological model is of practical value to flood forecasting and to the quantitative description of land use - land cover change related to the water cycle. We are convinced that this research is also helpful in the operation of a water supply system for the middle route of the large project involving water transfer from southern to northern China.
引用
收藏
页码:788 / 796
页数:9
相关论文
共 50 条
  • [21] Land use-land cover change in Himalayas processes, patterns and implications
    Sen, KK
    Semwal, RL
    Maikhuri, RK
    Rao, KS
    Saxena, KG
    LAND USE - HISTORICAL PERSPECTIVES: FOCUS ON INDO-GANGETIC PLAINS, 2002, : 457 - 474
  • [22] Effects of land use-land cover on soil water and salinity contents
    Li, Ang
    Wu, Ying-zhen
    Cao, Su-zhen
    ECOLOGICAL FRONTIERS, 2024, 44 (02): : 307 - 314
  • [23] Effects of Land Use-Land Cover Thematic Resolution on Environmental Evaluations
    Pelorosso, Raffaeleyyy
    Apollonio, Ciro
    Rocchini, Duccio
    Petroselli, Andrea
    REMOTE SENSING, 2021, 13 (07)
  • [24] Application of Remote Sensing Tools to Assess the Land Use and Land Cover Change in Coatzacoalcos, Veracruz, Mexico
    Revuelta-Acosta, Josept David
    Guerrero-Luis, Edna Suhail
    Terrazas-Rodriguez, Jose Eduardo
    Gomez-Rodriguez, Cristian
    Alcala Perea, Gerardo
    APPLIED SCIENCES-BASEL, 2022, 12 (04):
  • [25] From Land Cover to Land Use: A Methodology to Assess Land Use from Remote Sensing Data
    Martinez, Susana
    Mollicone, Danilo
    REMOTE SENSING, 2012, 4 (04) : 1024 - 1045
  • [26] From land cover to land use: A methodology to assess land use from remote sensing data
    IBADER, GI-1934 TB Department of Botany, University of Santiago de Compostela , E-27002 Lugo, Spain
    不详
    Remote Sens., 4 (1024-1045):
  • [27] Assessment of urban heat island effect for different land use-land cover from micrometeorological measurements and remote sensing data for megacity Delhi
    Mohan, Manju
    Kikegawa, Yukihiro
    Gurjar, B. R.
    Bhati, Shweta
    Kolli, Narendra Reddy
    THEORETICAL AND APPLIED CLIMATOLOGY, 2013, 112 (3-4) : 647 - 658
  • [28] The Use of Remote Sensing and GIS for Land Use and Land Cover Mapping in Eswatini: A Review
    Simelane, Sabelo P.
    Hansen, Christel
    Munghemezulu, Cilence
    SOUTH AFRICAN JOURNAL OF GEOMATICS, 2021, 10 (02): : 181 - 206
  • [29] Land-use and Land-cover Analysis with Remote Sensing Images
    Liu, Jinmei
    Li, Jizhong
    2013 INTERNATIONAL CONFERENCE ON INFORMATION SCIENCE AND TECHNOLOGY (ICIST), 2013, : 1175 - 1177
  • [30] Effect of Canal on Land Use/Land Cover using Remote Sensing and GIS
    Mukherjee, S.
    Shashtri, S.
    Singh, C. K.
    Srivastava, P. K.
    Gupta, M.
    JOURNAL OF THE INDIAN SOCIETY OF REMOTE SENSING, 2009, 37 (03) : 527 - 537