Impact assessment of rainfall-vegetation on sedimentation and predicting erosion-prone region by GIS and RS

被引:5
|
作者
Alam, Mahboob [1 ]
Hussain, Raja Rizwan [2 ]
Islam, A. B. M. Saiful [3 ]
机构
[1] COMSATS Inst Informat Technol, Dept Meteorol, Islamabad 44000, Pakistan
[2] King Saud Univ, Coll Engn, Dept Civil Engn, Riyadh 11421, Saudi Arabia
[3] Univ Malaya, Fac Engn, Dept Civil Engn, Kuala Lumpur 50603, Malaysia
关键词
SPAR PLATFORM; ENERGY;
D O I
10.1080/19475705.2014.942387
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
Water reservoirs are facing universal sedimentation problems worldwide. Land covers, whether natural or manmade, eventually change, and the vegetation cover and rainfall have a great effect on the sediment load. Traditional techniques for analysing this problem are time-consuming and spatially limited. Remote sensing (RS) provides a convenient way to observe land cover changes, and geographic information system (GIS) provides tools for geographic analysis. This study demonstrates a GIS-based methodology for calculating the impact of vegetation and rainfall on the sediment load using remotely sensed data. Moderate resolution imaging spectroradiometer data were used to observe temporal changes in the vegetation-cover area of the watershed surface. The total drainage area for the reservoir was calculated from shuttle radar topographic mission data. The annual rainfall amount was used to compute the annual available rainwater for the watershed, and the impact of the annual available rainwater on the vegetation-covered area was determined. In addition, areas that were adding sedimentation to the reservoir were identified. An inverse relationship between the rainfall and vegetation cover was observed, clearly showing the triggering of erosion.
引用
收藏
页码:667 / 679
页数:13
相关论文
共 5 条
  • [1] Prioritizing erosion-prone area through morphometric analysis: an RS and GIS perspective
    Sarita Gajbhiye
    S. K. Mishra
    Ashish Pandey
    [J]. Applied Water Science, 2014, 4 (1) : 51 - 61
  • [2] Prioritizing erosion-prone area through morphometric analysis: an RS and GIS perspective
    Gajbhiye, Sarita
    Mishra, S. K.
    Pandey, Ashish
    [J]. APPLIED WATER SCIENCE, 2014, 4 (01) : 51 - 61
  • [3] Erosive Rainfall Thresholds Identification Using Statistical Approaches in a Karst Yellow Soil Mountain Erosion-Prone Region in Southwest China
    Deng, Ou
    Li, Man
    Yang, Binglan
    Yang, Guangbin
    Li, Yiqiu
    [J]. AGRICULTURE-BASEL, 2024, 14 (08):
  • [4] Soil erosion and degradation assessment integrating multi-parametric methods of RUSLE model, RS, and GIS in the Shaqlawa agricultural area, Kurdistan Region, Iraq
    Abdi, Badeea
    Kolo, Kamal
    Shahabi, Himan
    [J]. ENVIRONMENTAL MONITORING AND ASSESSMENT, 2023, 195 (10)
  • [5] Soil erosion and degradation assessment integrating multi-parametric methods of RUSLE model, RS, and GIS in the Shaqlawa agricultural area, Kurdistan Region, Iraq
    Badeea Abdi
    Kamal Kolo
    Himan Shahabi
    [J]. Environmental Monitoring and Assessment, 2023, 195