Mapping inundation dynamics in a heterogeneous floodplain: Insights from integrating observations and modeling approach
Mapping inundation dynamics in a heterogeneous floodplain: Insights from integrating observations and modeling approach
复制标题
绘制异质洪泛区的洪水动态:综合观测和建模方法的见解
DOI:
10.1016/j.jhydrol.2019.02.039
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发表时间:
2019-05
影响因子:
6.4
通讯作者:
Zhang Qi
中科院分区:
文献类型:
--
作者:
Tan Zhiqiang;Li Yunliang;Xu Xiuli;Yao Jing;Zhang Qi
Determining the spatiotemporal dynamics of surface water in a heterogeneous floodplain is difficult, especially for its surrounding isolated lakes. Seasonal inundation patterns of these isolated lakes can be misestimated in a hydrodynamic model due to their short and erratic appearances. A surface water time series of Poyang Lake having an 8-day revisit frequency with a 30 m spatial resolution from 2000 to 2016 was conducted for the first time. This study was produced with a modified hierarchical spatiotemporal adaptive fusion model (HSTAFM) by integrating both Landsat and MODIS data. Discrepancies between model-based surface water and remotely-sensed surface water were evaluated, and possible causes were discussed. Results show that the modified HSTAFM can better detect the water features of a floodplain, thereby providing more detailed information in an seasonal isolated lake system than the MODIS MOD13Q1 product. With the fusion product, we found that Poyang Lake evidently shrank after experiencing a longer low-water period after the impoundment of the Three Gorges Dam. A large proportion of these discrepancies (averaging 36%) between model-based and remotely-sensed surface water distributed in seasonal isolated lakes, mainly occurred during high-water level periods. Uncertainties in the hydrodynamic model might attribute to smaller defined lake boundaries, bathymetric variations, human disturbance, and unconsidered groundwater recharge/discharge. These results provide a new insight into the temporally continuous and spatially dynamic assessment of simulated surface water, which is essential for the future improvement in the hydrodynamic model.
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影响因子:
2.3
作者:
Lu Shanlong;Jia Li;Zhang Lei;Wei Yongping;Baig Muhammad Hasan Ali;Zhai Zhaokun;Meng Jihua;Li Xiaosong;Zhang Guifang
通讯作者:
Zhang Guifang
影响因子:
2.7
作者:
Tan Zhiqiang;Z. Qi;Li Mengfan;Li Yunliang;X. Xiuli;Jiang Jiahu
通讯作者:
Tan Zhiqiang;Z. Qi;Li Mengfan;Li Yunliang;X. Xiuli;Jiang Jiahu
影响因子:
13.5
作者:
Hilker, Thomas;Wulder, Michael A.;White, Joanne C.
通讯作者:
White, Joanne C.
影响因子:
2
作者:
D. Shankman;B. Keim;T. Nakayama;R. Li;Dunyin Wu;W. C. Remington
通讯作者:
D. Shankman;B. Keim;T. Nakayama;R. Li;Dunyin Wu;W. C. Remington
影响因子:
6.4
作者:
Zhang X. L.;Zhang Q.;Werner A. D.;Tan Z. Q.
通讯作者:
Tan Z. Q.