Research of Impacts of the 2018 Hokkaido Eastern Iburi Earthquake on Sediment Transport in the Atsuma River Basin Using the SWAT Model

Chen, Yuechao; Nakatsugawa, Makoto; Ohashi, Hiroki

doi:10.3390/w13030356

Cited by 10 publications

(4 citation statements)

References 37 publications

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“…Fukuda et al [21] analyzed the sleep pattern data of junior high school students on the night of a blackout after an earthquake, comparing their sleep to a normal night. Chen et al [22] made a rough estimate of the sediment transport before and after the earthquake, and qualitatively judged that the sediment transport increased greatly after the earthquake. Although research on earthquakes has been in-depth and comprehensive, only a few researchers have quantified LULC change after an earthquake and studied its impact on the hydrological processes of the Atsuma River basin.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Changes in Land Use/Land Cover and Hydrological Processes Caused by Earthquakes in the Atsuma River Basin in Japan

Chen

Nakatsugawa

2021

Sustainability

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The 2018 Hokkaido Eastern Iburi earthquake and its landslides threaten the safety and stability of the Atsuma River basin. This study investigates land use and land cover (LULC) change by analyzing the 2015 and 2020 LULC maps of the basin, and its impact on runoff and sediment transport in the basin by using the soil and water assessment tool (SWAT) model to accurately simulate the runoff and sediment transport process. This study finds that the earthquake and landslide transformed nearly 10% of the forest into bare land in the basin. The simulation results showed that the runoff, which was simulated based on the 2020 LULC data, was slightly higher than that based on the 2015 LULC data, and the sediment transport after the earthquake is significantly higher than before. The rate of sediment transportation after the earthquake, adjusted according to the runoff, was about 3.42 times more than before. This shows that as the forest land decreased, the bare land increased. Conversely, the runoff increased slightly, whereas the sediment transport rate increased significantly in the Atsuma River basin after the earthquake. In future, active governance activities performed by humans can reduce the amount of sediment transport in the basin.

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Section: Introductionmentioning

confidence: 99%

Analysis of Changes in Land Use/Land Cover and Hydrological Processes Caused by Earthquakes in the Atsuma River Basin in Japan

Chen

Nakatsugawa

2021

Sustainability

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“…The estimation of soil erosion was performed using two approaches, the first is based on the application of the RUSLE equation and the second is based on the application of the SWAT model which is based on the MUSLE model for estimating sediment yields [53]. The climatic data were used to calculate the rainfall erosivity factor (R).…”

Section: Methodology Adoptedmentioning

confidence: 99%

Water Erosion Monitoring and Prediction in Response to the Effects of Climate Change Using RUSLE and SWAT Equations: Case of R’Dom Watershed in Morocco

Alitane¹,

Essahlaoui²,

Hafyani³

et al. 2022

Land

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Soil erosion is an increasingly issue worldwide, due to several factors including climate variations and humans’ activities, especially in Mediterranean ecosystems. Therefore, the aim of this paper is: (i) to quantify and to predict soil erosion rate for the baseline period (2000–2013) and a future period (2014–2027), using the Revised Universal Soil Loss Equation (RUSLE) and the Soil and Water Assessment Tool (SWAT) model in the R’Dom watershed in Morocco, based on the opportunities of Remote Sensing (RS) techniques and Geographical Information System (GIS) geospatial tools. (ii) we based on classical statistical downscaling model (SDSM) for rainfall prediction. Due to the lack of field data, the model results are validated by expert knowledge. As a result of this study, it is found that both agricultural lands and bare lands are most affected by soil erosion. Moreover, it is showed that soil erosion in the watershed was dominated by very low and low erosion. Although the area of very low erosion and low erosion continued to decrease. Hence, we hereby envisage that our contribution will provide a more complete understanding of the soil degradation in this study area and the results of this research could be a crucial reference in soil erosion studies and also may serve as a valuable guidance for watershed management strategies.

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“…To verify the accuracy of the simulation results, the error analysis was carried out. It was based on the Nash-Sutcliffe Efficiency coefficient (NSE; Chen et al 2021), and the wave shape error, the volume error, the peak flow error defined by the Japanese Institute of Construction Engineering. The error analysis methods and indicators are shown in Table 4.…”

Section: Error Analysismentioning

confidence: 99%

Application study of IFAS and LSTM models on runoff simulation and flood prediction in the Tokachi River basin

Chen

Gao

Bin

et al. 2021

Journal of Hydroinformatics

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Floods are often caused by short-term heavy rainfall. An Integrated Flood Analysis System (IFAS) model is good at runoff simulation and a Long Short-Term Memory (LSTM) model is good at learning massive data and realizing rainfall forecast. In this paper, the applicability of the IFAS model to runoff simulation in the Tokachi River basin and the LSTM model to forecast hourly rainfall was studied, and the accuracy of flood prediction was also studied by inputting the optimal rainfall data forecasted by the LSTM model into the IFAS model. The research results show that the IFAS model can accurately simulate the runoff process in the Tokachi River basin. In the calibration period and the verification period, the Nash–Sutcliffe efficiency coefficient (NSE) of all simulation results are above 0.75; the LSTM model can achieve forecast hourly rainfall with high precision, the NSE of best forecast results is 0.86; the IFAS model can achieve flood prediction with high precision by using the optimal rainfall data forecasted by the LSTM model, the NSE of simulation result is 0.81. The above conclusions show that it is of great significance to combine the hourly rainfall forecasted by the LSTM model with the IFAS model for flood prediction.

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Research of Impacts of the 2018 Hokkaido Eastern Iburi Earthquake on Sediment Transport in the Atsuma River Basin Using the SWAT Model

Cited by 10 publications

References 37 publications

Analysis of Changes in Land Use/Land Cover and Hydrological Processes Caused by Earthquakes in the Atsuma River Basin in Japan

Analysis of Changes in Land Use/Land Cover and Hydrological Processes Caused by Earthquakes in the Atsuma River Basin in Japan

Water Erosion Monitoring and Prediction in Response to the Effects of Climate Change Using RUSLE and SWAT Equations: Case of R’Dom Watershed in Morocco

Application study of IFAS and LSTM models on runoff simulation and flood prediction in the Tokachi River basin

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