TY - JOUR
T1 - MAPPING STREAMFLOW CHARACTERISTICS IN THE MOST UPSTREAM BASINS THROUGHOUT JAPAN USING ARTIFICIAL NEURAL NETWORKS
AU - Arai, Ryosuke
AU - Toyoda, Yasushi
AU - Kazama, So
N1 - Publisher Copyright:
© 2022 Japan Society of Civil Engineers. All rights reserved.
PY - 2022
Y1 - 2022
N2 - We developed and validated artificial neural networks (ANNs) to map the streamflow characteristics in the most upstream basins throughout Japan. The ANNs output mean annual runoff height (QMEAN) and percentiles of daily streamflow, including nine different groups, by inputting basin characteristics, including climate, land use, soils, geology, and topography. The generalization performances of the ANNs showed R2 = 0.70 in the QMEAN and R2 = 0.20 – 0.74 in the streamflow percentiles. We succeeded in mapping the streamflow characteristics in the most upstream basins throughout Japan, which reflected the rainfall and snowfall characteristics in the country. The streamflow characteristic maps revealed that developing run-of-river hydropower stations in heavy snowfall areas, such as the Tohoku and Hokuriku regions facing the Sea of Japan, is suitable.
AB - We developed and validated artificial neural networks (ANNs) to map the streamflow characteristics in the most upstream basins throughout Japan. The ANNs output mean annual runoff height (QMEAN) and percentiles of daily streamflow, including nine different groups, by inputting basin characteristics, including climate, land use, soils, geology, and topography. The generalization performances of the ANNs showed R2 = 0.70 in the QMEAN and R2 = 0.20 – 0.74 in the streamflow percentiles. We succeeded in mapping the streamflow characteristics in the most upstream basins throughout Japan, which reflected the rainfall and snowfall characteristics in the country. The streamflow characteristic maps revealed that developing run-of-river hydropower stations in heavy snowfall areas, such as the Tohoku and Hokuriku regions facing the Sea of Japan, is suitable.
KW - cross-validation
KW - data-driven approach
KW - flow regime
KW - run-of-river hydropower
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U2 - 10.2208/JOURNALOFJSCE.10.1_506
DO - 10.2208/JOURNALOFJSCE.10.1_506
M3 - Article
AN - SCOPUS:85143140352
SN - 2187-5103
VL - 10
SP - 506
EP - 512
JO - Journal of Japan Society of Civil Engineers
JF - Journal of Japan Society of Civil Engineers
IS - 1
ER -
