Hydrological Simulation of Small River Basins in Northern Kyushu, Japan, During the Extreme Rainfall Event of July 5–6, 2017

2018 ◽  
Vol 13 (2) ◽  
pp. 396-409 ◽  
Author(s):  
Shakti P. C. ◽  
◽  
Tsuyoshi Nakatani ◽  
Ryohei Misumi
Keyword(s):  
River Basin ◽  
Extreme Rainfall ◽  
Heavy Rain ◽  
River Basins ◽  
Rainfall Event ◽  
Distributed Model ◽  
Heavy Rainfall Event ◽  
Extreme Rainfall Event ◽  
Hydrological Simulation ◽  
Mountainous River

Extreme rainfall and associated flooding are common during the summer in Japan. Heavy rain caused extensive damage in many parts of Kyushu, Japan, on July 5–6, 2017. Many small mountainous river basins were subject to the core of this heavy rainfall event and were flooded, but no hydrological measurements were taken in most of these flooded basins during the event. There are few gauging stations in this mountainous region, and most that do exist are designed to monitor the larger watersheds. Consequently, it is difficult to determine the hydrological properties of the small subbasins within these larger watersheds. Therefore, to improve our understanding of the basic hydrological processes that affect small ungauged mountain river basins during periods of intense rainfall, a quasi-distributed model (i.e. the Hydrologic Engineering Center-Hydrologic Modeling System, HEC-HMS) was used in this study. The Hikosan (area: 65 km2) and Akatani (area: 21 km2) mountainous river basins were selected for the hydrological simulations. The model was validated using the Hikosan River basin because observational data are available from the outlet of this basin. However, there is no record of any hydrological observations for the Akatani River basin. Therefore, reference parameters from the Hikosan River basin were used for hydrological analysis of the Akatani River basin. This was possible because the basins are close to one another and have similar physiographic and topographic properties. The simulations of both basins, and the associated uncertainties, are discussed in detail in this paper. Based on the hydrological simulations, an attempt was made to analyze the maximum flood discharge caused by the event. The results generated using this approach to hydrological simulations in small ungauged basins could contribute to the management of water resources in these and other river basins during future extreme rain events.

scholarly journals River discharge prediction for ungauged mountainous river basins during heavy rain events based on seismic noise data

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
Shakti P.C. ◽  
Kaoru Sawazaki
Keyword(s):  
River Basin ◽  
Seismic Noise ◽  
River Discharge ◽  
Heavy Rain ◽  
River Basins ◽  
Peak Discharge ◽  
Discharge Data ◽  
Noise Data ◽  
Rain Events ◽  
Mountainous River

AbstractSeveral mountainous river basins in Japan do not have a consistent hydrological record due to their complex environment and remoteness, as discharge measurements are not economically feasible. However, understanding the flow rate of rivers during extreme events is essential for preventing flood disasters around river basins. In this study, we used the high-sensitivity seismograph network (Hi-net) of Japan to identify the time and peak discharge of heavy rain events. Hi-net seismograph stations are distributed almost uniformly at distance intervals of approximately 20 km, while being available even in mountainous regions. The Mogami River Basin in Northeastern Japan was selected as a target area to compare the seismic noise data of two Hi-net stations with the hydrological response of a nearby river. These stations are not located near hydrological stations; therefore, direct comparison of seismic noise and observed discharge was not possible. Therefore, discharge data simulated using a hydrological model were first validated with gauging station data for two previous rain events (10–23 July 2004 and 7–16 September 2015). Then, the simulated river discharge was compared with Hi-net seismic noise data for three recent events (10–23 July 2004, 7–16 September 2015, and 10–15 October 2019). The seismic noise data exhibited a similar trend to the time series of simulated discharge in a frequency range of 1–2 Hz for the selected events. Discharge values predicted from the noise data effectively replicate the simulated discharge values in many cases, especially the timing and amount of peak discharge.Simulated and predicted discharge near NIED Hi-net seismic stations in the Mogami River Basin for the event of October 2019 (Typhoon Hagibis).

scholarly journals Extreme rainfall impacts on soil CO2 efflux in an urban forest ecosystem in Beijing, China

2016 ◽  
Vol 96 (4) ◽  
pp. 504-514 ◽  
Author(s):  
Wenjing Chen ◽  
Xin Jia ◽  
Chunyi Li ◽  
Haiqun Yu ◽  
Jing Xie ◽  
...  
Keyword(s):  
Soil Respiration ◽  
Forest Ecosystem ◽  
Urban Forest ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event ◽  
Co2 Efflux ◽  
Abrupt Decrease ◽  
Environmental Controls ◽  
Beijing China

Extreme rainfall events are infrequent disturbances that affect urban environments and soil respiration (Rs). Using data measured in an urban forest ecosystem in Beijing, China, we examined the link between gross primary production (GPP) and soil respiration on a diurnal scale during an extreme rainfall event (i.e., the “21 July 2012 event”), and we examined diel and seasonal environmental controls on Rs. Over the seasonal cycle, Rs increased exponentially with soil temperature (Ts). In addition, Rs was hyperbolically related to soil volumetric water content (VWC), increasing with VWC below a threshold of 0.17 m3 m−3, and then decreasing with further increases in VWC. Following the extreme rainfall event (177 mm), Rs showed an abrupt decrease and then maintained a low value of ∼0.3 μmol m−2 s−1 for about 8 h as soil VWC reached the field capacity (0.34 m3 m−3). Rs became decoupled from Ts and increased very slowly, while GPP showed a greater increase. A bivariate Q10-hyperbolical model, which incorporates both Ts and VWC effects, better fits Rs than the Q10 model in summer but not for whole year.

Simulation of an extreme rainfall event over Mumbai using a regional climate model: a case study

2021 ◽  
Vol 134 (1) ◽  
Author(s):  
Manas Pant ◽  
Soumik Ghosh ◽  
Shruti Verma ◽  
Palash Sinha ◽  
R. K. Mall ◽  
...  
Keyword(s):  
Regional Climate Model ◽  
Climate Model ◽  
Regional Climate ◽  
Extreme Rainfall ◽  
Rainfall Event ◽  
Extreme Rainfall Event

scholarly journals Distributed model of hydrological and sediment transport processes in large river basins in Southeast Asia

2015 ◽  
Vol 12 (7) ◽  
pp. 6755-6797 ◽  
Author(s):  
S. Zuliziana ◽  
K. Tanuma ◽  
C. Yoshimura ◽  
O. C. Saavedra
Keyword(s):  
Sediment Transport ◽  
Suspended Sediment ◽  
River Basin ◽  
River Basins ◽  
Large River ◽  
Mekong River ◽  
Distributed Model ◽  
Mekong River Basin ◽  
Chao Phraya River ◽  
Large River Basins

Abstract. Soil erosion and sediment transport have been modeled at several spatial and temporal scales, yet few models have been reported for large river basins (e.g., drainage areas > 100 000 km2). In this study, we propose a process-based distributed model for assessment of sediment transport at a large basin scale. A distributed hydrological model was coupled with a process-based distributed sediment transport model describing soil erosion and sedimentary processes at hillslope units and channels. The model was tested on two large river basins: the Chao Phraya River Basin (drainage area: 160 000 km2) and the Mekong River Basin (795 000 km2). The simulation over 10 years showed good agreement with the observed suspended sediment load in both basins. The average Nash–Sutcliffe efficiency (NSE) and average correlation coefficient (r) between the simulated and observed suspended sediment loads were 0.62 and 0.61, respectively, in the Chao Phraya River Basin except the lowland section. In the Mekong River Basin, the overall average NSE and r were 0.60 and 0.78, respectively. Sensitivity analysis indicated that suspended sediment load is sensitive to detachability by raindrop (k) in the Chao Phraya River Basin and to soil detachability over land (Kf) in the Mekong River Basin. Overall, the results suggest that the present model can be used to understand and simulate erosion and sediment transport in large river basins.

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