scholarly journals Application of performance metrics to climate models for projecting future river discharge in the Chao Phraya River basin

2014 ◽  
Vol 8 (1) ◽  
pp. 33-38 ◽  
Author(s):  
Satoshi Watanabe ◽  
Yukiko Hirabayashi ◽  
Shunji Kotsuki ◽  
Naota Hanasaki ◽  
Kenji Tanaka ◽  
...  
Keyword(s):  
River Basin ◽  
River Discharge ◽  
Climate Models ◽  
Performance Metrics ◽  
Chao Phraya River

scholarly journals Future projection of mean river discharge climatology for the Chao Phraya River basin

2013 ◽  
Vol 7 (2) ◽  
pp. 36-41 ◽  
Author(s):  
Adisorn Champathong ◽  
Daisuke Komori ◽  
Masashi Kiguchi ◽  
Thada Sukhapunnaphan ◽  
Taikan Oki ◽  
...  
Keyword(s):  
River Basin ◽  
River Discharge ◽  
Future Projection ◽  
Chao Phraya River

scholarly journals Inclusion of flood diversion canal operation in the H08 hydrological model with a case study from the Chao Phraya River Basin – Part 1: Model development and validation

2021 ◽  
Author(s):  
Saritha Padiyedath Gopalan ◽  
Adisorn Champathong ◽  
Thada Sukhapunnaphan ◽  
Shinichiro Nakamura ◽  
Naota Hanasaki
Keyword(s):  
River Basin ◽  
Flood Risk ◽  
River Discharge ◽  
Maximum Level ◽  
River Network ◽  
Water Diversion ◽  
Annual Average ◽  
Canal Operation ◽  
Chao Phraya River ◽  
Flood Diversion

Abstract. Water diversion systems play crucial roles in assuaging flood risk by diverting and redistributing water within and among basins. For flood and drought assessments, including investigations of the effects of diversion systems on river discharge worldwide, the explicit inclusion of these systems into global hydrological models (GHMs) is essential. However, such representation remains in the pioneering stage because of complex canal operations and insufficient data. Therefore, we developed a regionalized canal operation scheme and implemented it in the H08 GHM for flood diversion in the Chao Phraya River Basin (CPRB), Thailand, which is a complex river network with several natural and man-made diversion canals and has been subject to severe flooding in the past, including recent years. Region-specific validation results revealed that the enhanced H08 model with the regionalized diversion scheme could effectively simulate the observed flood diversion pattern in the CPRB. Diverted water comprises approximately 49 % of the annual average river discharge in the CPRB. The simulations further confirmed that the presented canal scheme had the potential to reduce flood risk in the basin by significantly reducing the number of flooding days. A generalized canal scheme with simple input data settings was also constructed for future global applications, providing insights into the maximum level of discharge reduction achievable with diversion of nearly 57 % of the annual average river discharge of the CPRB. Overall, the enhanced H08 model with canal schemes can be adapted and applied to different contexts and regions, accounting for the characteristics of each river network by maintaining the basic principles unaltered.

scholarly journals Use of Seasonal Streamflow Forecasts for Flood Mitigation with Adaptive Reservoir Operation: A Case Study of the Chao Phraya River Basin, Thailand, in 2011

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 3210
Author(s):  
Wongnarin Kompor ◽  
Sayaka Yoshikawa ◽  
Shinjiro Kanae
Keyword(s):  
River Basin ◽  
Reservoir Operation ◽  
River Discharge ◽  
Flood Mitigation ◽  
Wet Season ◽  
Predictive Information ◽  
Streamflow Forecasts ◽  
History Of ◽  
Chao Phraya River ◽  
Seasonal Streamflow

Predicting streamflow can help water managers make policy decisions for individual river basins. In 2011, heavy rainfall from May until October resulted in the largest flood event in the history of Thailand. This event created difficulty for water managers, who lacked information to make predictions. Studies on the 2011 Thai flood have proposed alternative reservoir operations for flood mitigation. However, no study to date has used predictive information to determine how to control reservoirs and mitigate such extreme floods. Thus, the objective of this study is to update and develop a method for using streamflow predictive data to support adaptive reservoir operation with the aim of mitigating the 2011 flood. The study area was the Chao Phraya River Basin, one of the most important basins in Thailand. We obtained predictive information from a hydrological model with a reservoir operation module using an ensemble of seasonal precipitation data from the European Centre for Medium–Range Weather Forecasts (ECMWF). The six-month ECMWF prediction period was used to support the operation plan for mitigating flooding in 2011 around each reservoir during the wet season. Decision-making for reservoir operation based on seasonal predictions was conducted on a monthly time scale. The results showed that peak river discharge decreased slightly, by around 4%, when seasonal predictive data were used. Moreover, changing the reservoir operation plan and using seasonal predictions decreased the peak river discharge by around 20%.

scholarly journals Responses of Hydrological Processes under Different Shared Socioeconomic Pathway Scenarios in the Huaihe River Basin, China

Water ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 1053
Author(s):  
Yuan Yao ◽  
Wei Qu ◽  
Jingxuan Lu ◽  
Hui Cheng ◽  
Zhiguo Pang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
River Basin ◽  
Climate Models ◽  
Global Climate Models ◽  
Hydrological Response ◽  
Huaihe River Basin ◽  
Huaihe River ◽  
Infiltration Capacity ◽  
Change Analysis ◽  
Average Annual Runoff

The Coupled Model Intercomparison Project Phase 6 (CMIP6) provides more scenarios and reliable climate change results for improving the accuracy of future hydrological parameter change analysis. This study uses five CMIP6 global climate models (GCMs) to drive the variable infiltration capacity (VIC) model, and then simulates the hydrological response of the upper and middle Huaihe River Basin (UMHRB) under future shared socioeconomic pathway scenarios (SSPs). The results show that the five-GCM ensemble improves the simulation accuracy compared to a single model. The climate over the UMHRB likely becomes warmer. The general trend of future precipitation is projected to increase, and the increased rates are higher in spring and winter than in summer and autumn. Changes in annual evapotranspiration are basically consistent with precipitation, but seasonal evapotranspiration shows different changes (0–18%). The average annual runoff will increase in a wavelike manner, and the change patterns of runoff follow that of seasonal precipitation. Changes in soil moisture are not obvious, and the annual soil moisture increases slightly. In the intrayear process, soil moisture decreases slightly in autumn. The research results will enhance a more realistic understanding of the future hydrological response of the UMHRB and assist decision-makers in developing watershed flood risk-management measures and water and soil conservation plans.

scholarly journals Application of SWAT in Hydrological Simulation of Complex Mountainous River Basin (Part II: Climate Change Impact Assessment)

Water ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1548
Author(s):  
Suresh Marahatta ◽  
Deepak Aryal ◽  
Laxmi Prasad Devkota ◽  
Utsav Bhattarai ◽  
Dibesh Shrestha
Keyword(s):  
Climate Change ◽  
River Basin ◽  
Climate Models ◽  
Assessment Tool ◽  
Swat Model ◽  
Global Climate Models ◽  
Climate Data ◽  
The Future ◽  
The Impact ◽  
Mountainous River

This study aims at analysing the impact of climate change (CC) on the river hydrology of a complex mountainous river basin—the Budhigandaki River Basin (BRB)—using the Soil and Water Assessment Tool (SWAT) hydrological model that was calibrated and validated in Part I of this research. A relatively new approach of selecting global climate models (GCMs) for each of the two selected RCPs, 4.5 (stabilization scenario) and 8.5 (high emission scenario), representing four extreme cases (warm-wet, cold-wet, warm-dry, and cold-dry conditions), was applied. Future climate data was bias corrected using a quantile mapping method. The bias-corrected GCM data were forced into the SWAT model one at a time to simulate the future flows of BRB for three 30-year time windows: Immediate Future (2021–2050), Mid Future (2046–2075), and Far Future (2070–2099). The projected flows were compared with the corresponding monthly, seasonal, annual, and fractional differences of extreme flows of the simulated baseline period (1983–2012). The results showed that future long-term average annual flows are expected to increase in all climatic conditions for both RCPs compared to the baseline. The range of predicted changes in future monthly, seasonal, and annual flows shows high uncertainty. The comparative frequency analysis of the annual one-day-maximum and -minimum flows shows increased high flows and decreased low flows in the future. These results imply the necessity for design modifications in hydraulic structures as well as the preference of storage over run-of-river water resources development projects in the study basin from the perspective of climate resilience.

scholarly journals Prediction of extreme floods based on CMIP5 climate models: a case study in the Beijiang River basin, South China

2015 ◽  
Vol 19 (3) ◽  
pp. 1385-1399 ◽  
Author(s):  
C. H. Wu ◽  
G. R. Huang ◽  
H. J. Yu
Keyword(s):  
Climate Change ◽  
River Basin ◽  
South China ◽  
Climate Models ◽  
Annual Maximum ◽  
Emission Scenarios ◽  
Vic Model ◽  
Extreme Floods ◽  
Beijiang River ◽  
Increasing Trends

Abstract. The occurrence of climate warming is unequivocal, and is expected to be experienced through increases in the magnitude and frequency of extreme events, including flooding. This paper presents an analysis of the implications of climate change on the future flood hazard in the Beijiang River basin in South China, using a variable infiltration capacity (VIC) model. Uncertainty is considered by employing five global climate models (GCMs), three emission scenarios (representative concentration pathway (RCP) 2.6, RCP4.5, and RCP8.5), 10 downscaling simulations for each emission scenario, and two stages of future periods (2020–2050, 2050–2080). Credibility of the projected changes in floods is described using an uncertainty expression approach, as recommended by the Fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change (IPCC). The results suggest that the VIC model shows a good performance in simulating extreme floods, with a daily runoff Nash–Sutcliffe efficiency coefficient (NSE) of 0.91. The GCMs and emission scenarios are a large source of uncertainty in predictions of future floods over the study region, although the overall uncertainty range for changes in historical extreme precipitation and flood magnitudes are well represented by the five GCMs. During the periods 2020–2050 and 2050–2080, annual maximum 1-day discharges (AMX1d) and annual maximum 7-day flood volumes (AMX7fv) are expected to show very similar trends, with the largest possibility of increasing trends occurring under the RCP2.6 scenario, and the smallest possibility of increasing trends under the RCP4.5 scenario. The projected ranges of AMX1d and AMX7fv show relatively large variability under different future scenarios in the five GCMs, but most project an increase during the two future periods (relative to the baseline period 1970–2000).

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