A catastrophic flood event which caused massive economic losses occurred in Thailand, in 2011.Several studies have already been conducted to analyze the Thai floods, but none of them have assessed the impacts of reservoir operation on flood inundation. This study addresses this gap by combining physically based hydrological models to explicitly simulate the impacts of reservoir operation on flooding in the Chao Phraya River Basin, Thailand. H08, an integrated water resources model with a reservoir operation module, was combined with CaMa-Flood, a river routing model with representation of flood dynamics. The combined H08-CaMa model was applied to simulate and assess the historical and alternative reservoir operation rules in the two largest reservoirs in the basin. The combined H08-CaMa model effectively simulated the 2011 flood: regulated flows at a major gauging station have high daily NSE-coefficient of 92% as compared with observed discharge; spatiotemporal extent of simulated flood inundation match well with those of satellite observations. Simulation results show that through the operation of reservoirs in 2011, flood volume was reduced by 8.6 billion m 3 and both depth and area of flooding were reduced by 40% on the average. Nonetheless, simple modifications in reservoir operation proved to further reduce the flood volume by 2.4 million m 3 and the depth and area of flooding by 20% on the average. By modeling reservoir operation with a hydrodynamic model, a more realistic simulation of the 2011 Thai flood was made possible, and the potential of reducing flood inundation through improved reservoir management was quantified.

Abstract. Global-scale river models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representations of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe efficiency coefficients decreased by more than 50 % between simulation results at 10 km resolution and 1 km resolution. When multiple downstream connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions at finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings should be universal and may have significant impacts on large-to globalscale simulations, especially in regions where mega deltas exist.These results demonstrate that a GRM can be used for higher resolution simulations of large-scale floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.

Abstract:A quasi-real-time hydrological simulation system was developed for the Chao Phraya River in Thailand. The system was largely based on ground meteorological observations from the Thai Meteorological Department (TMD) Automatic Weather Stations (AWSs), which are updated daily and available online. As radiation data were not measured by the TMD AWSs, they were obtained from the global meteorological data of the Japan Meteorological Agency Climate Data Assimilation System. A macro-scale water resources model termed H08 was used for hydrological simulations. The model's hydrological parameters were set from a series of sensitivity simulations for 2012. The model effectively reproduced the monthly hydrograph at the Nakhon Sawan and other major river gauging stations. The performance at the Sirikit Dam was poor, which could be attributed to erroneous input rainfall data due to the low density of AWSs. The simulation was continued up to September 30, 2013, or the date for which the latest data were available. The overall performance was fair and implied potential applicability of the system for quasi-real-time flood tracking and basic forecasting.

Thailand plays a central economic and policy-making role in Southeast Asia. Although climate change adaptation is being mainstreamed in Thailand, a well-organized overview of the impacts of climate change and potential adaptation measures has been unavailable to date. Here we present a comprehensive review of climate-change impact studies that focused on the Thai water sector, based on a literature review of six sub-sectors: riverine hydrology, sediment erosion, coastal erosion, forest hydrology, agricultural hydrology, and urban hydrology. Our review examined the long-term availability of observational data, historical changes, projected changes in key variables, and the availability of economic assessments and their implications for adaptation actions. Although some basic hydrometeorological variables have been well monitored, specific historical changes due to climate change have seldom been detected. Furthermore, although numerous future projections have been proposed, the likely changes due to climate change remain unclear due to a general lack of systematic multi-model and multi-scenario assessments and limited spatiotemporal coverage of the study area. Several gaps in the research were identified, and ten research recommendations are presented. While the information contained herein contributes to state-of-the-art knowledge on the impact of climate change on the water sector in Thailand, it will also benefit other countries on the Indochina Peninsula with a similar climate.

Climate change adaptation has become the current focus of research due to the remarkable potential of climate change to alter the spatial and temporal distribution of global water availability. Although reservoir operation is a potential adaptation option, earlier studies explicitly demonstrated only its historical quantitative effects. Therefore, this article evaluated the possibility of reservoir operation from an adaptation viewpoint for regulating the future flow using the H08 global hydrological model with the Chao Phraya River basin as a case study. This basin is the largest river system in Thailand and has often been affected by extreme weather challenges in the past. Future climate scenarios were constructed from the bias‐corrected outputs of three general circulation models from 2080 to 2099 under RCP4.5 and RCP8.5. The important conclusions that can be drawn from this study are as follows: (i) the operation of existing and hypothetical (i.e., construction under planning) reservoirs cannot reduce the future high flows below the channel carrying capacity, although it can increase low flows in the basin. This indicates that changes in the magnitude of future high flow due to climate change are likely to be larger than those achieved by reservoir operation and there is a need for other adaptation options. (ii) A combination of reservoir operation and afforestation was considered as an adaptation strategy, but the magnitude of the discharge reduction in the wet season was still smaller than the increase caused by warming. This further signifies the necessity of combining other structural, as well as non‐structural, measures. Overall, this adaptation approach for assessing the effect of reservoir operation in reducing the climate change impacts using H08 model can be applied not only in the study area but also in other places where climate change signals are robust.

Abstract:We projected future river discharge in the Chao Phraya River basin and evaluated the uncertainty in future climate projections by using different resolutions and ensemble experiments of the Atmospheric General Circulation Model of the Meteorological Research Institute (MRI-AGCM). We also obtained estimates of precipitation, evaporation, runoff, and river discharge under climate conditions projected for the late 21st century. The results show that precipitation is projected to significantly increase in the future during April to August, excluding May. The projected river discharge at Nakhon Sawan located in the central region shows a peak in September, a delay of one month after the maximum monthly mean precipitation. The estimated reduction in river discharge for January and February was robust based on all members of the 60-km mesh MRI-AGCM ensembles changing in the same direction as that of the 20-km mesh MRI-AGCM. The uncertainty assessment conducted in this study could lead to increased robustness in projected changes in mean river discharge in the late 21 st century for this basin.

This research focuses on dam reservoir operation effective in flood mitigation and water resource reservation on a seasonal scale. Based on the relationship between discharge characteristics in the upper watershed of Chao Phraya River and flood occurrences in the lower watershed, it was clarified that the dam reservoir operation most effective in the rainy season was determining the lowest reservoir volume in August for the Sirikit Dam reservoir and in July for the Bhumibol Dam reservoir, and storing water until November. Furthermore, by the probability evaluation on the free reservoir capacities of both dams estimated from the predetermined lowest reservoir volume and inflow volume in both dams, the dam reservoir operation considering the importance of flood mitigation and water resource reservation on a seasonal scale can be achieved.

Global-scale River Models (GRMs) are core tools for providing consistent estimates of global flood hazard, especially in data-scarce regions. Due to former limitations in computational power and input datasets, most GRMs have been developed to use simplified representation of flow physics and run at coarse spatial resolutions. With increasing computational power and improved datasets, the application of GRMs to finer resolutions is becoming a reality. To support 15 development in this direction, the suitability of GRMs for application to finer resolutions needs to be assessed. This study investigates the impacts of spatial resolution and flow connectivity representation on the predictive capability of a GRM, CaMa-Flood, in simulating the 2011 extreme flood in Thailand. Analyses show that when single downstream connectivity (SDC) is assumed, simulation results deteriorate with finer spatial resolution; Nash-Sutcliffe Efficiency coefficient decreased by more than 35% between simulation results at 10km resolution and 1km resolution. When multiple downstream 20 connectivity (MDC) is represented, simulation results slightly improve with finer spatial resolution. The SDC simulations result in excessive backflows on very flat floodplains due to the restrictive flow directions in finer resolutions. MDC channels attenuated these effects by maintaining flow connectivity and flow capacity between floodplains in varying spatial resolutions. While a regional-scale flood was chosen as a test case, these findings are universal and can be extended to global-scale simulations. These results demonstrate that a GRM can be used for higher resolution simulations of large-scale 25 floods, provided that MDC in rivers and floodplains is adequately represented in the model structure.