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This study investigates the impact of future climate warming on tropical cyclones (TC) and extratropical cyclones (ETC) using the database for Policy Decision-Making for Future Climate Change (d4PDF) large ensemble simulations. Cyclone tracking was performed using the neighbor enclosed area tracking algorithm (NEAT), and TC and ETCs were identified over the western North Pacific Ocean (WNP). For cyclone frequency, it was revealed that, although a slight underestimation of the total number of TCs and ETCs in both the WNP and near Hokkaido, Japan, exists, the d4PDF reproduced the spatial distribution of both TC and ETC tracks well when compared with observations/reanalysis. The 4-K warming scenarios derived from six different sea surface temperature warming patterns showed robust decreases in TC frequency in the tropical WNP and a slight reduction in ETCs near Japan. Next, precipitation characteristics for TCs or ETCs in the vicinity of Hokkaido were examined using 5-km-mesh regional climate ensemble simulations. Four representative cyclone locations near Hokkaido are identified using K-means clustering and revealed distinct precipitation characteristics between clusters, with higher TC-associated precipitation than ETC-associated precipitation and the heaviest precipitation in the southern portion of the prefecture. The 4-K warming scenarios revealed increased precipitation for all cyclone placements for both TCs and ETCs. Last, average cyclone intensity, translation speed, and size were examined. It was shown that TCs in future climates are more intense, propagate more slowly, and are smaller in terms of enclosed vorticity area as they approach Hokkaido. For ETCs, mean intensity does not change much; they travel slightly faster, and become smaller.

Earlier onset of the Southeast Asian summer monsoon (SAM) was observed over the Chao Phraya River basin in Thailand using Thai Meteorological Department-derived high-resolution merged rainfall data from 1981 to 2016. SAM variability depends on numerous local and global factors, including thermal conditions over the Bay of Bengal (BoB) and Tibetan Plateau (TbT). Despite tremendous past research efforts, the effect of thermal heat contrast on the SAM remains unclear. Using observational and reanalysis datasets, we found that the absolute value of total heat over the BoB was increasing. However, the interannual variability of total heat was greater over the TbT. Changes in surface temperature (± 1.5 °C), air thickness (± 20 m), and geopotential height over the TbT were associated with the timing of SAM onset. The results also suggested that significant changes in air thickness are driven by surface temperature differences over the TbT, while changes in the integrated apparent heat source and integrated apparent moisture sink of ± 100 W m−2 resulted in anomalous convective activities over the BoB and mainland of the Indochina Peninsula in years of early and late SAM onset. At the intraseasonal timescale, Madden–Julian oscillation (MJO) was observed over the Indian Ocean and Western Hemisphere for 4–10 days in years of early SAM onset. The opposite situation was found for years of late SAM onset, with MJO located over the Western Pacific Ocean and Maritime Continent.

Uncertainty in hydrological statistics estimated with finite observations, such as design rainfall, can be quantified as a confidence interval using statistical theory. Ensemble climate data also enables derivation of a confidence interval. Recently, the database for policy decision making for future climate change (d4PDF) was developed in Japan, which contains dozens of simulated extreme rain-fall events for the past and 60 years into the future, allowing the uncertainty of design rainfall to be quantified as a confidence interval. This study applies an order statistics distribution to evaluate uncertainty in the order statistics of extreme rainfall from the perspective of mathematical theory, while a confidence interval is used for uncertainty evaluation in the probability distribution itself. An advantage of the introduction of an order statistics distribution is that it can be used to quantify the goodness-of-fit between observation and ensemble climate data under the condition that the extreme value distribution estimated from observations is a true distribution. The order statistics distribution is called the control density distribution, which is derived from characteristics that order statistics from standard uniform distribution follows beta distribution. The overlap ratio of the control density distribution and frequency distributions derived from ensemble climate data is utilized for evaluation of the degree of goodness-of-fit for both data.

An earlier onset of the Southeast Asian summer monsoon (SAM) was observed over the Chao Phraya River basin in Thailand using Thai Meteorological Department (TMD)-derived high-resolution merged rainfall from 1981 to 2016. As the SAM is precipitous, its variability depends on many local and global factors, such as thermal conditions over the Bay of Bengal (BoB) and Tibetan Plateau (TbT). Despite tremendous studies in the past, the role of thermal heat contrast over SAM is still not fully understood. Using the observation and reanalysis datasets, it was found that the absolute value of total heat over the BoB was higher. However, the interannual variability in total heat is higher over the TbT. Significant changes in surface temperature (±1.5°C), air thickness (±20 meters) and geopotential height found over the TbT were associated with early (late) SAM onset. The results also suggested that the significant changes in air thickness were influenced by the surface temperature difference over the TbT, and the changes in the integrated apparent heat source and integrated apparent moisture sink were up to ± 100 Wm−2, which resulted in stronger (weaker) convective activities over the BoB and mainland of the Indochina Peninsula during early (late) SAM onset. At the intraseasonal timescale, the instance MJO found over the Indian Ocean and Western Hemisphere at 4 to 10 days span during early SAM onset. An opposite scenario is found for a late SAM onset years with MJO location over Western Pacific and Maritime continent.

Line-shaped rainbands (LRBs), including Mesoscale Convective Systems (MCSs), stagnate on river basins and cause floods and landslides. Moreover, the frequency of LRBs is increasing around Hokkaido a part of northern Japan. Due to the complexity of the three-dimensional structures found in LRBs, some research dealt with two-dimensional observation data to identify them for the sake of simplicity. In previous studies, several methods to widely identify LRBs from radar rainfall data in terms of rainfall intensity, shape of rainfall area, and duration have been proposed. However, using the nationally consistent definition, the number of LRBs occurring in this region would be evaluated as very few due to the little rainfall climatology of this area. In this study, based on the previous studies, we adjust many combinations of threshold values, such as rainfall intensity, aspect ratio, and time duration in order to verify of validity the LRBs that occurred in northern Japan. The authors visually identified the six LRBs that caused the disaster and showed thresholds at which they were mechanically extractable by a computer program. The combination of thresholds that included at least six of those disaster-scale cases was “a rainfall area defined by a closed curve with a previous 3-hour rainfall of 40 mm or more, stagnating for 2 hours or more (covering 40% or more of its area), and with a maximum aspect ratio of 2.5 or more.”

The Hokkaido Eastern Iburi earthquake in 2018 induced the largest landslide over the Azuma River basin in Hokkaido, the north island of Japan. This study estimated the sediment erosion rate over the Azuma River basin using the universal soil loss equation (USLE) for the pre- and post-earthquake conditions. The results showed that the potential sediment erosion rate from the entire basin increased by 8–29 times more than the pre-earthquake condition. The primary cause of the increase in sediment erosion rate was deforestation due to the landslide, which generated 13% of the bare land area in the entire basin. In addition, the influence of interannual variability of rainfall on sediment erosion rate was calculated from observed rainfall data. As a result, the minimum annual sediment erosion rate after the earthquake exceeded the maximum before the earthquake, indicating that the post-earthquake sediment erosion rate is substantially higher than the pre-earthquake rate. These findings suggest that in order to assess the sediment erosion risk over the Azuma River basin, it is necessary to predict and monitor the vegetation recovery, considering the interannual variability of rainfall.

Atmospheric fronts play an important role on the day-to-day variation of rainfall in Japan, North-western Pacific. They are defined as a discrepancy of air density and have been depicted on surface weather charts for more than 100 years by Japan Meteorological Agency (JMA). This study develops an approach to detect fronts from the charts published from 1978 to 2020 and investigates how detected fronts could be utilized. The fronts which are depicted on the charts might have a diverse physical characteristic in each age. One of factors is a difference in how to represent fronts. The difference also prevents from detecting fronts under a certain accuracy. Previous study demonstrates detecting fronts based on the color available from the charts. However, this approach is applicable for weather charts published after 2000 by JMA. This paper describes consideration points for a unified detection of fronts from the charts for 43 years in detail. Furthermore, we compare fronts detected by several methods and discuss a spatial scale in which their differences could be neglected.

This study investigated the relationship between extreme precipitation and near-surface temperature (precipitation-temperature relation) from two different perspectives, the rate of change of precipitation with temperature and dynamic (i.e., effect of the change in atmospheric motion) and thermodynamic (i.e., effect of the change in atmospheric moisture content) aspects, using a 5-km dynamical downscaled hundreds-year data set for past climate condition (PAST; from 1951 to 2010) and future climate condition (FUTURE; 4 degrees C warmer than the preindustrial condition). Initially, using the observation and the PAST and FUTURE data sets, it was found that the 99th and 99.9th percentile hourly precipitation for each temperature bin (P-99 and P-99.9, respectively) paralleled the slope of the Clausius-Clapeyron (C-C) relation for a certain temperature range over the Tokachi River basin in Hokkaido, the northern island of Japan; however, both P-99 and P-99.9 decreased in the high-temperature range. Next, we examined the cause of the P-99 and P-99.9 differences between PAST and FUTURE for each temperature bin by classifying dynamic and thermodynamic factors. The result showed that the thermodynamic effect dominates the differences in P-99 and P-99.9 between PAST and FUTURE, which means that the thermodynamic effect is the main component of the precipitation-temperature relation. Similar analyses were applied to the whole river basin, including the mountainous area. The results showed that the differences in P-99 and P-99.9 between PAST and FUTURE are mainly due to the thermodynamic contribution, regardless of plain or mountain area. Using such large model data sets, we could make a robust assessment of the precipitation-temperature relation and the dynamic and thermodynamic contributions to precipitation changes. Moreover, using the 5-km resolution hundreds-year data set enabled us to quantify the spatial distribution of such precipitation characteristics over a thousands of square kilometer catchment.

Motivated by the problem of rainfall duration bias typically found in dynamical downscaling, its possible effect on hydrology was evaluated for heavy rainfall events over Kyushu, Japan, during summer. Heavy rainfall in western Kyushu is often related to a persistent Baiu rainband across Kyushu, while in eastern Kyushu it is related to the passage of typhoons near Kyushu. For typical heavy-rainfall periods, we ran a tank model for several target rivers to analyze runoff and water-depth sensitivity to the hyetograph by artificially extending the rainfall duration to 8 hours while maintaining the same total rainfall. This showed that a spike in peak runoff was suppressed by prolonged weak rainfall as typically found in downscaling outputs. The timing of rising runoff and water depth in the tank model was shifted earlier.

In this study, self-organizing maps in combination with K-means clustering are used to objectively classify the anomalous weather patterns (WPs) associated with the summertime [May–June (MJ) and July–August–September (JAS)] heavy rainfall days during 1979–2007 over the Upper Nan River basin, northwestern Thailand. The results show that in MJ, intensive rains are mainly brought by the remarkable enhancement of the westerly summer monsoon. Meanwhile, westward-propagating tropical disturbances including tropical cyclones are the primary factors that reproduce heavy rainfall over the Upper Nan in JAS. These results also suggest that the occurrence time of local heavy rainfall is strongly related to the seasonal transition of the summer monsoon over the Indochina Peninsula. The classification results are then implemented with the perfect prognosis and analog method to predict the occurrence (yes/no) of heavy rainfall days over the studied basin in summer 2008–17 using prognostic WPs from the operational Japan Meteorological Agency Global Spectral Model (GSM). In general, the forecast skill of this approach up to 3-day lead times is significantly improved, in which the method not only outperforms GSM with the same forecast ranges, but also its 3-day forecast is better than the 1–2-day forecasts from GSM. However, the false alarms ratio is still high, particularly in JAS. Nevertheless, it is expected that the new approach will provide warning and useful guidance for decision-making by forecasters or end-users engaging in water management and disaster prevention activities.

Refereed/Peer-reviewed The hydropolitics over the Abbay basin has a long history of hydrologic hegemony by Egypt. The conflict over the Abbay River mainly occurred between Egypt, Ethiopia, and Sudan. Even though the river is shared by 11 countries, the use is principally dominated by Egypt in the last decades. This paper aimed to review the hydropolitics of Abbay/Blue Nile, its challenges, opportunities, and also the impacts of constructing the GERD over the riparian states (Ethiopia, Egypt, and Sudan). This review was done by searching and reviewing of papers published in reputable journals (peer reviewed and open access) focused on Abbay Basin, GERD and transboundary rivers. Egyptians said that Abbay is the primary water resource and their lifeblood and desires to continue their power on the Abbay basin. On the opposite side, Ethiopia, contributing about 86% of the flow has not been benefited from the river. This controversy has brought disagreement between Ethiopia, Egypt, and Sudan but mainly the tensions between Egypt and Ethiopia are running high. For the last 40 years, the two nations haven't experienced such resistance. However, the starting of the construction of the Grand Ethiopian Renaissance Dam (GERD) brought deviation. Ethiopians are constructing the dam over the river Abbay by their source of finance and people for ensuring their capacity and the moral issue of the people. Egypt's hydrological hegemony on the Abbay river is reversed from the dominance of one state to the equitable and benefit-sharing of the transboundary river. Even though, the standard water program has been developed, the riparian states haven't entirely approved it due to current and projected water needs, conflict of interest, little data, and lack of mutual aid. The variety of hydrological processes within the Abbay basin makes it challenging to implement a standard plan that could be applied for overall riparian states. Although Egypt and Sudan are resisting the efforts to incorporate the other upstream riparian's within the negotiations, they have to understand that the river and its management must be advanced from a regional viewpoint. The development of GERD within the Abbay river by Ethiopia has a positive impact on downstream countries because it provides electricity, regulates the flow, controls flood, and reduces the cost of reservoir maintenance in downstream dams. A comprehensive understanding of hydrological processes is currently essential for effective water management in the Abbay basin.

Nonstationarity in hydrological variables has been identified throughout Japan in recent years. As a result, the reliability of designs derived from using method based on the assumption of stationary might deteriorate. Non-stationary hydrological frequency analysis is among the measures to counter this possibility. Using this method, time variations in the probable hydrological quantity can be estimated using a non-stationary extreme value distribution model with time as an explanatory variable. In this study, we build a new method for constructing the confidence interval regarding the non-stationary extreme value distribution by applying a theory of probability limit method test. Furthermore, by introducing a confidence interval based on probability limit method test into the non-stationary hydrological frequency analysis, uncertainty in design rainfall because of lack of observation information was quantified, and it is shown that assessment pertaining to both the occurrence risk of extremely heavy rainfall and changes in the trend of extreme rainfall accompanied with climate change is possible.

Record-breaking precipitation events have been frequent in Japan in recent years. To investigate the statistical characteristics of the frequency of record-breaking events, observations can be compared with the values derived from sampling theory with a stationary state. This study counted the number of record-breaking daily and 3-day total precipitation events at 58 rain-gauge stations in Japan between 1901 and 2018. The average number of record-breaking events over the 118-year period was 5.9 for daily total precipitation, which is larger than the theoretical value of 5.4 derived using the assumption that the climate system over the same period was stationary. Sampling theory was used to incorporate the influence of the long-term temperature trend from the Clausius&ndash, Clapeyron relation associated with the saturation vapor pressure. In theory, the long-term temperature trend gives a similar number of observed record-breaking events when the long-term temperature trend is approximately 0.5 Kelvin/100 years.

Existing flood control plans have been implemented based on rainfall estimated from observation data. However, we have data from the past several decades. Thus, it is not enough to project future extreme events from existing observation data. Therefore, Japan has been created huge ensemble of high-resolution climate model simulation based on the laws of physics. The data consist of past and future climate situations (past climate: total 3,000 years, 4 K warmer climate: total 5,400 years). It has enabled to quantitatively evaluate the probability of heavy rainfall and flooding on the future 4K-warmed earth.Moreover, we apply the statistical theory of extreme value to evaluate the probability of heavy rainfall and flooding in the future. The results from statistical method is equivalent to the results from the huge ensemble data from climate model. It supports Japanese governments in formulating and carrying out their adaptation plans.

Typhoon intensity changes according to the momentum and enthalpy flux supplied from the boundary layer. MPI theory uses the ratio between a drag coefficient and an enthalpy exchange coefficient, which are indexes that indicate how much momentum or enthalpy is exchanged between the air and the sea. Each is a coefficient depending on wind speed, temperature and SST.However, Lighthill (1999) is shown that latent heat exchange varies because sea spray generated from the sea surface evaporates in the boundary layer. In addition, Barenblatt (2005), inspired by Lighthill (1999), showed that the Karman constant changes according to the Froude number and the drag coefficient changes. Since both changes can change the MPI theory, it is necessary to quantitatively evaluate the effect of the droplets generated from the sea surface in order to grasp both accurately. In addition, it is necessary to consider the effects of rainfall in actual storms, which often involve rainfall.In this study, to evaluate the flux exchange in the boundary layer quantitatively, we show the drag coefficient and the enthalpy exchange coefficient taking into account sea spray and rain. In addition, we show the results of observation of sea spray and rain using disdrometer and X-band radar.

Typhoon Hagibis (2019) caused heavy rainfall and big flood damage in many river basins in Japan. In this research, we suggested the risk assessment method for heavy rainfall due to typhoon from the view point of a typhoon track by using records of rain gauges and typhoon track data from 1951. The relationships between typhoon position and rainfall intensity were obtained from the rain gauges and the typhoon track data for each rain gauge points. The relationships make it clear that typhoon track passes through the areas in which heavy rainfall occurred. The relationship can be used for risk assessment of heavy rainfall in terms of typhoon track. The track of Typhoon Hagibis is the heaviest rainfall track for some points located in north of the typhoon track. However, some points close to the typhoon center or in south of the typhoon track are not the heaviest rainfall track. It means that if typhoon Hagibis shifted the track, the typhoon would cause heavier rainfall in some points. The result can be used not only for estimation of potential rainfall but also for selection of dangerous typhoons from large ensemble dataset. We assessed heavy rainfall risk of typhoons similar to typhoon Hagibis under historical and future climate by using the large ensemble climate dataset (d4PDF).

Irrigation can affect climate and weather patterns from regional to global scales through the alteration of surface water and energy balances. Here, we couple a land-surface model (LSM) that includes various human land-water management activities including irrigation with an atmospheric general circulation model (AGCM) to examine the impacts of irrigation-induced land disturbance on the subseasonal predictability of near-surface variables. Results indicate that the simulated global irrigation and groundwater withdrawals (circa 2000) are ~3600 and ~370 km3/year, respectively, which are in good agreement with previous estimates from country statistics and offline&ndash, LSMs. Subseasonal predictions for boreal summers during the 1986&ndash, 1995 period suggest that the spread among ensemble simulations of air temperature can be substantially reduced by using realistic land initializations considering irrigation-induced changes in soil moisture. Additionally, it is found that the subseasonal forecast skill for near-surface temperature and sea level pressure significantly improves when human-induced land disturbance is accounted for in the AGCM. These results underscore the need to incorporate irrigation into weather forecast models, such as the global forecast system.

Dynamical downscaling (DDS) was conducted over Japan by using a regional atmospheric model with reanalysis data to investigate the rainfall duration bias over Kyushu, Japan, in July and August from 2006 to 2015. The model results showed that DDS had a positive rainfall duration bias over Kyushu and a dry bias over almost all of Kyushu, which were emphasized for extreme rainfall events. Investigated was the rainfall duration bias for heavy rainfall days, accompanied by synoptic-scale forcing, in which daily precipitation exceeded 30 mm day−1 and covered over 20% of the Kyushu area. Heavy rainfall days were sampled from observed rainfall data that were based on rain gauge and radar observations. A set of daily climatic variables of horizontal wind and equivalent potential temperature at 850 hPa and sea level pressure, around southwestern Japan, corresponding to the sampled dates, was selected to conduct a self-organizing map (SOM) and K-means method. The SOM and K-means method objectively classified three synoptic patterns related to heavy rainfall over Kyushu: strong monsoon, weak monsoon, and typhoon patterns. Rainfall duration had a positive bias in western Kyushu for the strong monsoon pattern and a positive bias in southern and east-coast Kyushu for the typhoon pattern, whereas there was little rainfall duration bias in the weak monsoon pattern. The bias for the typhoon pattern was related to rainfall events with a strong rainfall peak. The results suggest that bias correction for rainfall duration would be required for accurately estimating direct runoff in a catchment area in addition to the precipitation amount.

Extreme winter daily temperature is an important parameter for determining winter precipitation. This study used a principal component analysis and k-means clustering to characterize the circulation patterns of extreme daily temperatures for 19 winter seasons in Sapporo, Hokkaido, Japan. Climatological anomaly maps were constructed for sea level pressure (SLP) and the 500-hPa geopotential height for the identified minimum (Tmin10; 239 days) and maximum (Tmax90; 236 days) daily temperature extremes. The Tmax90 SLP anomaly pattern was the opposite (west–east orientation) of the Tmin10 pattern. The circulation patterns that predominantly contributed to winter rainfall were derived from cyclones over the Sea of Japan via instability created by abundant heat and moisture over the ocean and a strong positive 500-hPa height anomaly over Hokkaido.

In this study, the Self-Organizing Maps in combination with K-means clustering technique are used for classification of synoptic weather patterns inducing heavy rainfall exceeding 100 mm day−1 during the Baiu season (June–July) of 1979–2010 over northern Kyushu, southwestern Japan. It suggests that these local extreme rainfall events are attributed to four clustered patterns, which are primarily related to the Baiu front and the extratropical/tropical cyclone/depression activities and represented by the intrusion of warm and moist air accompanied by the low-level jet or cyclonic circulation. The classification results are then implemented with the analogue method to predict the occurrence (yes/no) of local heavy rainfall days in June–July of 2011–2016 by using the prognostic synoptic fields from the operational Japan Meteorological Agency (JMA) Global Spectral Model (GSM). In general, the predictability of our approach evaluated by the Equitable Threat Score up to 7-day lead times is significantly improved than that from the conventional method using only the predicted rainfall intensity from GSM. Although the false alarm ratio is still high, it is expected that the new method will provide a useful guidance, particularly for ranges longer than 2 days, for decision-making and preparation by weather forecasters or end-users engaging in disaster-proofing and water management activities.

Clarifying hydrologic behavior, especially behavior related to extreme events such as flash floods, is vital for flood mitigation and management. However, discharge and rainfall measurement data are scarce, which is a major obstacle to flood mitigation. This study (i) simulated flash floods on a regional scale using three types of rainfall forcing implemented in a land surface model and (ii) evaluated and compared simulated flash floods with the observed discharge. The three types of rainfall forcing were those observed by the Automated Meteorological Data Acquisition System (AMeDAS) (Simulation I), the observed rainfall from the Ministry of Land, Infrastructure and Transportation (MLIT) (Simulation II), and the estimated rainfall from the Multi-purpose Transport Satellite (MTSAT), which was downscaled by AMeDAS rainfall (Simulation III). MLIT rainfall observations have a denser station network over the Ishikari River basin (spacing of approximately 10 km) compared with AMeDAS (spacing of approximately 20 km), so they are expected to capture the rainfall spatial distribution more accurately. A land surface model, Minimal Advance Treatments of Surface Interaction and Runoff (MATSIRO), was implemented for the flash flood simulation. The river flow simulations were run over the Ishikari river basin at a 1-km grid resolution and a 1-h temporal resolution during August 2010. The statistical performance of the river flow simulations demonstrated that Simulation I was reasonable compared with Simulation III. The findings also suggest that the advantage of the MTSAT-based estimated rainfall (i.e., good spatial distribution) can be coupled with the benefit of direct AMeDAS observations (i.e., representation of the true rainfall).

This study aims to evaluate the change in flood inundation in the Chitose River basin (CRB), a tributary of the Ishikari River, considering the extreme rainfall impacts and topographic vulnerability. The changing impacts were assessed using a large-ensemble rainfall dataset with a high resolution of 5 km (d4PDF) as input data for the rainfall–runoff–inundation (RRI) model. Additionally, the prediction of time differences between the peak discharge in the Chitose River and peak water levels at the confluence point intersecting the Ishikari River were improved compared to the previous study. Results indicate that due to climatic changes, extreme river floods are expected to increase by 21–24% in the Ishikari River basin (IRB), while flood inundation is expected to be severe and higher in the CRB, with increases of 24.5, 46.5, and 13.8% for the inundation area, inundation volume, and peak inundation depth, respectively. Flood inundation is likely to occur in the CRB downstream area with a frequency of 90–100%. Additionally, the inundation duration is expected to increase by 5–10 h here. Moreover, the short time difference (0–10 h) is predicted to increase significantly in the CRB. This study provides useful information for policymakers to mitigate flood damage in vulnerable areas.

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.