Journal articles on the topic 'Hydrology Thailand'

Abstract. Only few data from South-East Asia document paleoenvironments evolution during the Cenozoic. Here we analyse palynological records from four sites of Thailand. The unique site dated from the Oligocene shows a temperate signal, while younger Miocene records show a tropical signal with variations in the hydrology of the deposition basin, as well as a temperate extra-local signal that could be related to a mid-altitude flora. The mid-Miocene Chiang Muan basin has delivered several occurrences of an opened biotope (Poaceae) alternatively replaced by what could be Syzygium gallery-forests. Khorat (−9 to −6.5 Ma) pollen records deliver similar results, but linked to a strong local signal. Regional and local signals remain difficult to separate, notably because of badly known palynomorphs, but our high resolution record confirm oceanic data that suggest high variability in Miocene climate, as well as modelling studies inferring an early onset of the Asian monsoon.

The Mekong River, well known for its aquatic biodiversity, is important to the social, physical, and economic health of millions living in China, Myanmar, Laos, Thailand, Cambodia, and Vietnam. This paper explores the social and environmental impacts of several Mekong basin hydropower dams and groupings of dams and the geographies of their impacts. Specifically, we examined the 3S (Sesan, Sekong Srepok) river system in northeastern Cambodia, the Central Highlands of Vietnam, and southern Laos; the Khone Falls area in southern Laos; the lower Mun River Basin in northeastern Thailand; and the upper Mekong River in Yunnan Province, China, northeastern Myanmar, northern Laos, and northern Thailand. Evidence shows that these dams and groupings of dams are affecting fish migrations, river hydrology, and sediment transfers. Such changes are negatively impacting riparian communities up to 1000 km away. Because many communities depend on the river and its resources for their food and livelihood, changes to the river have impacted, and will continue to negatively impact, food and economic security. While social and environmental impact assessments have been carried out for these projects, greater consideration of the scale and cumulative impacts of dams is necessary.

Seasonal flooded forest is one of the most important wetlands in northeastern Thailand, not only for its abundant biodiversity, but also as a source of carbon sequestration. Organic carbon plays an specially important role in the soil carbon cycle. To reinforce comprehension on soil organic carbon, five profiles in a northeast plateau were observed and determined. The most common trees were Albizzia Odoratissima, Combretum quadrangulare Kurz, and Streblusasper Lour. The contents of Soil Organic Carbon (SOC) varied from 3.52 g/kgto 5.90 g/kg in top soil and varied from 4.01 g/kg to 4.60 g/kg in sub soil. There was a close relationship between SOC content and basic soil properties, especially the bulk density of both top soil layer and sub soil layer. The distribution of SOC content was harmonized with distribution of plants. In comparative analysis, the flooded forest that composted with a high percentage of vegetation coverage (Khud Tew, Khud Chi Tao) had a significantly higher SOC content. The SOC storage varied from 2.65 kg/m2 to 4.18 kg/m2. Khud Chi Tao contained the maximum amount of SOC storage, whereas Kwo Chi Yai had the minimum. Limitation of flooded forest survival concerned over landscape change, particularly plant disappearance and waterlogged shortage. Therefore, vegetation and hydrology management have to be implemented practically to retain the existing organic carbon in wetlands and allow the soil to sequester additional carbon.

Land use land cover (LULC) change is one of the main drivers contributing to global climate change. It alters surface hydrology and energy balance between the land surface and atmosphere. However, its impacts on surface air temperature have not been well understood in a dynamic region of LULC changes like Southeast Asia (SEA). This study quantitatively examined the contribution of LULC changes to temperature trends in Myanmar and Thailand as the typical parts of SEA during 1990–2019 using the “observation minus reanalysis” (OMR) method. Overall, the average maximum, mean, and minimum temperatures obtained from OMR trends indicate significant warming trends of 0.17 °C/10a, 0.20 °C/10a, and 0.42 °C/10a, respectively. The rates of minimum temperature increase were larger than maximum and mean temperatures. The decreases of forest land and cropland, and the expansions of settlements land fractions were strongly correlated with the observed warming trends. It was found that the effects of forest land converted to settlement land on warming were higher than forest conversion to cropland. A comprehensive discussion on this study could provide scientific information for the future development of more sustainable land use planning to mitigate and adapt to climate change at the local and national levels.

The Mekong River Basin is one of the world’s major transboundary basins. The hydrology, agriculture, ecology, and other watershed functions are constantly changing as a result of a variety of human activities carried out inside and by neighboring countries including China, Myanmar, Thailand, Laos, Cambodia, and Vietnam in order to meet increased food and water demands for an increasing population. The Mekong River, which provides irrigation and fishing for a population of over 60 million people, also has an estimated 88,000 MW of untapped hydropower potential. The construction of dams for energy supply has a wide-ranging impact on downstream reservoir regions, resulting in unprecedented changes in hydrologic functions, the environment, and people’s livelihoods. We present a holistic view of how external stressors such as climate change and variability, land cover, and land-use change affect supply and demand. We present an integrated modeling framework for analyzing the supply–demand scenarios and tradeoffs between different sectors. Specifically, we evaluated the impacts of future climate on irrigation, hydropower, and other needs in the basin through a feedback loop. We focused on hydrologic extremes to evaluate their impacts on the reservoir operations during flood and low flow events. The inflow is projected to change by +13% to −50% in the future, while a 0.25% (15.24 billion m3) reduction is projected for the net irrigation water requirement (NIWR). A unit percentage increase in irrigation demand will reduce energy generation by 0.15%, but climate change has a beneficial impact on dam performance with a predicted increase in energy generation and supply to all sectors. Flood events will cause excessive stress on reservoir operation to handle up to six times more flow volumes; however, the low-flow events will marginally affect the system. While the flow and storage rule curves consider both supply and demand, changing human water use comes second to changing climate or other biophysical considerations. This paper emphasizes the importance of considering feedback between climate–water–human society in the systems modeling framework in order to meet societal and ecological challenges. The findings will provide information on the risks and tradeoffs that exist in the water, energy, and food sectors of the basin.

Water resources in Northern Thailand have been less explored with regard to the impact on hydrology that the future climate would have. For this study, three regional climate models (RCMs) from the Coordinated Regional Downscaling Experiment (CORDEX) of Coupled Model Intercomparison Project 5 (CMIP5) were used to project future climate of the upper Nan River basin. Future climate data of ACCESS_CCAM, MPI_ESM_CCAM, and CNRM_CCAM under Representation Concentration Pathways RCP4.5 and RCP8.5 were bias-corrected by the linear scaling method and subsequently drove the Hydrological Engineering Center-Hydrological Modeling System (HEC-HMS) to simulate future streamflow. This study compared baseline (1988–2005) climate and streamflow values with future time scales during 2020–2039 (2030s), 2040–2069 (2050s), and 2070–2099 (2080s). The upper Nan River basin will become warmer in future with highest increases in the maximum temperature of 3.8°C/year for MPI_ESM and minimum temperature of 3.6°C/year for ACCESS_CCAM under RCP8.5 during 2080s. The magnitude of changes and directions in mean monthly precipitation varies, with the highest increase of 109 mm for ACESSS_CCAM under RCP 4.5 in September and highest decrease of 77 mm in July for CNRM, during 2080s. Average of RCM combinations shows that decreases will be in ranges of −5.5 to −48.9% for annual flows, −31 to −47% for rainy season flows, and −47 to −67% for winter season flows. Increases in summer seasonal flows will be between 14 and 58%. Projection of future temperature levels indicates that higher increases will be during the latter part of the 20th century, and in general, the increases in the minimum temperature will be higher than those in the maximum temperature. The results of this study will be useful for river basin planners and government agencies to develop sustainable water management strategies and adaptation options to offset negative impacts of future changes in climate. In addition, the results will also be valuable for agriculturists and hydropower planners.

Napier grass is an energy crop that is promising for future power generation. Since Napier grass has never been planted extensively, it is important to understand the impacts of Napier grass plantations on local energetic, environmental, and socioeconomic features. In this study, the soil and water assessment tool (SWAT) model was employed to investigate the impacts of Napier grass plantation on runoff, sediment, and nitrate loads in Songkhla Lake Basin (SLB), southern Thailand. Historical data, collected between 2009 and 2018 from the U-tapao gaging station located in SLB were used to calibrate and validate the model in terms of precipitation, streamflow, and sediment. The simulated precipitation, streamflow, and sediment showed agreement with observed data, with the coefficients of determination being 0.791, 0.900, and 0.997, respectively. Subsequently, the SWAT model was applied to evaluate the impact of land use change from the baseline case to Napier grass plantation cases in abandoned areas with four different nitrogen fertilizer application levels. The results revealed that planting Napier grass decreased the average surface runoff and sediment in the watershed. A multidisciplinary assessment supporting future decision making was conducted using the results obtained from the SWAT model; these showed that Napier grass will provide enhanced benefits to hydrology and water quality when nitrogen fertilizers of 0 and 125 kgN ha−1 were applied. On the other hand, the benefits to the energy supply, farmer’s income, and CO2 reduction were highest when a nitrogen fertilization of 500 kgN ha−1 was applied. Nonetheless, planting Napier grass should be supported since it increases the energy supply and creates jobs while also reducing surface runoff, sediment yield, nitrate load, and CO2 emission.

Agriculture is one of the important and complex sectors, it is not only a simple economic sector but also a biological - technical system. Because the basis for agricultural development is the use of bio-energy - plants and animals. Agricultural sector, if understood in a narrow sense, is only the cultivation, husbandry and service sectors. As for agriculture, in broad terms it also includes forestry and fishery. Agriculture provides food and food for social needs, agriculture is the basic material production industry, plays a major role in economic development in most of the country, especially in developing countries. At present, Vietnam’s agriculture has great potential and can be enriched from agriculture. However, wastage and loss in agriculture are still high in the stages of processing, harvesting and preserving. Mechanization is still low, lower than Thailand, so agricultural labor productivity is not high. Over the past years, Vietnam’s Agriculture has achieved important developments, contributing to the development of Vietnam’s economy. However, to achieve higher goals in the next 10 years, Vietnam’s agriculture needs to promote its strengths, such as: Well implementing land policies in agriculture; training high quality human resources; building a credible agriculture, which is clean, safe, quality agriculture and organic agriculture; protect natural environment, such as: land, climate, weather, hydrology, etc. In order to ensure sustainable agricultural development.

The transformation of land-use and land cover in Nakhon Ratchasima province, Thailand has rapidly changed over the last few years. The major factors affecting the growth in the province arise from the huge expansion of developing areas, according to the government’s development plans that aim to promote the province as a central business-hub in the region. This development expansion has eventually intruded upon and interfered with sub-basin areas, which has led to environmental problems in the region. The scope of this study comprises three objectives, i.e., (i) to optimize the Cellular Automata (CA) model for predicting the expansion of built-up sites by 2022; (ii) to model a linear regression method for deriving the transition of the digital elevation model (DEM); and (iii) to apply Geographic Weighted Regression (GWR) for analyzing the risk of the stativity of flood areas in the province. The results of this study show that the optimized CA demonstrates accurate prediction of the expansion of built-up areas in 2022 using Land use (LU) data of 2-year intervals. In addition, the predicting model is generalized and converged at the iteration no. 4. The prediction outcomes, including spatial locations and ground-water touch points of the construction, are used to estimate and model the DEM to extract independent hydrology variables that are used in the determination of Flood Risk Susceptibility (FRS). In GWR in the research called FRS-GWR, this integration of quantitative GIS and the spatial model is anticipated to produce promising results in predicting the growth and expansion of built-up areas and land-use change that lead to an effective analysis of the impacts on spatial change in water sub-basin areas. This research may be beneficial in the process of urban planning with respect to the study of environmental impacts. In addition, it can indicate and impose important directions for development plans in cities to avoid and minimize flood area problems.

Investigations of land management impacts on hydrology are well developed in South–East Asia, having been greatly extended by national organizations in the last two decades. Regional collaborative efforts, such as the ASEAN–US watershed programme, have helped develop skills and long–running monitoring programmes. Work in different countries is significant for particular aspects: the powerful effects of both cyclones and landsliding in Taiwan, the significance of lahars in Java, of small–scale agriculture in Thailand and plantation establishment in Malaysia. Different aid programmes have contributed specialist knowledge such as British work on reservoir sedimentation, Dutch, Swedish and British work on softwood plantations and US work in hill–tribe agriculture. Much has been achieved through individual university research projects, including PhD and MSc theses. The net result is that for most countries there is now good information on changes in the rainfall–run–off relationship due to forest disturbance or conversion, some information on the impacts on sediment delivery and erosion of hillslopes, but relatively little about the dynamics and magnitude of nutrient losses. Improvements have been made in the ability to model the consequences of forest conversion and of selective logging and exciting prospects exist for the development of better predictions of transfer of water from the hillslopes to the stream channels using techniques such as multilevel modelling. Understanding of the processes involved has advanced through the detailed monitoring made possible at permanent field stations such as that at Danum Valley, Sabah.

Abstract Thailand's forests in reservoir watershed areas are declining at an alarming rate due to land use demand. Reforestation aiming at maintaining optimum forest areas becomes a top priority in reservoir management planning which needs hydrologic responses as inputs. This study aims at measurable assessment of the changes in hydrologic responses of the Ubolratana Reservoir in northeastern Thailand due to increasing forest areas. The assessment was done in two parts: (i) forest areas by CA Markov model and (ii) rainfall–runoff by Soil and Water Assessment Tool (SWAT) model. Assessment results indicate that increasing forest areas cause a decrease of runoff, peak flow, and hence, inflow volume into the reservoir. The optimum size of forest area was found to be much larger than the existing size, confirming the need for existing reforestation. Additional benefits of pursuing reforestation include less erosion and sedimentation which are required in reservoir management planning.

The riverine ecosystems of the Mekong River Basin possess the world’s most productive inland fishery and provide highly productive food crops for millions of people annually. The development of hydropower potential in the Mekong River has long been of interest to governments in the region. Among the existing 64 dams, 46 dams have been built in the Lower Mekong Basin (LMB) to produce up to 8650 MW of electricity. Additionally, of the 123 proposed built hydropower dams, eleven hydropower plants have been nominated for the river mainstream and are expected to install a total of 13,000 MW in the LMB countries. However, serious concerns have intensified over the potential negative economic consequences, especially on fisheries and agriculture in Cambodia and Vietnam. To date, most of the concerns have concentrated on the impacts on hydrology, environment, livelihood, and diversity in the LMB attributed to hydropower development. This paper, however, discusses the fishery and agricultural sectors of the LMB and focuses on the downstream floodplains of Cambodia and Vietnam. The dam construction has caused greater losses of biodiversity and fisheries than climate change in the LMB. The reduction of 276,847 and 178,169 t of fish, 3.7% and 2.3% of rice, 21.0% and 10.0% of maize will contribute to a decrease of 3.7% and 0.3% of the GDP of Cambodia and Vietnam, respectively. Lao PDR may benefit the most revenue from electricity generation than the other country in the LMB, as most of the proposed dams are projected in the country. Cambodia burdens 3/4 of the reduction of total capture fishery destruction, whilst Lao PDR, Thailand, and Vietnam endure the remaining 1/3 losses. The tradeoff analyses reveal that losses of capture fisheries, sediment or nutrients, and social mitigation costs are greater than the benefits from electricity generation, improved irrigation, and flood control of the LMB region. The socioeconomic and environmental damage caused by hydropower dams in developing countries, including the Mekong, is greater than the early costs in North America and Europe. It is proposed that dam construction for hydropower in the Mekong River, as well as other rivers in developing countries, should be gradually removed and shifted toward solar, wind, and other renewable resources.

Abstract. With remote sensing we can readily observe the Earth's surface, but direct observation of the sub-surface remains a challenge. In hydrology, but also in related disciplines such as agricultural and atmospheric sciences, knowledge of the dynamics of soil moisture in the root zone of vegetation is essential, as this part of the vadose zone is the core component controlling the partitioning of water into evaporative fluxes, drainage, recharge, and runoff. In this paper, we compared the catchment-scale soil moisture content in the root zone of vegetation, computed by a lumped conceptual model, with the remotely sensed Normalized Difference Infrared Index (NDII) in the Upper Ping River basin (UPRB) in northern Thailand. The NDII is widely used to monitor the equivalent water thickness (EWT) of leaves and canopy. Satellite data from the Moderate Resolution Imaging Spectroradiometer (MODIS) were used to determine the NDII over an 8-day period, covering the study area from 2001 to 2013. The results show that NDII values decrease sharply at the end of the wet season in October and reach lowest values near the end of the dry season in March. The values then increase abruptly after rains have started, but vary in an insignificant manner from the middle to the late rainy season. This paper investigates if the NDII can be used as a proxy for moisture deficit and hence for the amount of moisture stored in the root zone of vegetation, which is a crucial component of hydrological models. During periods of moisture stress, the 8-day average NDII values were found to correlate well with the 8-day average soil moisture content (Su) simulated by the lumped conceptual hydrological rainfall–runoff model FLEX for eight sub-catchments in the Upper Ping basin. Even the deseasonalized Su and NDII (after subtracting the dominant seasonal signal) showed good correlation during periods of moisture stress. The results illustrate the potential of the NDII as a proxy for catchment-scale root zone moisture deficit and as a potentially valuable constraint for the internal dynamics of hydrological models. In dry periods, when plants are exposed to water stress, the EWT (reflecting leaf water deficit) decreases steadily, as moisture stress in the leaves is connected to moisture deficits in the root zone. Subsequently, when the soil moisture is replenished as a result of rainfall, the EWT increases without delay. Once leaf water is close to saturation – mostly during the heart of the wet season – leaf characteristics and NDII values are not well correlated. However, for both hydrological modelling and water management, the stress periods are most important, which is why this product has the potential of becoming a highly efficient model constraint, particularly in ungauged basins.

Vegetation is the main body of the terrestrial ecosystem and is a significant indicator of environmental changes in the regional ecosystem. As an essential link connecting South Asia and Southeast Asia, the Lancang-Mekong River Basin(LMRB) can provide essential data support and a decision-making basis for the assessment of terrestrial ecosystem environmental changes and the research and management of hydrology and water resources in the basin by monitoring changes in its vegetation cover. This study takes the Lancang-Mekong River Basin as the study area, and employs the Sen slope estimation, Mann–Kendall test, and Hurst exponent based on the MODIS NDVI data from 2000 to 2021 to study the spatial and temporal evolution trend and future sustainability of its NDVI. Besides, the nonlinear characteristics such as mutation type and mutation year are detected and analyzed using the BFAST01 method. Results demonstrated that: (1) In the past 22 years, the NDVI of the Lancang-Mekong River Basin generally exhibited a fluctuating upward trend, and the NDVI value in 2021 was the largest, which was 0.825, showing an increase of 4.29% compared with 2000. However, the increase rate was different: China has the most considerable NDVI growth rate of 7.25%, followed by Thailand with an increase of 7.21%, Myanmar and Laos as the third, while Cambodia and Vietnam have relatively stable vegetation changes. The overall performance of NDVI is high in the south and low in the north, and is dominated by high and relatively high vegetation coverage, of which the area with vegetation coverage exceeding 0.8 accounts for 62%. (2) The Sen-MK trend showed that from 2000 to 2021, the area where the vegetation coverage in the basin showed a trend of increase and decrease accounted for 66.59% and 18.88%, respectively. The Hurst exponent indicated that the areas where NDVI will continue to increase, decrease, and remain unchanged in the future account for 60.14%, 25.29%, and 14.53%, respectively, and the future development trend of NDVI is uncertain, accounting for 0.04%. Thus, more attention should be paid to areas with a descending future development trend. (3) BFAST01 detected eight NDVI mutation types in the Lancang-Mekong River Basin over the past 22 years. The mutations mainly occurred in 2002–2018, while 2002–2004 and 2014–2018 were the most frequent periods of breakpoints. The mutation type of “interruption: increase with negative break” was changed the most during this period, which accounts for 36.54%, and the smallest was “monotonic decrease (with negative break)”, which only accounts for 0.65%. This research demonstrates that combining the conventional trend analysis method with the BFAST mutation test can more accurately analyze the spatiotemporal variation and nonlinear mutation of NDVI, thus providing a scientific reference to develop ecological environment-related work.

This study was a first attempt to portray the effects of land use and climate changes (CCs) on the hydrologic system in the Lamtakhong Basin in northeastern Thailand, which has been disturbed by various human activities, making it difficult to determine these impacts on hydrologic conditions. The hydrologic Soil and Water Assessment Tool model was set up with land use and soil data of 2002 and observed flow and weather data during 1999–2000. After the model was calibrated and validated against observed flow data during 2001–2009, its land use change scenario with input land use data of 2011 and its CC scenario with input weather data during 2010–2065 were simulated. The results showed that changing land use over the 10-year period had trivial influences on the hydrologic system, whereas changing climate over the 56-year period appeared to affect both water yields and flows. Water scarcity will tend to take place across the Lamtakhong Basin in the near future. Longer periods of severe droughts and floods might occasionally occur, particularly downstream. These findings will be useful for land and water resources managers and policy-makers to manage land and water resources in the river basin.

Accurate rainfall estimates are important in many hydrologic activities. Rainfall data are retrieved from rain gauges (RGs), satellites, radars, and re-analysis products. The accuracy of gauge-based gridded precipitation products (GbGPPs) relies on the distribution of RGs and the quality of rainfall data records obtained from these. The accuracy of satellite-based precipitation products (SbPPs) depends on many factors, including basin climatology, basin topography, precipitation mechanism, etc. The hydrologic utility of different precipitation products was examined in many developed regions; however, less focused on the developing world. The Huai Bang Sai (HBS) watershed in north-eastern Thailand is a less focused but an important catchment that significantly contributes to the water resources in Thailand. Therefore, this research presents the investigation results of the hydrologic utility of SbPPs and GbGPPs in the HBS watershed. The efficiency of nine SbPPs (including 3B42, 3B42-RT, PERSIANN, PERSIANN-CCS, PERSIANN-CDR, CHIRPS, CMORPH, IMERG, and MSWEP) and three GbGPPs (including APHRODITE_V1801, APHRODITE_V1901, and GPCC) was examined by simulating streamflow of the HBS watershed through the Soil & Water Assessment Tool (SWAT), hydrologic model. Subsequently, the streamflow simulation capacity of the hydrological model for different precipitation products was compared against observed streamflow records by using the same set of calibrated parameters used for an RG simulated scenario. The 3B42 product outperformed other SbPPS with a higher Nash–Sutcliffe Efficiency (NSEmonthly>0.55), while APHRODITE_V1901 (NSEmonthly>0.53) performed fairly well in the GbGPPs category with closer agreements with observed streamflow. In addition, the CMORPH precipitation product has not performed well in capturing observed rainfall and subsequently in simulating streamflow (NSEmonthly<0) of the HBS. Furthermore, MSWEP and CHIRPS products have performed fairly well during calibration; however, they showcased a lowered performance for validation. Therefore, the results suggest that accurate precipitation data is the major governing factor in streamflow modeling performances. The research outcomes would capture the interest of all stakeholders, including farmers, meteorologists, agriculturists, river basin managers, and hydrologists for potential applications in the tropical humid regions of the world. Moreover, 3B42 and APHRODITE_V1901 precipitation products show promising prospects for the tropical humid regions of the world for hydrologic modeling and climatological studies.

In the present study, the streamflow simulation capacities between the Soil and Water Assessment Tool (SWAT) and the Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) were compared for the Huai Bang Sai (HBS) watershed in northeastern Thailand. During calibration (2007–2010) and validation (2011–2014), the SWAT model demonstrated a Coefficient of Determination (R2) and a Nash Sutcliffe Efficiency (NSE) of 0.83 and 0.82, and 0.78 and 0.77, respectively. During the same periods, the HEC-HMS model demonstrated values of 0.80 and 0.79, and 0.84 and 0.82. The exceedance probabilities at 10%, 40%, and 90% were 144.5, 14.5, and 0.9 mm in the flow duration curves (FDCs) obtained for observed flow. From the HEC-HMS and SWAT models, these indices yielded 109.0, 15.0, and 0.02 mm, and 123.5, 16.95, and 0.02 mm. These results inferred those high flows were captured well by the SWAT model, while medium flows were captured well by the HEC-HMS model. It is noteworthy that the low flows were accurately simulated by both models. Furthermore, dry and wet seasonal flows were simulated reasonably well by the SWAT model with slight under-predictions of 2.12% and 13.52% compared to the observed values. The HEC-HMS model under-predicted the dry and wet seasonal flows by 10.76% and 18.54% compared to observed flows. The results of the present study will provide valuable recommendations for the stakeholders of the HBS watershed to improve water usage policies. In addition, the present study will be helpful to select the most appropriate hydrologic model for humid tropical watersheds in Thailand and elsewhere in the world.

Abstract. Thailand floods in 2011 caused an unprecedented economic damage in the Chao Phraya River basin. To diagnose the flood hazard characteristics, this study analyzes the hydrologic sensitivity of flood runoff and inundation to rainfall. The motivation is to address why the seemingly insignificant monsoon rainfall, or 1.2 times more rainfall than past large floods including the ones in 1995 and 2006, resulted in such a devastating flooding. To quantify the hydrologic sensitivity, this study simulated a long-term rainfall-runoff and inundation for the entire river basin (160 000 km2). The simulation suggested that the flood inundation volume in 2011 was 1.6 times more than past flood events. Furthermore the elasticity index suggested that 1% increase in rainfall causes 2.3% increase in runoff and 4.2% increase in flood inundation. This study highlights the importance of sensitivity quantification for better understanding of flood hazard characteristics; and the presented approach is effective for the analysis at large river basins.

A reservoir flood routing simulation software with spillway operation rules that are readable and configurable by the spillway operator is developed in this study. The software is part of the Dam Safety Remote Monitoring System used by the Electricity Generating Authority of Thailand. The flood routing simulation is implemented using a storage-indication routing method, which is a hydrologic method. The spillway operation rules are exhibited in a tree-based structure, in which the spillway gate opening is derived from the current reservoir water level (RWL), spillway gate opening, and flood situation if the peak inflow has passed. The simulation results show that the simulated RWL is similar to the RWL data in the dam construction manual. This verifies the accuracy of the reservoir flood routing simulation, which is useful for planning the spillway operation.

Abstract. The Thailand floods in 2011 caused unprecedented economic damage in the Chao Phraya River basin. To diagnose the flood hazard characteristics, this study analyses the hydrologic sensitivity of flood runoff and inundation to rainfall. The motivation is to address why the seemingly insignificant monsoon rainfall, or 1.2 times more rainfall than for past large floods, including the ones in 1995 and 2006, resulted in such devastating flooding. To quantify the hydrologic sensitivity, this study simulated long-term rainfall–runoff and inundation for the entire river basin (160 000 km2). The simulation suggested that the flood inundation volume was 1.6 times more in 2011 than for the past flood events. Furthermore, the elasticity index suggested that a 1 % increase in rainfall causes a 2.3 % increase in runoff and a 4.2 % increase in flood inundation. This study highlights the importance of sensitivity quantification for a better understanding of flood hazard characteristics; the presented basin-wide rainfall–runoff–inundation simulation was an effective approach to analyse the sensitivity of flood runoff and inundation at the river basin scale.

Abstract. Global Climate Models (GCMs) precipitation scenarios are often characterized by biases and coarse resolution that limit their direct application for basin level hydrological modeling. Bias-correction and spatial disaggregation methods are employed to improve the quality of ECHAM4/OPYC SRES A2 and B2 precipitation for the Ping River Basin in Thailand. Bias-correction method, based on gamma-gamma transformation, is applied to improve the frequency and amount of raw GCM precipitation at the grid nodes. Spatial disaggregation model parameters (β,σ2), based on multiplicative random cascade theory, are estimated using Mandelbrot-Kahane-Peyriere (MKP) function at q=1 for each month. Bias-correction method exhibits ability of reducing biases from the frequency and amount when compared with the computed frequency and amount at grid nodes based on spatially interpolated observed rainfall data. Spatial disaggregation model satisfactorily reproduces the observed trend and variation of average rainfall amount except during heavy rainfall events with certain degree of spatial and temporal variations. Finally, the hydrologic model, HEC-HMS, is applied to simulate the observed runoff for upper Ping River Basin based on the modified GCM precipitation scenarios and the raw GCM precipitation. Precipitation scenario developed with bias-correction and disaggregation provides an improved reproduction of basin level runoff observations.

Abstract The purpose of this study is to investigate the future runoff into the Nong Han Lake under the effects of climate change. The hydrological model Soil and Water Assessment Tool (SWAT) has been selected for this study. The calibration and validation were performed by comparing the simulated and observed runoff from gauging station KH90 for the period 2001–2003 and 2004–2005, respectively. Future climate projections were generated by Providing Regional Climates for Impacts Studies (PRECIS) under the A2 and B2 scenarios. The SWAT model yielded good results in comparison to the baseline; moreover, the results of the PRECIS model showed that both precipitations and temperatures increased. Consequently, the amount of runoff calculated by SWAT under the A2 and B2 scenarios was higher than that for the baseline. In addition, the amount of runoff calculated considering the A2 scenario was higher than that considering the B2 scenario, due to higher average annual precipitations in the former case. The methodology and results of this study constitute key information for stakeholders, especially for the development of effective water management systems in the lake, such as designing a rule curve to cope with any future incidents.

Abstract. Global Climate Models (GCMs) precipitation scenarios are often characterized by biases and coarse resolution that limit their direct application for basin level hydrological modeling. Bias-correction and spatial disaggregation methods are employed to improve the quality of ECHAM4/OPYC SRES A2 and B2 precipitation for the Ping River Basin in Thailand. Bias-correction method, based on gamma-gamma transformation, is applied to improve the frequency and amount of raw GCM precipitation at the grid nodes. Spatial disaggregation model parameters (β,σ2), based on multiplicative random cascade theory, are estimated using Mandelbrot-Kahane-Peyriere (MKP) function at q=1 for each month. Bias-correction method exhibits ability of reducing biases from the frequency and amount when compared with the computed frequency and amount at grid nodes based on spatially interpolated observed rainfall data. Spatial disaggregation model satisfactorily reproduces the observed trend and variation of average rainfall amount except during heavy rainfall events with certain degree of spatial and temporal variations. Finally, the hydrologic model, HEC-HMS, is applied to simulate the observed runoff for upper Ping River Basin based on the modified GCM precipitation scenarios and the raw GCM precipitation. Precipitation scenario developed with bias-correction and disaggregation provides an improved reproduction of basin level runoff observations.

Departures in precipitation from the normal are the cause of the onset of agricultural drought. In this study, we aim to identify extreme precipitation deficits using an index called Percent Normal (PN). We applied the proposed PN index to the agriculturally productive Mekong River Basin (MRB) to evaluate the propagation of precipitation deficits into agricultural drought based on the change in slope and mean of the precipitation, soil moisture and evapotranspiration anomalies. The results of the study showed the proposed PN index identified historical droughts in the years 1992, 1997–1998 and 2000–2006 in MRB; of these, 1992 was shown to be the longest drought, which lasted from the 43rd week (October) of 1991 to the 49th week (December) of 1994. The short-term but extreme drought was identified to occur in 2005 with below-normal precipitation that lasted for more than a year. An immediate effect of precipitation deficit was observed in evapotranspiration (ET) and soil water for agricultural (Thailand) and forested regions (Parts of Cambodia) of the basin with <5 weeks lag. We conclude that the drought indices adopted in this study are suitable to identify the small and long-term drought events, which will facilitate the development of a drought-resilient agricultural production system.

The Soil and Water Assessment Tool (SWAT) model is recognized as one of the top hydrological models applied for addressing hydrologic and environmental issues. This is the first review on the SWAT model studies in Southeast Asia, with an emphasis on its applications, current challenges and future research directions. A total of 126 articles were identified since 2006; roughly 50% of these studies were conducted in Vietnam or Thailand. About 16% of the studies were performed at a transnational scale, which included Cambodia, Lao PDR, Thailand, and Vietnam. Model capability assessment, land use, and climate change assessment are the main SWAT applications that have been reported for the region. Most of the SWAT calibration and validation results for these studies were classified as satisfactory to very good results based on widely recognized performance indicators. However, the parameterization, calibration and validation procedures are not well reported in some articles. Availability of reliable data is one of the main problems that SWAT users are confronted with, as these data are either not freely available or restricted from public access in some countries. Hence, future studies should be considered on identification and development of reliable input data for SWAT modeling. SWAT model modification based on the SEA climate, geographical and land use conditions is another research direction to be considered in the future. Moreover, application of SWAT for extreme events simulation requires more attention in this region.

The number and distribution of rainfall stations areneeded to simulate rainfall-run off transformation on hydrologic model. However, the availability of stations varies in watershed. The study aims to assess theinfluence of numberand distribution rainfall stations by a modelling approachto simulate run-off process. The use of HEC-HMS model is tocalibrate model parameters and simulaterun-offon 4 scenarios in Mae Caem Watershed (3,826 km2), Northern Thailand. The result shows the calibrated model parameters of 13 stationsare very satisfied by 0.826 of Nash coefficient. Based on the simulation result, the condition of 6 stations demonstrate the best fit regarding observation data by R2 = 0.927; the lowest correlation is three rainfall stations by 0.795 of R2. Also, simulated runoff rainfall for six stations (condition2) show results close to the observation discharge. Condition 1 (all stations) is somewhat higher than condition tworegarding pattern and peak discharge. Another result shows simulation of peak discharge condition 3 (station number 2, 5, and 13) has overestimate of observation discharge and condition 5 shows underestimate result to observation discharge. Overall the simulation results have met Nash's criteria, while the best results are in simulation with 6 stations (condition 2). Thus the number and position of rainfall stations have an influence on the modeling of rainfall runoff in the Ping River, Mae Caem Watershed.

The coastal areas of Phuket Island are facing the risk of seawater intrusion, because intense anthropic activity due to urbanization and the expansion of tourism influences coastal hydrologic systems. Indeed, the Kamala sub-district—on the western part of Phuket Island—is a well-known and attractive destination for tourists. Previous research indicates that there is likely to be a seawater intrusion in Kamala. The main purpose of this study was to delineate the seawater intrusion problem in a coastal aquifer in Kamala. Geo-electrical surveys of four lines were successfully conducted in the study area. Two-dimensional (2D) inversion models from the resistivity data show high-resolution subsurface resistivity anomalies of seawater intrusion. The concentration of the seawater intrusion decreases eastward toward the inland areas. Based on a sample measurement, the contaminated zone of seawater has a resistivity value smaller than 30 Ohm-m, and the empirical relationship between the formation conductivity and fluid conductivity of the study area was established. Finally, time-lapse Electrical Resistivity Imaging (time-lapse ERI) was conducted to prove that there was no presence of clay layers in study area; thus, the low resistivity plumes (smaller than 30 Ohm-m) were scientifically interpreted as being seawater intrusion.

Abstract The Mekong River is the lifeblood of the Southeast (SE) Asian economies. In situ and satellite-based precipitation are analyzed to assess the amount of water received as precipitation in the river basin (Mekong basin water), in particular, the amount each country receives. Laos, Thailand, and Cambodia contribute ~75% of the basin water during March–September, whereas China’s contribution is 10%–15%, except in winter when it rises to 25%. The processing of Mekong basin water into Mekong streamflow entails accounting for the uncertain water losses but, interestingly, interannual variations in Mekong basin water can be processed into Mekong streamflow using a simple hydrologic model, which is validated using monthly river discharge data from four stations. Preliminary evidence for the impact of upbasin dams on downstream flow, especially the timing of peak summer flow, is presented. Characterization of El Niño’s influence on SE Asian rainfall reveals significant rainfall reductions in the fall preceding and the spring following El Niño’s peak phase (winter); such reductions at the bookends of the dry season in SE Asia (winter) generate droughts, as in 2015–16. The linear trend in twentieth-century rainfall assesses the vulnerability of the region to climate change. The analysis indicates the feasibility of streamflow prediction using a simple hydrologic model driven by high-resolution precipitation observations and forecasts. It raises the prospects of drought prediction based on El Niño’s emergence/forecast. Finally, by showing the Mekong to be largely a rain-fed and not snowmelt-fed river, it provides quantitative context for assessing the notion of Chinese control on the lower Mekong via upbasin dams.

Optimal rule curves are necessary guidelines in the reservoir operation that have been used to assess performance of any reservoir to satisfy water supply, irrigation, industrial, hydropower, and environmental conservation requirements. This study applied the conditional genetic algorithm (CGA) and the conditional tabu search algorithm (CTSA) technique to connect with the reservoir simulation model in order to search optimal reservoir rule curves. The Ubolrat Reservoir located in the northeast region of Thailand was an illustrative application including historic monthly inflow, future inflow generated by the SWAT hydrological model using 50-year future climate data from the PRECIS regional climate model in case of B2 emission scenario by IPCC SRES, water demand, hydrologic data, and physical reservoir data. The future and synthetic inflow data of reservoirs were used to simulate reservoir system for evaluating water situation. The situations of water shortage and excess water were shown in terms of frequency magnitude and duration. The results have shown that the optimal rule curves from CGA and CTSA connected with the simulation model can mitigate drought and flood situations than the existing rule curves. The optimal future rule curves were more suitable for future situations than the other rule curves.

Due to a continuous increase in global temperature, the climate has been changing without sign of alleviation. An increase in the air temperature has caused changes in the hydrologic cycle, which have been followed by several emergencies of natural extreme events around the world. Thailand is one of the countries that has incurred a huge loss in assets and lives from the extreme flood and drought events, especially in the northern part. Therefore, the purpose of this study was to assess the hydrological regime in the Yom and Nan River basins, affected by climate change as well as the possibility of extreme floods and droughts. The hydrological processes of the study areas were generated via the physically-based hydrological model, namely the Soil and Water Assessment Tool (SWAT) model. The projected climate conditions were dependent on the outputs of the Global Climate Models (GCMs) as the Representative Concentration Pathways (RCPs) 2.6 and 8.5 between 2021 and 2095. Results show that the average air temperature, annual rainfall, and annual runoff will be significantly increased in the intermediate future (2046–2070) onwards, especially under RCP 8.5. According to the Flow Duration Curve and return period of peak discharge, there are fluctuating trends in the occurrence of extreme floods and drought events under RCP 2.6 from the future (2021–2045) to the far future (2071–2095). However, under RCP 8.5, the extreme flood and drought events seem to be more severe. The probability of extreme flood remains constant from the reference period to the near future, then rises dramatically in the intermediate and the far future. The intensity of extreme droughts will be increased in the near future and decreased in the intermediate future due to high annual rainfall, then tending to have an upward trend in the far future.

The climate change and insufficient data of the discharge and sediment yield in the catchment system are the main cause of the conflict amongst the consumers. The application of a semi-distributed hydrologic model and geographic information system can be a solution to this conflict. This study implemented the SWAT model to estimate the discharge and sediment yield in the Huay Luang Catchment, Northeast of Thailand. The accuracy of the model was affirmed and compared with the data from the Kh103 observed station during 2008–2016 via SWAT-CUP. The study outcome suggested that the SWAT model provided favourable results compared to the observed data where R2, NSE, and PBIAS of the discharge were 0.79, 0.77, and -18.1% respectively and those of the sediment yield were 0.68, 0.65, and -22.7% respectively. Additionally, the quantitative analysis on 22 sub-catchments as the spatial map derived from the Watershed Delineation indicated that both discharge and sediment yield during 2008–2011 were higher than the regular values by 35.9% and 109.6% consecutively, whereas during 2012–2015 were lower than the regulars by 22.4% and 45.4%. In the raining season, more than 50% of the sub-catchments demonstrated 9–20 cubic meter per second of the discharge and 1,000–5,000 tons of the sediment yield, while during the drought season, both volumes in most of the catchments indicated less than 6 cubic meter per second and 1,000 tons, respectively. These happened due to the changes of the rainfall each year. Hopefully, the result and spatial information from this study could be a great contribution to the water resource management and development in any catchment with insufficient data.

Climate change induced sea-level rise (SLR) is on its increase globally. Regionally the lowlands of China, Vietnam, Bangladesh, and islands of the Malaysian, Indonesian and Philippine archipelagos are among the world’s most threatened regions. Sea-level rise has major impacts on the ecosystems and society. It threatens coastal populations, economic activities, and fragile ecosystems as mangroves, coastal salt-marches and wetlands. This paper provides a summary of the current state of knowledge of sea level-rise and its effects on both human and natural ecosystems. The focus is on coastal urban areas and low lying deltas in South-East Asia and Vietnam, as one of the most threatened areas in the world. About 3 mm per year reflects the growing consensus on the average SLR worldwide. The trend speeds up during recent decades. The figures are subject to local, temporal and methodological variation. In Vietnam the average values of 3.3 mm per year during the 1993-2014 period are above the worldwide average. Although a basic conceptual understanding exists that the increasing global frequency of the strongest tropical cyclones is related with the increasing temperature and SLR, this relationship is insufficiently understood. Moreover the precise, complex environmental, economic, social, and health impacts are currently unclear. SLR, storms and changing precipitation patterns increase flood risks, in particular in urban areas. Part of the current scientific debate is on how urban agglomeration can be made more resilient to flood risks. Where originally mainly technical interventions dominated this discussion, it becomes increasingly clear that proactive special planning, flood defense, flood risk mitigation, flood preparation, and flood recovery are important, but costly instruments. 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Abstract. As a consequence of climate change, extreme and flood-causing precipitation events are expected to increase in magnitude and frequency, especially in today's high-precipitation areas. During the north-east monsoon seasons, Nakhon Si Thammarat in southern Thailand is flash-flooded every 2.22 years on average. This study investigates frequency and intensity of harmful discharges of the Tha Di River regarding the IPCC emission scenarios A2 and B2. The regional climate model (RCM) PRECIS was transformed using the advanced delta change (ADC) method. The hydrologic response model HBV-Light was calibrated to the catchment and supplied with ADC-scaled daily precipitation and temperature data for 2010–2089. Under the A2 (B2) scenario, the flood threshold exceedance frequency on average increases by 133 % (decreases by 10 %), average flood intensity increases by 3 % (decreases by 2 %) and the annual top five discharge peaks intensities increase by 46 % (decrease by 5 %). Yearly precipitation sums increase by 30 % (10 %) towards the end of the century. The A2 scenario predicts a precipitation increase during the rainy season, which intensifies flood events; while increases projected exclusively for the dry season are not expected to cause floods. Retention volume demand of past events was calculated to be up to 12 × 106 m3. Flood risks are staying at high levels under the B2 scenario or increase dramatically under the A2 scenario. Results show that the RCM scaling process is inflicted with systematic biases but is crucial to investigate small, mountainous catchments. Improvement of scaling techniques should therefore accompany the development towards high-resolution climate models.