The present study attempted estimations of watershed-scale storage changes at two mountainous watersheds in northern Thailand to understand the behaviors of watershed-scale storage under the 2011 Chao Phraya River flood. For this purpose, we applied a methodology that separates an hourly hydrograph into several discharge sub-components, and formulized watershed-scale storage-discharge relationships. The results showed that (1) this methodology was applicable to sub-tropic watersheds, (2) there were five different discharge sub-components, that correspond to the number of dominant rainfall-runoff processes, in two mountainous watersheds in northern Thailand, (3) the peak total storage in 2011 was estimated to occur in October because of strongly seasonal slower discharge sub-components, whereas the maximum total discharge was observed in June, (4) the sum of watershed-scale maximum storages of all the discharge sub-components in the upper Yom and Nan River watersheds were respectively estimated to be 135 mm and 405 mm, and the difference might be explained by the existence of the active fault running north-south in the upper Nan River watershed, and (5) the estimated storage with the recession time constants of 111 h at the beginnings of rainy seasons could explain the risk of slope failure occurrences within a watershed.
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.
This study analyzed the relationship between inundated area and actual water volume using data from satellites, including the Moderate Resolution Imaging Spectroradiometer (MODIS) and Gravity Recovery and Climate Experiment (GRACE) satellite systems. The results showed that using relatively simple assumptions for the flow of water, a clear relationship could be demonstrated between inundation ratio and water volume. In the Chao Phraya River basin, the spatial average of the converted data from MODIS showed good correlation with the water volume measured by GRACE. Since the method used in this study does not rely heavily on the characteristics of a specific region, it is expected the approach would be applicable on a global scale if the necessary data were available.
Depletion of groundwater is expected due to climate change. This study describes a catchment-scale study on projected groundwater recharge and storage in the Upper Chao Phraya River basin under changing climate scenarios. The period from 2026 to 2040 was assessed using climate projection results from global climate models (GCMs). Three GCMs, namely MIROC-ESM-CHEM (MIROC), HadGEM2-ES (HadGEM), and GFDL-ESM2M (GFDL), were used along with four greenhouse gas emission scenarios, namely RCP2.6, RCP4.5, RCP6.0, and RCP8.5, as the climate change conditions. The projected changes in groundwater recharge and storage were quantified as percent differences from the simulated recharge and storage for the reference period (1986–2000). A significant trend of decreasing mean monthly rainfall from April to June was detected for the HadGEM and the GFDL models. This change in rainfall pattern was projected to reduce the mean annual groundwater recharge (storage) by −12.9% (−1.46 km3), −9.7% (−1.35 km3), −13.9% (−1.49 km3), and −10.7% (−1.38 km3) for the RCP 2.6, 4.5, 6.0, and 8.5 scenarios, respectively. Based on the results of the relative change in groundwater storage, we expect that groundwater resources will be affected by climate change and that both groundwater recharge and storage will be reduced.
It is important to examine what future hydrological changes could occur as a result of climate change. In this study, we projected hydrological changes and their consistency under near-future and end-of-21st-century climate in the Chao Phraya River Basin. Through hydrological simulations using output from six AOGCMs under the RCP 4.5 and 8.5 scenarios, we have reached the following conclusions. Our results demonstrate a projected increase in mid-rainy season precipitation under future climate, which is a necessary condition for a large volume of runoff to occur in the late rainy season. Under end-of-21st-century climate, all simulations using six AOGCMs showed a large increase (> 20%) in runoff in Nakhon Sawan catchment under both RCP scenarios. Compared to the capacities of the Bhumibol and Sirikit dams, projected increases in runoff at the end of the 21st century are high. New flood management and mitigation plans will likely be necessary. Ensemble mean increases in precipitation and runoff were higher under RCP 8.5 than under the RCP 4.5 scenario in both projected periods. Thus, higher global mean temperature would cause higher precipitation and runoff in the basin. This inference is also supported by the higher precipitation and runoff projected under the late future compared with under the near-future climate.
Future river discharge in the Chao Phraya River basin was projected based on the performance of multiple General Circulation Models (GCMs). We developed a bias-corrected future climate dataset termed IDD (IMPAC-T Driving Dataset) under which the H08 hydrological model was used to project future river discharge. The IDD enabled us to conduct a projection that considered the spread in projections derived from multiple GCMs. Multiple performance-based projections were obtained using the correlation of monsoon precipitation between GCMs and several observations. The performance-based projections indicated that future river discharge in September increased 60%–90% above that of the retrospective simulation. Our results highlight the importance of appropriate evaluation for the performance of GCMs.
GSMaP_NRT (Near Real Time) is a viable tool to provide satellite-based precipitation data for further analysis. Its usefulness can be evident in the areas where continuous precipitation data is vital. This is why GSMaP_NRT performance has been evaluated globally. In this study, we evaluate its performance in terms of 1) rainfall detection capability based on Probability of Detection (POD) and False Alarm Ratio (FAR) and 2) estimation capability based on correlation coefficient and Root Mean Square Error (RMSE) over the Chaophraya River basin during 2009–2010. A non-realtime GSMaP_MVK (Moving Vector with Kalman filter) is also evaluated. Our results show that, at daily scale, both GSMaP_NRT/GSMaP_MVK performs well in rainy season (POD and FAR can reach 0.75/0.94 and 0.45/0.49, respectively) with acceptable RMSE of 14.64/14.23 mm. GSMaP_NRT tends to under-estimate whereas GSMaP_MVK slightly over-estimates the rain rates with correlation coefficient of 0.70 and 0.75. We conclude that GSMaP_NRT is considered good but not sufficient for near-realtime rainfall monitoring applications; whereas GSMaP_MVK is suitable for climate change studies.
Evapotranspiration (ET) over a diverse land use area in northern Thailand was successfully estimated by long-term eddy covariance measurements. Some measurement gaps due to instrumentation problems and administrative difficulties were unavoidable. Monthly ET trends revealed a maximum of 150 ± 10 mm in June and a minimum of 60 ± 10 mm in January. The annual mean ET was estimated to be 1300 ± 140 mm. The interannual variation in ET reflects the response of the land surface to meteorological events and land use/cover changes (LUCC); however, the effect of rainfall variation on ET was greater than that of LUCC. Effective heterogeneity was evaluated using the Bowen ratio; such information will be useful for understanding the effect of land surface heterogeneity on latent and sensible heat fluxes.
The objective of this study was to investigate the sensitivities of the parameters of the XinAnJiang model, hereinafter referred to as XAJ model. The XAJ model is the most popular rainfall-runoff model in China, and widely used all over the world. There were fifteen parameters in the modified XAJ model used in this study. Understanding the sensitivities is undoubtedly crucial for parameter optimization, even for manual calibration by trial and error. A sensitivity analysis technique proposed by Morris was used to analyze parameter sensitivities at time scales of year, month and day. The sensitivities of these parameters were shown to change. At annual scale, the parameters for input data adjustment are most sensitive. On the other hand, the parameters concerning runoff component separation and runoff concentration are sensitive at daily scale. The parameters relating to runoff generation are less sensitive at all three temporal scales. Additionally, strong interactions between the parameters were detected at all three temporal scales. The time scale dependent nature of the sensitivities offers the possibility to design more efficient optimization schemes for automatic model calibration of the XAJ model.
Rainfall patterns during summer monsoon in 2009 and 2010 over the middle of the Indochina Peninsula (ICP) are investigated using calibrated daily accumulated radar rainfall (CDARR). Empirical orthogonal function (EOF) analysis applied to CDARR shows that the first three modes explain 40% of the total rainfall variance. The pattern of the first EOF mode is only positive over the radar observation area with a large value near the foot of the Annam range in the eastern region of the radar site. The second EOF mode is a dipole pattern that has positive and negative regions in the eastern and western regions of the radar observation area, respectively. The third EOF mode also shows a dipole pattern with positive and negative areas in the southern and northern regions of the observation area, respectively. Composite analysis results suggest that the first EOF mode is possibly produced by a difference in positive vorticity, in which the difference in the southerly wind component likely causes orographic rainfall in the eastern region of the radar site. In addition, the second and third EOF modes are possibly produced by differences in westerly and southwesterly wind components, respectively.
This research aims to evaluate children’s awareness and preparedness toward potential flood risks in Zagreb, Croatia, and to identify key factors in future education for Disaster Risk Reduction (DRR) in the city. In 1964, Zagreb experienced a large flood leading to 17 casualties. There have been no major floods since the national government implemented flood protection, however, the river water levels rise markedly during unexpected heavy rainfall. Although various actions are ongoing in Croatia to raise children’s awareness of natural disasters, very little systematic research can be found on this important topic, especially vulnerability, awareness and preparedness of young generation. Hence, a social survey of children 14–17 years old was conducted in Zagreb. The findings suggest that a fear of extreme weather and preparation status are somewhat co-related. Although 75% of the respondents were aware of the possibility of future floods, preparedness among them was disproportionate to their awareness and there was a gender gap in preparation status. It was concluded that the use of experimental, visual tools would be the best DRR method to educate the children of Zagreb by giving them a clearer understanding of the potential flood risks with information from materials compiled by the Croatian government.
Statistical and dynamic methods were used in the downscaling process from Global Climate Model (GCM) to Regional Climate Model (RCM). We selected the European Centre for Medium-Range Weather Forecasts model, Hamburg version 4 (ECHAM4) with 300 × 300 km resolution for A2 scenario. We focused on SE Asia domain located between 20°S to 30°N and 80°E to 135°E for 1960–2099 with wind components, temperature, geo-potential height, and specific humidity as data input in Providing Regional Climates for Impacts Studies (PRECIS) RCM analysis. The downscaling process output was 50 km resolution for 1971–2010 and precipitation, temperature, wind, relative humidity, radiation from 8 meteorological stations in Chao Phaya River Basin; Lampang, Suphanburi, Nan, Sisamrong, Takfa, Chainat, Uthong and Bangna selected and used for bias correction. Three methods, namely 1) adjusting the mean based on RCM, 2) adjusting the mean based on observation, and 3) quantile-based mapping were used. Methods were compared using observed climatic data, RCM outputs of calibration period, and RCM outputs from the validation period. RSME was found to be lower for method 2 compared to other methods implying a relatively superior technique for improving the model. As such method 2 was used to correct the PRECIS products during 2001–2009. These products are useful in the studies of impact of climate change and for early warning systems in Thailand.