Estimating daily potential evapotranspiration using GNSS-based precipitable water vapor.

Potential evapotranspiration (PET) is a crucial component of the hydrological cycle and energy balance. Although the Penman-Monteith (PM) model is the most widely used method to estimate daily PET, it requires temperature, relative humidity, solar radiation, and wind speed. In Thailand, the number of potential weather stations to provide the required data is limited, which resulted in the absence of some input variables in many locations. The objective of this study is to develop the revised potential evapotranspiration (RPET) model to estimate daily PET using Global Navigation Satellite System-derived Precipitable Water Vapor (GNSS-PWV) and temperature data. The multiple linear regression analysis was used to develop and validate the RPET model. The performance of the RPET model along with the Global Land Evaporation Amsterdam Model (GLEAM v3.2 b) and the European Centre for Medium-Range Weather Forecasts Reanalysis-5 (ERA5-Land) products was investigated using the PM model. The results revealed that the RPET model showed a strong correlation with the PM model (r = 0.85, RMSE = 0.97 mm day-1, RSR = 0.53, NSE = 0.72) under limited meteorological inputs. The RPET model performance was superior when compared to GLEAM and ERA5-Land (r = 0.80, RMSE = 1.06 mm day-1). Therefore, the proposed model is greatly suitable for daily PET estimation with only required GNSS-PWV and temperature data, and this can be implemented for drought assessment and water resources management.

Earthquake precursory detection using diurnal GPS-TEC and kriging interpolation maps: 12 May 2008, Mw7.9 Wenchuan case study.

This study presents an alternative vertical total electron content (VTEC) anomaly detection technique based on diurnal VTEC values. In order to assess the consistency of the results, Mw7.9 Wenchuan earthquake occurred on May 12, 2008 was chosen as case study because several researches were performed on this earthquake event. In this detection technique, the daily mean of VTEC (AVTEC) and standard deviation of diurnal VTEC (SVTEC) were adopted in the analytical process instead of quartile-based technique. The spatial distribution of VTEC was illustrated by AVTEC and SVTEC maps which created from ordinary Kriging interpolation technique. The anomalous day derived from AVTEC and SVTEC was observed on May 9, 2008. The anomalous zone significantly appeared within the earthquake preparation zone in the southeast of the epicenter. The results were corresponding to the previous studies in terms of time and space. Thus, AVTEC, SVTEC and instantaneous ionospheric maps created from ordinary Kriging interpolation technique should be an alternative approach for detecting ionospheric anomaly prior to earthquake occurrence.•Simplified seismo-ionospheric anomaly detection technique•Ionospheric distribution is modelled by ordinary Kriging interpolation maps•The results are consistent with the previous studies in terms of time and space.

Evaluation of the CORDEX regional climate models (RCMs) for simulating climate extremes in the Asian cities.

This study evaluates the ability of 21 Regional Climate Models (RCMs) from the Coordinated Regional Climate Downscaling Experiment (CORDEX) in simulating climate extremes in the fast growing Asian cities which are highly vulnerable to climate change. The three Asian cities have two different climate characteristics, namely Bangkok and its vicinity and Ho Chi Minh City in tropical climate region and Kathmandu in sub-tropical and temperate climate region. The RCMs were evaluated to simulate the six climate indices; Consecutive Dry Days (CDD), Simple Daily Intensity Index (SDII), Number of extremely heavy precipitation days (R50mm), Maximum 1-day precipitation amount (RX1day), Mean of daily maximum temperature (TX mean) and Mean of daily minimum temperature (TN mean). The performance indicators used were correlation coefficient, normalized root mean square deviation, absolute normalized root mean square deviation and average absolute relative deviation. The Entropy method was endorsed to acquire weights of these four indicators and weightage average techniques were used for ranking of 21 RCMs. The result demonstrated that the best model for one climate index is not the same best model for other climate indices. The 3 RCMs; WAS44_SMHI_RCA4_IPSL_CM5A_MR, WAS44_SMHI_RCA4_MIROC5, and WAS44_IITM_REGCM4-4_CSIRO_MK3-6-0 are the best performing RCMs for simulating future climate extremes in Bangkok and its vicinity, Ho Chi Minh city and Kathmandu valley, respectively. Therefore, they are recommended to use for climate change impact and adaptation studies in water resources management in the selected cities.

Predicting flood events in Kathmandu Metropolitan City under climate change and urbanisation.

Urbanisation and climate change collectively impose the threat of urban flood. The impervious transformation and changes in local climatic conditions increase the risk of frequent pluvial flooding in Kathmandu. Therefore, this study aims to assess the integrated impact of urbanisation and climate change on pluvial flooding in Kathmandu Metropolitan City, using the Personal Computer Storm Water Management Model. The future daily rainfall from three Regional Climate Models under two Representative Concentration Pathways (RCPs) and the observed daily data has been disaggregated to hourly series using temporal rainfall disaggregation. The result shows that the combined impact on pluvial flood is likely to intensify with relatively more contribution from climate change. The CNRM-CM5-CSIRO-CCAM under the RCP 4.5 scenario projects the maximum increase (60-90%) in flood volume for current (75%) and extreme (90%) imperviousness, under a 2-year and 20-year return period (RP) with the extent of the flood area increasing more than the depth. For a 2-year RP, areas with a depth of 0.10-0.25 m are likely to expand while those from 0.25 to 0.40 m in depth are projected to have more velocity, and these trends are expected to be magnified for higher RPs. The study shows that even though urbanisation contributes less to urban pluvial flood, it can be a catalyst for exaggerating other factors and implementing management measures. For instance, the application of small-scale rainwater harvesting, and overflow storage reduced the runoff, thereby reducing the flood volume by 20-35%. Furthermore, the findings highlight the need for planning management strategies such as evaluation and upgrading of conventional drainage systems with low impact measures (rainwater harvesting and green roofs); technical and financial assistance to urban dwellers in adopting the management measures or a combination of them based on the location, requirements, and availability of information and resources to reduce the effects of pluvial flood in Kathmandu.

Pollution Assessment Based on Element Concentration of Tree Leaves and Topsoil in Ayutthaya Province, Thailand.

Atmospheric aerosol particles containing heavy metal contaminants deposit on the surface of plant leaves and the topsoil. Our aim was to reveal the pollution along an industrial-urban-rural gradient (IURG) in the central provinces of Thailand. Leaf samples from Ficus religiosa and Mimusops elengi were collected along with topsoil samples under the selected trees. Al, Ba, Ca, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn concentrations were determined by ICP-OES in soil and plant samples. Soils were not polluted according to the critical value; furthermore, the elemental composition did not differ among the sampling sites of the IURG. The rural site was also polluted due to heavy amounts of untreated wastewater of the adjacent Chao Phraya River. Bioaccumulation factors of Ba, Cu, and Mn was higher than 1, suggesting active accumulation of these elements in plant tissue. Our findings proved that the deposition of air pollutants and the resistance to air pollutants in the case of plant leaves were different and that humus materials of the soils had relevant role in bioaccumulation of Al, Ba, and Cu. At the same time, the geochemical background, the source of pollution, and the local plant species greatly influence the metal content of any given environmental compartment.

Non-Destructive Trace Detection of Explosives Using Pushbroom Scanning Hyperspectral Imaging System.

The aim of this study was to investigate the potential of the non-destructive hyperspectral imaging system (HSI) and accuracy of the model developed using Support Vector Machine (SVM) for determining trace detection of explosives. Raman spectroscopy has been used in similar studies, but no study has been published which is based on measurement of reflectance from hyperspectral sensor for trace detection of explosives. HSI used in this study has an advantage over existing techniques due to its combination of imaging system and spectroscopy, along with being contactless and non-destructive in nature. Hyperspectral images of the chemical were collected using the BaySpec hyperspectral sensor which operated in the spectral range of 400⁻1000 nm (144 bands). Image processing was applied on the acquired hyperspectral image to select the region of interest (ROI) and to extract the spectral reflectance of the chemicals which were stored as spectral library. Principal Component Analysis (PCA) and first derivative was applied to reduce the high dimensionality of the image and to determine the optimal wavelengths between 400 and 1000 nm. In total, 22 out of 144 wavelengths were selected by analysing the loadings of principal components (PC). SVM was used to develop the classification model. SVM model established on the whole spectrum from 400 to 1000 nm achieved an accuracy of 81.11%, whereas an accuracy of 77.17% with less computational load was achieved when SVM model was established on the optimal wavelengths selected. The results of the study demonstrate that the hyperspectral imaging system along with SVM is a promising tool for trace detection of explosives.

Spatio-temporal distribution and hotspots of Hand, Foot and Mouth Disease (HFMD) in northern Thailand.

Hand, Foot and Mouth Disease (HFMD) is an emerging viral disease, and at present, there are no antiviral drugs or vaccines available to control it. Outbreaks have persisted for the past 10 years, particularly in northern Thailand. This study aimed to elucidate the phenomenon of HFMD outbreaks from 2003 to 2012 using general statistics and spatial-temporal analysis employing a GIS-based method. The spatial analysis examined data at the village level to create a map representing the distribution pattern, mean center, standard deviation ellipse and hotspots for each outbreak. A temporal analysis was used to analyze the correlation between monthly case data and meteorological factors. The results indicate that the disease can occur at any time of the year, but appears to peak in the rainy and cold seasons. The distribution of outbreaks exhibited a clustered pattern. Most mean centers and standard deviation ellipses occurred in similar areas. The linear directional mean values of the outbreaks were oriented toward the south. When separated by season, it was found that there was a significant correlation with the direction of the southwest monsoon at the same time. An autocorrelation analysis revealed that hotspots tended to increase even when patient cases subsided. In particular, a new hotspot was found in the recent year in Mae Hong Son province.