Seeboonruang, Uma
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Seeboonruang, Uma
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Seeboonruang, U.
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uma.se@kmitl.ac.th
24 results
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Item type:Publication, The relationship between the climatic indices and the rainfall fluctuation in the lower central plain of Thailand(2019-02-01) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Predicting sheet and rill erosion of Shihmen reservoir watershed in Taiwan using machine learning(2019-07-01); Thomas, KentShihmen Reservoir watershed is vital to the water supply in Northern Taiwan but the reservoir has been heavily impacted by sedimentation and soil erosion since 1964. The purpose of this study was to explore the capability of machine learning algorithms, such as decision tree and random forest, to predict soil erosion (sheet and rill erosion) depths in the Shihmen reservoir watershed. The accuracy of the models was evaluated using the RMSE (Root Mean Squared Error), MAE (Mean Absolute Error), and R<sup>2</sup>. Moreover, the models were verified against the multiple regression analysis, which is commonly used in statistical analysis. The predictors of these models were 14 environmental factors which influence soil erosion, whereas the target was 550 erosion pins installed at 55 locations (on 55 slopes) and monitored over a period of approximately three years. The data sets for the models were separated into 70% for the training data and 30% for the testing data, using the simple random sampling and stratified random sampling methods. The results show that the random forest algorithm performed the best of the three methods. Moreover, the stratified random sampling method had better results among the two sampling methods, as anticipated. The average error (RMSE relative to 1:1 line) of the stratified random sampling method of the random forest algorithm is 0.93 mm/yr in the training data and 1.75 mm/yr in the testing data, respectively. Finally, the random forest algorithm predicted that type of slope, slope direction, and sub-watershed are the three most important factors of the 14 environmental factors collected and used in this study for splits in the trees and thus they are the three most important factors affecting the depth of sheet and rill erosion in the Shihmen Reservoir watershed. The results of this study can be employed by decision-makers to improve soil conservation planning and watershed remediation. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Wavelet relationship between climate variability and deep groundwater fluctuation in Thailand’s Central Plains(2018-02-01)Groundwater is constantly under direct and indirect pressures from the anthropogenic effects, long-term climate change, and climate variability. This research investigates the association, in the time-frequency domain, between the groundwater fluctuations in Thailand’s Lower Chao Phraya Basin and specific climate variability forces: the El Nino/Southern Oscillation (ENSO), the Indian Ocean Dipole (IOD), and the Asian Summer Monsoons (ASM). The analysis was carried out using the wavelet method and the findings presented in the form of the complete, global, and local wavelet spectrums. In addition, the Pearson correlation was utilized to establish the linkages between the groundwater and the climate variability forces. The results indicated that the deep groundwater signals of the Lower Chao Phraya Basin were linked to the ENSO, IOD and ASM with the absolute correlation coefficients in excess of 0.5. Moreover, the recent climatic indices exerted greater influence on the groundwater than in the past, given the former’s correlation coefficients of 0.9 on average. By comparison, the deep groundwater was strongly associated with the recent ENSO and ASM but weakly linked to the IOD, with the absolute coefficients of around 0.5. The findings revealed the resilience of the deep groundwater under such high frequency signal conditions as the seasonal and tidal oscillations. Moreover, the results showed that the groundwater could be an alternative source of water supply during periods of droughts in the region. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An empirical decomposition of deep groundwater time series and possible link to climate variability(2014-01-01)Deep groundwater data reflects hydrological processes, climate change and variability, as well as any anthropogenic influence. Decomposition of deep groundwater signal examines the history of the groundwater region. Detrending is a vital step in decomposition of groundwater time series because it is expected to remove anthropogenic effects and long-term cyclic patterns. Eight detrending methods were applied to long-term groundwater records monitored in the Lower Chao Phraya basin in Thailand. Detrended residuals and subsequently periodograms of the residuals were computed by applying the Fourier series analysis. The result from this study indicates that the 5<sup>th</sup> order polynomial interpolation provides the trendlines that significantly relate to the groundwater withdrawal background. The detrended residual function is imbedded with two major cyclic patterns, which can be the result from global climate variability, e.g. Indian Ocean Dipole and the El Niño Southern Oscillation. The magnitude of deep groundwater dynamics as the result from the anthropogenic effect, is much greater than that of the climate variability in this region. In addition, this study demonstrates that caution must be exercised when fitting groundwater time series with different detrending techniques can yield mistaken cyclic patterns and may infer to different climate variability phenomenon. © 2014 Global NEST Printed in Greece. All rights reserved. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Assessment of social impacts of a reservoir on a saline soil area in northeast thailand(2013-01-28) - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Relationship between groundwater properties and soil salinity at the Lower Nam Kam River Basin in Thailand(2013-07-01)The Lower Nam Kam River Basin lies in the vicinity of the Mekong River and is located in the eastern section of the Nakhon Panom Province in northeastern Thailand. Drought, particularly in the winter and summer seasons, is the main environmental challenge in this area. In addition, soil becomes saline and groundwater is brackish in some locations. This problem worsens the drought crisis in the area. Groundwater is known to closely relate to the soil salinity distribution. To successfully manage highly saline areas, saline groundwater and soil properties must be evaluated together. Therefore, the main objective was to study the shallow groundwater physical and chemical properties in conjunction with surface soil salinity. Soil samples were collected and measured for physical and chemical properties. Shallow groundwater was measured for depth from ground surface and sampled from the sites in the study area. The water samples were measured for pH, total dissolved solids, electrical conductivity, and salinity. Results were interpolated and displayed via a geographic information system and further analyzed by simple linear regressions between surface soil salinity and the other factors. The results show that the topsoil contaminated with salinity is typically situated in relatively low areas with shallow groundwater levels and low head gradient of groundwater. This is due to the characteristics of the soil profile and groundwater depth. © 2012 Springer-Verlag Berlin Heidelberg. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Physico-chemical characterization of saline subsurface system near small endorheic ponds in Thailand(2014-04-01)The problem of salt-ravaged lands is reported in many parts of the world and could be exacerbated by the presence of an endorheic pond normally associated with a saline low-lying area. An endorheic or playa pond accumulates dissolved salts which can be carried primarily by groundwater before discharging into the pond; then, intense evaporation produces salt residues which can wreak havoc on the adjacent areas. The objective of this study is to investigate the subsurface conditions and groundwater interactions beneath two endorheic saline ponds of Thailand's Great Mekong Basin to have a better understanding and thereby efficiently manage the resources. A comprehensive analysis of the physical and geochemical properties (limited to pH, specific conductance and salinity) of the subsurface system was performed to determine the processes that regulated the migration of dissolved salt. The data collected from the deep and shallow groundwater of the basin were analyzed to determine their physical and chemical properties. Soil samples of various depths were examined to determine their respective geologic, chemical and unsaturated properties. The groundwater near the salt ponds was different from that of other areas in that its groundwater table was closer to the surface soil and its deep groundwater, which is of high pressure, was more saline than its shallow groundwater. As the capillary rise influences the topsoil, particularly in the saline pond areas, the vertical upward flow and the capillary force are thus the additional mechanisms of salt transportation to the endorheic ponds. Since these surface water bodies are the discharge sites for saline groundwater and are not perennial, a practical solution is to localize the saline groundwater. © 2014 Springer-Verlag Berlin Heidelberg. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Geographic information system-based impact assessment for illegal dumping in borrow pits in Chachoengsao Province, Thailand(2016-01-01)Rapid industrial development along Thailand's eastern seaboard has increased pollution and environmental degradation in this densely populated region of the country. A growing problem is illegal disposal of industrial waste in abandoned borrow pits in many locations, especially in the capital Bangkok and its neighboring provinces. Previous work has identifi ed the most likely illegal dumping sites in Chachoengsao Province. The focus of this work was to establish an impact assessment of potential dumping sites using a geographic information system (GIS) in order to create a patrolling and monitoring program for areas at highest risk. The impact assessment is based upon exposure and sensitivity factors of the illegal dumping sites. The exposure factor attempts to quantify the likelihood of illegal dumping; it includes distances from borrow pits to the nearest villages and highways, as well as the areas of the borrow pits. The sensitivity factor assesses the probability of environmental contamination; it includes site topography, ground permeability, aquifer characteristics, and distances to the nearest rivers. GIS was used to compute distances and to overlay other site characteristics. Variables within exposure and sensitivity factors were weighted based upon previous studies and recent expert analysis to compute exposure and sensitivity indices. Maps were then created in GIS for particular exposure and sensitivity factors, and overall impact assessment maps were constructed to indicate zones with low, medium, and high risk. These assessment maps could be adopted by local and regional governmental agencies, as well as local citizens, as part of preventive measures to conserve the local community and environment. Identifi cation of high-risk areas can contribute to the initiation of a monitoring and patrolling program to prevent illegal dumping and preserve environmental and natural resources. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The influence of climate variability effects on groundwater time series in the lower central plains of Thailand(2018-03-08); Saraphirom, PhayomThis research studies the relationship between the climate index and the groundwater level of the lower Chao Phraya basin, in order to forecast the groundwater level in the studied area by using Autoregressive IntegratedMoving Average with Explanatory (ARIMAX). The combination of 6 climate indices-Dipole Mode Index, Indian Summer Monsoon Index, Multivariate ENSO Index, Sea Surface Temperature NINO4, Southern Oscillation Index and theWestern North PacificMonsoon Index-were used, along with the groundwater level data from 14 stations during the period 1980-2011 to develop the forecastmodel and verify itwith the data of 2012.The first stepwas correlation of the ARIMAmodel with Autocorrelation Function and Partial Autocorrelation Function. The possible model was then selected using BIC statistics. Diagnostic Checking was done to consider the white noise characteristic of estimated residuals by using the statistics of Box and Ljung (Q-statistic). If the selected models were found to be proper, then the Granger Causality Test of the leading parameters or the climate index would be performed as the next step. The results show that there is a relationship between the groundwater level and the climate index. The model could be used to forecast effectively the average RMSE value at 0.6. The last step was to develop theMODFLOWfor a conceptualmodel and synthesize groundwater levels in the study area, which covers around 43,000 km<sup>2</sup> and has 8 layers of groundwater, with Bangkok clay on the top. All other boundary values were set to be steady. The calibration was done using the data of 325 observed wells. The normalized RMS value was 9.705%. The results were verified by the data using ARIMAX over the same time periods. To conclude, the simulated results of the monthly groundwater level in 2012 of the wells have a confidence interval of around 95%, which is near the result from the ARIMAX model. The advantages of the ARIMAX model include high accuracy, no requirement for a large amount of data and inexpensive implementation. It is one of the effective tools for the groundwater prediction. - Some of the metrics are blocked by yourconsent settings
Item type:Publication, A statistical assessment of the impact of land uses on surface water quality indexes(2012-06-30)The release of wastewater from various land uses is threatening the quality of surface water. Different land uses pose varying degrees of danger to water resources. The hazardous extent of each activity depends on the amount and characteristics of the wastewater. The concept of the contamination potential index (CPI) of an activity is introduced and applied here. The index depends on the quantity of wastewater from a single source and on various chemicals in the waste whose concentrations are above allowable standards. The CPI concept and the land use impact assessment are applied to the surface water conditions in Nakhon Nayok Province in the central region of Thailand. The land uses considered in this study are residential area, industrial zone, in-season and off-season rice farming, and swine and poultry livestock. Multiple linear regression analysis determines the impact of the CPIs of these land uses on certain water quality characteristics, i.e., total dissolved solids, electrical conductivity, phosphate, and chloride concentrations, using CPI. s and previous water quality measurements. The models are further verified according to the current CPIs and measured concentrations. The results of the backward and forward modeling show that the land uses that affect water quality are off-season rice farming, raising poultry, and residential activity. They demonstrate that total dissolved solids and conductivity are reasonable parameters to apply in the land use assessment. © 2012 Elsevier Ltd.