Impact of climate change on the groundwater sustainability in the lower Chao Phraya basin, Thailand

This research investigates the impact of climate change on the hydraulic heads of Thailand's Lower Chao Phraya basin. The research also determines the sustainability of groundwater as the result from climate change. In the study, the climatic scenario (IPSL-CM5A-MR) of the Representative Concentration Pathways (RCP) between 2.6, 4.5 and 8.5 were considered, and the simulations were carried out using the three-dimensional groundwater flow model (i.e. MODFLOW-2000) predicting the groundwater behavior between 2017 and 2036. The findings revealed that the impact of climate change on the hydraulic head fluctuation was positively correlated. Specifically, under the IPSL-CM5A-MR RCP 4.5 that has the highest average precipitation, the average hydraulic head increased. In conclusion, the sustainability of groundwater in the Lower Chao Phraya basin was sufficient during the simulated time. However, the groundwater budget was lower than the average groundwater budget during 2009 – 2014 indicating, the groundwater storage was continuously decreased. Specifically, the 2nd, and 3rd (Phra Pradeang and Nakorn Luang) aquifers may be facing the groundwater shortage in the future

Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI

Comparing watershed soil erosion of Taiwan and Thailand

Tropical watersheds in Taiwan and Thailand face the same severe soil erosion problem that is increasing at an alarming rate. In order to evaluate the severity of soil erosion, we quantitatively investigate the issue using a common soil erosion model (Universal Soil Loss Equation, USLE) on the Shihmen reservoir watershed of Taiwan and the Lam Phra Ploeng basin of Thailand, and compare their respective erosion factors. The results show an interesting contrast between the two watersheds. Some of the factors (rainfall factor, slope-steepness factor) are higher in the Shihmen reservoir watershed, while others (soil erodibility factor, cover and management factor) are higher in the Lam Phra Ploeng basin. The net result is that these factors cancel each other out, and the amount of soil erosion of the two watersheds are very similar at 68.03 t/ha/yr and 67.57 t/ha/yr, respectively

Numerical Modeling of Single Pile Behaviors Due to Groundwater Level Rising

Behaviors of the pile foundation due to groundwater level rising were analyzed by a series two-dimensional finite element analyses with fully coupled flow-deformation analysis. The different numerical models of single bore pile depth and diameter in Bangkok subsoil were represented with the parametric study. The pile–soil movement due to groundwater levels rising between numerical simulation and a previous experiment of the centrifuge test as the same condition are in good agreement. With rising groundwater level, the reduction of pile capacity can be evidently performed by the increase of pile settlement relative to soil surface. Moreover, the development of the plastic point captured by the finite element analysis revealed the mechanism behind the reduction of pile capacity. In this study, the evaluation of pile stability due to groundwater level rising for preliminary guidelines to protect existing structures are proposed

Cluster and regression analysis for predicting salinity in groundwater

Groundwater salinity is a major problem particularly in the northeastern region of Thailand. Saline groundwater can cause widespread saline soil problem resulting in reducing agricultural productivity as in the Lower Nam Kam River Basin. In order to better manage the salinity problem, it is important to be able to predict the groundwater salinity. The objective of this research was to create a cluster-regression model for predicting the groundwater salinity. The indicator of groundwater salinity in this study was electrical conductivity because it was simple to measure in field. Ninety-eight parameters were measured including precipitation, surface water levels, groundwater levels and electrical conductivity. In this study, the highest groundwater salinity at 3 wells was predicted using the combined cluster and multiple linear regression analysis. Cross correlation and cluster analysis were applied in order to reduce the number of parameters to effectively predict the quality. After the parameter selection, multiple linear regression was applied and the modeling results obtained were R2 of 0.888, 0.918, and 0.692, respectively. This linear regression model technique can be applied elsewhere in the similar situation

Impact of climate change on the groundwater sustainability in the lower Chao Phraya basin, Thailand

This research investigates the impact of climate change on the hydraulic heads of Thailand's Lower Chao Phraya basin. The research also determines the sustainability of groundwater as the result from climate change. In the study, the climatic scenario (IPSL-CM5A-MR) of the Representative Concentration Pathways (RCP) between 2.6, 4.5 and 8.5 were considered, and the simulations were carried out using the three-dimensional groundwater flow model (i.e. MODFLOW-2000) predicting the groundwater behavior between 2017 and 2036. The findings revealed that the impact of climate change on the hydraulic head fluctuation was positively correlated. Specifically, under the IPSL-CM5A-MR RCP 4.5 that has the highest average precipitation, the average hydraulic head increased. In conclusion, the sustainability of groundwater in the Lower Chao Phraya basin was sufficient during the simulated time. However, the groundwater budget was lower than the average groundwater budget during 2009 – 2014 indicating, the groundwater storage was continuously decreased. Specifically, the 2nd, and 3rd (Phra Pradeang and Nakorn Luang) aquifers may be facing the groundwater shortage in the future

The Influence of Climate Variability Effects on Groundwater Time Series in the Lower Central Plains of Thailand

This 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 Integrated Moving 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 the Western North Pacific Monsoon Index—were used, along with the groundwater level data from 14 stations during the period 1980–2011 to develop the forecast model and verify it with the data of 2012.The first step was correlation of the ARIMA model 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 the MODFLOW for a conceptual model and synthesize groundwater levels in the study area, which covers around 43,000 km2 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

Comparing watershed soil erosion of Taiwan and Thailand

Tropical watersheds in Taiwan and Thailand face the same severe soil erosion problem that is increasing at an alarming rate. In order to evaluate the severity of soil erosion, we quantitatively investigate the issue using a common soil erosion model (Universal Soil Loss Equation, USLE) on the Shihmen reservoir watershed of Taiwan and the Lam Phra Ploeng basin of Thailand, and compare their respective erosion factors. The results show an interesting contrast between the two watersheds. Some of the factors (rainfall factor, slope-steepness factor) are higher in the Shihmen reservoir watershed, while others (soil erodibility factor, cover and management factor) are higher in the Lam Phra Ploeng basin. The net result is that these factors cancel each other out, and the amount of soil erosion of the two watersheds are very similar at 68.03 t/ha/yr and 67.57 t/ha/yr, respectively

Impact of Climate Change on Soil Erosion in the Lam Phra Phloeng Watershed

Soil erosion plays a vital role in reducing reservoir capacity. The Lam Phra Phloeng (LPP) dams were built for flood protection and irrigation. However, they have experienced reservoir sedimentation, and the capacity of the reservoir has decreased. The surrounding soil surface was easily eroded and transported by heavy rainfall and surface runoff to streams and eventually into the reservoir. Understanding this soil erosion and sedimentation is necessary for preventing further decline of reservoir capacity and water management. This research aims to estimate long-term average annual soil erosion and predict sediment yield in the reservoir due to climate change. The methodology is determined soil loss parameters and sediment yield using the Universal Soil Loss Equation (USLE) with the Sediment Delivery Ratio (SDR). The USLE and SDR methods differed from field data, with an average absolute error of 4.0%. The Global Climatic Model, Institute Pierre Simon Laplace-Climate Model version 5A (IPSL-CM5A-MR), with Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, was downscaled and analyzed to forecast future rainfall in the watershed. The high intensity of rainfall contributed to higher soil erosion, in RCP 8.5. Interestingly, the high and very high-risk areas increased, but the moderate risk area declined, indicating that the moderate risk area should be a priority in land management. However, the heavy rainfall and high slope gradient led to a slight increase in the soil erosion in some areas because the land covers were evergreen and deciduous forest. The prediction of sediment yield was positively correlated with the intensity of rainfall in the central part of the watershed, because the rainfall and runoff led the sediment to the river and streams, indicating that the land cover should be managed to prevent capacity decline