26 research outputs found
The increased carbon storage changes with a decrease in phosphorus availability in the organic paddy soil
This study aimed to investigate the effect of organic rice farming on the various forms of inorganic phosphorus, the concentration of dissolved organic carbon (DOC) and carbon storage, and the relationship between DOC and P fractions in organic rice farming (ORF). The soil samples were taken from 11 organic plots, and three pseudo-replicates were sampled from individuals of various soil depths. The P-fractions, the soil organic carbon (SOC), DOC, and other soil properties were analyzed by standard methods from soils. The data were analyzed using One-way and Two-way ANOVA and tested using the least significant difference. The results showed that ORF soils had less labile P than conventional rice farming, while ORF had a higher average of DOC, SOC, and C stock than conventional rice soil (P<0.05). Organic fertilizers such as animal manure application and rice straw retention were used for ten years in the ORF. The agricultural practices of ORF would convince the amount of amorphous Fe and Al on soil minerals significantly and would increase the adsorption capacity of the soil mineral surfaces by organic fertilization. The Fe-P fraction responded to the increased adsorption capacity in the ORF and shown along with the DOC and P which were less than in ORF. Both of them were more adsorbed on the surface mineral. Meanwhile, the lower P for nutrient cycling in ORF soil, the lesser the decomposition of DOC and SOC, which then affected the increase of soil C storage
āļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāļāļāļāđāļāļāļāļģāļĨāļāļāļāļļāļāļāļ§āļīāļāļĒāļē SWAT āđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļāļāļāļĨāļļāđāļĄāļāđāļģāļ§āļąāļPerformance of SWAT Hydrologic Model for Runoff Simulation in Wang River Basin
āļāļēāļĢāļĻāļķāļāļĐāļēāļāļĩāđāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļāļāļĢāļ°āđāļĄāļīāļāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāļāļāļāđāļāļāļāļģāļĨāļāļāļāļļāļāļāļ§āļīāļāļĒāļē SWAT āđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāđāļāļĨāļļāđāļĄāļāđāļģāļ§āļąāļ āļāđāļāļĄāļđāļĨāļāļģāđāļāđāļēāļāļĢāļ°āļāļāļāđāļāļāđāļ§āļĒāļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāļāļļāļāļļāļāļīāļĒāļĄāļ§āļīāļāļĒāļēāļĢāļēāļĒāļ§āļąāļ āļāļĩ āļ.āļĻ. 2547â2556 āļāđāļāļĄāļđāļĨāļāļēāļĢāđāļāđāļāļĩāđāļāļīāļāļāļĩ āļ.āļĻ. 2552 āđāļĨāļ°āļāđāļāļĄāļđāļĨāļ āļđāļĄāļīāļāļĢāļ°āđāļāļĻ āļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ·āđāļāļāļĩāđāļĨāļļāđāļĄāļāđāļģ āđāļāđāļāđāļāđāļ 18 āļĨāļļāđāļĄāļāđāļģāļĒāđāļāļĒ āđāļĨāļ°āļāļģāļŦāļāļāļāļļāļāļāļēāļāļāļāļāļāļāļāļĨāļļāđāļĄāļāđāļģāļāļĩāđāļĄāļĩāļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļĢāļēāļĒāļ§āļąāļāļāļģāļāļ§āļ 10 āļāļļāļ āđāļāļ·āđāļāđāļāđāļŠāļāļāđāļāļĩāļĒāļāđāļāļāļāļģāļĨāļāļ SWAT āļāļāļāļāļēāļāļāļĩāđāļĒāļąāļāđāļāđāļāļģāļāļēāļĢāļāļĢāļąāļāļāđāļēāļāļēāļĢāļēāļĄāļīāđāļāļāļĢāđāļāđāļēāļāđāļāļĩāđāđāļāđāļāļāđāļāļĄāļđāļĨāđāļāļīāļāļāļēāļĒāļ āļēāļāļāļāļāļĨāļļāđāļĄāļāđāļģ āđāļāđāđāļāđ āļāđāļģāļāļīāļ§āļāļīāļ āļāđāļģāđāļāđāļāļīāļ āļĨāļļāđāļĄāļāđāļģ āļāļīāļ āđāļĨāļ°āļāļēāļĢāđāļŦāļĨāđāļāļāļēāļāļāđāļģ āđāļāļ·āđāļāđāļāļīāđāļĄāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāļāļāļāđāļāļāļāļģāļĨāļāļāļŠāļēāļĄāļēāļĢāļāļāļģāļĨāļāļāđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļē āļāļēāļāļāļĨāļāļēāļĢāļĻāļķāļāļĐāļēāļāļāļ§āđāļēāđāļāļāļāļģāļĨāļāļ SWAT āļĄāļĩāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļāļāļāļĨāļļāđāļĄāļāđāļģāļ§āļąāļāđāļāđāļāļāļāđāļāļĩāđāļĒāļāļĄāļĢāļąāļāđāļāđāđāļāļĒāđāļāļāļēāļ°āđāļāļĨāļļāđāļĄāļāđāļģāļĒāđāļāļĒāļāļĩāđāđāļĄāđāļĄāļĩāđāļāļ·āđāļāļāļāļāļāļāļĨāļēāļĒāļāļāļāļĨāļļāđāļĄāļāđāļģāļ§āļąāļāđāļĨāļ°āđāļŦāļĄāļēāļ°āļŠāļĄāđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāđāļāļāđāļ§āļāļĪāļāļđāļāļāļĄāļēāļāļāļ§āđāļēāļĪāļāļđāđāļĨāđāļ āļāļĒāđāļēāļāđāļĢāļāđāļāļēāļĄ āđāļāļāļāļģāļĨāļāļ SWAT āļĒāļąāļāļĄāļĩāļāđāļāļāļģāļāļąāļāđāļāļāļēāļĢāļāļģāļĨāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļĢāļēāļĒāđāļāļ·āļāļāļŠāļđāļāļŠāļļāļ āđāļāļĒāđāļāļāļēāļ°āđāļāđāļāļ·āļāļāļāļĩāđāļĄāļĩāļāļąāļāļŦāļēāļāđāļģāļāđāļ§āļĄāļāļĢāļīāļĄāļēāļāļāđāļģāļāđāļēāļŠāļđāļāļŠāļļāļāļĢāļēāļĒāđāļāļ·āļāļāļāļēāļāđāļāļāļāļģāļĨāļāļāļĄāļĩāļāđāļēāļāđāļģāļāļ§āđāļēāļāđāļēāļāļĢāļ§āļāļ§āļąāļāļāļĢāļīāļThe purpose of this study was to evaluate the efficiency of SWAT hydrological model for runoff simulation in Wang River Basin. The input data includes the daily meteorological observation data during the year 2004â2013, land-use of the year 2009 and topographical data. The analyses were divided the whole basin into 18 sub-basins and defined the basin outlets at 10 stations of observed daily runoff data to calibrate the SWAT model. In addition, the basin physical parameters including surface water, groundwater, watershed, soil, and channel flow, have been adjusted to improve the efficiency of the model in the runoff simulation. The results showed that the SWAT model was effective in simulating the runoff of the Wang River Basin, especially in the non-dam sub-basin and the end of the Wang River Basin. The model is appropriate to simulate the runoff during the wet season rather than the dry season. However, the SWAT model has limitations on the maximum monthly runoff model, especially in the month of flood problem, the maximum monthly runoff from the model was lower than the observed value
āļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļĨāļāļĢāļ°āļāļāļāļēāļāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāļāđāļāļĻāļąāļāļĒāļ āļēāļāļāļēāļĢāđāļāļīāļāđāļāļāđāļēāđāļāļāļąāļāļŦāļ§āļąāļāđāļāļĩāļĒāļāđāļŦāļĄāđāđāļāļĒāđāļāđāđāļāļāļāļģāļĨāļāļāļāļēāļĢāļāļāļāļāļĒAnalysis of Impact of Climate Change on Forest Fire Potential in Chiang Mai by Using of Regression Model
āļāļēāļĢāļĻāļķāļāļĐāļēāļāļĩāđāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļĨāļāļĢāļ°āļāļāļāļēāļāļāļēāļĢāđāļāļĨāļĩāđāļĒāļāđāļāļĨāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāļāđāļāļĻāļąāļāļĒāļ āļēāļāđāļāļāļēāļĢāđāļāļīāļāđāļāļāđāļēāđāļāļāļąāļāļŦāļ§āļąāļāđāļāļĩāļĒāļāđāļŦāļĄāđ āļāđāļ§āļĒāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļĨāļ°āļŠāļĢāđāļēāļāđāļāļāļāļģāļĨāļāļāļāļēāļĢāļāļāļāļāļĒāļāļąāđāļāđāļāļāđāļŠāđāļāļāļĢāļāđāļĨāļ°āđāļĄāđāđāļāđāļāđāļŠāđāļāļāļĢāļ āđāļāļĒāđāļāđāļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāđāļĨāļ°āļāđāļāļĄāļđāļĨāļāļ·āđāļāļāļĩāđāđāļāļēāđāļŦāļĄāđāļāļąāđāļāļāļēāļāļ āļēāļāļāļēāļ§āđāļāļĩāļĒāļĄāđāļĨāļ°āļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāđāļāļāđāļ§āļāļĪāļāļđāđāļāļāđāļē (āļāļąāļāļ§āļēāļāļĄâāļāļĪāļĐāļ āļēāļāļĄ) āđāļāļŠāđāļ§āļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļāļ§āđāļāđāļĄāļāļēāļĢāđāļāļīāļāļāļ·āđāļāļāļĩāđāđāļāļāđāļēāđāļāļāļāļēāļāļāđāļāđāļāđāļāļĄāļđāļĨāļāļ§āļēāļĄāļāļ·āđāļāļŠāļąāļĄāļāļąāļāļāđāļāļēāļāđāļāļāļāļģāļĨāļāļ WRF-ECHAM5 āļāļģāđāļāđāļēāļŠāļĄāļāļēāļĢāļāļāļāļāļĒāļāđāļēāļāļāđāļ āļāļķāđāļāļāļēāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāđāļāļĢāļĩāļĒāļāđāļāļĩāļĒāļāļāļāļ§āđāļēāđāļāļāļāļģāļĨāļāļāļāļēāļĢāļāļāļāļāļĒāđāļāļāđāļĄāđāđāļāđāļāđāļŠāđāļāļāļĢāļāđāļāđāļāļ§āļīāļāļĩāļāļĩāđāļĒāļ·āļāļŦāļĒāļļāđāļāđāļĨāļ°āđāļŦāļĄāļēāļ°āļŠāļĄāļāļ§āđāļēāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāđāļ§āļĒāļ§āļīāļāļĩāļāļēāļĢāļāļāļāļāļĒāđāļāļāđāļŠāđāļāļāļĢāļ āđāļāļĒāļāļąāļāļāļąāļĒāļāļĩāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāđāļēāļŠāļĄāļāļēāļĢāļāļāļāļāļĒāļĄāļĩāđāļāļĩāļĒāļāļāļ§āļēāļĄāļāļ·āđāļāļŠāļąāļĄāļāļąāļāļāđāđāļāļĩāļĒāļāļāļąāļāļāļąāļĒāđāļāļĩāļĒāļ§ āļŠāđāļ§āļāļāļąāļāļāļąāļĒāļāļąāļ§āđāļāļĢāļ āļđāļĄāļīāļāļēāļāļēāļĻāļāļ·āđāļāđ āđāļĄāđāļŠāļēāļĄāļēāļĢāļāļāļģāđāļāđāļēāđāļāđāđāļāļ·āđāļāļāļāļēāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļĒāļāļĄāļĢāļąāļāļāļēāļāļŠāļāļīāļāļīāđāļāđ āđāļĄāļ·āđāļāļāļģāļŠāļĄāļāļēāļĢāļāļāļāļāļĒāđāļāļāđāļĄāđāđāļāđāļāđāļŠāđāļāļāļĢāļāļāļĩāđāđāļāđāļāļģāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļĄāļēāļāļāļŠāļāļāļāļąāļāļāđāļāļĄāļđāļĨāļāļ§āļēāļĄāļāļ·āđāļāļŠāļąāļĄāļāļąāļāļāđāļāļēāļāđāļāļāļāļģāļĨāļāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāļ āļđāļĄāļīāļ āļēāļ WRFECHAM5 āļāļāļ§āđāļēāļāļ§āļēāļĄāļāļ·āđāļāļĄāļĩāđāļāļ§āđāļāđāļĄāļĨāļāļĨāļāđāļāļāļąāļāļĢāļē 1.3% āđāļĨāļ°āļĄāļĩāļāļ§āļēāļĄāđāļāļĢāļāļĢāļ§āļāļĢāļ°āļŦāļ§āđāļēāļāļāļĩāļāļāļāļāļ§āļēāļĄāļāļ·āđāļāļŠāļđāļ āļāļķāđāļāļāļģāđāļŦāđāđāļĄāļ·āđāļāļāļģāļāļ§āļēāļĄāļāļ·āđāļāļāļēāļāđāļāļāļāļģāļĨāļāļāđāļāđāļēāļŠāļĄāļāļēāļĢāļāļāļāļāļĒāđāļāļāđāļĄāđāđāļāđāļāđāļŠāđāļāļāļĢāļāļāļĩāđāđāļāđāļŠāđāļāļāļĨāļāļģāđāļŦāđāļĻāļąāļāļĒāļ āļēāļāđāļāļāļēāļĢāđāļāļīāļāđāļāļāđāļēāđāļāļāļāļēāļāļāļĄāļĩāđāļāļ§āđāļāđāļĄāļĨāļāļĨāļ āļāļĒāđāļēāļāđāļĢāļāđāļāļēāļĄ āļāļēāļāļāļēāļĢāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļāļ§āđāļēāļāļ§āļēāļĄāđāļāļĢāļāļĢāļ§āļāļāļāļāļŠāļ āļēāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāđāļāļāļŠāļļāļāļāļĩāļāđāļāļāļāļēāļāļāļĄāļĩāđāļāļ§āđāļāđāļĄāļĄāļēāļāļāļķāđāļāđāļāļĒāļĄāļĩāļāļēāļāđāļāļāļēāļĢāđāļāļīāļāļāļļāļ 5 āļāļĩ āđāļĨāļ°āļŠāđāļāļāļĨāļāđāļāļāļ§āļēāļĄāđāļāļĢāļāļĢāļ§āļāļĨāļ°āļāļ§āļēāļĄāļĢāļļāļāđāļĢāļāļāļāļāļĻāļąāļāļĒāļ āļēāļāļāļēāļĢāđāļāļīāļāđāļāļāđāļē āļāļāļāļāļēāļāļāļĩāđāļĒāļąāļāļāļāļ§āđāļēāļĻāļąāļāļĒāļ āļēāļāđāļāļāļēāļĢāđāļāļīāļāđāļāļāđāļēāđāļāļāļāļēāļāļāļĄāļĩāļāđāļ§āļāđāļ§āļĨāļēāļāļēāļĢāđāļāļīāļāļāļĩāđāđāļĢāđāļ§āļāļķāđāļāļāļ§āđāļēāđāļāļīāļĄ āļāļķāđāļāđāļāđāļāļāļĨāļĄāļēāļāļēāļāļāļ§āļēāļĄāļāļ·āđāļāđāļāđāļāļ·āļāļāļĄāļāļĢāļēāļāļĄāđāļĨāļ°āđāļāļ·āļāļāļāļļāļĄāļ āļēāļāļąāļāļāđāļĄāļĩāđāļāļ§āđāļāđāļĄāļĨāļāļĨāļāđāļāļāļāļ°āļāļĩāđāđāļāļ·āļāļāļāļ·āđāļāđ āļĄāļĩāđāļāļ§āđāļāđāļĄāļāļ§āļēāļĄāļāļ·āđāļāđāļāļīāđāļĄāļāļķāđāļThis study aims to analyze the impact of climate change on future forest fire potential in Chiang Mai Province, analyzed by regression analysis with the linear and non-linear approach. Following the approach used to observe weather data and burn scar area from both MODIS sensor and forest fire hotspot. In a part of burn area trend analysis in the future used absolute humidity data from WRF-ECHAM5 model, which used into following regression model. The result of the comparative analysis, nonlinear regression models are more flexible and appropriate than linear regression analysis. Climatic factors that can be applied to the regression equation are relative humidity only. While other climate variables could not be imported because the results were not statistically unacceptable. When applied the acceptable nonlinear regression model with the relative humidity data from the WRF-ECHAM5 regional climate model, it was found that relative humidity decreased by 1.3%, and there is high yearly variation in relative humidity, which leads to the decrease in the forest fires potential in the future when the modeled relative humidity is applied to the non-linear regression equation. However, the analysis found that the variability of extreme climate in the future is more likely to occur every 5 years, and is likely to affect the variability and severity of the potential forest fires. In addition, the potential for future forest fires is much faster than ever before. As a result of the humidity in January and February tend to decrease while other months tend to increase humidity
Study of the Interaction of Dissolved Organic Carbon, Available Nutrients, and Clay Content Driving Soil Carbon Storage in the Rice Rotation Cropping System in Northern Thailand
The appropriate management of crop residues in a rice rotation cropping system (RRCS) can promote carbon storage and contribute to soil health. The objective of this study was to determine and analyze the amount of organic carbon in the soil, the amount of labile carbon in a dissolved state in the soil, and the physicochemical properties of the soil and their relationship with soil organic carbon dynamics under the RRCS in northern Thailand. The RRCS can be divided into the following four categories by pattern: (1) Rice_F (rice (Oryza sativa) followed by a fallow period); (2) Rice_S (rice followed by shallots (Allium cepa L.); (3) Rice_Mixed crop (rice followed by tobacco (Nicotiana tabacum), vegetables, or maize (Zea mays)); and (4) Rice_P (rice followed by potatoes (Solanum tuberosum)). These patterns can be classified according to the dissolved organic carbon (DOC), the availability of nutrients from fertilization, and clay contents. In our study, the Rice-F and Rice-S patterns led to higher soil organic carbon (SOC) and dissolved organic carbon (DOC) in the soil, but when the Rice-P pattern was followed, the soil had a lower clay content, lower available phosphorus (Avail P), the lowest DOC, and high contents of calcium (Ca2+) and magnesium (Mg2+). This study also revealed that on the basis of relationships, clay content, Avail P, and DOC were the most important factors for the formation of SOC, while Ca2+ and Mg2+ were the subordinate factors for the decreased formation of SOC and carbon storage when the RRCS was followed. In addition, low SOC/clay when the Rice-P pattern was followed could reflect carbon saturation, while the percentages of DOC/SOC could indicate the decomposition and formation of SOC
āļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļāļāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāđāļāļāļ·āđāļāļāļĩāđāļ āļēāļāđāļŦāļāļ·āļāļāļāļāļāļāļāļāļāļāļĢāļ°āđāļāļĻāđāļāļĒāđāļĨāļ°āļāļ·āđāļāļāļĩāđāđāļāļĒāļĢāļāļāļāđāļāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5: āļāļĢāļāļĩāļĻāļķāļāļĐāļēāļāđāļ§āļāļĪāļāļđāļŦāļĄāļāļāļāļ§āļąāļ āļāļĩ āļ.āļĻ. 2562 Relationship of Fire Hotspot, PM2.5 Concentrations, and Surrounding Areas in Upper Northern Thailand: A Case S
āļāļēāļĢāļ§āļīāļāļąāļĒāļāļĩāđāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļ·āđāļāļĻāļķāļāļĐāļēāļāļĨāļāļĢāļ°āļāļāļāļāļāļāļĢāļīāļĄāļēāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļāđāļāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āđāļāļāļ·āđāļāļāļĩāđāļ āļēāļāđāļŦāļāļ·āļāļāļāļāļāļāļāļāļāļāļĢāļ°āđāļāļĻāđāļāļĒ āļāđāļ§āļāļ§āļąāļāļāļĩāđ 1 āļĄāļāļĢāļēāļāļĄ â 31 āļāļĪāļĐāļ āļēāļāļĄ āļ.āļĻ. 2562 āđāļāļĒāļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļĢāļīāļĄāļēāļāđāļĨāļ°āļāļ§āļēāļĄāļŦāļāļēāđāļāđāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāđāļāļāļ·āđāļāļāļĩāđāļĻāļķāļāļĐāļēāđāļĨāļ°āļāļ·āđāļāļāļĩāđāđāļāļĒāļĢāļāļ āļ§āļīāđāļāļĢāļēāļ°āļŦāđāļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļāļēāļĄāđāļ§āļĨāļēāđāļĨāļ°āļŠāļąāļĄāļāļĢāļ°āļŠāļīāļāļāļīāđāļŠāļŦāļŠāļąāļĄāļāļąāļāļāđ (r) āļāļāļāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āļāļąāļāļāļĢāļīāļĄāļēāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļāļēāļāļ āļēāļāļāđāļēāļĒāļāļēāļ§āđāļāļĩāļĒāļĄ āđāļĨāļ°āļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāļāļąāļāļāļąāļĒāļāļēāļāļāļļāļāļļāļāļīāļĒāļĄāļ§āļīāļāļĒāļēāļāļēāļ 9 āļŠāļāļēāļāļĩ āļāļĨāļāļēāļĢāļ§āļīāļāļąāļĒāļāļāļ§āđāļē āļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāđāļāļāļ·āđāļāļāļĩāđāļĻāļķāļāļĐāļēāļĄāļĩāļāļĢāļīāļĄāļēāļāđāļāļīāđāļĄāļŠāļđāļāđāļāļāđāļ§āļāļāļĩāđāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āļāļĒāļđāđāđāļāđāļāļāļāđāļŠāđāļāļāļĨāļāļĢāļ°āļāļāļāđāļāļŠāļļāļāļ āļēāļ āđāļāļĒāļāļāļŦāļāļēāđāļāđāļāļŠāļđāļāļāļĢāļīāđāļ§āļāļĢāļāļĒāļāđāļāļĢāļ°āļŦāļ§āđāļēāļāļāļąāļāļŦāļ§āļąāļ āļāļ·āđāļāļāļĩāđāļāđāļēāđāļĨāļ°āļāļ·āđāļāļāļĩāđāđāļāļĐāļāļĢāđāļāļĨāđāđāļāļĩāļĒāļ āļŠāđāļ§āļāļāļ·āđāļāļāļĩāđāđāļāļĒāļĢāļāļāļāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļŦāļāļēāđāļāđāļāļŠāļđāļāļāļĢāļīāđāļ§āļāđāļāļĨāđāļāļąāļāļāļ·āđāļāļāļĩāđāļĻāļķāļāļĐāļēāđāļāļāļēāļāđāļŦāļāļ·āļ āļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āļāļāļāļŠāļāļēāļāļĩāļŠāđāļ§āļāđāļŦāļāđāļĄāļĩāļāđāļēāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļāļāļāļāļ·āđāļāļāļĩāđāđāļāļĒāļĢāļāļāļĄāļēāļāļāļ§āđāļēāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļāļāļāļāļąāļāļŦāļ§āļąāļ āļāļķāđāļāđāļŦāđāļāđāļāđāļāļēāļāļāđāļē r āļāļĩāđāļŠāļāļāļāļĨāđāļāļāļāļąāļāđāļāđāļāļāļāđāļāļēāļāļāļĨāļēāļ-āļŠāļđāļ (r = 0.5 â 0.7) āļŠāđāļ§āļāļāļļāļāļāļ§āļēāļĄāļĢāđāļāļāļāļāļāļāļąāļāļŦāļ§āļąāļāļŠāļāļāļāļĨāđāļāļāļāļąāļāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āđāļāđāļāļāļąāļ āļāđāļ§āļĒāļāđāļē r āļāļĩāđāļāđāļāļĒāļāļ§āđāļē āļāļķāđāļāđāļŠāļāļāđāļŦāđāđāļŦāđāļāļāļķāļāļāļīāļāļāļīāļāļĨāļāļāļāđāļŦāļĨāđāļāļāļģāđāļāļīāļāļāļēāļāļāļ·āđāļāļāļĩāđāđāļāļĒāļĢāļāļāļāļĩāđāļŠāđāļāļāļĨāļāđāļāļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļāđāļāļāļ·āđāļāļāļĩāđāļāļąāļāļŦāļ§āļąāļāļāļąāđāļ āđ āļāđāļēāļāļ§āļēāļĄāđāļāđāļĄāļāđāļ PM2.5 āđāļāļŠāļāļēāļāļĩāļŠāđāļ§āļāđāļŦāļāđāđāļāļĢāļāļāļāļąāļāļāļąāļāļāļąāļāļāļąāļĒāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāđāļĨāļ°āļāļ§āļēāļĄāđāļĢāđāļ§āļĨāļĄThe objective of this research is to study the effects of thermal hotspots on PM2.5 concentrations in the upper northern of Thailand during 1 Januaryâ31 May 2019. The number and the density of fire hotspots of the examined and adjacent areas was investigated. The time-series relationships between PM2.5 concentrations, the number of satellite-based fire hotspots, and meteorological factors derived from 9 stations were analyzed. As results, the greater number of hotspots was correlated with increased levels of PM2.5 concentrations. Such conditions exhibit considerable impacts on health. High PM2.5 concentrations were specifically found around provincial boundaries, in forests, agricultural areas, as well as in Thailandâs neighboring countries. As for the surrounding areas, the areas that have high density of fire hotspots were found near investigated areas in the north region. Provincial fire hotspots were correlated to high PM2.5 concentration, with a lower r-value. The thermal hotspot locations from the surrounding areas have effects on provincial PM2.5 concentrations. Finally, the effect of meteorological factors on PM2.5 concentrations was analyzed. As a result, precipitation and wind speed have inverse effects on PM2.5 concentrations
āļāļēāļĢāļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļāļēāļāđāļāļāļāļģāļĨāļāļ WRF-CFSR āđāļāļĒāļ§āļīāļāļĩ EOF āļ āļēāļāđāļŦāļāļ·āļāļāļāļāļāļāļāļāļāļāļĢāļ°āđāļāļĻāđāļāļĒPrecipitation Bias Correction of WRF-CFSR Model by EOF Method Over Upper Northern Thailand
āļĢāļ°āļāļāđāļāļāļāļģāļĨāļāļāļ āļđāļĄāļīāļāļēāļāļēāļĻāđāļāđāļāļāļēāļāļāļĩāđāļĄāļĩāļāļ§āļēāļĄāļāđāļēāļāļēāļĒāđāļĨāļ°āļĄāļĩāļāļ§āļēāļĄāļĒāļēāļ āđāļāļ·āđāļāļāļāļēāļāļāļēāļĢāļāļĢāļ°āļĄāļ§āļĨāļāļĨāļāļēāļāđāļāļāļāļģāļĨāļāļāļĄāļĩāļāļ§āļēāļĄāđāļĄāđāđāļāđāļāļāļāļāļķāđāļāđāļāļīāļāļāļēāļāļŦāļĨāļēāļĒāļāļąāļāļāļąāļĒāļŠāđāļāļāļĨāļāđāļāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļāļāļāļĨāļāļēāļĢāļāļģāļĨāļāļāļāļąāđāļāđāļāđāļāļīāļāļāļ·āđāļāļāļĩāđāđāļĨāļ°āđāļ§āļĨāļē āļāļ°āļāļąāđāļāđāļāļāļēāļĢāļĻāļķāļāļĐāļēāļāļĢāļąāđāļāļāļĩāđāļāļķāļāļĄāļĩāļ§āļąāļāļāļļāļāļĢāļ°āļŠāļāļāđāđāļāļāļēāļĢāļāļĢāļ°āļĒāļļāļāļāđāđāļāđāļ§āļīāļāļĩāļāļēāļĢāļŦāļĢāļ·āļāđāļāļāļāļīāļāļāļēāļĢāļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļŠāļģāļŦāļĢāļąāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļāļēāļāđāļāļāļāļģāļĨāļāļāļŠāļ āļēāļāļāļēāļāļēāļĻāļĢāļ°āļāļąāļāļ āļđāļĄāļīāļ āļēāļ WRF-CFSR āđāļĨāļ°āļāļĢāļ°āđāļĄāļīāļāļāļĢāļ°āļŠāļīāļāļāļīāļ āļēāļāļ§āļīāļāļĩāļāļēāļĢāļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļāļēāļāđāļāļāļāļģāļĨāļāļāļŠāļ āļēāļāļāļēāļāļēāļĻāļĢāļ°āļāļąāļāļ āļđāļĄāļīāļ āļēāļ WRF-CFSR āđāļāļĒāđāļāļāļēāļĢāļĻāļķāļāļĐāļēāđāļāđāđāļĨāļ·āļāļāđāļāđāļ§āļīāļāļĩāļāļēāļĢ Empirical Orthogonal Function (EOF) āđāļāļāļēāļĢāļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāđāļāļāļĢāļēāļĒāđāļāļ·āļāļ āđāļāļĒāļĻāļķāļāļĐāļēāđāļāļāļ·āđāļāļāļĩāđāļ āļēāļāđāļŦāļāļ·āļāļāļāļāļāļāļāļāļāļāļĢāļ°āđāļāļĻāđāļāļĒāļāļąāđāļāļŦāļĄāļ 18 āļŠāļāļēāļāļĩ āļāļĢāļāļāļāļĨāļļāļĄāļāļąāđāļāđāļāđāļāļĩ āļ.āļĻ. 1980-2010 (31āļāļĩ) āđāļĨāļ°āđāļāđāļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāđāļāļāļāļĢāļīāļ (APHRODITE CRU āđāļĨāļ°GPCP) āđāļāļāļēāļĢāđāļāļĢāļĩāļĒāļāđāļāļĩāļĒāļāļāļĨāļĢāđāļ§āļĄāļāļąāļāļāđāļāļĄāļđāļĨāđāļāļāļāļģāļĨāļāļāļŠāļ āļēāļāļāļēāļāļēāļĻāļĢāļ°āļāļąāļāļ āļđāļĄāļīāļ āļēāļ WRF-CFSR āļāļēāļāļāļēāļĢāļĻāļķāļāļĐāļēāļāļāļ§āđāļēāļ§āļīāļāļĩāļāļĢāļąāļāđāļāđ EOF āļŠāļēāļĄāļēāļĢāļāļĨāļāļāđāļēāļāļ§āļēāļĄāđāļāļāļāđāļēāļāļĢāļ°āļŦāļ§āđāļēāļāļāđāļēāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļāļīāļāļāļāļāļīāđāļĨāļ°āļāđāļēāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļāļāļāļīāđāļāļĨāļĩāđāļĒāđāļŦāđāļĄāļĩāļāļ§āļēāļĄāđāļāļĨāđāđāļāļĩāļĒāļāļāļąāļāļāđāļēāļāļ§āļēāļĄāđāļāļāļāđāļēāļāļāļāļāļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļ āđāļĨāļ°āđāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļ§āļēāļĄāļāļđāļāļāđāļāļāļāđāļ§āļĒāļāđāļēāļĢāļēāļāļāļĩāđāļŠāļāļāļāļāļāļāđāļēāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļģāļĨāļąāļāļŠāļāļāđāļāļĨāļĩāđāļĒ (RMSE) āļāļāļ§āđāļēāļ§āļīāļāļĩāļāļēāļĢāļāļĢāļąāļāđāļāđāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļ EOF āļĒāļąāļāđāļĄāđāļŠāļēāļĄāļēāļĢāļāļĨāļāļāđāļēāļāļ§āļēāļĄāļāļĨāļēāļāđāļāļĨāļ·āđāļāļāļāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāđāļāđ āđāļāđāļāļĒāđāļēāļāđāļĢāļāđāļāļēāļĄāļāļēāļāļāļēāļĢāļāļĢāļ§āļāļŠāļāļāļāļ§āļēāļĄāļāļđāļāļāđāļāļāļāđāļ§āļĒāļāđāļēāļŠāļąāļĄāļāļĢāļ°āļŠāļīāļāļāļīāđāļŠāļŦāļŠāļąāļĄāļāļąāļāļāđ (r) āļāļāļ§āđāļēāļ§āļīāļāļĩ EOF āļŠāļēāļĄāļēāļĢāļāļĢāļąāļāļĐāļēāļāļ§āļēāļĄāļāđāļāđāļāļ·āđāļāļāđāļāļīāļāļāļ·āđāļāļāļĩāđāļāļāļāļāļĢāļīāļĄāļēāļāļāđāļģāļāļāļĢāļēāļĒāđāļāļ·āļāļāđāļāđ āđāļāļĒāđāļāļāļēāļ°āļāļēāļĢāļāļĢāļąāļāđāļāđāļāđāļāļĄāļđāļĨāđāļāļāļāļģāļĨāļāļāļŠāļ āļēāļāļāļēāļāļēāļĻāļĢāļ°āļāļąāļāļ āļđāļĄāļīāļ āļēāļ WRF-CFSR āđāļĨāļ°āļāđāļāļĄāļđāļĨāļāļĢāļ§āļāļ§āļąāļāļāļĢāļīāļ GPCP āļĄāļĩāļāđāļē r āļāļĒāļđāđāđāļāļāđāļ§āļ 0.52 āļāļķāļ 0.97 āļāļķāđāļāđāļāđāļāļāđāļēāļāļ§āļēāļĄāļŠāļąāļĄāļāļąāļāļāđāļŦāļĨāļąāļāļāļĢāļąāļāđāļāđāļāļĩāđāļāļĩāļāļĩāđāļŠāļļāļClimate modeling system is a challenging and difficult task. Because uncertainty of the model processing is caused by many factors that influence the discrepancy of model output in both spatial and time. Therefore, in this study, the objective of this study was to apply methods or techniques for precipitation bias correction method from the WRF-CFSR regional climate model and to evaluate the efficiency of precipitation bias correction methods from the WRF-CFSR regional climate model. This study was selected the Empirical Orthogonal Function (EOF) for the monthly precipitation bias correction method in the upper northern region of Thailand, all 18 stations covering from 1980-2010 (31 years) and use observation grids data (APHRODITE CRU and GPCP) to compare the results with the WRF-CFSR regional climate model data. The result that the EOF correction method can reduce the difference between the precipitation anomaly and mean precipitation to be closer to the difference of the observation data. For validation with the Root Mean Square Error (RMSE) was found that the EOF bias correction method was unable to reduce the precipitation error. However, the validation with correlation coefficient values, the EOF method can maintain the spatial continuity of monthly precipitation. In particular, the correction of the WRF-CFSR regional climate model data and the GPCP grid observation data had r values 0.52 to 0.97 which is the best correction correlation
Chemical Fertilization Alters Soil Carbon in Paddy Soil through the Interaction of Labile Organic Carbon and Phosphorus Fractions
The influence of long-term chemical fertilization in paddy soils is based on the interaction between labile carbon and phosphorus fractions and the manner in which this influences soil organic carbon (SOC). Four soil depths (0â30 cm) were analyzed in this study. Easily oxidized organic carbon components, such as permanganate oxidized carbon (POXC) and dissolved organic carbon (DOC), and other physicochemical soil factors were evaluated. The correlation and principal component analyses were used to examine the relationship between soil depth and the parameter dataset. The results showed that Fe-P concentrations were greater in the 0â5 cm soil layer. DOC, inorganic phosphate fraction, and other soil physiochemical characteristics interacted more strongly with SOC in the 0â5 cm soil layer, compared to interactions in the 10â15 cm layer, influencing soil acidity. An increase in DOC in the 0â5 cm soil layer had a considerable effect on lowering SOC, consistent with P being positively correlated with POXC, but negatively with SOC and water-soluble carbon (WSC). The changes in SOC could be attributed to the relationship between DOC and inorganic phosphate fractions (such as Fe-P) under specific soil pH conditions. An increase in soil DOC could be caused by changes in the P fraction and pH. The DOC:Avai. P ratio could serve as a compromise for the C and P dynamic indicators. The soil depth interval is a critical element that influences these interactions. Agricultural policy and decision-making may be influenced by the P from chemical fertilization practices, considering the yields and environmental effects
Evolution of Urban Haze in Greater Bangkok and Association with Local Meteorological and Synoptic Characteristics during Two Recent Haze Episodes
This present work investigates several local and synoptic meteorological aspects associated with two wintertime haze episodes in Greater Bangkok using observational data, covering synoptic patterns evolution, day-to-day and diurnal variation, dynamic stability, temperature inversion, and back-trajectories. The episodes include an elevated haze event of 16 days (14–29 January 2015) for the first episode and 8 days (19–26 December 2017) for the second episode, together with some days before and after the haze event. Daily PM2.5 was found to be 50 µg m−3 or higher over most of the days during both haze events. These haze events commonly have cold surges as the background synoptic feature to initiate or trigger haze evolution. A cold surge reached the study area before the start of each haze event, causing temperature and relative humidity to drop abruptly initially but then gradually increased as the cold surge weakened or dissipated. Wind speed was relatively high when the cold surge was active. Global radiation was generally modulated by cloud cover, which turns relatively high during each haze event because cold surge induces less cloud. Daytime dynamic stability was generally unstable along the course of each haze event, except being stable at the ending of the second haze event due to a tropical depression. In each haze event, low-level temperature inversion existed, with multiple layers seen in the beginning, effectively suppressing atmospheric dilution. Large-scale subsidence inversion aloft was also persistently present. In both episodes, PM2.5 showed stronger diurnality during the time of elevated haze, as compared to the pre- and post-haze periods. During the first episode, an apparent contrast of PM2.5 diurnality was seen between the first and second parts of the haze event with relatively low afternoon PM2.5 over its first part, but relatively high afternoon PM2.5 over its second part, possibly due to the role of secondary aerosols. PM2.5/PM10 ratio was relatively lower in the first episode because of more impact of biomass burning, which was in general agreement with back-trajectories and active fire hotspots. The second haze event, with little biomass burning in the region, was likely to be caused mainly by local anthropogenic emissions. These findings suggest a need for haze-related policymaking with an integrated approach that accounts for all important emission sectors for both particulate and gaseous precursors of secondary aerosols. Given that cold surges induce an abrupt change in local meteorology, the time window to apply control measures for haze is limited, emphasizing the need for readiness in mitigation responses and early public warning