The study of drought factors to analyze and manage water is very important. The main contributing factor to drought is unusual summer weather wind pressure and air mixtures include water vapor and water droplets. In this factors can be analyzed for rainfall in the lower central river basin area and the preliminary data of the research used to analyze drought from Thai Meteorological Department (TMD). This research analyzes the factors that cause drought including rainfall temperature pressure wind and precipitation. The Multiple linear regression analysis used to determine the relationship of factors causing drought. It was found that rainfall had a statistically significant relationship with temperature and pressure. In addition using the Geographic Information System (GIS) an analysis of rainfall in the lower central river basin from October 1920 to September 2021 to found that from August to October there is a lot of heavy rainfall according to the multiple linear regression equation. Therefore the created multiple linear regression equations can be effectively used in the analysis of drought areas in the lower central river basin area.

This research aimed to study the causes of changes in water quality and compare the water quality in Khlong Bang Khen Mai when the seasons and sampling points are different. These factors may cause a change in water quality. A total 50 of water samples were collected from 5 sampling points each point approximately 300 meters apart for a total distance of 1.5 kilometers. They cover three seasons such as winter (October 2020 to February 2021) summer (March to May 2021) and rainy (June and July 2021). Three parameters of this research which consist of both the chemical and physical quality parameters are pH Dissolved Oxygen (DO) and Electrical Conductivity (EC). The result shows that the average pH has ranged from 7.10 - 7.74 the dissolved oxygen (DO) was in 1.80 - 2.84 mg/L and the electrical conductivity (EC) was in the range of 327 - 517 μs/cm. A two-way analysis of variance is a statistical method used to compare the water quality in Khlong Bang Khen Mai. The results indicate that the test differences between seasons affected the change in water quality in all parameters with a statistically significant level of 0.05. Afterward the comparison of multiple comparisons by Scheffes method showed that the pH and dissolved oxygen (DO) in the rainy season were significantly different from winter and summer at the level of 0.05. For the electrical conductivity (EC) there was significant differences between summer and winter at the 0.05 level.

Due to the need for Thailand to adapt and develop its economy to keep up with the changes of the world it has to develop technology and innovations with efficiency in order to drive Thailands economy to prosper and keep pace with the rapidly changing global economy. Therefore it is important that educational institutions can help Thailand to have a good economy that is comparable to other countries is to organize the education system with courses that meet the needs of the enterprises. In addition a new generation of entrepreneurs (Start-up) must be created and developed to have knowledge and abilities to drive the countrys economy to be sustainable and efficient. The new generation of entrepreneurs must have knowledge and ability to use technology and innovation in business operations create added value to the economy and bring Thailand into a high income country and people in the country have a better life. Therefore the researcher aims to find guidelines for the development of the Faculty of Science and Technology. Lets step into the development of technology to promote innovation to create a new generation of entrepreneurs with the ability to operate business by using information technology to drive business progress. The samples used to collecte data were personnel students of the Faculty of Science and Technology and establishments related to the occupation of students in both government and private sectors and the research instruments were 2 sets of questionnaires including the 1st set a questionnaire to survey opinions on the development approach of the Faculty of Science and Technology and the second set of questionnaires for enterprises to explore the need for building and develop entrepreneurs in the new era with characteristics that meet the needs of the establishment. The results obtained from the statistical data analysis are guidelines for the development of the Faculty of Science and Technology in creating a proactive strategy to develop the faculty and up-to-date personnel skills training. Access to technology and innovation to step into a university in technology and promote the creation of appropriate innovations to create and develop entrepreneurs effectively.

he monthly rainfall forecasts are very important in Thailand because the most of people has a career in agriculture. The monthly rainfall forecasts can be analyzed for manage water resources. In addition the monthly rainfall forecasting is used to manage water for consume in Thailand. This research is forecasting monthly rainfall under the global warming using a multilayer neural network. It is a network with one hidden layer. The data from the Meteorological Department is use. Imported variables include temperature humidity and wind. The forecast from January to December 2018. The mean square error (MSE) to measure forecasting accurate and found that the value is suitable error (10.25). The neural network can provide accurate monthly rainfall forecasts from January to December. It was found that the southern region had the highest rainfall and the eastern region northeastern region northern region central and western regions respectively. Therefore neural networks can be forecast rainfall accurately and efficiently. It can be used to analyze and manage water resources effective.

The forecasting method is important because it can predict phenomena in the future. The accuracy of the forecast depends on the model and the initial conditions. In addition the predictability measurement method is important can be check the accurate of forecasts. In this research is winter monsoon forecasts in Thailand by the shallow water model. The data from The Bjerknes Centre for Climate Research (BCCR) University of Bergen Norway. The global climate model is Bergen Climate Model (BCM) Version 2.0 (BCCR-BCM2.0) of the Intergovernmental Panel on Climate Change (IPCC) is used. The Lyapunov exponent (LE) is the predictability measurement method for verify the efficiency of model and establish the new predictability measurement method by the time series analysis. The result to show that the new predictability measurement method by the time series analysis can be measure the efficiency of the winter monsoon forecasts in Thailand by the shallow water model for December 2015 to December 2056 are suitable.