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ABSTRACT:The purpose of this study is to determine the hydrological impacts of land use/land cover (LULC) change in the Yom watershed in central-northern Thailand over a 15-year period using an integration of remote sensing, Geographic Information System, statistical methods, and hydrological modelling. The LULC changes showed an expansion of urban areas by 132% (from 210 km 2 in 1990 to 488 km 2 in 2006). The Yom River's daily discharge long-term trend significantly increased at most of the measurement stations (p value <0.05), and the rate of increase in discharge at areas downstream of the rapid urbanisation was significantly greater than that at areas upstream. There were no significant long-term trends in precipitation characteristics in the basin, except for one station. The rate of change in discharge after changes in LULC showed a systematic increase over a range from 0.0039 to 0.0180 m 3 s −1 day −1 over a 15-year period, with the increase in urbanised area spanning a range from 81 to 149% in two flood-prone provinces. A rainfall-runoff model simulated a small increase (∼10%) in peak flows. The coupling of surface observations, remote sensing, and rainfall-runoff modeling demonstrated the impacts of changes in LULC on peak river discharge, hence flooding behaviour, of a major river in central-northern Thailand.

Abstract:A quasi-real-time hydrological simulation system was developed for the Chao Phraya River in Thailand. The system was largely based on ground meteorological observations from the Thai Meteorological Department (TMD) Automatic Weather Stations (AWSs), which are updated daily and available online. As radiation data were not measured by the TMD AWSs, they were obtained from the global meteorological data of the Japan Meteorological Agency Climate Data Assimilation System. A macro-scale water resources model termed H08 was used for hydrological simulations. The model's hydrological parameters were set from a series of sensitivity simulations for 2012. The model effectively reproduced the monthly hydrograph at the Nakhon Sawan and other major river gauging stations. The performance at the Sirikit Dam was poor, which could be attributed to erroneous input rainfall data due to the low density of AWSs. The simulation was continued up to September 30, 2013, or the date for which the latest data were available. The overall performance was fair and implied potential applicability of the system for quasi-real-time flood tracking and basic forecasting.

Climate change is progressing and is now one of the most important global challenges for humanities. Water resources management is one of the key challenges to reduce disaster risk. In Northern Thailand, flood and drought have always occurred because of the climate change impact and non-systematic management in the conjunctive use of both sources of water. Therefore, this study aims to assess the climate change impact on surface water and groundwater of the Yom and Nan river basins, located in the upper part of Thailand. The surface water and groundwater regimes are generated by a fully coupled SWAT-MODFLOW model. The future climate scenarios are considered from the Representative Concentration Pathways (RCPs) 2.6 and 8.5, presented by the Coupled Model Intercomparison Project Phase 5 (CMIP5), in order to mainly focus on the minimum and maximum Green House Gas (GHG) emissions scenarios during the near future (2021–2045) periods. The results show that the average annual air temperature rises by approximately 0.5–0.6 °C and 0.9–1.0 °C under the minimum (RCP 2.6) and maximum (RCP 8.5) GHG emission scenarios, respectively. The annual rainfall, obtained from both scenarios, increased by the same range of 20–200 mm/year, on average. The summation of surface water (water yield) and groundwater recharge (water percolation) in the Yom river basin decreased by 443.98 and 316.77 million m3/year under the RCPs 2.6 and 8.5, respectively. While, in the Nan river basin, it is projected to increase by 355 million m3/year under RCP 2.6 but decrease by 20.79 million m3/year under RCP 8.5. These quantitative changes can directly impact water availability when evaluating the water demand for consumption, industry, and agriculture.

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