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    <subfield code="a">AIT Diss. no.WM-21-02  </subfield>
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    <subfield code="a">Khadka, Dibesh  </subfield>
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    <subfield code="a">Climate change and land use change impacts on hydro meteorological extremes in the Mun River Basin, Thailand</subfield>
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    <subfield code="a">Pathum Thani, Thailand :</subfield>
    <subfield code="b">Asian Institute of Technology,</subfield>
    <subfield code="c">2021</subfield>
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    <subfield code="a">210 leaves :</subfield>
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    <subfield code="a">Dissertation ;</subfield>
    <subfield code="v">no. WM-21-02</subfield>
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    <subfield code="a">A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Engineering in Water Engineering and Management, School of Engineering and Technology</subfield>
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    <subfield code="a">Thesis (Ph. D.) - Asian Institute of Technology, 2021</subfield>
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    <subfield code="a">Climate change (CC) is expected to exacerbate the hydro-meteorological extremes in  the future. Improving the climate projections and quantifying the plausible future  extremes are paramount in understanding climate-related risks and formulating suitable  policies. In addition to CC, land-use changes (LUC) may also amplify future extreme  events, particularly the droughts. Although the CC impacts on the hydro-meteorological  extremes are extensively studied, there are no such studies which have assessed LUC's  impacts on the hydro-meteorological extremes. This study aims to provide a  comprehensive assessment of climate change and land-use change on the hydro meteorological extremes in the Mun River Basin in Northeast of Thailand. Extreme  climate indices, drought indices, and the probability distributions are used for the  assessment.  Process-based evaluation of 60 climate models (from CMIP5 and CMIP6) is carried out  to identify models that better replicate southeast Asia's regional climate (SEA) and  produce robust future projections in the region. Fourteen most apt models from CMIP5  and eight models from CMIP6 are selected to provide near future (2021-2050) climate  assessments with reference to baseline (1981-2010). The future river flows under CC  and LUC are simulated using the Soil and Water Assessment Tool (SWAT). The  meteorological, hydrological, and agricultural droughts are characterized for the  observed period using three standardized drought indices (SPEI, SRI, and SSMI) at four  timescales (1-, 3-, 6-, and 12-month). The projected changes in the drought  characteristics are assessed under CC and LUC scenarios (Business as usual-BAU and  Combination of forest conservation and urban growth-CCU).  Evaluation of climate models shows the superiority of CMIP6 models to CMIP5 models  in simulating annual rainfall cycle and large-scale atmospheric circulation patterns. The  subsets of most skilled models from both phases of CMIPs are identified for their  applicability in the SEA domain. In the near future, the trends of temperature rise will  get stronger. The CMIP6 ensemble suggests an increase in maximum and minimum  temperatures by 1.45&#xB0;C (0.8-1.9&#xB0;C) and 1.54&#xB0;C (1.1-1.9&#xB0;C) under the high emission  scenario, which is well above the projections of CMIP5: 1.10&#xB0;C (0.5-1.7&#xB0;C) and 1.13&#xB0;C  (0.7-1.6&#xB0;C) respectively. Although the annual average rainfall will not change  significantly, it will be temporally more uneven with projected decreases (6-11%)  during the pre-rainy season (March-May) and increases (2-8%) during the rainy season  (June-October). An increase in the magnitude of temperature extremes will be higher  than the mean temperature as the 20-year return values of maximum and minimum  temperature will increase by 2.3-3.3&#xB0;C and 1.7-2.0&#xB0;C, respectively. Annual warm spells  will also increase by 26-32 days. The rainfall intensity is expected to increase by 10%,  and the 20-year return values of 1-day and consecutive 5-day maximum rainfall will  also increase by 26-49%. These, along with the projected decrease of the annual number  of rainy days as much as 15, indicate temporal re-distribution of the rainfall  consequently increase in both rainfall extremities (wet/dry) in the near future. CC and LUC will have the opposite effect on future water yield in the basin as the flows  will increase by 11% under CC while decrease by 6% under LUC. Under the combined  drivers of CC and LUC, the annual flows will increase by 8%, which shows CC has a  dominating impact on future flows than LUC. Observed drought analyses suggest the  meteorological droughts in the basin propagate to agricultural droughts with a lag of 1  month and to hydrological droughts with a lag of 2 months. Drought hazards are high  in the central region of Nakhon Ratchasima and Buriram provinces and the southern  part of Si Sa Ket province. Under CC, the average durations and severities of the  meteorological droughts will increase by 9-22% and 45-63%, respectively. Increases  are mainly due to higher evapotranspiration demands under increased temperature and  increased temporal variabilities of the rainfall. As water yield is expected to rise under  CC, hydrological droughts at intermediate timescales (3- and 6-month) will be shorter  in the near future while they will increase at a longer timescale of 12-month. LUCs will  have negligible impacts on the hydrological droughts as compared to CC. However, the  study's important findings are that LUCs have comparable impacts on agricultural  droughts as of CC, and the impacts of both drivers will amplify drought durations and  severities. Under the combined stressors, the average drought durations and severities  are expected to increase by 60% and 165%, respectively. The finding of this study will be helpful in updating disaster mitigation plans and  policies based on projected changes in future extremes. It will also have relevance in  risk assessments, disaster risk reduction, disaster preparedness, infrastructure planning,  and developing adaptation measures for the basin to cope with expected future changes. </subfield>
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    <subfield code="a">Climatic changes</subfield>
    <subfield code="z">Thailand</subfield>
    <subfield code="z">Mun River Basin</subfield>
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    <subfield code="a">Land use</subfield>
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    <subfield code="a">Hydrometeorology</subfield>
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    <subfield code="z">Mun River Basin</subfield>
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    <subfield code="a">Babel, Mukand Singh,</subfield>
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    <subfield code="a">Asian Institute of Technology Fellowship,</subfield>
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