Multi reanalysis data driven SWAT model building and its application in hydrology response to climate change in cau river basin of northern vietnam

分 类 号 密 级 U D C 编 号 10486 博 士 学 位 论 文 基于多源再分析数据的 SWAT 模型构建及 其在越南北部 Cau 河流域水文对气候变化 的响应研究 研 究 生 姓 名 ： DAO DUY MINH 指 导 教 师 姓 名 、 职称 ： 陈. Investigating the possibility of CFSR and CMADS data in hydrometeorological studies in the Cau river basin, Northern Vietnam

分类号 密 级 U 编 号 10486 D C 博 士 学 位 论 文 基于多源再分析数据的 SWAT 模型构建及 其在越南北部 Cau 河流域水文对气候变化 的响应研究 研 究 生 姓 名 ：DAO DUY MINH 指导教师姓名、 职称 陈晓玲 教授 ： 陆建忠 副教授 学 科 、 专 业 名 称 ：地图与地理信息系统 研 究 方 向 ：遥感 GIS 应用；水文模型 二〇二二年五月 PhD Dissertation of Wuhan University Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam By DAO DUY MINH Supervised by Prof Xiaoling Chen A Prof Jianzhong Lu Wuhan University May, 2022 Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam By DAO DUY MINH Ph.D Dissertation Submitted to State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS) Of the WUHAN UNIVERSITY In partial Fulfillment of the Requirements for the Degree of DOCTOR OF PHILOSOPHY In CARTOGRAPHY and GEOGRAPHIC INFORMATION SYSTEM Prof Xiaoling Chen A Prof Jianzhong Lu May, 2022 学位论文创新点 (INNOVATION) 本论文具有如下三个创新点： (1) 探讨 CFSR 和 CMADS 数据用于越南北部 Cau 河流域水文气象研究的可能性 由于第 章的研究重点是评估水文研究中重新分析数据的可能性，因此本节保留了 GMS 控制模型中修正的参数，在 SWAT 模型中使用月尺度的 CMDAS 天气数据集(以下 简称 SWAT 模型，使用 CMADS 气象数据和校准的 GMS、SUC-CG 参数)。在校准(20092011)和验证(2012-2013)期间，利用 GCM、CMADS 和 SUC-CG 在 Gia Bay 水物站的模 拟结果对观测流量进行验证。根据每月时步的推荐性能评级记录结果为“良好”， 将评价指标采用 R2>0.8 和 NSE>0.7。这些指标的结果略优于使用常规的 CMADS 进行 校准, PBIAS 值达到-5.47 和-9.3% (相比之下，CMADS 分别为-16.19 和-19.35%)。 分析表明，与传统策略相比，该方法显著提高了模型的性能。如果对参数进行校准 以提高模型的性能，这种方法为水文研究重新分析数据的潜力提供了一种新的解决 方案。 (2) 气候预测的降尺度 第四章的研究重点是气候变化项目中全球尺度的气象数据降尺度到高分辨率局部尺 度数据。偏差校正空间分解方法 BCSD (Wood et al 2004)被认为是最可靠、最有 效的方法之一，在世界许多地区的各种气候相关影响评估研究中被广泛采用。在本 研究中，我们首先对 BCSD 方法进行了详细的描述，以方便未来的用户，这在以前 的研究中没有很好的文献记录。将 BCSD 降尺度过程分为偏置校正(BC)和空间分解 (SD)两个主要阶段，将 GCM 数据从 1°× 1°的中间分辨率转化为 0.1°× 0.1°的 目标分辨率。据我们所知，这是在越南盆地研究中发现的最佳空间分辨率。 (3) 气候变化对 Cau 河流域水文过程的影响 CMADS 数据在访问、数据使用和在中国的研究中令人鼓舞的表现方面已被广泛使用， 并具有许多便利性。 我们的研究是在越南水文研究中引入该数据集的首次尝试。 此外，首次使用 GCM-CMIP6 数据对 CRB 上的温度、降水和径流变化进行的预测是 最新的，目前尚未广泛使用 附页二 论文原创性声明 本人郑重声明： 所呈交的学位论文， 是本人在导师指导下，独 立进行研究工 作所取得的研究成果。除文中已经标明引用的内容外, 本论文不包含任何其他个 人或集体已发表或撰写的研究成果。对本 文的研究做出贡献的个人和集体，均 已在文中以明确方式标明。本声明的法律结果由本人承担。 学位论文作者（签名） ：DAO DUY MINH 2022 年 04 月 25 日 武汉大学博士学位论文 ABSTRACT According to the Intergovernmental Panel on Climate Change (IPCC, 2013) the global average surface temperature warmed by 0.85°C from 1880 to the 2012 year, causing changes in precipitation and considerably impacting hydrological processes Variations in temperature and precipitation were found influential affect water yield, Evapotranspiration (ET), surface runoff, the magnitude, and frequency of floods in the river basins Therefore hydrological models are developed to capture current hydrological processes as well as the associated effects of climate change on the water resources is extremely important for prevention and mitigation actions to be taken The Soil Water Assessment Tool (SWAT), a semi-distributed model, was developed to analyze the impacts of land use and climate changes on discharge, erosion, sedimentation, and water quality in gauged and ungauged watersheds (Arnold et al., 1998) SWAT has received international acceptance as a robust interdisciplinary catchment-scale modeling tool because user-friendly nature, broad application capability, and the fact that is well-evaluated, well-promoted, and well-supported Recent studies by the United Nations Environment Programme (UNEP) indicate that Vietnam is one of the countries most affected by climate change with the air temperature will increase by approximately 1,3 to 4°C by end of the 21st century Under these circumstances, water sources in rivers including the Cau river basin (CRB), a large river in northern Vietnam may be adversely affected Surprisingly, this area has only been recognized for studies in the direction of assessing the current state of surface water quality Therefore, a thorough understanding of the current status and changing trends of hydrological processes under changing climate conditions in the CRB for developing sustainable water resources management in the state Investigating the possibility of CFSR and CMADS data in hydrometeorological studies in the Cau river basin, Northern Vietnam In Chapter Three, the potential application of two GCPs, the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) and Climate Forecast System Reanalysis (NECP-CFSR), are compared for the first time with data from ground-based meteorological stations over the CRB, northern Vietnam These products are used because they have higher spatial resolutions than other products and are openly available for the study areas, covering both temperature and precipitation, and can be used immediately in flow simulations This is a major advantage of CFSR and CMADS over satellite precipitation data that often lack associated temperature data and heterogeneous time scales Major input data for SWAT include DEM, LULC, soil properties, and daily weather data (includes grid points and ground measurement stations located around or covering the catchment area) The period for collection and processing from January 2008 to 31 December 2013 to ensure consistency in the evaluation and comparison of the performances of the input data The 2012 ArcSWAT version, an interface in ArcGIS used to perform simulations i Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam controlled by CFSR_, CMADS_, and GMS_ The lack of gauge stations is a major issue in different parts of the world, including the CRB Besides, some uncertainties may arise during interpolation of measuring stations with grid-based monitoring data, so the evaluation is limited between grids containing corresponding measured observed values Hence, the climate aspect comparison was conducted using the point-to-grid approach, where the gauge stations were directly compared to their respective grids’ values The mean CC value of Tmax and Tmin obtained from CFSR is > 0.92, while that of CMADS is > 0.96 In addition, the MAE ranged from 0.95 to 2.47, and the RMSE varied from 1.27 to 2.85 indicating that the GCPs are in good agreement with the temperature variation at the observation stations Although the negative PBIAS value at most stations reflects that both the CFSR and CMADS data tend to underestimate the Tmax and Tmin temperatures but CFSR and CMADS can be used as an alternative to GMS in the CRB hydrometeorological studies A difference is found in that the CMADS values underestimated the actual precipitation, with a PBIAS value of -16.64%, while CFSR overestimated with a PBIAS of 99.2% Therefore, the MAE value of CMADS was much lower than that of CFSR, 5.7 and 8.01 mm/day, respectively Furthermore, the analysis results of the seasonal statistical indicators obtained from the CFSR data show the largest mean errors, with MAE and RMSE values that are too large As expected, at the pixel scale in the basin, the CFSR rainfall data was overestimated over most of the basin, with a prevalence value between 60% and 150% In contrast, the rainfall data of CMADS tends to underestimate with an average PBIAS of -16%, but the data exhibit different states rainfall is underestimated in the western mountains the while the data have slightly higher ratings in the southern plains In areas with tropical climates such as the Cau river, rainfall is the major source and greatly affects the runoff simulation results The analysis showed that the rainfall data obtained from GMS and CMADS reached an agreement better than the agreement between CFSR and GMS In general, the SWAT model based on the GMS data is best suited during the calibration and validation periods at both daily and monthly scales The simulated flow reproduced by SWAT_GMS at Gia Bay station is “Good”, with NSE> 0.79 and R2>0.68 The simulations performed using the SWAT_CMADS tend to underestimate the observed flow, with PBIAS values varying from -16.19 to -19.35%, but with R2> 0.76 and NSE> 0.78; thus, flow simulations performed by CMADS data were within "satisfactory" on the monthly scale according to the given criteria Finally, the SWAT_CFSR is not suitable for flow simulations over the CRB basin with, R2 and NSE values that are "Unsatisfactory" based on the given criteria Some studies have also found that integrating temperature data from CFRS with the precipitation data of the other GCPs did not cause any difference compared to conventional simulations mainly because these data overestimate the actual precipitation values Because the research focus of Chapter is to evaluate the possibility of re-analytical data in hydrological studies, in this section the parameters corrected in the GMS control model are preserved, and use CMDAS weather dataset in the SWAT model on a monthly scale (hereinafter referred to as SWAT model Using CMADS's meteorological data and Calibrated ii 武汉大学博士学位论文 parameters of GMS, SUC-CG) The observed flow was used for validation with simulation results by GCM, CMADS, and SUC-CG at Gia Bay hydrological station during calibration (2009-2011) and validation (2012-2013) period The evaluation indicators with R2 value > 0.8, while NSE > 0.7 records result as “good” by the recommended performance rating for the monthly time step These indicators show slightly better results than using calibration by conventional CMADS with PBIAS values reaching -5.47 and -9.3% (compare to -16.19 and 19.35% for CMADS, respectively) The flow tends to peak in August, which is consistent with the rainiest times of the year for GMS, CMADS, and even SUC-CG However, simulation results from SUC-CG reproduce better at peak flows and degradation phases than CMADS The obtained flow curves are closer to the hydrological station than the CMADS in the flood season (May to October) showing SUC-CG can get better results than conventional CMADS simulations Despite the same tendency to underestimate the actual flow as SWAT_CMADS but SWAT_SUC-CG has a better PBIAS value The analyzes have shown that this method has significantly improved the performance of the model compared with the conventional strategy This approach provides an additional new solution to the potential of reanalyzed data for hydrological studies if the parameters are calibrated to improve the performance of the model If the model input, especially the precipitation variable, is verified before application in hydrological studies (e.g CFSR) it gives the modeler confidence in the model outputs Projections of Future Climate Change over the Cau river basin Using the BCSD Downscaling Method Downscaling from global-scale meteorological data to high-resolution local-scale data in climate change projects is the research focus of Chapter Four Global climate models (GCMs) are robust tools for quantitatively assessing climate change impacts However, GCMs outputs are insufficient to provide accurate information for local to regional scale needs due to their inadequately coarse horizontal resolutions (typically at 100-300 km) The Bias Correction Spatial Disaggregation method, BCSD (Wood et al 2004) is widely used in climate-related impact assessment studies throughout the world and is regarded as one of the most trustworthy and successful methodologies In this study, we first present a detailed description of the BCSD method for the convenience of future users, which has not been well documented in previous research Firstly, the observed station data were interpolated to a 0.1° x 0.1° gridded dataset (hereinafter called OBS) by using the interpolation techniques for T2m (mean temperatures), daily Tmax, Tmin, and rainfall The newly-created gridded OBS dataset will be used further in this study to bias-correct GCM data and to estimate future climate patterns in the CRB Then, The BCSD downscaling process was divided into two major stages, namely Bias Correction (BC) and Spatial Disaggregation (SD), to spatially translate GCM data from the intermediate resolution of 1° × 1° to the targeted high-resolution of 0.1° × 0.1° To our knowledge, this is the best spatial resolution found in a study of a basin in Vietnam iii Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam The correlation of representative GCMs (including CNRM-ESM2-1, EC-Earth3, GFDL-ESM4, HadGEM-GC31-LL, MPI-ESM1-2-HR) is downscaled with meter-based data in the CRB for the period 1985-2014 Based on the locations of all points on the scatter plot, it can be seen that BCSD produces similar monthly mean temperature and mean monthly precipitation outputs at all GCMs at the observation station in the basin The accuracy of the GCMs with CC is mostly greater than 0.99 for both T2m, Tmax and Tmin The correlation results of cumulative monthly observed precipitation (mm/day) and GCMs data show values in the range of 0.994 to 0.998 during this period Dimensional and dimensionless measures are also recommended in this study to evaluate the performance of the model these results suggest that the statistics are within the reasonable range between representative GCM models and observation stations Besides, the calculation results from a refined index of agreement (dr), indicate that the value of the BCSD model error, represented by MAE, is lower than the mean, implying that BCSD values can be reasonably used in the input of future climate/hydrology scenarios Future scenarios are downgraded for climate variables (precipitation, T2m, Tmax, and Tmin) to detect the general trend for the period 1985-2100 in the CRB Accordingly, a profound warming trend is recorded with the annual average Tmax and Tmin both increasing at all future meteorological stations and consistent with the increasing trend in average temperature At the end of this century, SSP5-8.5 makes the worst assumption with increases in Tmax and Tmin of 3.3oC and 3.2oC respectively, significantly higher than the scenario SSP2-4.5 With regard to precipitation, the results showed an increasing trend at all SSPs in the near-future (the 2030s) and mid-future (the 2060s); while SSP5-8.5 showed the opposite trend with the decline of average annual rainfall in the distant future period (the 2080s) In general, these outcomes imply that the CRB is likely to be hotter in future periods, which may cause potential issues relating to agricultural activities and water consumption Impacts of Climate Change on Hydrology Processes in the Cau river basin The projected changes in climate will have direct and indirect effects on the natural environment as well as on human society, especially on hydrology and water resources In Chapter Five, we introduce a quantitative assessment of the changes in the flow regime of the CRB under climate change impacts First, historical streamflow on the basin was simulated from topography, land cover, soil, and ground weather observations by the SWAT model Second, project streamflow on the basin by inputting climate change data under SSP scenarios over the twenty-first century into a well-validated SWAT model Finally, differences in flow regime between climate change scenarios and baseline period were analyzed The calculation results of the water balance in climate change scenarios show that precipitation will increase (2-12%), while ET will decrease (2-7%), leading to an increase in runoff (9-34%) compared to the baseline period (1997-2013) In terms of precipitation, climate projections in both scenarios SSP2.45 and 5.85 show a significant upward trend in the middle of the dry season or the wet season while the decreasing trend of rainfall occurs mainly at the iv Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam models are expected to be necessary to interface with economic and social models The focus of future study will be on the link and interaction between 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Prediction of tropical monsoon hydrology using gridded meteorological products over the Cau river basin in Vietnam 5th International Electronic Conference on Water Sciences (ECWS-5, MDPI), Online (11/2020); DuyMinh Dao, Jianzhong Lu, Xiaoling Chen, Sameh A.Kantoush, Doan Van Binh, Phamchimai Phan, Nguyen Xuan Tung; Predicting tropical monsoon hydrology using gridded meteorological products over the Cau River basin in Vietnam, Water, Volume 13, Issue 9, 1314, doi.org/10.3390/w13091314; Phamchimai Phan, Nengcheng Chen, Lei Xu, DuyMinh Dao, Dinh Kha Dang; NDVI Variation and Yield Prediction in Growing Season: A Case Study with Tea in Tanuyen Vietnam, Atmosphere, 12(8), 962, doi.org/10.3390/atmos12080962 124 武汉大学博士学位论文 ACKNOWLEDGEMENTS I would like to express my warmest gratitude to all my mentors, colleagues, friends and family who helped me in the completion of the work on my PhD’s thesis I would like to express my deepest gratitude to my two supervisors, Professor Xiaoling Chen and Associate Professor Jianzhong Lu This thesis would not have been possible without the expertise, incredible patience, and consistent and discerning guidance and direction of the teachers They have guided me throughout my graduate life, and have always been there with motivation, encouragement and support Their accurate and valuable criticism has helped me academically and professionally, helping me to overcome countless obstacles during my PhD pursuit Next, I would like to thank the Professors, PhDs and assistants at the State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (LIESMARS) They have helped me acquire rich professional knowledge and supported me a lot in the process of doing the thesis I would also like to thank my friends, and fellow graduate students who have supported me throughout this endeavor I would like to express my gratitude to my family, especially my parents Without their unconditional love and support and endless motivation this achievement would not be gained 125 Multi reanalysis data-driven SWAT model building and its application in hydrology response to climate change in Cau river basin of northern Vietnam 附页三 武汉大学学位论文使用授权协议书 （一式两份，一份论文作者保存，一份留学校存档） 本学位论文作者愿意遵守武汉大学关于保存、使用学位论文的管理办法及规定， 即：学校有权保存学位论文的印刷本和电子版，并提供文献检索与阅览服务；学校可 以采用影印、缩印、数字化或其它复制手段保存论文；在以教学与科研服务为目的前 提下，学校可以在校园网内公布部分或全部内容。 一、在本论文提交当年，同意在校园网内以及中国高等教育文献保障系统 （CALIS）、高校学位论文系统提供查询及前十六页浏览服务。 二、在本论文提交□当年/□一年/□两年/□三年以后，同意在校园网内允许读 者在线浏览并下载全文，学校可以为存在馆际合作关系的兄弟高校用户提供文献传递 服务和交换服务。（保密论文解密后遵守此规定） 论文作者（签名）： 学 号： 2016176190006 学 院： 测绘遥感信息工程国家重点实验室 日期： 2022 年 06 月 10 日 126