Advancements in Satellite-Based Drought Monitoring Methods: Novel Indices and Their Applications at Various Scales

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姓名

蔡明信(Thai Minh Tin) 查詢紙本館藏

畢業系所

環境科技博士學位學程

論文名稱

(Advancements in Satellite-Based Drought Monitoring Methods: Novel Indices and Their Applications at Various Scales)

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至系統瀏覽論文 (2026-1-1以後開放)

摘要(中)

乾旱是一種嚴重的自然災害，對全球的生態系統、環境和人類生活產生廣泛的影響。近期台灣的乾旱情況引起了重大關注，尤其是對半導體晶片生產這樣的重要產業。本研究使用衛星基礎指數來監測及分析乾旱狀態，因為準確乾旱評估在有效的水資源管理中起著關鍵作用。溫度-植被乾旱指數（TVDI），使用經驗技術結合地表溫度（LST）和植被覆蓋分數（FVC），被廣泛使用。然而，其在植被稀疏地區的適用性受到限制，促使我們探索替代方法。最近發展的溫度-土壤水分乾旱指數（TMDI），用標準化差異潛熱指數（NDLI）替代植被指數，顯示出做為一種合適替代品的潛力。研究的第一個關鍵部分介紹了使用從NDLI衍生出的新的表面水分可用性（FSWA）對TMDI的改進。該部分深入探討了在LST-FSWA空間內精煉邊緣選擇以觀察乾旱。已經採用了一種實用的方法來準確地識別這個空間內的乾和濕邊緣。為了評估TMDI的可靠性，該研究使用各種指標進行了全面的評估，包括由地表能量平衡算法（SEBAL）衍生的蒸散量（ET）、作物水分壓力指數（CWSI）、初級生產力（GPP）和降水數據。結果顯示，TMDI與SEBAL衍生的CWSI、ET和GPP之間的相關性高於TVDI。此外，TMDI與降水之間的強關聯突顯了其捕捉乾旱模式的有效性。該部分還提出了一個標準的TMDI閾值，用於評估2014年至2021年台灣西南部的乾旱。本文的後續部分應用新穎的 FSWA 來監測全國範圍內的農業缺水和乾旱狀況。 FSWA 與其他兩個指數一起用於分析 2001 年至 2022 年澳洲的年度乾旱模式。在澳洲的大多數農業地區，FSWA 顯示出與土壤濕度 (SM)、ET 和降雨量的強大時間相關性。鑑於SWAT的簡化計算和全國範圍的適用性，其實際利用已在全球範圍內進行評估。研究發現SWAT可以代表土壤水分並生成高分辨率的乾旱地圖。此外，SWAT被應用於評估2011年至2022年的全球乾旱狀況。基於SWAT指數的乾旱分佈和趨勢分析顯示出不同土地覆蓋類型之間的廣泛變化。總的來說，TMDI和SWAT都作為實際運行的乾旱指數。先進的TMDI，依賴於僅兩個變量的整合：FSWA和LST，在區域範圍的乾旱監測中表現出色，特別是在農業區。另一方面，由於其更廣泛的規模適用性和更簡單的方法，基於衛星的SWAT指數提供了一種實用的替代方案。

摘要(英)

Drought, a detrimental natural disaster, has extensive impacts on ecosystems, the environment, and human life globally. Its recent emergence in Taiwan has sparked significant concerns, especially for vital industries like semiconductor chip production. This dissertation uses satellite-based indices to monitor drought status, given the crucial role of accurate drought assessment in effective water management. The Temperature-Vegetation Dryness Index (TVDI), which combines Land Surface Temperature (LST) and Fractional Vegetation Cover (FVC) using empirical techniques, is widely utilized. However, its applicability is limited in regions with sparse vegetation, prompting the exploration of alternative methods. The recently introduced Temperature-Soil Moisture Dryness Index (TMDI), which substitutes the vegetation index with the Normalized Difference Latent Heat Index (NDLI), shows potential as a suitable alternative. The first key section of the dissertation presents advancements in the TMDI using the new Fractional Surface Water Availability (FSWA) derived from the NDLI. This section delves into refining edge selection within the LST–FSWA space to observe drought. A practical method has been adopted to accurately identify the dry and wet edges within this space. To evaluate the reliability of TMDI, the study conducted comprehensive assessments using various indicators, including the evapotranspiration (ET), Crop Water Stress Index (CWSI) derived from the Surface Energy Balance Algorithm for Land (SEBAL), Gross Primary Productivity (GPP), and precipitation data. The results reveal high correlations between the TMDI and SEBAL-derived CWSI, ET, and GPP, surpassing those obtained with TVDI. Moreover, strong associations between the TMDI and precipitation underscore its effectiveness in capturing drought patterns. This section also proposes a standard TMDI threshold for assessing drought in southwestern Taiwan from 2014 to 2021. The subsequent section of this dissertation applies the novel FSWA to monitor agricultural water stress and drought status at the national scale. The FSWA is employed alongside two other indices to analyze annual drought patterns in Australia from 2001 to 2022. The analyses reveal high correlations between the FSWA against soil moisture (SM), ET, and rainfall. Across most agricultural regions in Australia, the FSWA shows robust temporal correlations with the SM, ET, and rainfall. Furthermore, given the SWAT’s simplified calculations and wide applicability, its practical utilization has been evaluated at the global scale. It is found that the SWAT can represent SM and generate high-resolution drought maps. The SWAT was applied to assess global drought conditions from 2011 to 2022. The analysis of drought distributions and trends based on the SWAT index exhibited wide variations across different land cover types. In conclusion, both the TMDI and SWAT function as practically operational drought indices. The advanced TMDI, relying on the integration of only two variables: FSWA and LST, excels in regional-scale drought monitoring, particularly in agricultural zones. On the other hand, the satellite-based SWAT index, due to its broader scale applicability and more straightforward methodology, offers a viable alternative to empirical models.

關鍵字(中)

★ 乾旱
★ 溫度-土壤水分乾燥指數（TMDI）
★ 溫度-植被乾燥指數（TVDI）
★ 全球乾旱

關鍵字(英)

★ Drought
★ Temperature-Soil Moisture Dryness Index (TMDI)
★ Temperature-Vegetation Dryness Index (TVDI)
★ Global drought

論文目次

摘要 (Abstract) ii
ABSTRACT iv
ACKNOWLEDGMENTS vi
TABLE OF CONTENTS vii
LIST OF FIGURES xi
LIST OF TABLES xiv
SYMBOLS xv
CHAPTER 1. INTRODUCTION 1
1.1. Background and Motivation 1
1.1.1. Background 1
1.1.2. Motivation 3
1.2. Research Objectives 5
1.3. Scientific Contribution and Innovation 6
CHAPTER 2. LITERATURE REVIEW 8
2.1. Dryness and Drought Definitions 8
2.2. Drought Monitoring Methods 10
2.2.1. Univariate Indices 10
2.2.2. Bivariate Indices 11
2.2.3. Trivariate Indices 13
CHAPTER 3. METHODOLOGY 16
3.1. Classification of Land Use/Land Cover 16
3.2. Calculations of the Indices and LST 17
3.3. Estimates of ET and CWSI Based on SEBAL 20
3.4. The Conceptual Framework of the TVDI 24
3.5. The Conceptual Framework of the Original TMDI 24
3.6. The Conceptual Framework of the TVSDI 25
3.7. The Conceptual Framework of the 26
3.8. Assessment of Drought Trends 27
CHAPTER 4. ADVANCEMENTS IN TEMPERATURE-SOIL MOISTURE DRYNESS INDEX (TMDI) FOR REGIONAL DROUGHT ASSESSMENT 28
4.1. Regional Context and Data Acquisition 28
4.1.1. Regional Context of Southwestern Taiwan 28
4.1.2. Data Acquisition 30
4.2. The Original TMDI and Its Results 32
4.2.1. Dry and Wet Edges of Original LST–NDLI Spaces 32
4.2.2. Performance Evaluation of the Drought Indices 34
4.3. Advancements and Validations of the TMDI 37
4.3.1. Advancements of the TMDI 37
4.3.2. Identification of Dry and Wet Edges in Novel LST–FSWA Spaces 41
4.3.3. Verification of the Results 43
4.3.4. Drought Classification Categories 53
4.4. Applications of the Advanced TMDI 55
4.4.1. Yearly Drought Variations in the YCNK region 55
4.4.2. Dryness-Wetness Trends 59
4.5. Summary of Findings 61
CHAPTER 5. FRACTIONAL SURFACE WATER AVAILABILITY (FSWA): A NOVEL SATELLITE INDEX FOR DROUGHT MONITORING 63
5.1. Geographical Context and Data Acquisition 63
5.1.1. Geographical Context of Australia 63
5.1.2. Data Acquisition 64
5.2. The Performance of the Indices and Indicators 66
5.3. Spatiotemporal Correlations Between FSWA and Three RDs 71
5.4. Comparisons of FSWA and RZ SM 73
5.5. RZ SM Mapping Capabilities of the FSWA 76
5.6. Multiyear Dryness-Wetness Conditions in Australia 77
5.7. Summary of Findings 79
CHAPTER 6. SURFACE WATER AVAILABILITY AND TEMPERATURE (SWAT) FOR GLOBAL DROUGHT MONITORING 81
6.1. Regional Context and Data Acquisition 81
6.1.1. Regional Context of Globe 81
6.1.2. Data Acquisition 83
6.2. The Validation of the SWAT Index 85
6.2.1. 3D Space of SWAT with SMAP SM Distribution 85
6.2.2. Drought Indices vs. GLASS SM at the National/Regional Scale 86
6.2.3. Drought Indices vs. SMAP SM at the Continental Scale 87
6.2.4. Spatiotemporal Relationships of SWAT and Drought Indicators 89
6.3. Utilization of SWAT for Global Drought Assessment 91
6.3.1. Yearly Drought Variations Across the Globe 91
6.3.2. Drought Trends Across the Globe 93
6.4. Summary of Findings 94
CHAPTER 7. CONCLUSIONS AND FUTURE DIRECTIONS 96
7.1. Conclusions 96
7.2. Recommendations for Future Research 97
REFERENCES 99

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指導教授

劉說安(Yuei-An Liou)

審核日期

2024-7-3

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