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研究生: 祝福
Dlamini, Sibusiso Bongani
論文名稱: 評估 SMAP 推導之土壤水分指數與 Eswatini(史瓦帝尼)乾旱監測系統 在農業乾旱監測中的一致性
Evaluating the Consistency of SMAP-Derived Soil Moisture Index with the Eswatini Drought Monitoring System for Agricultural Drought Monitoring.
指導教授: 羅偉誠
Lo, Wei-Cheng
學位類別: 碩士
Master
系所名稱: 工學院 - 自然災害減災及管理國際碩士學位學程
International Master Program on Natural Hazards Mitigation and Management
論文出版年: 2026
畢業學年度: 114
語文別: 英文
論文頁數: 91
外文關鍵詞: Soil moisture, SMAP, drought monitoring, standardized soil moisture index, Eswatini
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  • Soil moisture is a key climate variable and an important indicator of agricultural drought, yet satellite estimates remain uncertain at field scale in semi-arid, data-scarce regions such as Eswatini’s Lowveld. This study evaluated the ability of NASA’s SMAP Level-4 soil moisture product to represent field-scale soil moisture variability and support drought monitoring in Nkilongo Inkhundla (constituency), using a decade-long in situ observations and the Composite Drought Indicator (CDI). Multi-depth capacitance probes at four sites provided soil moisture measurements at 100, 200, 300, 400, 600, and 800 mm depths from 2015 to 2025. Missing data were reconstructed using Random Forest regression, which performed best in the mid-root-zone and less consistently at shallower and deeper layers. Monthly in situ and SMAP soil moisture series were then used to derive anomalies, standardized soil moisture indices (SSMI), and drought classes. SMAP and in situ anomalies showed weak to moderate agreement, while SSMI values showed stronger correspondence and moderate categorical agreement. Comparison of SMAP root-zone SSMI with CDI showed over 50% exact agreement and more than 80% agreement within one drought class, with a significant negative correlation. Overall, the findings show that SMAP Level-4 root-zone soil moisture can complement CDI and improve drought monitoring and early warning in Eswatini when used together with field observations.

    ABSTRACT I DEDICATION II ACKNOWLEDGEMENTS III TABLE OF CONTENTS IV LIST OF TABLES VII LIST OF FIGURES VIII LIST OF ACRONYMS X 1 INTRODUCTION 1 1.1 Background 1 1.2 Research Motivation 3 1.3 Research Objectives 4 1.3.1 General Objective 4 1.3.2 Specific Objectives 4 1.3.3 Research Questions 5 2 LITERATURE REVIEW 6 2.1 Drought Categories 6 2.2 Drought indices 8 2.3 Drought in Southern Africa and Eswatini 10 2.4 Importance of early warning and monitoring 11 2.5 Remote sensing of soil moisture and SMAP L4 12 2.5.1 Microwave remote sensing of soil moisture 12 2.5.2 Limitations and enhancement of satellite soil moisture estimates 12 2.6 SMAP mission and Level‑4 soil moisture product 13 2.7 Standardized satellite soil moisture indices for drought monitoring 13 2.8 Validation against in situ data and drought indicators 14 2.9 In situ soil moisture observation and gap filling strategies 14 2.10 Methods for validating satellite soil moisture 16 2.11 Linking satellite soil moisture to drought classifications. 17 2.12 Drought climatology of Southern Africa and Eswatini 19 2.13 National drought monitoring and early warning systems in Eswatini 19 2.14 Role of satellite soil moisture in Eswatini's drought monitoring system 21 2.15 STUDY AREA AND DATA 22 2.15.1 Eswatini Climate, Hydrology and Agriculture 22 2.15.2 Field Soil Moisture Dataset 24 2.15.3 SMAP Soil Moisture Data 25 2.15.4 NDMA Composite Drought Indicator 25 2.15.5 Data Pre-processing and Quality Control 26 3 RESEARCH DESIGN 27 3.1 Overall methodological framework 27 3.2 Identification of missing data 28 3.3 Random Forest gap filling of field soil moisture and validation 29 3.3.1 Validation Equations 30 3.4 Temporal aggregation and variability metrics 31 3.5 Climatology and anomaly computation 32 3.6 Z score / SSMI Formulation and Drought Classes 32 3.7 Spatial matching of field observations and SMAP data 33 3.8 Statistical evaluation of SMAP and field soil moisture 34 3.9 Categorical agreement between in situ and SMAP drought classes 34 3.10 Temporal and spatial alignment with CDI 34 3.11 Concordance analysis 35 4 RESULTS AND DISCUSSIONS 36 4.1 Data quality and in Situ observation gap-filling results 36 4.2 Gap-filling Results 38 4.3 Results Validation 41 4.4 Agreement Between In Situ and SMAP Soil Moisture Anomalies 42 4.5 Categorical agreement between in situ and SMAP drought classes 45 4.6 Consistency between SMAP-derived and In Situ surface SSMI 47 4.7 Consistency between SMAP-derived and In Situ Root-zone SSMI 50 4.8 Overview of the CDI–SSMI Comparison 53 4.8.1 Exact Agreement 54 4.8.2 Within One-Class (±1) Agreement 55 4.8.3 Spearman Rank Correlation 56 4.8.4 Summary of agreements 57 5 CONCLUSION 59 5.1 Limitations of the Study 61 5.2 Future Work 62 6 REFERENCES 63

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