University of Twente Student Theses
Unraveling the Spatial-Temporal Dynamics of Drought Anomalies and Their Interactions with Vegetation
Swai, Calvin Samwel (2024) Unraveling the Spatial-Temporal Dynamics of Drought Anomalies and Their Interactions with Vegetation.
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| Abstract: | The future projections sketched in the various Climate reports predict a global increase in severe weather conditions, particularly excessive decline both in summer precipitation and winter snowfall accompanied by periods of extremely high temperatures. Consequently, these projections are expected to intensify the frequency and intensity of drought events affecting thereby water and food security on a global scale. Due to expected local shifts in weather conditions, understanding the effect on drought dynamics at a local catchment will be critical for coordinated risk management and informed mitigations of drought impacts on both water resources and the ecosystem. However, complexities in the development of drought scenarios limit the capacity to establish a conclusive link of drought propagation in a local area. Moreover, the uneven distribution of the Root Zone Soil Moisture (RZSM) dataset also limits the assessment of the relationship between drought and vegetation anomalies. The purpose of this study is to analyze the spatial-temporal dynamics of drought anomalies and their causal relationships with vegetation conditions in Overijessel, Netherlands. To address the issue of limited coverage of the RZSM dataset, the readily available data on Surface Soil Moisture at 1km (1KmSSM) was validated with the in-situ Twente soil moisture measurements. These data were then used to calibrate the two models to derive RZSM from Surface Soil Moisture (SM). The Cumulative Distribution Function (CDF) and Exponential Low Pass Filter (ELPF) models. The optimal calibrated model was used to retrieve the RZSM time series in the Witharen groundwater monitoring network (location: Twente the Netherlands). Thereafter, the estimated RZSM time series, along with precipitation measurements, and groundwater time series were used to estimate soil moisture and meteorological, and groundwater anomalies for drought monitoring in the region. Additionally, optical vegetation indices Near-Infrared reflectance of vegetation (NIRv) and Normalized Difference Water Index (NDWI) were used to monitor both the anomalies of the vegetation photosynthetic activities and hydrology dynamics during various drought conditions. Finally, a Convergent Cross-Mapping (CCM) was used to assess the causal relationships between drought and vegetation anomalies in the Witharen region. The findings of this study showed that the ELPF method estimated the most optimal RZSM time series from 1KmSSM in Twente stations, with a mean unbiased Root Mean Square Error (ubRMSE) of 0.056 m3/m3. The temporal analysis of drought anomalies indicated a higher drought frequency and intensity in the last decade, while spatial analysis revealed an association between groundwater depth and the development of groundwater drought. Issues such as delayed response and periodic recovery of vegetation anomalies during drought events were identified in the time series analysis. Moreover, the detected significant drought interactions aligned with the prior knowledge of the Witharen region. For instance, the interaction between shallow groundwater levels (0.7 to 3 m) and both vegetation and soil moisture anomalies. Moreover, this study also highlighted the use of both surface and root zone soil moisture anomalies for monitoring meteorological drought propagation and the initiation of vegetation and groundwater anomalies respectively. Nevertheless, this study suffered from key sources of uncertainties related to the spatial and temporal resolution of the analysis, and the accuracy of the grid soil moisture datasets. Future studies should address these issues to improve the comprehensive assessment of drought development in local areas. This study concludes that CCM can be used to reveal valuable information about the local causal interactions between drought and vegetation anomalies through time series analysis. The use of both surface and root zone soil moisture in drought analysis opens a potential to uncover significant drought interactions both on the surface and sub-surface. |
| Item Type: | Essay (Master) |
| Faculty: | ITC: Faculty of Geo-information Science and Earth Observation |
| Subject: | 05 communication studies, 42 biology, 43 environmental science, 48 agricultural science |
| Programme: | Geoinformation Science and Earth Observation MSc (75014) |
| Link to this item: | https://purl.utwente.nl/essays/102081 |
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