Dr. Anton Vrieling Profile

Dr. Anton Vrieling

at Univ Twente

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Proceedings Article | 17 October 2023 Presentation + Paper

Association of catchment characteristics to Budyko hydrologic model’s uncertainty in humid catchments

Lilin Zhang, Michael Marshall, Anton Vrieling, Andrew Nelson

Proceedings Volume 12727, 127270W (2023) https://doi.org/10.1117/12.2679836

KEYWORDS: Vegetation, Climatology, Correlation coefficients, Statistical analysis, Soil science, Hydrology, Earth observing sensors, Water

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Accurate quantification of precipitation partitioning into evapotranspiration and runoff is important for global water balance estimation and water resources managements. The Budyko framework is a simple yet robust solution to parameterize precipitation partitioning and has been widely applied for studying catchment-level water and energy fluxes. However, substantial variations between the observed and Budyko-predicted evaporative indices have been observed. Many studies have attributed the scatter around the Budyko curve to catchment characteristics (e.g., vegetation and soil property), which are not directly accounted for in the Budyko framework. However, modified Budyko-type equations that consider catchment characteristics are not transferable between regions and the interannual catchment behaviours still fail to follow the adjusted Budyko trajectories. To explore if the pronounced Budyko scatter in humid catchments has a systematic pattern caused by measurable catchment properties, this study comprehensively investigated the relationship between Budyko scatter and multiple catchment biophysical features from both spatial and temporal perspectives. Results reveal that for humid catchments, topography and seasonal cumulative moisture surplus can explain the spatial distributions of Budyko scatter with r higher than 0.65, whereas soil properties and vegetation indices explained little of the variance (r≤0.30). Temporally, the interannual variability of Budyko scatter was negatively correlated with annual average vegetation indices, particularly for catchments with relatively low vegetation cover. Overall, this study provides valuable insights to the interpretation of Budyko framework and offers possible solutions to improve its performance to predict the spatio-temporal variability of water balances.

Proceedings Article | 2 October 2008 Paper

Recent trends in agricultural production of Africa based on AVHRR NDVI time series

Anton Vrieling, Kirsten de Beurs, Molly Brown

Proceedings Volume 7104, 71040R (2008) https://doi.org/10.1117/12.799824

KEYWORDS: Agriculture, Molybdenum, Satellites, Vegetation, Clouds, Climate change, Statistical analysis, Raster graphics, Climatology, Remote sensing

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African agriculture is expected to be hard-hit by ongoing climate change. Effects are heterogeneous within the continent, but in some regions resulting production declines have already impacted food security. Time series of remote sensing data allow us to examine where persistent changes occur. In this study, we propose to examine recent trends in agricultural production using 26 years of NDVI data. We use the 8-km resolution AVHRR NDVI 15-day composites of the GIMMS group (1981-2006). Temporal data-filtering is applied using an iterative Savitzky-Golay algorithm to remove noise in the time series. Except for some regions with persistent cloud cover, this filter produced smooth profiles. Subsequently two methods were used to extract phenology indicators from the profiles for each raster cell. These indicators include start of season, length of season, time of maximum NDVI, maximum NDVI, and cumulated NDVI over the season. Having extracted the indicators for every year, we aggregate them for agricultural areas at sub-national level using a crop mask. The aggregation was done to focus the analysis on agriculture, and allow future comparison with yield statistics. Trend analysis was performed for yearly aggregated indicators to assess where persistent change occurred during the 26-year period. Results show that the phenology extraction method chosen has an important influence on trend outcomes. Consistent trends suggest a rising yield trend for 500-1100 mm rainfall zones ranging from Senegal to Sudan. Negative yield trends are expected for the southern Atlantic coast of West Africa, and for western Tanzania.

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