Angulo Villacís, Carlos Lenín: Re-Solution - understanding the uncertainty in regional applications of crop models. - Bonn, 2015. - Dissertation, Rheinische Friedrich-Wilhelms-Universität Bonn.
Online-Ausgabe in bonndoc: https://nbn-resolving.org/urn:nbn:de:hbz:5n-38928
@phdthesis{handle:20.500.11811/6225,
urn: https://nbn-resolving.org/urn:nbn:de:hbz:5n-38928,
author = {{Carlos Lenín Angulo Villacís}},
title = {Re-Solution - understanding the uncertainty in regional applications of crop models},
school = {Rheinische Friedrich-Wilhelms-Universität Bonn},
year = 2015,
month = feb,

note = {Uncertainties emerging from the scale change and data constraints when analyzing and further utilizing the results of regional crop model applications are largely unclear. The present thesis offers a systematic analysis on the uncertainties related to model parameters and input data. Three specific studies were designed to increase understanding on these two issues:
1. In a continental simulation study (EU25) the influence of considering the sub-regional differences in environmental and management conditions on the parameter estimation process of a model were investigated. Taking into consideration sub-regional differences of model parameters related to crop growth in addition to crop phenology resulted in the best agreement between simulated and observed yield at the European scale.
2. A regional study in Jokioinen, representing an important barley producing region in South-West Finland, was undertaken in order to systematically analyse the influence of aggregation of weather data on yield simulations. The responses of four crop models of different complexity to five weather data aggregation levels (Weather station, 10 km x 10 km, 20 km x 20 km, 50 km x 50 km , and 100 km x 100 km) were compared. Differences between models were larger than the effect of the chosen spatial weather data resolution. Models showed different characteristic ‘fingerprints’ of simulated yield frequency distributions independent of the resolution used for yield simulation
3. A complementary study to the weather data aggregation was formulated for soil input data and undertaken in the State of North-Rhine Westphalia in Germany. This comprised a systematic analysis of the influence of three different spatial soil data resolutions on simulated regional yields and simulated total growing season evapotranspiration. The resolutions used corresponded to soil maps of the scales: 1 : 50 000; 1 : 300 000 and 1 : 1 000 000. Differences between models were again larger than the effect of the chosen spatial soil data resolution. Three main causes were identified as possible explanations for the low influence of soil data resolution on yield simulations: a) the high precipitation amount in the region b) the methods applied to calculate water retention properties and c) the method of data aggregation. No characteristic “fingerprint” between sites, years and resolutions could be found for any of the models.
The utilization of various crop models differing in complexity and approaches of modelling relevant processes should become common practice for large area impact assessment studies since the uncertainties introduced by the model choice have been shown in this study to be more important than the uncertainties caused by the input data resolution.},

url = {https://hdl.handle.net/20.500.11811/6225}
}

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