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Abstract on the dissertation on:"The effect of hillslope processes on long-term landscape evolution""Construction of an integrated geographical landscape model" By Jasper LaurentThis dissertation is a continuation of the work carried out by Campforts B. for his thesis project in 2011-2012. Therefore field work was carried out in the Pauté catchment in southern Ecuador. Data was gathered under the form of knick points found in the drainage system of the catchment. These knick points can be translated into discrete uplift events or pulses which are a result of the formation of the Andean cordillera. In a next step this information was entered in a MATLAB model in order to construct a River Incision Model (RIM). The interplay between uplift (calculated from the knick point data) and river incision into the bedrock could be investigated. The goal of this dissertation is to upgrade the RIM and obtain a physical, distributed and integrated landscape model. This is a model, based on scientific formulas and theories. Crucial in the construction of this model is the implication of hillslope processes. These were not well represented in the RIM. So, two main goals can be distinguished. (1) A hillslope evolution model (HEM) will be constructed. This model will calculate the landscape evolution as if it was only influenced by erosion, sediment transport and accumulation of sediments. In a next step (2) the HEM will be adapted and merged with the RIM. This way a landscape model is obtained that can calculate evolutions over long periods of time (>1Ma).The mayor part of the effort was put into coding the different processes into MATLAB. But once this is done the model should be applicable on different settings. It can be used to calculate average erosion rates on a (supra)catchment scale. This claim is backed up by the first model results. Modeled erosion rates are of the same order of magnitude as erosion rates measured with the cosmogenic radionuclides method in the field. ...

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Rice cultivation is critical for food security since it is the main staple food for more than half of the world’s population. The advent of high-resolution remote sensing satellite imagery posed new opportunities to monitor rice growth dynamics with high reliability. The monitoring of rice growth dynamics is vital for future’s food security. Especially, the importance of synergistic use of state-of the art radar and optical-based satellites is rising, because these can enhance the rice monitoring ability. The purpose of this thesis is to analyse the influence of rice flooding time on the cumulative NDVI during the rice growth season. The latter was introduced as a proxy for rice growth dynamics and can be indirectly related to rice yields. This study focusses on north-east Madagascar during the rice season of 2017-2018. In order to obtain insights on rice growth dynamics, the potential of synergistic use of Sentinel-1 and Sentinel-2 for mapping rice and rice dynamics is investigated. During this research different kinds of data were used. Remote sensing data consisted of one year (2017-2018) imagery of Sentinel-1, Sentinel-2 and Landsat 8. Moreover, a calibration and validation dataset with information on rice cultivation and rice growth dynamics was compiled. Additionally, some field data were collected by Drs. Liesa Brosens (KU Leuven) during a field campaign. Firstly, the synergistic use of Sentinel-1 and Sentinel-2 for rice mapping revealed that the use of both sensors for rice classification outperforms the result for the optical-only classification. Rice cultivation could be predicted with an accuracy of 97%. Secondly, rice growth dynamics were identified by using three satellites. The timing of three rice phenological events was determined, including flooding time, Start Of Season (SOS) and End Of Season (EOS). All three events were detected by optimising several thresholds on the temporal profile of rice in the optical and the microwave spectrum of radar. Sentinel-1 was able to detect rice flooding within 5 days accurate. On the other hand, the SOS and EOS were detected on a smoothed NDVI-profile within 12 days accurate. Finally, the influence of rice flooding time on the cumulative NDVI showed a negative relationship between both. Moreover, it was found that a delay in rice flooding time also delayed the SOS and EOS. Based on literature review it can be assumed that cumulative NDVI is positively related with rice yields. The developed approach provides some new insights on rice growth dynamics and can form the basis for mapping and timely monitoring of rice growth dynamics. The possibility of timely monitoring will allow the government to take timely and adequate action for rice fields with delayed flooding. Consequently, rice growth can potentially be optimised, which will be beneficial for future’s food security. The gap of Sentinel-1 images between November and half December prevented to fully explore the potential of synergistic use of Sentinel-1 and Sentinel-2. However, it could be expected that further research could benefit from the availability of entire Sentinel-1 time series. Moreover, in further research the possibility of citizen science to collect information on the rice growth dynamics and rice yields could be investigated. The availability of these data would allow to further refine the developed approach for rice growth dynamics detection and to relate it with the rice yield.

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The páramo consists of a collection of grassland ecosystems located on the higher elevations of the South American Andes mountain range. The soils underlying the páramo grasslands are known to have extraordinary water holding capacities. Because of this, the páramo soils are an important freshwater reservoir for the local societies. The aim of this study was to investigate the spatial variation in soil thickness and soil water holding capacity in the Soroche river catchment, a catchment in the páramo grasslands near the city of Cuenca (Ecuador) which has been partly converted to agricultural land. The influence of topographic variables and land use on soil thickness and soil water holding capacity was investigated in order to determine how these relations influence their spatial variability in the catchment. To conduct this study, an approach was chosen that encompasses field work, followed by a lab analysis and a statistical analysis to investigate the relations between the factors mentioned above. These relations were thereafter used to create predictions for the spatial variations of soil thickness and soil water holding capacity in the catchment. The results first show that significant statistical relations exist between soil thickness and topography. Because of this, the highest predicted soil depths in the study area are mostly located on relatively flat or concave hillslopes. Second, the associated water holding capacities of the soil samples show a significant statistical relation with hillslope curvature, one of the investigated topographic variables. Hereafter, to obtain the available water content for the entire soil profile at each location, the water holding capacities of each soil sample were multiplied with the soil thickness. When the statistical analysis is repeated for these combinations of soil thickness and soil water holding capacity, new significant relations arise with topography. Therefore, the highest predicted available water contents are also found on rather flat or concave slopes. Furthermore, land use change has a twofold impact on the results: on the one hand, the calculated available water contents are significantly lower in the soils under cultivated areas compared to untouched natural páramo grasslands. On the other hand, cultivation also affects the observed statistical relations with topography, as most of the significant relations with topographic variables disappear in cultivated areas. Hence, this study shows that the soil water holding capacities are generally lower after cultivation, and that its spatial variation becomes more unpredictable when soils are cultivated. This study has two main conclusions: first, although other research on water holding capacity of the páramo soils does not consider soil thickness as a crucial factor to understand spatial variability of the available water contents in the soils, this thesis has shown that soil thickness can play an important role. Therefore, more future research should consider soil thickness to understand the spatial variation of soil water holding capacities in the páramo. Second, this study shows that cultivation of the páramo soils can have negative effects on their available water contents. Therefore, a sustainable land use management of the páramo grasslands is recommended in order to make sure that future generations can keep relying on the freshwater reserves in this unique ecosystem.

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From the moment of their origin, landscapes all across the world have undergone several changes and modifications as a consequence of tectonic activity, climate and more recently, anthropogenic land use changes. Soil erosion studies are very interesting in this story, because they can learn us how landscapes have developed through time and what kind of processes may have caused these changes. Spain is a country that is believed to be highly affected by soil erosion. Many Spanish soils are in a heavily degraded state, especially the ones that are located on steep hill slopes in southeastern Spain. However, the question is whether this is a consequence of A) high CURRENT erosion rates or B) the cumulative effect of millennia of soil erosion and slope profile truncation during THE PAST. In this paper, an erosion study was performed in a first order river catchment in southeastern Spain. In order to get more insight in the hill slope dynamics that have shaped/reshaped the study area, short-term (i.e. last 50-60 years) erosion rates were compared with long-term (i.e. Holocene) erosion rates. For the short time scale, the radionuclide 137Cs was used as a soil erosion tracer. For the longer time scales, erosion rates were established based on 14C-analysis of charcoal fragments that were encountered in the alluvial valley of the study area. Our study has shown that, during the last decades, no net soil movement took place from the steep hill slopes to the alluvial valley of the study area. However, soil erosion and deposition took place on the local hill slope scale. In order to calculate net erosion rates from the collected 137Cs data, two different conversion models were applied. A profile distribution model (PDM) was used to calculate erosion rates on uncultivated soils while a mass balance model (MBM) was used to calculate erosion rates on cultivated soils. Net soil erosion rates derived from the MBM range between 8,86 and 11,40 t*ha-1*yr-1, while net soil erosion rates calculated with the PDM range between 3,80 and 10,65 t*ha-1*yr-1. However, at two sample locations (P5 & P7), the PDM calculated net soil deposition of 2,18 and 4,67 t*ha-1*yr-1. No real trend in erosion rates could be obtained on the hill slope scale, indicating that local factors may control local soil distribution and/or deposition during rainfall events. The 14C results of the charcoal fragments on the other hand suggest that the study area has already known a long history of soil erosion and deposition. From the 6,05 m thick sediment layer that is deposited in the study area, 4,65 m was already deposited before the Iron age and not less than 5,55 m before 520 yr BP. These results suggest that the stored sediments in the valley of the study area are accumulated over thousands of years. Therefore, we believe that abrupt Holocene climate changes and early Neolithic farmers had a more important role in the landscape development of the study area compared to the intensification of human activities during Roman times. This study learns that current erosion rates in Southeastern Spain may be overestimated, because one does not take into account the longer time-spans over which soil erosion may act. The analysis of colluvial deposits and soil erosion rates thus requires the incorporation of longer time-scales, something that is often neglected in literature and may therefore lead to an overestimation of current soil erosion rates.