Sökresultat

Hydrological processes in a watershed consist of multiple sub-processes (such as plant growth, evapotranspiration, water yield, and soil–water balance) that have complex interactions. The common practice of calibrating hydrological models against only a single variable (e.g., streamflow) can lead to parameter uncertainty (also known as equifinality), resulting in significant uncertainties in the r

Recurrent neural networks (RNNs) are efficient for classification of sequential data such as speech and audio due to their high precision on tasks. However, power efficiency, the required memory capacity and bandwidth requirements make them less suitable for battery powered devices. In this work, we introduce FLoPAD-GRU: a system on a chip (SoC) for efficient processing of gated recurrent unit (GR

There is a large variability between individuals in the response to anesthetic drugs, that seriously limits the achievable performance of closed-loop controlled drug dosing. Full individualization of patient models based on early clinical response data has been suggested as a means to improve performance with maintained robustness (safety). We use estimation theoretic analysis and realization theo

This thesis deals with the general problem of controlling rigid-body systems through space, with a special focus on unmanned aerial vehicles (UAVs). Several promising UAV control algorithms have been developed over the past decades, enabling truly astounding feats of agility when combined with modern sensing technologies. However, these control algorithms typically come without global stability gu

A hyperspectral field sensor (FloX) was installed in Adventdalen (Svalbard, Norway) in 2019 as part of the Svalbard Integrated Arctic Earth Observing System (SIOS) for monitoring vegetation phenology and Sun-Induced Chlorophyll Fluorescence (SIF) of high-Arctic tundra. This northernmost hyperspectral sensor is located within the footprint of a tower for long-term eddy covariance flux measurements

The ice phenology of alpine lakes on the Tibetan Plateau (TP) is a rapid and direct responder to climate changes, and the variations in lake ice exhibit high temporal frequency characteristics. MODIS and passive microwave data are widely used to monitor lake ice changes with high temporal resolution. However, the low spatial resolutions make it difficult to effectively quantify the freeze-melt dyn

In a mineral concentrator, ore is milled and later separated into concentrate and tailing by a process called flotation. When a milling line abruptly stops, a significant inflow disturbance to the downstream flotation series is often observed. To avoid de-tuning the flotation level controller to handle the worst case scenario, we introduce a feed-forward model predictive controller (MPC) that cons

Cities, where human energy activities and greenhouse gas emissions are concentrated, contribute significantly to alleviating the impacts of global climate change. Utilizing the China Carbon Emissions Accounting Database (CEADs) to provide carbon dioxide emission inventories for urban areas in China at the prefecture level, this study closely examines the historical evolution trajectories of carbon

This study compared two different methods, the satellite altimetry-based and DEM (digital elevation model)-based, for estimating lake water volume changes. We focused on 34 lakes in China as the testing sites to compare the two methods for lake water volume changes from 2005 to 2020. The satellite altimetry-based method used water levels provided by the DAHITI (Database for Hydrological Time Serie

Remote sensing precipitation data have the characteristics of wide coverage and revealing spatiotemporal information, but their spatial resolution is low. The accuracy of the data is obviously different in different study areas and hydrometeorological conditions. This study evaluated four precipitation products in the Yellow River basin from 2001 to 2019, constructed the optimal combined product,

Accurate monitoring of daily precipitation is essential for many applications, such as simulation and prediction of watershed water-related disasters. However, precipitation data from satellite and gauge-based precipitation products face challenges in capturing true observations because of their large uncertainties. To improve daily precipitation estimates, this study proposed a new merging framew

The investigation of triggers causing the onset and intensification of Northern Hemisphere Glaciation (NHG) during the late Pliocene is essential for understanding the global climate system, with important implications for projecting future climate changes. Despite their critical roles in the global climate system, influences of land-ocean interactions on high-latitude ice sheets remain largely un

Variations in solar activity have been proposed to play an important role in recent and past climate change. To study this link on longer timescales, it is essential to know how the Sun has varied over the past millennia. Direct observations of solar variability based on sunspot numbers are limited to the past 400 years, and beyond this we rely on records of cosmogenic radionuclides, such as 14C a

Text i utställningskatalog till utställningen: AS IF HERE – Samaneh Reyhani & Marcus Matt på Trelleborgs museer 8 June 2024- 1 September 2024.

The remote forcing from land surface changes in the Sahara is hypothesized to play a pivotal role in modulating the intensity of the East Asian summer monsoon (EASM) through ocean-atmospheric teleconnections. This modulation has far-reaching consequences, particularly in facilitating societal shifts documented in northern China. Here, we present a well-dated lake-level record from the Daihai Lake

Drought is a natural disaster that occurs globally and can damage the environment, disrupt agricultural production and cause large economic losses. The accurate prediction of drought can effectively reduce the impacts of droughts. Deep learning methods have shown promise in drought prediction, with convolutional neural networks (CNNs) being particularly effective in handling spatial information. I

Global warming has largely advanced spring vegetation phenology, which has subsequently affected terrestrial carbon and water cycles. However, further shifts in vegetation phenology under future climate change remain unclear. We estimated the start of the growing season (SOS) by applying multiple extraction methods based on the NDVI3g data set, and then parameterized and evaluated 11 spring vegeta

The Sun’s energy is effectively limitless. While resources such as coal or gas are finite, if you are able to capture and use solar power it doesn’t prevent anyone else from also using as much sunshine as they need.Except that isn’t quite the full story. Beyond a certain size, solar farms become large enough to affect the weather around them and ultimately the climate as a whole. In our new resear

An Extended Triple Collocation for maximized Correlation (ETCC) method was proposed with a unique correlation function, the purpose of which is to maximize the correlation between the merged product and unknown truth. The method was tested over quasi-global land by combining three independent precipitation products. The performance of the ETCC-merged product was then evaluated against three refere

Because of varied topography and landscape heterogeneity，Tianshan Mountain has extremely complex hydrological processes. Considering that the climate change poses a great threat to the water security，it’s necessary to simulate the change of water elements quantitatively and systematically along with elevation. In this study，we applied the modified FLEXG-Δh model to four classic river basins in Tia