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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

We study input and state constrained inverse optimal control problems starting from a stabilizing controller with a control Lyapunov function, where the goal is to make the controller an explicit solution of the resulting constrained optimal control problem. For an appropriate cost design and initial states for which a sublevel set of the Lyapunov function is contained in the state constraint set

This work presents an assessment of the precipitation deficit in the São Francisco River Basin (SFRB) based on temporal, seasonal and regional analyses of two decades of precipitation data products derived from satellite missions launched since 1997. The temporal analyses were performed by means of three 3-month SPI time series, consisting of 250 values each derived from TRMM, CHIRPS and PERSIANN-

Lake level, area and volume are sensitive indicators of climate change. At present, many studies have focused on the interannual water balance of lakes, but lake level and area can change remarkably with seasons, especially for lakes with seasonal ice cover. Zhari Namco, a seasonal frozen lake, was selected as an example to investigate its seasonal water balance. Multi-source altimetry and Landsat

Personalized patient care has gained increasing attention in recent years. Precise drug dosing is critical for patient safety and good clinical outcomes, especially in intensive care units, where patients often are in critical conditions. Such treatments can include stabilizing blood pressure and heart rate or maintaining safe anesthesia levels. However, the inter-patient variability in the drug r

This paper introduces P-expo, a do-it-yourself open-source software solution for enhancing online lectures. P-expo seamlessly integrates text, images, videos, webcams, and audio, with support for text-based tools like git for collaboration. Additionally, the paper introduces affordable DIY hardware components to enrich online education seminars, and presents a curated selection of accessible open-

Ocean evaporation, represented by latent heat flux (LE), plays a crucial role in global precipitation patterns, water cycle dynamics, and energy exchange processes. However, existing bulk methods for quantifying ocean evaporation are associated with considerable uncertainties. The maximum entropy production (MEP) theory provides a novel framework for estimating surface heat fluxes, but its applica

To carry out the search mission, an additional narrow-angle video camera is installed on board the unmanned aerial vehicle (UAV). This video camera can be re-aimed at objects detected in the image frame received from the main (navigation) video camera. The movement of the additional video camera is carried out by two coordinated electric drives using direct current motors or brushless direct curre

The study is devoted to the development of the 2DCAM hardware and software complex for the physical modeling of the two-coordinate positioning system of the additional video camera of the UAV using the Simulink environment. DYNAMIXEL actuator systems were used to create a complex prototype. They combine DC motor, reduction gearhead, controller, driver and network components.The AH-12A actuator is

This work is devoted to the development of a prototype of a small-sized information display system (SSIDS) for UAVs, which implements a human-machine interface. This system in field conditions in the presence of electromagnetic interference allows you to enter and adjust the flight task.The research used a liquid crystal display (LCD) based on the GC9A01 driver and a WeActStudio development board

Modern hydrological modeling frequently incorporates global remote sensing or reanalysis products for multivariate calibration. Although these datasets significantly contribute to model accuracy, the inherent uncertainties in the datasets and multivariate calibration present challenges in the modeling process. To address this issue, this study introduces an adaptive, process-wise fitting framework

Accurately representing and predicting hydrological processes in terrestrial ecosystems is crucial for understanding the impacts of global environmental change, particularly climate change. This doctoral thesis aims to advance the understanding of vegetation-hydrology interactions and provides new modelling approaches to enhance hydrological prediction abilities. The thesis is grounded in the eval

Tropical oceans are the main global water vapor and latent heat sources, but their responses to radiative forcing remain unclear. Here, we investigate oceanic moisture dynamics of the western tropical Pacific (WTP) over the past 210,000 years through an approach of planktonic foraminiferal triple oxygen isotope (Δ′17O). The Δ′17O record is dominated by the precession cycles (~23,000 years), with l

High-latitude vegetation experience different temperatures than the ambient air temperature. While lacking a regional plant temperature product, we drove the dynamic ecosystem model, LPJ-GUESS, with widely used ERA5-land surface temperature (Tsurf, at radiative equilibrium) and air temperature to understand ecosystem process responses to these two temperatures. We show that tundra plants' growth i