Indicator-based assessments of the coupling coordination degree and correlations of water-energy-food-ecology nexus in Uzbekistan.

Grappling with the global ecological concern of the Aral Sea disaster, Uzbekistan exemplifies the urgent necessity of unravelling and addressing the complex Water-Energy-Food-Ecology (WEFE) nexus conflicts in arid regions, a critical task yet largely uncharted. Through the strategic process of 'Indicator Articulation - Weight Calibration - Nexus Coordination Quantification - Correlational Analysis', this work has developed a tailored framework that integrates a novel, context-specific indicator system, enabling an illumination of the intricate dynamics within the WEFE nexus in arid regions. During 2000-2018, the WEFE Nexus in Uzbekistan showed low-level coordination, indicating systemic imbalances. The Aral Sea crisis was the central disruptor, resulting in a moderately disordered ecological subsystem. Concurrently, disorder was observed in water resources, signaling inadequate management and potential overutilization. Furthermore, Coordination for energy and food were barely coordinated and under primary coordination respectively, underlining critical challenges in energy efficiency and food security. Over the last two decades, the WEFE Nexus has evolved towards a tighter interlinkage, yet the stability of this coupling coordination has experienced increased fluctuations, indicating that Uzbekistan's policies in the WEFE subsystems have been less stable in the last two decades and are in need of further adjustment and improvement. To address the challenges, we recommend a comprehensive approach that integrates technological, infrastructure, and policy solutions is needed. Specifically, promoting water-saving irrigation technology, renewing and maintaining outdated energy facilities, and raising public awareness of ecological protection are part of the essential measures. Furthermore, alleviating the contradiction between economic growth and ecological conservation remains a major challenge. Collectively, our constructed WEFE Nexus framework, with its extendable and context-specific indicators, holds significant potential for broad application in the analysis of multi-sectoral sustainability, particularly within arid regions globally, and forms a solid foundation for the formulation of effective, targeted policies and sustainable development strategies.

Probabilistic assessment of vegetation vulnerability to drought stress in Central Asia.

The increasing frequency and intensity of droughts in a warming climate are likely to exacerbate adverse impacts on ecosystems, especially for water-limited regions such as Central Asia. A quantitative understanding of the impacts of drought on vegetation is required for drought preparedness and mitigation. Using the Global Inventory Modeling and Mapping Studies NDVI3g data and Standardized Precipitation Evapotranspiration Index (SPEI) from 1982 to 2015, we evaluate the vegetation vulnerability to drought in Central Asia based on a copula-based probabilistic framework and identify the critical regions and periods. Furthermore, a boosted regression trees (BRT) model was also used to explore the relative importance of environmental factors and plant traits on vegetation response to drought. Additionally, we also investigated to what extent irrigation could alleviate the impacts of drought. Results revealed that months from June to September was the critical period when vegetated areas were most vulnerable to drought stress. The probabilities of vegetation loss below 20th quantile under extremely dry in these months were 68.7%, 69.4%, 71.0%, and 67.0%, respectively. Regarding vegetation-vulnerable regions, they shifted with different growth stages. During the middle of the growing season, semi-arid areas were the most vulnerable regions, whereas the highest drought-vulnerable regions were observed in arid areas during other periods. The BRT results showed that plant traits accounted for a large fraction (58.9%) of vegetation response to drought, which was more important than ambient soil environment (20.8%). The analysis also showed that mitigations from irrigation during July to September were smaller than in other months. The results of this paper provide insight into the influences of drought on vegetation and may contribute to drought mitigation and land degradation measures in Central Asia under accelerating global warming.

Identification of conservation priorities in the major basins of Central Asia: Using an integrated GIS-based ordered weighted averaging approach.

Ecosystem services (ESs) provided by the major basins of Central Asia are critical to human well-being and have attracted the attention of the international community. The identification of conservation priorities is of great significance for the maintenance and protection of key ESs. In this study, we quantified the spatiotemporal changes of net primary productivity (NPP), soil conservation (SC), water yield (WY) and habitat quality (HQ) in the major basins of Central Asia from 1995 to 2015. In addition, a GIS-based ordered weighted averaging (OWA) multi-criterion valuation method was adopted to identify potential conservation areas under 11 scenarios. Conservation priorities were determined by comparing the conservation efficiency under each scenario. Then, a broad range of indicators were considered to distinguish the driving factors affecting ESs in conservation priorities. The results show that the average conservation efficiency in the Issyk-Kul Basin was the highest, followed by the Am Darya Basin, Ili-Balkhash Basin and Syr Darya Basin. We observed that the conservation efficiency of the four ESs declined continuously in the Ili-Balkhash Basin from 1995 to 2015, while it changed steadily in the other three basins. Correlation analysis indicated that natural factors (e.g., precipitation and topography) were the main driving factors of WY, SR and NPP in conservation priorities, while HQ was more affected by socio-economic factors (e.g., population density and both cropland and urban percentages). The identification of conservation priorities and their driving factors plays an important role in ensuring the ecological security of the lower reaches, regulating the regional water balance and stabilizing the climate pattern.

Assessing vegetation stability to climate variability in Central Asia.

The dramatic climate change has far-reaching impacts on vegetation in drylands such as Central Asia. Recent attempts to assess vegetation stability to short-term climate variability often account solely for vegetation sensitivity or resilience but ignore the composite effects of these two indicators. Meanwhile, our understanding of the vegetation stability at the seasonal scale remains insufficient. In this study, considering the cumulative effects of vegetation response to three key climate factors, we assessed the stability of vegetation in Central Asia using normalized difference vegetation index (NDVI) and the meteorological data from 1982 to 2014 by integrating vegetation sensitivity and resilience, and further identified the critical regions and seasons of vegetation that experience high risks of pending change. The results show that the sensitivity of vegetation has a strong correlation (R2 = 0.83, p < 0.001) with the aridity index (AI), with the vegetation of drier areas having lower sensitivities to climate variability. At the temporal scale, the sensitivity of vegetation to climate variability varied among different seasons. The average vegetation sensitivity index (VSI) is 41.17, 33.32 and 28.63 in spring, summer and autumn, respectively. Spatially, a trade-off between vegetation sensitivity and resilience is found both for the growing season (R2 = 0.67) and seasonal scale (R2 = 0.71, 0.32 and 0.43 for spring, summer and autumn, respectively), regions with high vegetation sensitivity were always accompanied by strong resilience. Based on the relationship between vegetation sensitivity and resilience, we further identify the critical regions and periods of vegetation with high change risk in Central Asia. Results suggest that herbaceous plants in semi-arid areas present high instability, especially in summer. This study offers a comprehensive perspective to assess vegetation stability to climate variability and the results will facilitate the protection of ecosystems and the implementation of sustainable development goals in Central Asia.

Support vector regression for high-resolution beach surface moisture estimation from terrestrial LiDAR intensity data.

Beach Surface Moisture (BSM) is a key attribute in the coastal investigations of land-atmospheric water and energy fluxes, groundwater resource budgets and coastal beach/dune development. In this study, an attempt has been made for the first time to estimate BSM from terrestrial LiDAR intensity data based on the Support Vector Regression (SVR). A long-range static terrestrial LiDAR (Riegl VZ-2000) was adopted to collect point cloud data of high spatiotemporal resolution on the Ostend-Mariakerke beach, Belgium. Based on the field moisture samples, SVR models were developed to retrieve BSM, using the backscattered intensity, scanning ranges and incidence angles as input features. The impacts of the training samples' size and density on the predictive accuracy and generalization capability of the SVR models were fully investigated based on simulated BSM-intensity samples. Additionally, we compared the performance of the SVR models for BSM estimation with the traditional Stepwise Regression (SR) method and the Artificial Neural Network (ANN). Results show that SVR could accurately retrieve the BSM from the backscattered intensity with high reproducibility (average test RMSE of 0.71% ± 0.02% and R2 of 0.98% ± 0.002%). The Radial Basis Function (RBF) was the most suitable kernel for SVR model development in this study. The impacts of scanning geometry on the intensity could also be accurately corrected in the process of estimating BSM by the SVR models. However, compared to the SR method, the predictive accuracy and generalization performance of SVR models were significantly dependent on the training samples' coverage, size and distribution, suggesting the need for the training samples of uniform distribution and representativeness. The minimum size of training samples required for SVR model development was 54. Under this condition, SVR performed similarly to ANN with a test RMSE of 1.06%, but SVR still performed acceptably (with an RMSE of 1.83%) even using extremely few training samples (only 16 field samples of uniform distribution), far better than the ANN (with an RMSE of 4.02%).

Genetically modified crops and small-scale farmers: main opportunities and challenges.

Although some important features of genetically modified (GM) crops such as insect resistance, herbicide tolerance, and drought tolerance might seem to be beneficial for small-scale farmers, the adoption of GM technology by smallholders is still slight. Identifying pros and cons of using this technology is important to understand the impacts of GM crops on these farmers. This article reviews the main opportunities and challenges of GM crops for small-scale farmers in developing countries. The most significant advantages of GM crops include being independent to farm size, environment protection, improvement of occupational health issues, and the potential of bio-fortified crops to reduce malnutrition. Challenges faced by small-scale farmers for adoption of GM crops comprise availability and accessibility of GM crop seeds, seed dissemination and price, and the lack of adequate information. In addition, R&D and production costs in using GM crops make it difficult for these farmers to adopt the use of these crops. Moreover, intellectual property right regulations may deprive resource poor farmers from the advantages of GM technology. Finally, concerns on socio-economic and environment safety issues are also addressed in this paper.

Combining user logging with eye tracking for interactive and dynamic applications.

User evaluations of interactive and dynamic applications face various challenges related to the active nature of these displays. For example, users can often zoom and pan on digital products, and these interactions cause changes in the extent and/or level of detail of the stimulus. Therefore, in eye tracking studies, when a user's gaze is at a particular screen position (gaze position) over a period of time, the information contained in this particular position may have changed. Such digital activities are commonplace in modern life, yet it has been difficult to automatically compare the changing information at the viewed position, especially across many participants. Existing solutions typically involve tedious and time-consuming manual work. In this article, we propose a methodology that can overcome this problem. By combining eye tracking with user logging (mouse and keyboard actions) with cartographic products, we are able to accurately reference screen coordinates to geographic coordinates. This referencing approach allows researchers to know which geographic object (location or attribute) corresponds to the gaze coordinates at all times. We tested the proposed approach through two case studies, and discuss the advantages and disadvantages of the applied methodology. Furthermore, the applicability of the proposed approach is discussed with respect to other fields of research that use eye tracking-namely, marketing, sports and movement sciences, and experimental psychology. From these case studies and discussions, we conclude that combining eye tracking and user-logging data is an essential step forward in efficiently studying user behavior with interactive and static stimuli in multiple research fields.

Ecological security warning in Central Asia: Integrating ecosystem services protection under SSPs-RCPs scenarios.

Ecological security patterns (ESPs) are designed to enhance ecosystem structure and functionality while preserving vital ecosystem services (ESs). This study not only integrated the ES trade-offs related to ecological security warning, but also considered the effects of future climate changes and human activities on ESPs. By combining the revised universal soil loss equation (RUSLE), the revised wind erosion equation (RWEQ), the dry sedimentation (DS) model, the recreation opportunity map (ROM) and the integrated valuation of ESs and trade-offs (InVEST) model, this study projected provisioning services, regulation services and cultural services in Central Asia (CA) for historical periods (1995-2014) and future scenarios (2021-2099). An ecological security early-warning (source - corridor - barriers) framework was constructed based on the protection of ESs under the SSP126, SSP245 and SSP585 scenarios. The ordered weighted averaging method (OWA) was applied to this framework to identify ecological sources. The Minimum cumulative resistance model (MCR) and circuit theory were used to construct ecological corridors and barriers. Our results revealed that ES hotspot areas will decrease by 11.75 % to 16.42 % in CA under the SSP126, SSP245, and SSP585 scenarios. Under the ecological warning framework, the ecological source warning area will reach 792 km2-1942 km2 and 6591 km2-17,465 km2 under the SSP126 and SSP585 scenarios, respectively. In particular, in the 2050s under the SSP245 scenario, the number of key ecological corridor warnings will exceed 50 % of the total number of corridors. We found that ecological barrier warnings will mainly be distributed in desert areas with low vegetation coverage in southwestern CA. Building upon the reorganization of ESs within the ESP framework, we propose an ecological early warning strategy referred to as "one axis, two belts, two cores, and three zones". This novel approach aims to enhance our ability to predict and respond to ecological threats and challenges.

Dynamics of algal blooms in typical low-latitude plateau lakes: Spatiotemporal patterns and driving factors.

The alpine lakes distributed on the plateau are crucial for the hydrological, and biogeochemical cycle, and also serve as a guarantee for regional economic development and human survival. However, under the influence of human interference and climate fluctuations, lakes are facing problems of eutrophication and subsequent algal blooms (ABs) with acceleration, and the development and driving factors of this phenomenon need to be considered as a whole. In this study, ten lakes located on the Yunnan-Guizhou Plateau were selected as the study area to analyze the spatiotemporal distribution of ABs and possible controlling forces. The FAI (Floating Algae Index) derived from multiple MODIS products and water quality data under high-frequency monitoring were selected as the data sources for characterizing ABs. Three nutrient parameters and five meteorological variables were used to explore the driving factors affecting ABs. Various methods of trend detection and correlation analysis have been applied. The main results are as follows: (1) Dianchi Lake (in lake area) and Xingyun Lake (in area proportion) are the two lakes with the most serious ABs in the historical period; (2) ABs are mainly distributed on the shoreline and northern edge of lakes, and tend to stay away from the lake center during high-temperature periods of the day; (3) Six lakes show a decreasing trend in ABs, especially after 2018, while other lakes (including Fuxian, Chenghai, Yangzong, and Erhai) are increasing, not only in peak value but also in duration; (4) Lakes with severe ABs are all P-restricted lakes, the minimum temperature is the most sensitive meteorological factor, while the impact of precipitation against ABs has a time lag; (5) Establishing a warning system of temperature and nutrient concentration is critical in ABs adaptive strategy. This study is expected to provide scientific references for regional water management and the restoration of the eutrophic aquatic ecosystem.

Organic agriculture and undernourishment in developing countries: main potentials and challenges.

While much has been published on the advantages of organic agriculture, less has addressed its potentials and challenges to fight undernourishment in developing countries. This article aims at reviewing the main potentials and challenges of this approach when dealing with "undernourishment" as a multifaceted concept in developing countries. Accordingly, 2 main issues of the concept which are "food security" and "food safety" are discussed in the context of both developed and developing countries to understand their different food policies' priorities. Next, the main potentials, challenges and tradeoffs of the organic approach are analyzed to understand whether the approach is capable to provide a secure or a safe food-production system which can meet the food policy priorities in developing countries. With respect to food security, the article concludes that conventional and biotechnological approaches still produce higher yields than organic agriculture. However, considering the many advantages of organic agriculture, it can in a long run, be more conducive than now to meet food security. Thus, conventional approach is still needed to feed the hungers in developing countries [corrected]. Accordingly, the article emphasizes on the importance of providing farmers in developing countries with the possibility of implementing different approaches. Therefore, policy makers should be aware of a realistic and gradual transition from the other approaches to the organic that should be projected only in "long run," and after conducting a series of risk assessment studies on the bases of both "crop-case" and "region-case."

The impact of neighborhood deprivation on patients' unscheduled out-of-hours healthcare seeking behavior: a cross-sectional study.

BACKGROUND: The use of unscheduled out of hours medical care is related to the social status of the patient. However, the social variance in the patient's preference for a hospital based versus a primary care based facility, and the impact of specific patient characteristics such as the travel distance to both types of facilities is unclear. This study aims to determine the social gradient in emergency care seeking behavior (consulting the emergency department (ED) in a hospital or the community-based Primary Care Center (PCC)) taking into account patient characteristics including the geographical distance from the patient's home to both services. METHODS: A cross-sectional study, including 7,723 patients seeking out-of-hours care during 16 weekends and 2 public holidays was set up in all EDs and PCCs in Ghent, Belgium. Information on the consulted type of service, and neighborhood deprivation level was collected, but also the exact geographical distance from the patient's home to both types of services, and if the patient has a regular GP. RESULTS: Patients living in a socially deprived area have a higher propensity to choose a hospital-based ED than their counterparts living in more affluent neighborhoods. This social difference persists when taking into account distance to both services, having a regular GP, and being hospitalized or not. The impact of the distance between the patient's home address and the location of both types of services on the patient's choice of service is rather small. CONCLUSIONS: Initiatives aiming to lead patients more to PCC by penalizing inappropriate ED use might increase health inequity when they are not twinned with interventions improving the access to primary care services and tackling the underlying mechanisms of patients' emergency care seeking behavior. Further research exploring the impact of out-of-hours care organization (gatekeeping, payment systems, …) and the patient's perspectives on out-of-hours care services is needed.

Perception and communication of flood risks: a systematic review of empirical research.

Flood hazards are the most common and destructive of all natural disasters. For decades, experts have been examining how flood losses can be mitigated. Just as in other risk domains, the study of risk perception and risk communication has gained increasing interest in flood risk management. Because of this research growth, a review of the state of the art in this domain is believed necessary. The review comprises 57 empirically based peer-reviewed articles on flood risk perception and communication from the Web of Science and Scopus databases. The characteristics of these articles are listed in a comprehensive table, presenting research design, research variables, and key findings. From this review, it follows that the majority of studies are of exploratory nature and have not applied any of the theoretical frameworks that are available in social science research. Consequently, a methodological standardization in measuring and analyzing people's flood risk perceptions and their adaptive behaviors is hardly present. This heterogeneity leads to difficulties in comparing results among studies. It is also shown that theoretical and empirical studies on flood risk communication are nearly nonexistent. The article concludes with a summary on methodological issues in the fields of flood-risk perception and flood-risk communication and proposes an agenda for future research.

Interannual and seasonal relationships between photosynthesis and summer soil moisture in the Ili River basin, Xinjiang, 2000-2018.

Soil moisture (SM) is essential for controlling terrestrial carbon uptake, as it directly provides moisture for photosynthesis, especially in arid and semiarid regions. We selected the arid and semiarid Ili River basin (IRB) of Xinjiang as the study area, and investigated the spatial and temporal characteristics and interrelationships with SM and photosynthesis from 2000 to 2018 using the ERA5 products and solar-induced chlorophyll fluorescence (SIF). SM and photosynthesis showed a decreasing trend during the study period. Compared with those in spring and autumn, the variation of summer SM and SIF was more consistent with the interannual variation. Anomaly analysis showed that negative SM anomalies were most profound in 2012-2015, 2008, and 2014. Additionally, we quantified the effect of seasonal SM deficits on photosynthesis by performing model-based experiments. The results indicated that the gross primary productivity (GPP) simulated by the P-model could capture the characteristics of photosynthesis in the IRB, which had a high correlation with SIF (R2 = 0.82, p < 0.001). In 2012-2015, 2008, and 2014, SM deficits caused more GPP reduction in the summers than in the springs or the autumns. The trends were mainly visible in the northern IRB, where GPP was below 40 % of the multi-year mean, and SM was below 23 %. GPP decreased more significantly in grassland than in the forest under the influence of SM deficit. This study reveals seasonal differences in the effects of SM deficit on photosynthesis and emphasizes that the summer SM deficit was the main factor responsible for decreases in GPP in the IRB during the study period. These findings contribute to a better understanding of the relationships between photosynthesis and environmental factors, and provide a reference for an accurate assessment of the regional carbon cycle.

Recent impacts of water management on dryland's salinization and degradation neutralization.

Reducing soil salinization of croplands with optimized irrigation and water management is essential to achieve land degradation neutralization (LDN). The effectiveness and sustainability of various irrigation and water management measures to reduce basin-scale salinization remain uncertain. Here we used remote sensing to estimate the soil salinity of arid croplands from 1984 to 2021. We then use Bayesian network analysis to compare the spatial-temporal response of salinity to water management, including various irrigation and drainage methods, in ten large arid river basins: Nile, Tigris-Euphrates, Indus, Tarim, Amu, Ili, Syr, Junggar, Colorado, and San Joaquin. In basins at more advanced phases of development, managers implemented drip and groundwater irrigation and thus effectively controlled salinity by lowering groundwater levels. For the remaining basins using conventional flood irrigation, economic development and policies are crucial for establishing a virtuous circle of "improving irrigation systems, reducing salinity, and increasing agricultural incomes" which is necessary to achieve LDN.

Monitoring of carbon-water fluxes at Eurasian meteorological stations using random forest and remote sensing.

Simulating the carbon-water fluxes at more widely distributed meteorological stations based on the sparsely and unevenly distributed eddy covariance flux stations is needed to accurately understand the carbon-water cycle of terrestrial ecosystems. We established a new framework consisting of machine learning, determination coefficient (R2), Euclidean distance, and remote sensing (RS), to simulate the daily net ecosystem carbon dioxide exchange (NEE) and water flux (WF) of the Eurasian meteorological stations using a random forest model or/and RS. The daily NEE and WF datasets with RS-based information (NEE-RS and WF-RS) for 3774 and 4427 meteorological stations during 2002-2020 were produced, respectively. And the daily NEE and WF datasets without RS-based information (NEE-WRS and WF-WRS) for 4667 and 6763 meteorological stations during 1983-2018 were generated, respectively. For each meteorological station, the carbon-water fluxes meet accuracy requirements and have quasi-observational properties. These four carbon-water flux datasets have great potential to improve the assessments of the ecosystem carbon-water dynamics.

The informed society: an analysis of the public's information-seeking behavior regarding coastal flood risks.

Recent flood risk management puts an increasing emphasis on the public's risk perception and its preferences. It is now widely recognized that a better knowledge of the public's awareness and concern about risks is of vital importance to outline effective risk communication strategies. Models such as Risk Information Seeking and Processing address this evolution by considering the public's needs and its information-seeking behavior with regard to risk information. This study builds upon earlier information-seeking models and focuses on the empirical relationships between information-seeking behavior and the constructs of risk perception, perceived hazard knowledge, response efficacy, and information need in the context of coastal flood risks. Specific focus is given to the mediating role of information need in the model and to the differences in information-seeking behavior between permanent and temporary residents. By means of a structured on-line questionnaire, a cross-sectional survey was carried out in the city of Ostend, one of the most vulnerable places to coastal flooding on the Belgian coast. Three hundred thirteen respondents participated in the survey. Path analysis reveals that information need does not act as a mediator in contrast to risk perception and perceived knowledge. In addition, it is shown that risk perception and perceived hazard knowledge are higher for permanent than temporary residents, leading to increased information-seeking behavior among the former group. Implications for risk communication are discussed.

Phenology-based seasonal terrestrial vegetation growth response to climate variability with consideration of cumulative effect and biological carryover.

Vegetation growth is influenced not only by climate variability but also by its past states. However, the differences in the degree of the climate variability and past states affecting vegetation growth over seasons are still poorly understood, particularly given the cumulative climate effects. Relying on the Normalized Difference Vegetation Index (NDVI) data from 1982 to 2014, the vegetation growing season was decomposed into three periods (sub-seasons) - green-up (GSgp), maturity (GSmp), and senescence (GSsp) - following a phenology-based definition. A distributed lag model was then utilized to analyze the time-lag effect of vegetation growth response to climatic factors including precipitation, temperature, and solar radiation during each sub-season. On this basis, the relative importance of climatic factors and vegetation growth carryover (VGC) effect on vegetation growth was quantified at the phenology-based seasonal scale. Results showed that the longest peak lag of precipitation, temperature, and solar radiation occurred in the GSmp, GSsp, and GSgp, with 1.27 (1.13 SD), 0.89 (1.02 SD), and 0.80 (1.04 SD) months, respectively. The influence of climate variability was strongest in the GSgp, and diminished over the season, while the opposite for the VGC effect. The relative influence of each climatic factor also varied between sub-seasons. Vegetation in more than 58% of areas was more affected by temperature in the GSgp, and the proportion decreased to 34.00% and 31.78% in the GSmp and GSsp, respectively. Precipitation and solar radiation acted as the dominant climatic factors in only 28.80% and 20.88% of vegetation areas in the GSgp, but they increased to 35.21%, 32.61% in the GSmp, and 38.20%, 30.02% in the GSsp, respectively. The increased regions influenced by precipitation were mainly in dry areas especially for the boreal and cool temperate climate zones, while increased regions influenced by solar radiation were primarily located in moist areas of mid-high latitudes of the Northern Hemisphere. By introducing the cumulative climate effect, our findings highlight seasonal patterns of vegetation growth affected by climate variability and the VGC effect. The results provide a more comprehensive perspective on climate-vegetation interactions, which may help us to accurately forecast future vegetation growth under accelerating global warming.

Shifting in the global flood timing.

Climate change will have an impact on not only flood magnitude but also on flood timing. This paper studies the shifting in flood timing at 6167 gauging stations from 1970 to 2010, globally. The shift in flood timing and its relationship with three influential factors (maximum 7-day precipitation, soil moisture excess, and snowmelt) are investigated. There is a clear global pattern in the mean flooding date: winter (Dec-Feb) across the western Coastal America, western Europe and the Mediterranean region, summer (Jun-Aug) in the north America, the Alps, Indian Peninsula, central Asia, Japan, and austral summer (Dec-Feb) in south Africa and north Australia area. The shift in flood timing has a trend from - 22 days per decade (earlier) to 28 days per decade (delayed). Earlier floods were found extensively in the north America, Europe and northeast Australia while delayed floods were prevailing in the Amazon, Cerrado, south Africa, India and Japan. Earlier flood timing in the north America and Europe was caused by earlier snowmelt while delayed extreme soil moisture excess and precipitation have jointly led to delayed floods around the monsoon zone, including south Africa, India and Japan. This study provides an insight on the shifting mechanism of flood timing, and supports decisions on the global flood mitigation and the impact from future climate change.

Impacts of climate change and evapotranspiration on shrinkage of Aral Sea.

The massive desiccation of the Aral Sea, the fourth largest lake in the world, has led to severe ecological problems, expansion of cropland was thought to be the main factor driving that shrinkage. But this study performed a long-term land cover and use change assessment for Aral Sea Basin (ASB) to show that the cropland has stopped expanding in 2000, of which the cropland in the ASB plain area has decreased significantly (-140 km2/year) from 2001 to 2019. By contrast, this study finds the hydrological cycle in the ASB has intensified through a spatial and temporal scale approach based on Earth observation. Specifically, there is a 7.21 % (+304.56 × 108 m3) increase in annual total precipitation and a 10.13 % (+376.21 × 108 m3) increase in annual total actual evapotranspiration (AET) for the whole ASB during 1980-2019. In particular, the total annual AET in the ASB plain area has increased by 37.81 % (+718.92 × 108 m3), which almost depletes the water that should have flowed into the Aral Sea. Therefore, the Aral Sea shrank by 5625 × 108 m3 (or 42,944.32km2) from 1980 to 2019. Changing climate and increasing AET have accelerated the desiccation of the Aral Sea, and the expansion of cropland is no longer the main factor of that shrinkage. After more water was conserved in the ASB plain area, evapotranspiration plays a more vital role in the Aral Sea shrinkage. Reducing AET and unproductive water losses are key initiatives in future projects to save the Aral Sea. This study explores the causes of Aral Sea shrinkage from an integrated perspective of climate-land-water-ecological change across the ASB, bridging the limitations of previous studies that have focused on Aral Sea waters and subbasins.

An analysis of the public perception of flood risk on the Belgian coast.

In recent years, perception of flood risks has become an important topic to policy makers concerned with risk management and safety issues. Knowledge of the public risk perception is considered a crucial aspect in modern flood risk management as it steers the development of effective and efficient flood mitigation strategies. This study aimed at gaining insight into the perception of flood risks along the Belgian coast. Given the importance of the tourism industry on the Belgian coast, the survey considered both inhabitants and residential tourists. Based on actual expert's risk assessments, a high and a low risk area were selected for the study. Risk perception was assessed on the basis of scaled items regarding storm surges and coastal flood risks. In addition, various personal and residence characteristics were measured. Using multiple regression analysis, risk perception was found to be primarily influenced by actual flood risk estimates, age, gender, and experience with previous flood hazards.