Interannual Changes Research Articles

A novel coupled algorithm-based method, and the characteristics and driving mechanism of water shortage in the upper Yellow River

ABSTRACT Gaining a clear understanding of the spatiotemporal characteristics of water shortage and their driving mechanism in the upper Yellow River (UYR) is crucial for the assessment and effective management of water resources in the region. The standardized streamflow index (SSI) and the improved Hilbert-Huang transform (IHHT) algorithm are combined to form a coupled SSI-IHHT method (CSIHM). The streamflow above Lanzhou Station over 1969–2015 is analysed. Results show that summer and autumn are high-risk periods of continuous water shortage. Annual streamflow has inter-annual change cycles of 3.5–9.0 a and inter-decadal change cycles between 16.4 and 28.2 a. The annual streamflow change is mainly affected by climate change. But the seasonal streamflow change is mainly influenced by human activities resulting from the operation of reservoirs. The CSIHM has advantages of mutual verification of the results and wide applicability to the field of water shortage.

Modeled variations in the inherent optical properties of summer Arctic ice and their effects on the radiation budget: a case based on ice cores from 2008 to 2016

Abstract. Variations in Arctic sea ice are apparent not only in its extent and thickness but also in its internal properties under global warming. The microstructure of summer Arctic sea ice changes due to varying external forces, ice age, and extended melting seasons, which affect its optical properties. Sea ice cores sampled in the Pacific sector of the Arctic obtained by the Chinese National Arctic Research Expedition (CHINARE) during the summers of 2008 to 2016 were used to estimate the variations in the microstructures and inherent optical properties (IOPs) of ice and determine the radiation budget of sea ice based on a radiative transfer model. The variations in the volume fraction of gas bubbles (Va) of the ice top layer were not significant, and the Va of the ice interior layer was significant. Compared with 2008, the mean Va of interior ice in 2016 decreased by 9.1 %. Meanwhile, the volume fraction of brine pockets increased clearly during 2008–2016. The changing microstructure resulted in the scattering coefficient of the interior ice decreasing by 38.4 % from 2008 to 2016, while no clear variations can be seen in the scattering coefficient of the ice top layer. These estimated ice IOPs fell within the range of other observations. Furthermore, we found that variations in interior ice were significantly related to the interannual changes in ice ages. At the Arctic basin scale, the changing IOPs of interior ice greatly changed the amount of solar radiation transmitted to the upper ocean even when a constant ice thickness is assumed, especially for thin ice in marginal zones, implying the presence of different sea ice bottom melt processes. These findings revealed the important role of the changing microstructure and IOPs of ice in affecting the radiation transfer of Arctic sea ice.

Phytoplankton spring bloom in the NW Mediterranean Sea under climate change

The spring phytoplankton bloom is the main event influencing ecosystem richness in the pelagic realm of the Northwestern Mediterranean Sea (NW Med Sea). The Marine Strategy Framework Directive requires the achievement of a good ecological status for the pelagic habitat, and phytoplankton bloom phenology has been used as an indicator of the status of offshore waters. In this work we investigate interannual changes in the timing and magnitude of the phytoplankton bloom in the NW Med Sea, using phenological metrics. Daily maps of Chl-a concentration from 1998 to 2022 obtained by CMEMS were used to analyse bloom phenological metrics in 5 representative sites in the area. Chlorophyll-a data from 1998 to 2007 were used for determining the climatological behaviour, while 2008–2022 was identified as the study period. For this latter period, yearly spring bloom were identified and interannual variability and overall trends were analysed for each of the phenological metrics considered. Winter oceanographic and meteorological data were analysed to investigate possible correlations with the subsequent spring bloom. The frequency of anomalous years is increasing, both for bloom intensity and sea temperature. Bloom analysis revealed a negative trend only in some areas, but a steep decrease in the last 7 years was noticeable for all sites considered. Correlations of the Chl-a concentration during bloom with oceanographic variables revealed the importance of temperature, both marine and atmospheric, while Mixed Layer Depth played a lesser role. This work contributes to a better understanding of the dynamics of an area already under severe threat from human activities.

Asynchronous changes in terrestrial near-surface wind speed among regions across China from 1973 to 2017

Understanding the characteristics and causes of asynchronous changes in near-surface wind speed (NSWS) improves the ability of climate projection, but yet to be comprehended are the asynchronous features in NSWS and possible causes over China. In this study, the asynchronous variations in NSWS among regions are considerable across China. The non-synchronization of variations in intra-annual NSWS was manifested in the amplitudes and periods of NSWS. The amplitudes and periods of intra-annual NSWS among regions were in the ranges of 0.08–0.20 m s−1 and 0.24–0.32 years, respectively. The intra-annual changes in NSWS in different regions were influenced by different large–scale ocean–atmosphere circulations (LOACs). The non-synchronization of variations in interannual NSWS was also manifested in the amplitudes and periods of NSWS, and the strongest and weakest interannual variations in NSWS occurred over northeast and northwest China. The interannual variations in NSWS could be induced by El Niño–Southern Oscillation (ENSO). At intra-annual and interannual scales, LOACs mainly controlled the changes in the phase of NSWS, which could not be responsible for the amplitudes of NSWS. The interdecadal NSWS also showed regional differences, and it mainly exhibited an increase after the 1990s in all regions except for South China. The interdecadal changes in NSWS among regions were also dominated by LOACs, which contributed reached 50.0% to the NSWS changes. Furthermore, the LOACs dominated not only the changes in the phase of interdecadal NSWS but also the changes in amplitudes of interdecadal NSWS.

The spatiotemporal variation characteristics of extreme temperature events in the Liaohe River Basin from 1961 to 2020

In recent years, China has frequently experienced extreme climate events. Analyzing the trends in these extreme weather changes is crucial to mitigating the adverse impacts on human lives and preventing the disruption of water resource distribution. Based on the daily maximum and daily minimum temperatures at 139 meteorological grid points in the Liaohe River Basin from 1961 to 2020, six extreme temperature indices were calculated and selected to explore the temporal and spatial characteristics of the extreme temperature events in the Liaohe River Basin by using the linear trend analysis, the Mann-Kendall (M-K) mutation test, and the Kriging interpolation method. The results show that the index characterizing extreme warm events in the Liaohe River Basin in time shows a significant upward trend on both interannual and seasonal scales, while the index characterizing extreme cold events shows a significant downward trend. The mutation points of interannual changes were mainly distributed between 1980 and 2010. In the spatial distribution, the Liaohe River Basin as a whole is warming, and the northern part is warming more than the southern part.

Research on tourism ecological safety evaluation of Huizhou Cultural and ecological reserve based on entropy -TOPSIS

Tourism ecological security is the basic guarantee for the sustainable development of tourist sites, Huizhou Cultural and Ecological Reserve is an important area for the im-plementation of ecological protection in China, and it is of great significance to carry out research on tourism ecological security. The study adopted the DPSIR model to construct a comprehensive evaluation index system for tourism ecological security and used entropy value-TOPSIS and ArcGIS software to analyze the inter-annual changes and spatial change characteristics of tourism ecological security in the study area. The results show that: firstly, the comprehensive index of tourism ecological safety in the study area from 2010 to 2021 shows a trend of “decreasing-increasing" and an overall increasing trend; secondly, all the sub-systems show an increasing or stabilizing state in recent years during 2010–2021; the state and response sub-systems show an increas-ing or stabilizing state in recent years; and the state and response sub-systems show an increasing trend in recent years. Secondly, all the subsystems showed an increase or stabilization in recent years between 2010 and 2021, and the state and response sub-systems are the main systems to improve the ecological safety of tourism in the study area; thirdly, the difference in the level of ecological safety of tourism in each county of the study area increased and then narrowed from 2010 to 2021, and the change of safety level usually shifted between neighboring levels, and the probability of transfer-ring across the levels was relatively small. , Shexian County, Yixian County, Qimen County, Tunxi District, and the tourism eco-safety level of Huangshan District, Hui-zhou District, Jixi County, and Xiuning County increased at a faster rate than other counties. The study further extends the scale to the district and county level, tries to explore the relevant factors affecting the ecological security of tourism, and proposes countermeasures for the sustainable development of the study area based on the re-sults, which will bring some reference value to the ecological governance and policy formulation of this kind of research.

The Impact of Groundwater Burial Depth on the Vegetation of the Dariyabui Oasis in the Central Desert

Vegetation and groundwater are important components of the ecological environment of oases in desert hinterlands and their relationship is crucial to ecosystem stability. In this study, Sentinel-2 data for 2016–2022 and measured groundwater burial depths were analysed for the Dariyabui Oasis in the hinterland of the Taklamakan Desert. The spatial and temporal changes in vegetation and groundwater burial depth from 2019 to 2022 were analysed based on the image–element dichotomous model of the normalised difference vegetation index, utilising the inverse distance weight interpolation method, cubic curve regression, image–element difference, slope trend analysis, and the Markov transfer matrix for determining the temporal and spatial response law between the two. Finally, the threshold value of groundwater burial depth for different vegetation cover types was clarified. The fractional vegetation cover of the Dariyabui Oasis showed a slight increase from 2016 to 2022. Vegetation in the northwest and southeast of the oasis increased, whereas vegetation decreased in the mid-north and northeast regions; 5.14% of the total area experienced increased coverage, whereas 3.35% experienced decreased coverage. The depth of groundwater in the oasis showed a pattern of gradual increase from the entrance to the end of the oasis, that is, south to north. The depth of groundwater in the oasis from 2019 to 2022 was stable, with a 4-year average depth of 4.1069 m and a maximum fluctuation of 0.4560 m. The interannual changes in the groundwater level showed an increasing trend in January–April, while groundwater levels showed a decreasing trend in May–July and August–October and remained constant in June–July and October–December. Oasis vegetation cover showed a negative correlation with groundwater depth, with a depth interval for the highest low-cover vegetation distribution of 3–6 m, and an ultimate depth threshold of 7 m. The depth interval with the highest medium-cover vegetation distribution was 3–4 m, that with the highest high-cover distribution was 2–4 m, and the ultimate depth threshold was 6 m. The depth of the oasis ranged from 3 to 6 m and the ultimate depth threshold was 7 m.

An ARGO and XBT Observing System for the Atlantic Meridional Overturning Circulation and Meridional Heat Transport (AXMOC) at 22.5°S

AbstractChanges in the Atlantic Meridional Overturning Circulation (AMOC) and associated Meridional Heat Transport (MHT) can affect climate and weather patterns, regional sea levels, and ecosystems. Direct observations of the AMOC are still limited, particularly in the South Atlantic. This study establishes a cost‐effective trans‐basin section to estimate for the first time the AMOC and MHT at 22.5°S, using only sustained ocean observations. For this, an optimal mapping method that minimizes the difference between surface in situ dynamic height and satellite altimetry was developed to retrieve monthly temperature and salinity profiles from Argo and XBT data along the 22.5°S section. The mean states, as well as the interannual and seasonal changes of the obtained AMOC and MHT were compared with other products. The mean AMOC and MHT for 22.5°S are 16.3 ± 3.2 Sv and 0.7 ± 0.2 PW, respectively, showing stronger transports during austral fall/winter and weaker in spring. The high‐density XBT data available at the western boundary were vital for capturing the highly variable Brazil Current (BC), whose mean and variability was improved compared to other products. At 22.5°S, the North Atlantic Deep Water is divided into two cores that flow along both the western and the eastern boundaries near 2,500 m depth. Our results (a) suggest a greater influence of the western boundary current system on the AMOC variability at 22.5°S, (b) highlight the importance of high‐density in situ data for AMOC estimates, and (c) contribute to a better understanding of the AMOC and MHT variability in the South Atlantic.

Analysis of the state of conservation of Trachurus trachurus in the Western Mediterranean Sea based on the interannual (2009–2020) changes in their life history traits

Horse mackerel is a semi-pelagic fish widely distributed in the eastern Atlantic, where it represents a species of interest for fisheries and is subject to intense exploitation, leading to its global classification as a vulnerable species by IUCN. In the Northwestern (NW) Mediterranean Sea, the knowledge of their distribution, abundance and main biological parameters is fundamental to achieve their sustainable exploitation and contribute to the ecosystem approach to fisheries management. The time series (2009–2020) data set analyzed in this study came from two geographical subareas (GSAs) defined by the General Fisheries Commission for the Mediterranean (GFCM), Northern Spain (GSA06) and Northern Alboran Sea (GSA01) sampled in July during the MEDiterranean International Acoustic Survey (MEDIAS). Our results suggest that in summer, a higher concentration and aggregation of fish exists in GSA01, with a density ten times greater than in GSA06. Possible life history changes can be inferred through the analysis of the biological parameters of Trachurus trachurus in the NW Mediterranean Sea. In both GSAs, the annual decline of the size at first maturity (L50) and condition factor (Kn) was prominent. Moreover, the population structure lacked adult modes that could guarantee a successful recuperation of future stocks. Nonetheless, fish inhabiting GSA01 seem to have a better adaptive response to the events responsible for these alterations. In comparison, GSA01 is under less fishing pressure and the upwelling occurring in this area contributes to a higher availability of food, in addition to reducing the increases in sea surface temperature due to climate change during the study period.

Hydrothermal Conditions in Deep Soil Layer Regulate the Interannual Change in Gross Primary Productivity in the Qilian Mountains Area, China

The variability in soil hydrothermal conditions generally contributes to the diverse distribution of vegetation cover types and growth characteristics. Previous research primarily focused on soil moisture alone or the average values of soil hydrothermal conditions in the crop root zone (0–100 cm). However, it is still unclear whether changes in gross primary productivity (GPP) depend on the hydrothermal conditions at different depths of soil layers within the root zone. In this study, the soil hydrothermal conditions from three different layers, surface layer 0–7 cm (Level 1, L1), shallow layer 7–28 cm (Level 2, L2), and deep layer 28–100 cm (Level 3, L3) in the Qilian Mountains area, northwestern China, are obtained based on ERA5-Land reanalysis data. The Sen-MK trend test, Pearson correlation analysis, and machine learning algorithm were used to explore the influence of these three soil hydrothermal layers on GPP. The results show that soil moisture values increase with soil depth, while the soil temperature values do not exhibit a stratified pattern. Furthermore, the strong correlation between GPP and deep soil hydrothermal conditions was proved, particularly in terms of soil moisture. The Random Forest feature importance extraction revealed that deep soil moisture (SM-L3) and surface soil temperature (ST-L1) are the most influential variables. It suggests that regulations of soil hydrothermal conditions on GPP may involve both linear and nonlinear effects. This study can obtain the temporal and spatial dynamics of soil hydrothermal conditions across different soil layers and explore their regulations on GPP, providing a basis for clarifying the relationship between soil and vegetation in arid mountain systems.

Fast but transient recovery of aquatic and terrestrial communities after a large dam removal

IntroductionEcological restoration through dam removals receives increasing attention from scientists, environmental managers and policy makers. However, most dam removal projects focus on small structures (< 10 m in height) and on few ecosystem compartments at a time (e.g. river morphology, reservoir sedimentation, aquatic invertebrates, terrestrial vegetation), but rarely aquatic and riparian ecosystems simultaneously.MethodsWe explored the joint taxonomic recovery (temporal patterns in α- and β-diversity) of three communities after the removal of the Vezins dam (36 m in height; Sélune River, France): aquatic benthic invertebrates, riparian invertebrates, and the riparian vegetation. These communities were monitored yearly, during three years after the dam removal, on sites located within (n = 3; restored sites) and outside (n = 3; two upstream and one downstream; non-impounded sites) the former reservoir.ResultsResults showed a fast recovery of the three ecological communities, as patterns in α-diversity between restored and non-impounded sites were not necessarily different from each other 1.5 years after complete reservoir dewatering. The mean number of species or morphospecies (± standard deviation) reached up to 28.2 ± 5.2, 17.0 ± 2.3 and 77.5 ± 11.2 for the aquatic invertebrates, and the riparian vegetation and invertebrates, respectively. Relative to the sampled area, the riparian invertebrates were the most diversified of all ecological communities with > 500 taxa (i.e., pooling all sites and years). In addition, in some restored sites, α-diversity kept increasing over time while species turnover (β-diversity) remained high after three years for all ecological communities suggesting a transient recovery (i.e., still facing temporal changes in species diversity and composition). This recovery was mediated by the identity of the ecological community as inter-annual changes in α- and β-diversity of the riparian vegetation were less pronounced compared to those of aquatic and terrestrial invertebrates. This recovery depended also on site-specific features as the most distant restored site from the former dam had more time for recovery following the slow reservoir dewatering and through increased sedimentation in the downstream site.DiscussionDifferential patterns of recovery in α- and β-diversity found in this study are discussed in light of species functional traits and ecosystem functioning.

Monitoring and understanding chlorophyll-a concentration changes in lakes in northeastern China using MERIS and OLCI satellite data

ABSTRACTLakes in the Northeast Plains-Mountain Lake Region (NPLR) of China face severe risks of eutrophication due to climate change and intensive anthropogenic pressures. As a vital indicator for eutrophication status, the dynamics of chlorophyll-a (Chl-a) concentrations in NPLR lakes were, for the first time, comprehensively investigated in this study. A support vector regression (SVR)-based model was established and applied to the MERIS (2003–2011) and OLCI (2016–2019) observations to derive a long-term Chl-a record for 33 NPLR lakes. The NPLR lakes exhibited a climatological annual mean Chl-a of 12.3 mg m−3, ranging from 6.8 to 18.6 mg m−3 among the 33 studied lakes. During the study period, 11 lakes exhibited statistically significant increases in Chl-a concentrations (p < 0.05), and 3 lakes showed significantly decreasing trends. Spatially, lakes in lowland regions had higher Chl-a than those in mountainous regions. This study quantified the relative importance of seven explanatory factors in influencing interannual Chl-a changes for each lake. Results showed statistically significant impacts of agricultural fertilizer (10 lakes), wastewater (4 lakes), runoff (7 lakes), and wind (5 lakes) in affecting the interannual variations of Chl-a. The decreases in Chl-a were primarily attributed to the reduced livestock excrement. Compared to hydro-climatic factors, anthropogenic pressures (i.e. agriculture fertilizer, livestock excrement, and wastewater discharge) had more significant impacts on the interannual variations of Chl-a, accounting for more than 50% of 18 lakes. This study enhances our understanding of the long-term Chl-a dynamics in NPLR lakes and their responses to hydro-climatic factors and anthropogenic forcing. These findings are valuable for basin-scale water environment protection and sustainable development.

Annual patterns of green tides blooms in the coastal waters of Qinhunagdao from 2018 to 2020

Green tide disasters have been occurring along the Qinhuangdao coastal area for several years since 2015. This study investigated the interannual changes of green tides in Qinhuangdao from 2018 to 2020 and found that the green algae biomass was significantly reduced in 2020. The peak biomass of the green tide in July was only 151.5 g m−3, which is significantly lower than 7789.4 g m−3 in July 2018 and 5873.9 g m−3 in July 2019. Further comparative analysis showed that the decrease in nutrients, reduction in the density of Ulva microscopic propagules, and low biomass of attached macroalgae on the seaweed beds along the Jinmenghaiwan bath coastal area were the main causes for the decrease in the scale of green tides in Qinhuangdao in 2020. This paper also summarizes the factors of green tide formation in Qinhuangdao and proposes relevant prevention and control suggestions for the local governments based on the previous research.

How did the COVID-19 pandemic affect net working capital in industrial production companies?

Industry is one of the key sectors of Slovakia's economy and accounts for approximately 22% of GDP. Industrial production accounts for an average of 85% of the industry's contribution to GDP. The period of 2020 and 2021 was a crisis for all sectors of the economy due to the announcement of the global COVID-19 pandemic. Regarding the importance of industrial production in Slovakia's economy, we examine the impact of the coronavirus crisis on a sample of companies operating in this sector. Changes in the operational activity of enterprises are directly reflected in the volume of their net working capital. The aim of the study is to research changes in the volume of net working capital of enterprises in individual branches of the manufacturing industry in Slovakia from 2017 to 2021. The Wilcoxon signed-rank test was used to examine the significance of interannual changes in this indicator. The findings point to the growth of the volume of net working capital in crisis periods in almost all branches of industrial production and confirm the increase in requirements for managing working capital in periods of economic decline.

Interannual and Interhemispheric Comparisons of Q2DW Bimodal and Unimodal Structures During the 2003–2020 Summer Period

AbstractBy analyzing Sounding of the Atmosphere using Broadband Emission Radiometry and the Modern‐Era Retrospective analysis for Research Applications Version 2 reanalysis observations from 2003 to 2020, we found that the structural variation of the westward quasi‐2‐day wave (Q2DW) is related to the mean zonal wind in the background atmosphere, and the zonal wavenumber 3 (W3) is more affected by the background atmosphere than the zonal wavenumber 4 (W4). Our study focuses on the spatial structure of ∼50–95 km and ∼50°S–50°N. The spatial structure of W3 and W4 in the Northern and Southern Hemispheres is unimodal and bimodal, while the bimodal structure of W3 in the Southern Hemisphere is more obvious in some years. In the unimodal structure, W3 has a higher (altitude) peak in the Southern Hemisphere (∼82 km) than in the Northern Hemisphere (∼70 km), while W4 peaks at ∼70 km in both hemispheres. In the bimodal structure, W3 in the Southern Hemisphere fluctuates mostly at ∼82 km, followed by ∼68 km, while W3 in the Northern Hemisphere fluctuates mostly at ∼70 km, followed by ∼82 km. The spatial structure of W4 in both hemispheres fluctuates mainly at ∼70 km, followed by ∼82 km. In addition, W3 is stronger in the Southern Hemisphere than the Northern Hemisphere, W4 is stronger in the Northern Hemisphere than the Southern Hemisphere, and peak amplitudes of both W3 and W4 are larger in a bimodal structure than unimodal structure. The diagnostic analysis shows that the interannual and interhemispheric structure changes of Q2DWs may be due to the larger mean flow instabilities, background winds, and refractive index in the mesosphere, which make the bimodal structure of W3 and W4 obtain larger energy for propagation and amplification, resulting in higher (altitude) and larger amplitudes. This indicates that the background atmosphere of the mesosphere can affect the spatial structure of Q2DWs.

Spatiotemporal Variation in Vegetation and Its Driving Mechanisms in the Southwest Alpine Canyon Area of China

The Southwest Alpine Canyon Area (SACA), a well-known ecological vulnerability region, plays a very important role in China. Identifying the driving force of the spatial heterogeneity of vegetation and the response of interannual vegetation changes to climate change and human activities would be helpful for ecosystem management. Based on the NDVI dataset, the study analyzed the trend of NDVI change from 2000 to 2019 using the Theil–Sen trend analysis and the Mann–Kendal significance test, detected the driving forces of the spatial heterogeneity of NDVI by the means of the geographical detector, and analyzed the relative contribution of climate change and human activities to interannual NDVI changes using residual analysis model. The results showed that, in terms of the spatial distribution, the pattern of NDVI showed that it is higher in the southeast and lower in the northwest region of the SACA. Elevation was the dominant factor influencing the spatial heterogeneity of NDVI, with the explanatory power of 64%, much larger than other factors, and vegetation type, temperature, precipitation, land use type, and soil type were the main factors. In addition, the explanatory power of the dual factor interaction was higher than that of the single factor effect, which showed two kinds of interaction relationships: bivariate enhancement and nonlinear enhancement. In terms of the temporal variation, 85.59% of the study area showed an increasing trend, and only 14.41% of the area showed a decreasing trend. The main factor affecting NDVI changes was human activities, and climate change was the secondary factor, with relative contributions of 71.35% and 28.65%, respectively. The study will promote a better understanding of the complex mechanisms of vegetation changes and provide scientific recommendations for the prevention of vegetation degradation and vegetation restoration in the SACA.

The link between surface and sub-surface chlorophyll-a in the centre of the Atlantic subtropical gyres: a comparison of observations and models

Satellite observations have given us a clear idea of the changes in chlorophyll in the surface ocean on both a seasonal and interannual basis, but repeated observations at depth are much rarer. The permanently-stratified subtropical gyres in the Atlantic are highly oligotrophic, with most production centred on a deep chlorophyll maximum (DCM) just above the nitracline. This study explores the variations in this feature in the core of both gyres, considering both seasonal and interannual variations, and the linkages between changes at the surface and sub-surface. The in situ observations come from the Atlantic Meridional Transect (AMT), a long-running UK monitoring programme, and also from biogeochemical Argo floats. AMT provides measurements spanning more than 25 years directed through the centres of these gyres, but samples only 2 to 4 months per year and thus cannot resolve the seasonal variations, whereas the profiling floats give coverage throughout the year, but without the rigid spatial repeatability. These observational records are contrasted with representation of the centres of the gyres in two different biogeochemical models: MEDUSA and ERSEM, thus fulfilling one of AMT’s stated aims: the assessment of biogeochemical models. Whilst the four datasets show broadly the same seasonal patterns and that the DCM shallows when surface chlorophyll increases, the depth and peak concentration of the DCM differ among datasets. For most of the datasets the column-integrated chlorophyll for both gyres is around 19 mg m-2 (with the AMT fluorescence-derived values being much lower); however the MEDUSA model has a disparity between the northern and southern gyres that is not understood. Although the seasonal increase in surface chlorophyll is tied to a commensurate decrease in concentration at depth, on an interannual basis years with enhanced surface levels of chlorophyll correspond to increases at depth. Satellite-derived observations of surface chlorophyll concentration act as a good predictor of interannual changes in DCM depth for both gyres during their autumn season, but provide less skill in spring.

Geographical characteristics and influencing factors of the influenza epidemic in Hubei, China, from 2009 to 2019.

Influenza is an acute respiratory infectious disease that commonly affects people and has an important impact on public health. Based on influenza incidence data from 103 counties in Hubei Province from 2009 to 2019, this study used time series analysis and geospatial analysis to analyze the spatial and temporal distribution characteristics of the influenza epidemic and its influencing factors. The results reveal significant spatial-temporal clustering of the influenza epidemic in Hubei Province. Influenza mainly occurs in winter and spring of each year (from December to March of the next year), with the highest incidence rate observed in 2019 and an overall upward trend in recent years. There were significant spatial and urban-rural differences in influenza prevalence in Hubei Province, with the eastern region being more seriously affected than the central and western regions, and the urban regions more seriously affected than the rural region. Hubei's influenza epidemic showed an obvious spatial agglomeration distribution from 2009 to 2019, with the strongest clustering in winter. The hot spot areas of interannual variation in influenza were mainly distributed in eastern and western Hubei, and the cold spot areas were distributed in north-central Hubei. In addition, the cold hot spot areas of influenza epidemics varied from season to season. The seasonal changes in influenza prevalence in Hubei Province are mainly governed by meteorological factors, such as temperature, sunshine, precipitation, humidity, and wind speed. Low temperature, less rain, less sunshine, low wind speed and humid weather will increase the risk of contracting influenza; the interannual changes and spatial differentiation of influenza are mainly influenced by socioeconomic factors, such as road density, number of health technicians per 1,000 population, urbanization rate and population density. The strength of influenza's influencing factors in Hubei Province exhibits significant spatial variation, but in general, the formation of spatial variation of influenza in Hubei Province is still the result of the joint action of socioeconomic factors and natural meteorological factors. Understanding the temporal and spatial distribution characteristics of influenza in Hubei Province and its influencing factors can provide a reasonable decision-making basis for influenza prevention and control and public health development in Hubei Province and can also effectively improve the scientific understanding of the public with respect to influenza and other respiratory infectious diseases to reduce the influenza incidence, which also has reference significance for the prevention and control of influenza and other respiratory infectious diseases in other countries or regions.

Study on the water-carbon coupling coordination function on the eastern edge of the Qinghai-Tibet plateau

The Qilian Mountains on the eastern edge of the Tibetan Plateau are an important ecological security barrier in northwestern China and an extremely critical water-carbon conservation area. The water and carbon cycles are closely linked, and the water-carbon coupling process has become further complicated under global climate change and through the intensification of human activities. A better understanding of the impacts and potential mechanisms of water-carbon interactions is the key to improving the efficiency of water-carbon resource utilization. To rationalize the relationship between water and carbon, we used data from statistical almanacs, land use, DEM and various climatic elements to estimate the water-carbon nutrition in the Qilian Mountains from 2000 to 2020 based on the InVEST model and the Coupled Coordination Degree Model (CCDM) and to explore the coupling mechanism of water-carbon, spatial-temporal dynamics, and the influencing factors. The results showed that: 1). the average annual water and carbon storage in the Qilian Mountains are 63.21 × 108 m3 and 77.82 × 107 t, respectively, showing a spatial distribution pattern of high in the northeast and low in the southwest. The inter-annual changes in water (y=-0.451x+968.920) and carbon (y = 0.082x-87.808) showed different trends. 2). The annual average of the water-carbon coupling coordination degree of 0.280 in the Qilian Mountains was low in general, and the trends declined over time from 0.273 in 2000 to 0.264 in 2020. However, the spatial distribution was relatively clustered, and the spatial correlation improved from 0.69 in 2000 to 0.74 in 2020. 3). Precipitation, potential evapotranspiration and temperature were important elements driving water-carbon coupling. Among them, precipitation was significantly positively correlated with water-carbon coupling (r = 0.88), and potential evapotranspiration (r=-0.56) and temperature (r=-0.39) showed significant negative correlations with water-carbon coupling. This study can provide information for management and decision-making in carbon sequestration, water resource utilization, ecological protection and climate change, and promote the study of the spatial and temporal coupling functions of water and carbon with in the Qilian Mountains. Meanwhile, this study can provide a reference for the environmental management and protection of the Qilian Mountain ecosystem.

Predictions of runoff and sediment discharge at the lower Yellow River Delta using basin irrigation data

Accurately predicting runoff (Q) and Suspended Sediment Concentration (SSC) is crucial for the environmental and geological evolution of the Yellow River Delta, a region with numerous oil fields and wetlands. However, accurate prediction of Q and SSC in the Yellow River Delta, characterized by the intricate interplay of high-frequency and low-frequency environmental factors, poses significant scientific challenges. This study introduces a novel framework focused on predicting Q and SSC exclusively using irrigation data. In this framework, Spatial Autocorrelation measures potential interactions among irrigation points, while Q-learning Swarm Optimization identifies high-impact irrigation areas. Ridge Regression (RR) is then applied to predict Q and SSC using the irrigation data. To comprehensively assess factors beyond irrigation, Empirical Mode Decomposition decomposes the residuals. The periodicity of each Intrinsic Mode Function (IMF) is ascertained using a zero-crossing method. IMF1, IMF2, and IMF3 are identified as seasonal signals, capturing the alternation between dry and rainy seasons, as well as inter-annual changes. Subsequently, Gated Recurrent Units (GRU) are further employed to extract this IMF information, expanding the dataset using bootstrap techniques. In the culmination of this research, the proposed framework emerges as an amalgamation of the RR model and the GRU models. Numerical examples substantiate the efficacy of this approach, demonstrating its ability to provide one-month ahead forecasts for Q and SSC with a Mean Absolute Percentage Error of 15% and 12%, respectively.