Significant Seasonal Differences Research Articles

Numerical Simulation Study on Interactions between the Wave and Newborn Sandbank in the Xisha Islands of the South China Sea

As a unique landform in the island and reef area, the newborn sandbank is not only the initial stage of island development, but also has a rapid evolution and a complex dynamic mechanism. However, the dynamic geomorphology mechanism of the newborn sandbank is still lacking extensive study and direct evidence of the interaction process between the marine dynamics and the newborn sandbank geomorphology. Therefore, in order to reveal the interaction mechanisms between marine dynamics and newborn sandbanks, a newborn sandbank in the sea area of the Xisha Islands, in the South China Sea, has been selected as the focus of this research. The method of numerical simulation was used to discuss and analyze the wave field characteristics around the newborn sandbank and their impacts on the sandbank’s migration and development. The results show that: (1) The islands and reefs have significant refraction, diffraction, and energy dissipation effects on waves, and the newborn sandbank has the same effect, but with a weaker function. The wave height around the reef islands reduced by approximately 60–67% in dominated and strong wave directions. At the same time, the wave height attenuation in the wave shadow zone, behind the newborn sandbank, can reach approximately 27–33%. (2) Wind is important for the evolution of wave fields; in particular, when the wind speed exceeds grades four and five, the effect of the wind on the waves is particularly significant, causing the winds to control the wave characteristics around the islands and newborn sandbanks. This results in significant seasonal differences in wave fields within the sea area. (3) The wave direction primarily controls the migration direction of the newborn sandbank, and the wave height primarily controls the migration speed and distance. After one month of wave action in the strong wave direction, the maximum eastward deposition length was approximately 50 m. After one month of wave action in the dominated wave direction, the maximum eastward deposition length was approximately 60 m. Therefore, the topography of the newborn sandbank affects the wave propagation, meanwhile, the wave conversely determines migration and development of the newborn sandbank in a short term. The dynamic geomorphology action between the wave and newborn sandbank is a fast two-way process, and occurs not only during storms or the winter monsoon, but also during other, more common, weather events.

Addressing the challenge of marine plastic litter in the Moroccan Mediterranean: A citizen science project with schoolchildren.

In this study, based on data collected by citizen science, we studied the abundance, spatial and temporal distribution of marine litter in three beaches of the Moroccan Mediterranean. A total of 14,042 litter items were collected with an average abundance of 0.58 items/m2. The most of litter were composed of anthropic polymeric materials, representing 74% of the total litter collected. Plastics account for the majority of the items collected and are mainly caps/lids, crisp/sweet packets, plastic/polystyrene, cigarette butts and small plastic bags. Litter abundance displayed significant seasonal differences, with the highest during summer. Tourism and poor waste management practices are the major sources of plastic on the beaches surveyed. The use of the Clean Coast Index (CCI) and the Plastics Abundance Index (PAI) permits the classification of the three beaches in the Moroccan Mediterranean as a "moderately clean" coastal area with a "very high abundance" of plastics. In addition, the Hazardous Items Index (HII) allows classification of the region as highly polluted by hazardous litter. Best management measures are needed to promote the environmental quality of the beaches of the Moroccan Mediterranean.

Çanakkale Kıyılarında Dağılım Gösteren Holothuria (Roweothuria) poli (Delle Chiaje, 1823)'nin Besin ve Mineral Kompozisyonlarındaki Mevsimsel Değişimler

Sea cucumbers are soft-bodied echinoderms and some species are highly economic thanks to their unique biochemical compositions. Holothuria (Roweothuria) poli is an economically important species in Turkey and has been extensively exploited in the Mediterranean to meet the international market demand in the last decade. In this study, meat yield, proximate and mineral compositions of H. poli from the coasts of Çanakkale,Turkey, were investigated to determine the effect of seasons on food product quality and safety. The lowest meat yield was determined in the autumn samples, whereas the highest levels were in the samples from the spring to summer. The percent levels of moisture, protein, fat, ash, and carbohydrate levels were in the range of 80.8 - 84.0, 7.6 - 10.1, 1.4 - 1.8, 6.2 - 7.1, and 0.2 - 0.8, respectively. The levels of minerals were found in declining order; Na >Ca>Mg> K >S> P>Si> B> Mn> Zn> Fe> Cu> Hg> Pb> Sn> Se> Cr> As> Co> Sb> Ni> Cd> Pt. Apart from macro minerals, Si and B were determined as the most abundant minerals. The important minerals in human nutrition were found to be at desirable levels, whereas toxic minerals were found under the threshold levels. Our findings indicated significant seasonal differences in meat yield, proximate and mineral compositions of H. poli, but more importantly, this species tends to accumulate some minerals regardless of seasons. Further studies to better understand the optimal utilization season by determining the mineral accumulation tendency and product quality will be valuable for future research.

Seasonal variation and ecological risk assessment of Pharmaceuticals and Personal Care Products (PPCPs) in a typical semi-enclosed bay — The Bohai Bay in northern China

The Bohai Bay as a typical semi-enclosed bay in northern China with poor water exchange capacity and significant coastal urbanization, is greatly influenced by land-based inputs and human activities. As a class of pseudo-persistent organic pollutants, the spatial and temporal distribution of Pharmaceuticals and Personal Care Products (PPCPs) is particularly important to the ecological environment, and it will be imperfect to assess the ecological risk of PPCPs for the lack of systematic investigation of their distribution in different season. 14 typical PPCPs were selected to analyze the spatial and temporal distribution in the Bohai Bay by combining online solid-phase extraction (SPE) and HPLC-MS/MS techniques in this study, and their ecological risks to aquatic organisms were assessed by risk quotients (RQs) and concentration addition (CA) model. It was found that PPCPs widely presented in the Bohai Bay with significant differences of spatial and seasonal distribution. The concentrations of ∑PPCPs were higher in autumn than in summer. The distribution of individual pollutants also showed significant seasonal differences. The high values were mainly distributed in estuaries and near-shore outfalls. Mariculture activities in the northern part of the Bohai Bay made a greater contribution to the input of PPCPs. Caffeine, florfenicol, enrofloxacin and norfloxacin were the main pollutants in the Bohai Bay, with detection frequencies exceeding 80 %. The ecological risk of PPCPs to algae was significantly higher than that to invertebrates and fish. CA model indicated that the potential mixture risk of total PPCPs was not negligible, with 34 % and 88 % of stations having mixture risk in summer and autumn, respectively. The temporary stagnation of productive life caused by Covid-19 weakened the input of PPCPs to the Bohai Bay, reducing the cumulative effects of the pollutants. This study was the first full-coverage investigation of PPCPs in the Bohai Bay for different seasons, providing an important basis for the ecological risk assessment and pollution prevention of PPCPs in the bay.

Analysis of the Image of Global Glacier Tourism Destinations from the Perspective of Tourists

Glaciers are attracting increasing attention in the context of climate change, and glacier tourism has also become a popular tourist product. However, few studies have been conducted concerning the image of glacier tourism destinations. To address this gap in the literature, in this study, we extracted destination images from 138,709 visitor reviews of 107 glacier tourism destinations on TripAdvisor using latent Dirichlet allocation (LDA) topic modeling, identified destination image characteristics using salience−valence analysis (SVA), and analyzed the differences in glacier tourism destination image characteristics across seasons and regions. According to the findings, the image of a glacier tourism destination consists of 14 dimensions and 53 attributes, with landscapes and specific activities representing the core image and viewing location and necessity representing the unique image. We identified significant seasonal and regional differences in the image of glacier tourism destinations. Finally, we discussed the unique image of glacier tourism destinations, the reasons for differences in the images, and the characteristics of different glacier tourism regions. This research could assist in the scientific management of their core images by glacier tourism destinations, as well as in the rational selection of destinations and travel timing by glacier tourists.

Deformation monitoring and influence factor analysis of expressway over strong saline soil based on an advanced multi-temporal InSAR technique

Saline soil harbors crystallized salt in the solid phase and salt solution in the liquid phase. By the natural environmental and human activity factors, migration and accumulation of the salt and crystallization process alternated with dissolving, which makes saline soil with significant seasonal differences appear in the deformation and regional scattering characteristic. These phenomena raise the limitation of conventional multi-temporal interferometric synthetic aperture radar (MT-InSAR) technique and consequently high-precision deformation monitoring of strong saline soil subgrade and pavement. To overcome the limitations, this study aimed to propose an advanced MT-InSAR method, which considers the seasonal interferometric coherences caused by precipitation and the temporal physical deformation evolution of the subgrade and pavement over strong saline soil. To present the better performance of the advanced method, a segment of the Qarhan–Golmud Expressway (QGE), which is the first expressway built in the strong saline soil area in China, was selected for this study. Two sets of SAR images acquired from January 2018 to January 2022 from Sentinel-1A ascending and descending orbits over the QGE were utilized, 774 and 928 seasonal filtered interferograms are optimized for deformation monitoring based on the deformation Poisson curve (PC) model. Compared with the method in the previous studies, the accuracy, efficiency, and reliability of the monitoring results increased dramatically. Subsequently, further discussions are conducted in detail on the regularity of expressway deformation over strong saline soil, especially from physical and chemical perspectives. Findings show that the ratio between Cl− and SO42- determines the deformation distribution and morphology. Also, the precipitation and temperature affect the seasonal characteristics. The contributions of this investigation might provide technical references for related expressway management and policy-making departments to ensure the long-term safe operation and stability of the QGE.

Remote Sensing of Chlorophyll-a in Xinkai Lake Using Machine Learning and GF-6 WFV Images

Lake ecosystem eutrophication is a crucial water quality issue that can be efficiently monitored with remote sensing. GF-6 WFV with a high spatial and temporal resolution provides a comprehensive record of the dynamic changes in water quality parameters in a lake. In this study, based on GF-6 WFV images and the field sampling data of Xingkai Lake from 2020 to 2021, the accuracy of three machine learning models (RF: random forest; SVR: support vector regression; and BPNN: back propagation neural network) was compared by considering 11 combinations of surface reflectance in different wavebands as input variables for machine learning. We mapped the spatiotemporal variations of Chl-a concentrations in Xingkai Lake from 20192021 and integrated machine learning algorithms to demonstrate that RF obtained a better degree of derived-fitting (Calibration: N = 82, RMSE = 0.82 μg/L, MAE = 0.57 μg/L, slope = 0.94, and R2 = 0.98; Validation: N = 40, RMSE = 2.12 μg/L, MAE = 1.58 μg/L, slope = 0.91, R2 = 0.89, and RPD = 2.98). The interannual variation from 2019 to 2021 showed that the Chl-a concentration in Xingkai Lake was low from June to July, while maximum values were observed from October to November, thus showing significant seasonal differences. Spatial distribution showed that Chl-a concentrations were higher in Xiao Xingkai Lake than in Da Xingkai Lake. Nutrient inputs (N, P) and other environmental factors such as high temperature could have an impact on the spatial and temporal distribution characteristics of Chl-a, therefore, combining GF-6 WFV satellite images with RF could realize large-scale monitoring and be more effective. Our results showed that remote-sensing-based machine learning algorithms provided an effective method to monitor lake eutrophication as well as technical support and methodological reference for inland lake water quality parameter inversion.

Spectral Light Absorption Coefficient of Particles and Colored Dissolved Organic Matter in the Sea of Azov

The research was carried out based on the results of measuring the concentration of chlorophyll-a (TChl-a), spectral coefficient of light absorption by phytoplankton, non-algal particles (NAP) and colored dissolved organic matter (CDOM) in the southern part of the Sea of Azov in different seasons from 2016 to 2020. New data for the Sea of Azov on the variability of the spectral coefficient of light absorption by all optically active components have been obtained. A high (more than an order of magnitude) variability of all studied parameters was shown. The seasonal dynamics of TChl-a shows maxima in winter and summer. A relationship between the phytoplankton absorption and TChl-a has been revealed, which is described by a power function. Significant seasonal differences (two or more times) between the coefficients in the equation for parametrization of light absorption by phytoplankton were revealed. The NAP and CDOM light absorption were parametrized, the ranges of variability of the absorption coefficient and the exponential slope were revealed, and their seasonal dynamics was shown. Annual variability of absorption coefficient of NAP and CDOM was opposite to the annual cycle of TChl-a. The NAP and CDOM absorption coefficients increased after phytoplankton blooms, when TChl-a decreased. The relative contribution of phytoplankton, NAP, and CDOM to the total absorption by particles and dissolved matter at 440 nm varied significantly over the year. The share of phytoplankton was maximum in winter and summer, while in spring and autumn the maximum contribution to absorption was made by CDOM and NAP.

Spatiotemporal Evolution of NPP in Sandy Land of China's Seasonal Freezing-Thawing Typical Region

Based on the data set of AVHRR GIMMS, TERRA/AQUA MODIS NDVI, and climate data from 1982 to 2018, CASA model, GIS spatial analysis, and mathematical statistics were used to study the changing law in the category of time and space, spatial distribution, and the correlativity between the NPP and meteorological factors in the sandy land of China's Seasonal Freezing-Thawing Typical Region. The results showed that the average annual NPP value of vegetation in the growing season of the sandy land from 1982 to 2018 fluctuated between 217.65-356.61 gC/m2a, showing an obvious seasonality and a significant increase. The spatial distribution of NPP in the sandy land in the near 37a is significantly different. There are significant seasonal differences in vegetation responses to temperature, precipitation, wind speed, evaporation, and other meteorological factors in different regions. The increase of vegetation cover in sandy land of China's Seasonal Freezing-Thawing Typical Region is controlled by regional atmospheric circulation and human dynamics.

Season-Invariant GNSS-Denied Visual Localization for UAVs

Localization without Global Navigation Satellite Systems (GNSS) is a critical functionality in autonomous operations of unmanned aerial vehicles (UAVs). Vision-based localization on a known map can be an effective solution, but it is burdened by two main problems: places have different appearance depending on weather and season, and the perspective discrepancy between the UAV camera image and the map make matching hard. In this work, we propose a localization solution relying on matching of UAV camera images to georeferenced orthophotos with a trained convolutional neural network model that is invariant to significant seasonal appearance difference (winter-summer) between the camera image and map. We compare the convergence speed and localization accuracy of our solution to six reference methods. The results show major improvements with respect to reference methods, especially under high seasonal variation. We finally demonstrate the ability of the method to successfully localize a real UAV, showing that the proposed method is robust to perspective changes.

Impact of Environmental Conditions and Seasonality on Ecosystem Transpiration and Evapotranspiration Partitioning (T/ET Ratio) of Pure European Beech Forest

Partitioning of evapotranspiration (ET) into transpiration (T) and residual evaporation (E) is a challenging but important task in order to assess the dynamics of increasingly scarce water resources in forest ecosystems. The T/ET ratio has been linked to the ecosystem water use efficiency of temperate forests, and thus is an important index for understanding utilization of water resources under global climate change. We used concurrent sap flow and eddy-covariance measurements to quantify the ET partitioning in pure European beech forest during the 2019–2020 period. The sap flow data were upscaled to stand level T and combined with stand level ET to calculate the T/ET ratio. We analysed intra-annual dynamics, the effect of seasonality and the impact of meteorological conditions on T, ET and T/ET. Annual T/ET of a pure European beech ecosystem was 0.48, falling at the lower end of reported global T/ET values for forest ecosystems. T/ET showed significant seasonal differences throughout spring (T/ET = 0.28), summer (T/ET = 0.62) and autumn (T/ET = 0.35). Air temperature (R2 = 0.45–0.63), VPD (R2 = 0.47–0.6) and PAR (R2 = 0.32–0.63) affected the daily dynamics of T, ET and T/ET; however, soil water content (SWC) had no significant effect. Mature European beech trees showed more anisohydric behaviour and relatively stable T/ET, even under decreasing SWC. The results improve the understanding of ecosystem scale T, ET and T/ET intra-annual dynamics and environmental constraints in anisohydric mature European beech.

Analysis and Prediction of Wind Speed Effects in East Asia and the Western Pacific Based on Multi-Source Data

With the increasing problem of global warming caused by the massive use of fossil fuels, biomass energy as a renewable energy source has attracted widespread attention throughout the globe. In this paper, we analyzed the spatial and temporal variation in wind energy in the East Asia and Western Pacific areas using IGRA site data, ERA5, and NCEP/NCAR reanalysis data from 2000 to 2021, and multi-variate empirical orthogonal function (MV-EOF) decomposition with the Pettitt mutation test, and the seasonal autoregression integrated moving average (SARIMA) model was used to predict the trend of wind speed. The spatial and temporal variations in wind energy in East Asia and Western Pacific areas were analyzed, and it was found that the richer wind-energy resources were mainly concentrated in the “Three Norths” (North China, Northwest China, and Northeast China) and Mongolia, followed by the Western Pacific areas. In addition, the T’ai-hang Mountains and the Qinghai-Tibet Plateau in China block the wind resources in the eastern and southern regions of East Asia, resulting in a shortage of wind resources in this region. In addition, the summer wind speed is significantly lower than in the other three seasons. The first-mode contributions of the MV-EOF wind field and geopotential heights, respectively, are 29.47% and 37.75%. The results show that: (1) There are significant seasonal differences in wind-energy resources in the study area, with the lowest wind speed in summer and the highest wind speed in winter. (2) The wind energy in the study area has significant regional characteristics. For example, China’s Qinghai-Tibet Plateau, Inner Mongolia, Xinjiang region, and Mongolia are rich in wind-energy resources. (3) Wind-energy resources in the study area have gradually increased since 2010, mainly due to changes in large-scale oceanic and atmospheric circulation patterns caused by global warming.

Assessing the indoor air quality and their predictor variable in 21 home offices during the Covid-19 pandemic in Norway

In this study, concentrations of pollutants: formaldehyde, carbon dioxide (CO2), and total volatile organic compounds (TVOC) and parameters: indoor room temperature and relative humidity (RH) were measured in 21 home offices for at least one week in winter in Trondheim, Norway. Eleven of these were measured again for the same duration in summer. Potentially explanatory variables of these parameters were collected, including building and renovation year, house type, building location, trickle vent status, occupancy, wood stove, floor material, pets, RH, and air temperature.The association between indoor air pollutants and their potential predictor variables was analyzed using generalized estimation equations to determine the significant parameters to control pollutants. Significantly seasonal differences in concentrations were observed for CO2 and formaldehyde, while no significant seasonal difference was observed for TVOC. For TVOC and formaldehyde, trickle vent, RH, and air temperature were among the most important predictor variables. Although higher concentrations of CO2 were measured in cases where the trickle vent was closed, the most important predictor variables for CO2 were season, RH, and indoor air temperature.The formaldehyde concentrations were higher outside working hours but mostly below health thresholds recommendations; for CO2, 11 of the measured cases had indoor concentrations exceeding 1000 ppm in 10% of the measured time. For TVOC, the concentrations were above the recommended values by WHO in 73% of the cases. RH was generally low in winter. The temperature was generally kept over the recommended level of 22–24 °C during working hours.

Long-Term Monitoring of the Seasonal Abundance of Basidiobolus spp. in Gecko Feces in KwaZulu-Natal (South Africa).

The fungal genus Basidiobolus is typically associated with ectothermic animals such as amphibians and reptiles. In rare cases, it can cause infections in humans, which are often misdiagnosed. Although usually restricted to tropical and subtropical countries, infections have recently been more frequently reported in hot-dry regions such as Arizona and Saudi Arabia. Reptiles such as geckos are known to shed Basidiobolus spp. via feces and frequently live in close proximity to humans. To establish the frequency and burden of Basidiobolus spp. released by geckos in a suburban location, we regularly quantified viable Basidiobolus units per gram of feces from indoors and outdoors over 3.5 years between 2018 and 2022 using a selective medium. Geckos were shedding Basidiobolus spp. in all seasons, with most counts established ranging between 5.0 and 6.5 log10 cfu per gram. Statistically significant seasonal differences per location were only observed for the outside winter counts and, apparently, correlated to lower temperatures, while inside counts showed no seasonal difference. Overall, counts for droppings collected outdoors were significantly higher than counts for droppings collected indoors. Our data confirm that geckos, which frequently enter homes and are global invaders, are a regular source of this fungus.

Analysis of Atmospheric Pollutants and Meteorological Factors on PM2.5 Concentration and Temporal Variations in Harbin

With rapid economic development, the problem of air pollution has become increasingly prominent. Countries have paid attention to PM2.5, one of the main air pollutants, and have gradually addressed this issue. Based on the 2015–2019 air quality data, meteorological data, and aerosol optical depth data from Harbin, China, this study investigated the relationship between PM2.5, a number of influencing factors, and their temporal changes using a machine-learning method. It can be seen from the analysis that the random forest model can predict PM2.5 concentration. In this model, the mean RH and AOD have a high impact on PM2.5 concentration, but there was negligent correlation with PM2.5. The results indicated that the level of PM2.5 pollution continuously decreased from 2015 to 2019, and there were significant seasonal differences in PM2.5 concentration and its variations. In 2019, due to the impact of heating and adverse meteorological conditions, PM2.5 pollution during the heating period increased significantly. This study provides theoretical and data support for the analysis of PM2.5 pollution in Harbin and formulation of air pollution control policies.

Optical properties and potential sources of water-soluble and methanol-soluble organic aerosols in Taipei, Taiwan

The optical properties and sources of brown carbon (BrC) have been poorly constrained in climate models due to the variability of spatiotemporal characteristics, impeding the accurate understanding of its impact on air quality and climate. In this study, daily PM2.5 samples, which were collected from January to November 2021 in urban Taipei, Taiwan, and seasonal variations of optical properties of water-soluble and methanol-soluble organic carbon (WSOC and MSOC) were evaluated. The light absorption coefficients at 365 nm (Abs365) of both extracts, which strongly correlated with WSOC and MSOC mass concentrations, displayed distinct seasonal variations with the highest in winter and the lowest in summer. The Absorption Ångström Exponent of WSOC and MSOC ranged from 4.16 to 7.75 and 4.03–6.83, with averages of 6.05 ± 0.56 and 5.29 ± 0.61, respectively. The mass absorption efficiency (MAE365), which normalizes the Abs365 of both extracts to the mass of WSOC and MSOC, showed significant seasonal difference with the high MAE365, WSOC of 0.96 ± 0.29 m2 g−1 in winter and the lowest in summer of 0.49 ± 0.07 m2 g−1, whereas contrasting with the largest MAE365, MSOC of 0.99 ± 0.46 m2 g−1 in summer and the lowest in winter of 0.66 ± 0.28 m2 g−1, respectively. Fossil fuel combustion, such as traffic emission, and biomass burning, such as crematorium, were identified to be important contributors to light-absorbing substances. The estimated fractional radiative forcing by WSOC and MSOC to elemental carbon was most significant during winter (8.15 ± 3.77%) and spring (13.90 ± 4.38%), respectively, which may greatly affect the atmospheric photochemistry and climate. This study suggests that the impact of BrC in Taiwan on the local and regional air quality and climate is non-negligible.

Experimental Study on the Impact of Seasonal Sound Speed Variability on Signal Detection Range in Arabian Sea


 
 
 Temporal variability of Signal Detection Range (SDR) with respect to measured noise level and sound speed is examined. An N x 2D acoustic model which included bathymetric variations, was used to study detection ranges for an area in Arabian Sea. Azimuthal and seasonal SDR at octave bands within 500 Hz were determined at different receiver depths. Study shows that seasonal change in sound speed profile resulted in high SDR and noise level in winter at the location. Study also confirms the significant seasonal difference in detection range corresponds to the cut off frequency at 160 Hz. Detection range for a receiver at a depth 40 m is observed to be high across the azimuth and seasons of study.
 
 

Sources and distribution of microplastics in the east China sea under a three-dimensional numerical modelling

Microplastics are new pollutants found in various environments; moreover, high concentrations of microplastics have been proved to harm aquatic organisms. To understand the high abundance of microplastics in the East China Sea (ECS), where the Zhoushan fishing ground is located, this study investigated the transportation and spatial distribution of microplastics from the Changjiang River Estuary (CE) to the ECS via three-dimensional numerical modelling. Utilising observations of microplastics at the surface of the ECS and backward particle tracking, three sources of microplastics were identified: the Changjiang River, Hangzhou Bay, and coastal area of Nantong city. Moreover, Southern Korea contributed to the microplastics in ECS. After microplastics are released from these sources, monsoons, currents, the Changjiang plume, and tides cause significant seasonal differences in the hot spots for microplastics in the ECS; moreover, the generation of ocean fronts may promote microplastic accumulation. In addition, the settling characteristics of microplastics were shown to influence their distributions; for example, large amounts of microplastics accumulated at the bottom of the riverbeds. This study enables a more complete assessment of microplastic transport from estuaries to the open sea and provides a spatial and temporal distribution of microplastics at the surface of the ECS.

Effects of land use, meteorology, and hydrology on nutrients, biochemical indexes, and heavy metals in Qingjiang River Basin, China

Land use, meteorology, and hydrology can critically influence the water quality in rivers. However, few studies have comprehensively assessed the influences of these factors on nutrients, biochemical indexes, and heavy metals. In this study, water samples were collected monthly from 10 sampling sites in a headwater region of Qingjiang River Basin from 2016 to 2020. Nutrients, biochemical indexes, and heavy metals were analyzed to explore their spatial-temporal distributions, identify the significance of pollution types, and study the effects of land use, meteorology, and hydrology on water quality. The results indicated that there were significant spatial differences for nutrients and biochemical indexes, while significant seasonal differences for heavy metals in the study area. The seasonal Manne-Kendall test suggested there were increasing trends of nutrients, while relatively stable trends of biochemical indexes and decreasing trends of heavy metals during the study period. The principal component analysis showed nutrients were the key pollution type in urban areas, while biochemical indexes were the key pollution type near the dam. The redundant analysis indicated that explained rates of land use compositions on the water quality were in the order: riparian buffer zones > sub-watershed zones > upstream circle buffer zones > Thiessen polygons zones. The explained rates were larger during the wet season than the dry season except for upstream circle buffer zones, which might be the result of diverse influences of the precipitation on different land use types. The classification and regression tree model showed nutrients were more affected by urban compositions, and biochemical indexes were influenced by both the precipitation and agriculture compositions. The nonparametric change point analysis further indicated total nitrogen, total phosphorus, and potassium permanganate index would increase abruptly when urban compositions were above 3.7%, 9.94%, and agriculture compositions were above 36.55% respectively at the 900 m riparian buffer zone. Cu, Pb, and As, however, were more associated with the precipitation, and they might decrease abruptly when the precipitation was above 4.68 mm. The results highlighted the inconsistent role of land use, meteorology, and hydrology on different water quality indexes, which can provide the scientific basis for the management of the water environment in rivers.

Climate change impacts on irrigated crops in Cambodia

Increasing heat-stress conditions, rising evaporative demand and shifting rainfall patterns may have multifaceted impacts on Cambodia's agricultural systems, including vegetable production. Concurrently, domestic vegetable supply is highly seasonal and inadequate to meet the domestic food demand, which consequently poses risks to food security locally, particularly in rural areas. This study assesses the impact of climate change on the yields and crop water productivity (CWP) of tomato, pak choi and yard-long bean cultivated year-round under different irrigated conditions (drip, furrow and net irrigation) in Siem Reap, Cambodia. The findings of this study show a similar annual precipitation decline (-23%) when comparing the 2017–2040 and 2070–2099 periods for both Representative Concentration Pathways (RCPs 4.5 and 8.5), though with significant seasonal differences between the two climate scenarios. Increasing water and heat-stress conditions are expected to have adverse impacts on tomato plants compared to pak choi and yard-long bean, which have a much higher heat tolerance. Differing yield trends are expected depending on the transplanting/sowing date, irrigation method and RCP. In tomato, for example, a -55% yield loss is projected by the end-century (2070–2099) when transplanting in January, whereas a + 37% yield increase is expected between November and December over the same period. In addition, pak choi yield enhancements of up to +30% are projected if sowing in May under RCP 8.5 for both drip and net irrigation conditions. Similarly, higher yard-long bean yields are simulated under RCP 8.5 (+29%) compared to RCP 4.5 (+11%) for the average of all sowing dates (January to December) and irrigation methods (drip, furrow and net irrigation). In sum, the findings of this work are relevant for evidence-based decision-making and the development of projects, policies and programmes increasingly informed by simulation results from bundling climate-crop approaches to transform agriculture in response to climate change.