Characteristics and Influencing Factors of Microplastics in Snow in the Inner Mongolia Plateau, China

Microplastics(MPs;<5 mm)have become one of the most prominent global environmental pollution problems.MPs can spread to high altitudes through atmospheric transport and can be deposited by rainfall or snowfall,potentially threatening the structure and function of natural ecosystems.MPs in terrestrial and aquatic ecosystems alter the growth and functional characteristics of organisms.However,little attention has been given to the possible harm associated with MPs deposited in snow,particularly in the context of global climate warming.MPs collected from surface snow in the Inner Mongolia Plateau,China,were used for quantitative analysis and identification.The results showed that MPs were easily detected,and the related concentration was approximately(68±10)–(199±22)MPsL1 in snow samples.Fibers were the most common morphology,the polymer composition was largely varied,and the abundance and composition of MPs were linked to human activity to a great extent.High-throughput sequencing results showed that the composition and abundance of microorganisms also differed in snow samples from areas with different MP pollution characteristics,indicating a considerable difference in microbial functional diversity.MPs may have an interference effect on the individual growth and functional expression of microorganisms in snow.In addition,the results showed that functional living areas(e.g.,landfills and suburban areas)in cities play an important role in the properties of MPs.For instance,the highest abundance of MPs was found in thermal power plants,whereas the abundance of polymers per sample was significantly lower in the suburban area.The MP contaminants hidden in snow can alter microbial structure and function and are therefore a potential threat to ecosystem health.

基于River 2D模型的黄河花园口河段生态流量研究

针对目前生态流量研究方法难以充分考虑鱼类栖息地等生境因素的问题,以黄河花园口鲤鱼核心保护区为研究区域,选取黄河鲤鱼为研究物种,基于耦合水动力学模型和栖息地模型的River 2D模型确定黄河鲤鱼的生态流量,将水深和流速作为鱼类生存保护的限定性因子,采用栖息地模型模拟不同流量下对应的黄河鲤鱼的适宜栖息地面积。计算结果表明:花园口河段鲤鱼产卵期的最小生态流量为230 m^(3)/s,生长期的最小生态流量为430 m^(3)/s,越冬期的最小生态流量为150 m^(3)/s。计算结果可以为花园口核心鱼类保护区的鱼类保护以及黄河小浪底水库的生态调度提供参考。

A progress review of black carbon deposition on Arctic snow and ice and its impact on climate change

The rapid warming of the Arctic,accompanied by glacier and sea ice melt,has significant consequences for the Earth’s climate,ecosystems,and economy.Black carbon(BC)deposition on snow and ice can trigger a significant reduction in snow albedo and accelerate melting of snow and ice in the Arctic.By reviewing the published literatures over the past decades,this work provides an overview of the progress in both the measurement and modeling of BC deposition and its impact on Arctic climate change.In summary,the maximum value of BC deposition appears in the western Russian Arctic(26 ng·g^(–1)),and the minimum value appears in Greenland(3 ng·g^(–1)).BC records in the Arctic ice core already peaked in 1920s and 1970s,and shows a regional difference between Greenland and Canadian Arctic.The different temporal variations of Arctic BC ice core records in different regions are closely related to the large variability of BC emissions and transportation processes across the Arctic region.Model simulations usually underestimate the concentration of BC in snow and ice by 2–3 times,and cannot accurately reflect the seasonal and regional changes in BC deposition.Wet deposition is the main removal mechanism of BC in the Arctic,and observations show different seasonal variations in BC wet deposition in Ny-Ålesund and Barrow.This discrepancy may result from varying contributions of anthropogenic and biomass burning(BB)emissions,given the strong influence by BC from BB emissions at Barrow.Arctic BC deposition significantly influences regional climate change in the Arctic,increasing fire activities in the Arctic have made BB source of Arctic BC more crucial.On average,BC in Arctic snow and ice causes an increase of+0.17 W·m^(–2)in radiative forcing and 8 Gt·a^(–1)in runoff in Greenland.As stressed in the latest Arctic Monitoring and Assessment Programme report,reliable source information and long-term and high-resolution observations on Arctic BC deposition will be crucial for a more comprehensive understanding and a better mitigation strategy of Arctic BC.In the future,it is necessary to collect more observations on BC deposition and the corresponding physical processes(e.g.,snow/ice melting,surface energy balance)in the Arctic to provide reliable data for understanding and clarifying the mechanism of the climatic impacts of BC deposition on Arctic snow and ice.

Numerical study on local scour characteristics around submarine pipelines in the Yellow River Delta silty sandy soil under waves and currents

Due to their high reliability and cost-efficiency,submarine pipelines are widely used in offshore oil and gas resource engineering.Due to the interaction of waves,currents,seabed,and pipeline structures,the soil around submarine pipelines is prone to local scour,severely affecting their operational safety.With the Yellow River Delta as the research area and based on the renormalized group(RNG)k-εturbulence model and Stokes fifth-order wave theory,this study solves the Navier-Stokes(N-S)equation using the finite difference method.The volume of fluid(VOF)method is used to describe the fluid-free surface,and a threedimensional numerical model of currents and waves-submarine pipeline-silty sandy seabed is established.The rationality of the numerical model is verified using a self-built waveflow flume.On this basis,in this study,the local scour development and characteristics of submarine pipelines in the Yellow River Delta silty sandy seabed in the prototype environment are explored and the influence of the presence of pipelines on hydrodynamic features such as surrounding flow field,shear stress,and turbulence intensity is analyzed.The results indicate that(1)local scour around submarine pipelines can be divided into three stages:rapid scour,slow scour,and stable scour.The maximum scour depth occurs directly below the pipeline,and the shape of the scour pits is asymmetric.(2)As the water depth decreases and the pipeline suspension height increases,the scour becomes more intense.(3)When currents go through a pipeline,a clear stagnation point is formed in front of the pipeline,and the flow velocity is positively correlated with the depth of scour.This study can provide a valuable reference for the protection of submarine pipelines in this area.

Interdecadal variability of summer precipitation in the Three River Source Region: Influences of SST and zonal shifts of the East Asian subtropical westerly jet

Summer precipitation in the Three Rivers Source Region(TRSR)of China is vital for the headwaters of the Yellow,Yangtze,and Lancang rivers and exhibits significant interdecadal variability.This study investigates the influence of the East Asian westerly jet(EAWJ)on TRSR rainfall.A strong correlation is found between TRSR summer precipitation and the Jet Zonal Position Index(JZPI)of the EAWJ from 1961 to 2019(R=0.619,p<0.01).During periods when a positive JZPI indicates a westward shift in the EAWJ,enhanced water vapor anomalies,warmer air,and low-level convergence anomalies contribute to increased TRSR summer precipitation.Using empirical orthogonal function and regression analyses,this research identifies the influence of large-scale circulation anomalies associated with the Atlantic–Eurasian teleconnection(AEA)from the North Atlantic(NA).The interdecadal variability between the NA and central tropical Pacific(CTP)significantly affects TRSR precipitation.This influence is mediated through the AEA via a Rossby wave train extending eastward along the EAWJ,and another south of 45°N.Moreover,the NA–CTP Opposite Phase Index(OPI),which quantifies the difference between the summer mean sea surface temperatures of the NA and the CTP,is identified as a critical factor in modulating the strength of this teleconnection and influencing the zonal position of the EAWJ.

Inter-comparison of field snow measurements using different instruments in Türkiye

Snow is important in Türkiye especially in the mountainous eastern areas where it may stay on the ground for more than half of the year.This region plays a vital role in feeding the water resources of the trans-boundary Euphrates-Tigris Basin,supporting crucial dams for water supply,irrigation and energy production.Thus,easy,frequent,correct and economical ways of measuring the snowpack is crucial.The snow properties at specific locations in the mountainous eastern regions over the two snow seasons(2018 and 2019)were studied by using different instruments and techniques,snow pit(box/cylinder/wedge cutter types),snow tube(Federal Sampler)and SnoTel(Snowpack Analyzer).The results point out a 1.7%-7.1%variation between different cutter type snow density measurements within snow pit analysis and the long-term utilized snow tube observations show a closer relation to box/cylinder type cutters.As for the continuous SnoTel observations,a variation of 2.4%-9.8%with various cutter types and a 5.9%difference regarding the snow tube density results are detected.These findings indicate a close range among different instruments,but it is the best when all three systems complement each other to characterize the snowpack effectively in the complex terrain since each has its own advantages.

Discovery and inspiration of large-and medium-sized glutenite-rich oil and gas fields in the eastern South China Sea:An example from Paleogene Enping Formation in Huizhou 26 subsag,Pearl River Mouth Basin

Based on the practice of oil and gas exploration in the Huizhou Sag of the Pearl River Mouth Basin,the geochemical indexes of source rocks were measured,the reservoir development morphology was restored,the rocks and minerals were characterized microscopically,the measured trap sealing indexes were compared,the biomarker compounds of crude oil were extracted,the genesis of condensate gas was identified,and the reservoir-forming conditions were examined.On this basis,the Paleogene Enping Formation in the Huizhou 26 subsag was systematically analyzed for the potential of oil and gas resources,the development characteristics of large-scale high-quality conglomerate reservoirs,the trapping effectiveness of faults,the hydrocarbon migration and accumulation model,and the formation conditions and exploration targets of large-and medium-sized glutenite-rich oil and gas fields.The research results were obtained in four aspects.First,the Paleogene Wenchang Formation in the Huizhou 26 subsag develops extensive and thick high-quality source rocks of semi-deep to deep lacustrine subfacies,which have typical hydrocarbon expulsion characteristics of"great oil generation in the early stage and huge gas expulsion in the late stage",providing a sufficient material basis for hydrocarbon accumulation in the Enping Formation.Second,under the joint control of the steep slope zone and transition zone of the fault within the sag,the large-scale near-source glutenite reservoirs are highly heterogeneous,with the development scale dominated hierarchically by three factors(favorable facies zone,particle component,and microfracture).The(subaqueous)distributary channels near the fault system,with equal grains,a low mud content(<5%),and a high content of feldspar composition,are conducive to the development of sweet spot reservoirs.Third,the strike-slip pressurization trap covered by stable lake flooding mudstone is a necessary condition for oil and gas preservation,and the NE and nearly EW faults obliquely to the principal stress have the best control on traps.Fourth,the spatiotemporal configuration of high-quality source rocks,fault transport/sealing,and glutenite reservoirs controls the degree of hydrocarbon enrichment.From top to bottom,three hydrocarbon accumulation units,i.e.low-fill zone,transition zone,and high-fill zone,are recognized.The main area of the channel in the nearly pressurized source-connecting fault zone is favorable for large-scale hydrocarbon enrichment.The research results suggest a new direction for the exploration of large-scale glutenite-rich reservoirs in the Enping Formation of the Pearl River Mouth Basin,and present a major breakthrough in oil and gas exploration.

Restoration or Rehabilitation of the Faleme River Affected by Mining Activities: What Methods?

The Faleme River, a West Africa long transboundary stream (625 km) and abundant flow (>1100 million m3) is affected by severe erosion because of mining activities that takes place throughout the riverbed. To preserve this important watercourse and ensure the sustainability of its services, selecting and implementing appropriates restorations techniques is vital. In this context, the purpose of this paper was to present an overview of the actions and techniques that can be implemented for the restoration/rehabilitation of the Faleme. The methodological approach includes field investigation, water sampling, literature review with cases studies and SWOT analysis of the four methods presented: river dredging, constructed wetlands, floating treatment wetlands and chemical precipitation (coagulation and flocculation). The study confirmed the pollution of the river by suspended solids (TSS > 1100 mg/L) and heavy metals such as iron, zinc, aluminium, and arsenic. For the restoration methods, it was illustrated through description of their mode of operation and through some case studies presented, that all the four methods have proven their effectiveness in treating rivers but have differences in their costs, their sustainability (detrimental to living organisms or causing a second pollution) and social acceptance. They also have weaknesses and issues that must be addressed to ensure success of rehabilitation. For the case of the Faleme river, after analysis, floating treatment wetlands are highly recommended for their low cost, good removal efficiency if the vulnerability of the raft and buoyancy to strong waves and flow is under control.

Numerical Simulations of Snow Accumulation in the Bogie Region of a Train Considering Snow Particle Rotation

To investigate the influence of snow particle rotational motion on the accumulation of snow in the bogie region of high-speed trains,an Euler‒Lagrange numerical approach is adopted.The study examines the effects of snow particle diameter and train speed on the ensuing dynamics.It is shown that considering snow particle rotational motion causes significant deviation in the particle trajectories with respect to non-rotating particles.Such a deviation increases with larger snow particle diameters and higher train speeds.The snow accumulation on the overall surface of the bogie increases,and the amount of snow on the vibration reduction device varies greatly.In certain conditions,the amount of accumulated snow can increase by several orders of magnitudes.

Spatiotemporal Changes of Snow Depth in Western Jilin,China from 1987 to 2018

Seasonal snow cover is a key global climate and hydrological system component drawing considerable attention due to glob-al warming conditions.However,the spatiotemporal snow cover patterns are challenging in western Jilin,China due to natural condi-tions and sparse observation.Hence,this study investigated the spatiotemporal patterns of snow cover using fine-resolution passive mi-crowave(PMW)snow depth(SD)data from 1987 to 2018,and revealed the potential influence of climate factors on SD variations.The results indicated that the interannual range of SD was between 2.90 cm and 9.60 cm during the snowy winter seasons and the annual mean SD showed a slightly increasing trend(P>0.05)at a rate of 0.009 cm/yr.In snowmelt periods,the snow cover contributed to an increase in volumetric soil water,and the change in SD was significantly affected by air temperature.The correlation between SD and air temperature was negative,while the correlation between SD and precipitation was positive during December and March.In March,the correlation coefficient exceeded 0.5 in Zhenlai,Da’an,Qianan,and Qianguo counties.However,the SD and precipitation were neg-atively correlated over western Jilin in October,and several subregions presented a negative correlation between SD and precipitation in November and April.

Impact of Climate Change on Mountaineering Activities in Haba Snow Mountain Reserve and the Development of Surrounding Communities

In the context of global climate change, this study reviews and discusses the three aspects of ecology, economic development of surrounding communities, ecological balance and snow mountain activities in the Haba Snow Mountain Reserve through literature collation and research. 1) The Hengduan Mountain Plate of Haba Snow Mountain is affected by the high altitude temperate monsoon and is sensitive to climate change. There has been continuous glacier melting and snow line fluctuations. Although there is no forest line movement, the vegetation at the junction of the forest line has increased. 2) Human activities in the Haba Snow Mountain Reserve have shown an active trend, and the Biomass in various ecosystems in the region is inversely correlated. 3) Climate change will have a negative impact on landscape attraction and tourism safety in snowy mountain areas. 4) Haba Snow Mountain Reserve needs more perfect biological species statistical research and dynamic vegetation research to support the establishment of a perfect ecological protection strategy and ecological early warning in the region. 5) As the frequency of tourist activities in the Haba Protected Area increases, corresponding environmental protection signage, garbage cleaning methods, and tourist education have not been synchronizedly improved.

Industrial Carbon Emission Distribution and Regional Joint Emission Reduction:A Case Study of Cities in the Pearl River Basin,China

China’s low-carbon development path will make significant contributions to achieving global sustainable development goals.Due to the diverse natural and economic conditions across different regions in China,there exists an imbalance in the distribution of car-bon emissions.Therefore,regional cooperation serves as an effective means to attain low-carbon development.This study examined the pattern of carbon emissions and proposed a potential joint emission reduction strategy by utilizing the industrial carbon emission intens-ity(ICEI)as a crucial factor.We utilized social network analysis and Local Indicators of Spatial Association(LISA)space-time trans-ition matrix to investigate the spatiotemporal connections and discrepancies of ICEI in the cities of the Pearl River Basin(PRB),China from 2010 to 2020.The primary drivers of the ICEI were determined through geographical detectors and multi-scale geographically weighted regression.The results were as follows:1)the overall ICEI in the Pearl River Basin is showing a downward trend,and there is a significant spatial imbalance.2)There are numerous network connections between cities regarding the ICEI,but the network structure is relatively fragile and unstable.3)Economically developed cities such as Guangzhou,Foshan,and Dongguan are in the center of the network while playing an intermediary role.4)Energy consumption,industrialization,per capita GDP,urbanization,science and techno-logy,and productivity are found to be the most influential variables in the spatial differentiation of ICEI,and their combination in-creased the explanatory power of the geographic variation of ICEI.Finally,through the analysis of differences and connections in urban carbon emissions under different economic levels and ICEI,the study suggests joint carbon reduction strategies,which are centered on carbon transfer,financial support,and technological assistance among cities.

Changes in Spring Snow Cover over the Eastern and Western Tibetan Plateau and Their Associated Mechanism

The spring snow cover(SC)over the western Tibetan Plateau(TP)(TPSC)(W_TPSC)and eastern TPSC(E_TPSC)have displayed remarkable decreasing and increasing trends,respectively,during 1985–2020.The current work investigates the possible mechanisms accounting for these distinct TPSC changes.Our results indicate that the decrease in W_TPSC is primarily attributed to rising temperatures,while the increase in E_TPSC is closely linked to enhanced precipitation.Local circulation analysis shows that the essential system responsible for the TPSC changes is a significant anticyclonic system centered over the northwestern TP.The anomalous descending motion and adiabatic heating linked to this anticyclone leads to warmer temperatures and consequent snowmelt over the western TP.Conversely,anomalous easterly winds along the southern flank of this anticyclone serve to transport additional moisture from the North Pacific,leading to an increase in snowfall over the eastern TP.Further analysis reveals that the anomalous anticyclone is associated with an atmospheric wave pattern that originates from upstream regions.Springtime warming of the subtropical North Atlantic(NA)sea surface temperature(SST)induces an atmospheric pattern resembling a wave train that travels eastward across the Eurasian continent before reaching the TP.Furthermore,the decline in winter sea ice(SIC)over the Barents Sea exerts a persistent warming influence on the atmosphere,inducing an anomalous atmospheric circulation that propagates southeastward and strengthens the northwest TP anticyclone in spring.Additionally,an enhancement of subtropical stationary waves has resulted in significant increases in easterly moisture fluxes over the coastal areas of East Asia,which further promotes more snowfall over eastern TP.

Study on Image Recognition Algorithm for Residual Snow and Ice on Photovoltaic Modules

The accumulation of snow and ice on PV modules can have a detrimental impact on power generation,leading to reduced efficiency for prolonged periods.Thus,it becomes imperative to develop an intelligent system capable of accurately assessing the extent of snow and ice coverage on PV modules.To address this issue,the article proposes an innovative ice and snow recognition algorithm that effectively segments the ice and snow areas within the collected images.Furthermore,the algorithm incorporates an analysis of the morphological characteristics of ice and snow coverage on PV modules,allowing for the establishment of a residual ice and snow recognition process.This process utilizes both the external ellipse method and the pixel statistical method to refine the identification process.The effectiveness of the proposed algorithm is validated through extensive testing with isolated and continuous snow area pictures.The results demonstrate the algorithm’s accuracy and reliability in identifying and quantifying residual snow and ice on PV modules.In conclusion,this research presents a valuable method for accurately detecting and quantifying snow and ice coverage on PV modules.This breakthrough is of utmost significance for PV power plants,as it enables predictions of power generation efficiency and facilitates efficient PV maintenance during the challenging winter conditions characterized by snow and ice.By proactively managing snow and ice coverage,PV power plants can optimize energy production and minimize downtime,ensuring a sustainable and reliable renewable energy supply.

Classifying moisture sources associated with snowfall in the mountains of Lesotho

An average of eight snowfall events occur each year in the eastern Lesotho Highlands.These snowfall events are typically associated with cut-off low(CoLs)systems and mid-latitude cyclones.However,the moisture sources of the snowfall are unclassified and unclear.The Hybrid Single-Particle Lagrangian Integrated Trajectory(HYSPLIT)model,an air mass back trajectory model,has been used to evaluate moisture source waters locally in southern Africa and internationally in China and Europe.This study uses HYSPLIT to determine the source moisture of snow in Lesotho.A list of all 82 snowfall events in Lesotho spanning 2017 to 2022 was compiled using the Snow Report SA Instagram page,including the date and location of snowfall.A 72-hour back trajectory for each snowfall event was initiated for both Afriski and the whole of Lesotho.This amounts to models of moisture source trajectories for 28 and 82 snowfall days,respectively.These air mass pathways are classified according to their frequency per snowfall event,per month in the snow season,per year and for the full period.From this,associated moisture source regions and dominant air mass trajectories were identified.This study reports that the air mass trajectories associated with Afriski and Lesotho as a whole are very similar.The most common pathway of air mass trajectories transporting snow-bearing moisture to Lesotho was an inland trajectory from the northern regions of southern Africa.This pathway makes up 16.6%of all trajectories reported and is associated with the Angola Low,the Congo Air Boundary and the St.Helena High Pressure.

Evaluation of Four Anthropogenic Activity Impacts on Heavy Metal Quality of the Kumba River in the South West Region of Cameroon

Anthropogenic activities have contributed to pollution of water bodies through deposition of diverse pollutants amongst which are heavy metals. These pollutants, which at times are above the maximum concentration levels recommended, are detrimental to the quality of the water, soil and crops (plant) with subsequent human health risks. The objective of the work was to evaluate the impacts of human-based activities on the heavy metal properties of surface water with focus on the Kumba River basin. Field observations, interviews, field measurements and laboratory analyses of different water samples enabled us to collect the different data. The results show four main human-based activities within the river basin (agriculture, livestock production, domestic waste disposal and carwash activities) that pollute surface water. Approximately 20.61 tons of nitrogen and phosphorus from agricultural activities, 156.48 tons of animal wastes, 2517.5 tons of domestic wastes and 1.52 tons of detergent from carwash activities were deposited into the river each year. A highly significant difference at 1% was observed between the upstream and downstream heavy metal loads in four of the five heavy metals tested except for copper that was not significant. Lead concentrations were highest in all the activities with an average of 2.4 mg∙L−1 representing 57.81%, followed by zinc with 1.596 mg∙L−1 (38.45%) and manganese with 0.155 mg∙L−1 (3.74%) for the different anthropogenic activities thus indicating that these activities highly lead to pollution of the Kumba River water. The level of zinc and manganese was significantly influenced at ρ 005 by anthropogenic activities though generally the variations were in the order: carwash (3.196 mg∙L−1) < domestic waste disposal (3.347 mg∙L−1) < agriculture (4.172 mg∙L−1) < livestock (4.886 mg∙L−1) respectively and leading to a total of 14.04 tons of heavy metal pollutants deposited each day.

Infestation Study of Sclerophrys camerunensis and Sclerophrys regularis (Anura: Bufonidae) by Ascaris sp in Mfilou and Ngamboulou Rivers in Brazzaville (Congo)

A study of toad infestation was carried out from July to December 2022, in the vicinity of the Mfilou and Ngamboulou Rivers, with the aim of determining the prevalence rate of parasitic carriage in these toads. After collecting 289 specimens, all belonging to the Anuran order and Bufonidae family, three species were identified: Sclerophrys camerunensis (Parker, 1936), Sclerophrys regularis (Reuss, 1834) and Sclerophrys sp. The most abundant species were Sclerophrys camerunensis, followed by Sclerophrys regularis. With regard to parasitological aspects, of the 289 specimens collected, 195 were parasitized, i.e. a percentage of 67.47%. The only parasitic species identified was Ascaris sp., which is preferentially located in the intestine.

Microbial Degradation of Organic Contaminants in Streambed/Floodplain Sediments in Passaic River—New Jersey Area

This paper is intended to explore soil organic matter and carbon isotope fractionation at three locations of the Passaic River to determine if microbial degradation of organic contaminants in soil is correlated to the surrounding physical environment. Microbial degradation of organic contaminants is important for the detoxification of toxic substances thereby minimizing stagnation in the environment and accumulating in the food chain. Since organic contaminants are not easily dissolved in water, they will penetrate sediment and end up enriching the adjacent soil. The hypothesis that we are testing is microbial activity and carbon isotope fractionation will be greater in preserved soils than urban soils. The reason why this is expected to be the case is the expectation of higher microbial activity in preserved environments due to less exposure to pollutants, better soil structure, higher organic matter content, and more favorable conditions for microbial growth. This is contrasted with urban soils, which are impacted by pollutants and disturbances, potentially inhibiting microbial activity. We wish to collect soil samples adjacent to the Passaic River at a pristine location, Great Swamp Wildlife Refuge, a suburban location, Goffle Brook Park, Hawthorne NJ, and an urban location, Paterson NJ. These soil samples will be weighed for soil organic matter (SOM) and weighed for isotope ratio mass spectrometry (IRMS) to test organic carbon isotopes. High SOM and δ13C depletion activity indicate microbial growth based on the characteristics of the soil horizon rather than the location of the soil sample which results in degradation of organic compounds.

Prediction of discharge in a tidal river using the LSTM-based sequence-to-sequence models

The complexity of river-tide interaction poses a significant challenge in predicting discharge in tidal rivers.Long short-term memory(LSTM)networks excel in processing and predicting crucial events with extended intervals and time delays in time series data.Additionally,the sequence-to-sequence(Seq2Seq)model,known for handling temporal relationships,adapting to variable-length sequences,effectively capturing historical information,and accommodating various influencing factors,emerges as a robust and flexible tool in discharge forecasting.In this study,we introduce the application of LSTM-based Seq2Seq models for the first time in forecasting the discharge of a tidal reach of the Changjiang River(Yangtze River)Estuary.This study focuses on discharge forecasting using three key input characteristics:flow velocity,water level,and discharge,which means the structure of multiple input and single output is adopted.The experiment used the discharge data of the whole year of 2020,of which the first 80%is used as the training set,and the last 20%is used as the test set.This means that the data covers different tidal cycles,which helps to test the forecasting effect of different models in different tidal cycles and different runoff.The experimental results indicate that the proposed models demonstrate advantages in long-term,mid-term,and short-term discharge forecasting.The Seq2Seq models improved by 6%-60%and 5%-20%of the relative standard deviation compared to the harmonic analysis models and improved back propagation neural network models in discharge prediction,respectively.In addition,the relative accuracy of the Seq2Seq model is 1%to 3%higher than that of the LSTM model.Analytical assessment of the prediction errors shows that the Seq2Seq models are insensitive to the forecast lead time and they can capture characteristic values such as maximum flood tide flow and maximum ebb tide flow in the tidal cycle well.This indicates the significance of the Seq2Seq models.

Modelling Land Use/Land Cover Change of River Rwizi Catchment, South-Western Uganda Using GIS and Markov Chain Model

Analysis of catchment Land use/Land cover (LULC) change is a vital tool in ensuring sustainable catchment management. The study analyzed land use/land cover changes in the Rwizi catchment, south western Uganda from 1989-2019 and projected the trend by 2040. Landsat images, field observations, key informant interviews and focus group discussions were used to collect data. Changes in cropland, forestland, built up area, grazing land, wetland and open water bodies were analyzed in ArcGIS version 10.2.2 and ERDAS IMAGINE 14 software and a Markov chain model. All the LULC classes increased in area except grazing land. Forest land and builtup area between 2009-2019 increased by 370.03% and 229.53% respectively. Projections revealed an increase in forest land and builtup area by 2030 and only built up area by 2040. LULCC in the catchment results from population pressure, reduced soil fertility and high value of agricultural products.