Fluctuation Trend Research Articles

Seepage Prediction Model for Roller-Compacted Concrete Dam Using Support Vector Regression and Hybrid Parameter Optimization

In this study, a seepage prediction model was established for roller-compacted concrete dams using support vector regression (SVR) with hybrid parameter optimization (HPO). The model includes data processing via HPO and machine learning through SVR. HPO benefits from the correlation extraction capability of grey relational analysis and the dimensionality reduction technique of principal component analysis. The proposed model was trained, validated, and tested using 22 years of monitoring data regarding the Shuidong Dam in China. We compared the performance of HPO with other popular methods, while the SVR method was compared with the traditional time-series prediction method of long short-term memory (LSTM). Our findings reveal that the HPO method proves valuable real-time dam safety monitoring during data processing. Meanwhile, the SVR method demonstrates superior robustness in predicting seepage flowrate post-dam reinforcement, compared with LSTM. Thus, the developed model effectively identifies the factors related to seepage and exhibits high accuracy in predicting fluctuation trends regarding the Shuidong Dam, achieving a determination coefficient R2 > 0.9. Further, the model can provide valuable guidance for dam safety monitoring, including diagnosing the efficacy of monitoring parameters or equipment, evaluating equipment monitoring frequency, identifying locations sensitive to dam seepage, and predicting seepage.

Multi-source remote sensing data and image fusion technology reveal significant spatiotemporal heterogeneity of inundation dynamics in a typical large floodplain lake system

Study regionThe Poyang Lake, which is located on the south bank of the middle-lower Yangtze River basin. The lake is the largest freshwater lake in China, and also a typical floodplain lake in the world. Study focusThe spatiotemporal heterogeneity of inundation dynamics of large floodplain lake system has not been paid enough attention. Based on the reconstructed high spatial and temporal resolution inundation dataset using the image fusion model and multi-source remote sensing data, this study systematically analyzed the spatiotemporal heterogeneity of inundation dynamics in the Poyang Lake- floodplain system. New hydrological insights for the regionIt is found that within the same floodplain lake, the inundated area and inundation frequency in different regions of the lake (the main lake region and the adjacent floodplain region) can have asynchronous intra-annual fluctuation and opposite inter-annual change trend. This is highly related to the hydrological complexity of the lake: the relative impacts of catchment inflow and the Yangtze River varies in different regions across the lake. The stage-area relationship at the central station along the flow direction of the lake has the highest linear correlation, which might provide more accurate estimates of lake surface/volume. In addition, this study highlights the importance of reconstructed high spatial-temporal resolution of remote sensing data for the accurate assessment of inundation dynamics in floodplain lakes. All the results enrich the understanding of complex hydrological regime of large floodplain lakes and are valuable for the practice of water resources management and ecological conservation in such lakes.

Spatiotemporal analysis of groundwater level trends and recharge rate estimation in the unconfined aquifer of Yogyakarta-Sleman Groundwater Basin, Indonesia

Groundwater is the primary water resource used for domestic, industrial, and agricultural needs for the community in the Yogyakarta-Sleman Groundwater Basin area. The urbanization rate has increased since the 1970s and has made massive use of groundwater, causing environmental problems, including the quality and quantity of groundwater. Therefore, this study aimed to investigate the spatiotemporal groundwater fluctuation trends based on the non-parametric Mann-Kendall test and recharge rate estimation using the water table fluctuation (WTF) method. The groundwater level data were collected from monitoring wells across the study area during 2018-2022, particularly emphasizing 8 wells representing recharge, transition, and discharge areas. The results showed that the groundwater fluctuation pattern generally followed the season. During the rainy season from January to April, groundwater reached the shallowest level and began to decline gradually when it entered the dry season from May to October. Groundwater recharge rate was estimated to vary from 171.49 to 1,505.56 mm/year. Meanwhile, the Mann-Kendall test showed that most of the Yogyakarta-Sleman Groundwater Basin area did not experience significant fluctuation trends, except for two monitoring wells in the center of Yogyakarta City which had increasing groundwater level trends. The rising groundwater levels were expected to be caused by urban wastewater recharge. This study has provided a new description and insights into spatiotemporal changes in the groundwater table and the quantification of groundwater recharge.

Research on the spatial-temporal evolution pattern of China's industrial carbon emission efficiency-based on the super-efficiency SBM model

This paper uses the super efficiency SBM model based on unexpected output to calculate the industrial carbon emission efficiency of 30 provinces in China from 2005 to 2019, and uses spatial autocorrelation and other methods to conduct an empirical analysis on the dynamic evolution process and temporal and spatial differences of carbon emission efficiency. The results show that China's industrial carbon emission efficiency is still in the low efficiency stage, with an average value of 0.34. In the study period, although the overall trend is rising, the spatial and temporal differences between provinces are obvious. The overall Moran's I index is subject to the impact of social policy environment on the time path, showing an overall "M" type fluctuation trend, and its spatial difference characteristics change in stages. At the same time, there is a significant global spatial agglomeration effect across the country, and there is a spatial dependency between provinces. The agglomeration trend is significant, forming a cluster with the eastern coastal area as the high value center, and the northwest inland area as the low value center. The Getis OrdGI * index reveals that the local spatial agglomeration characteristics of China's industrial carbon emission efficiency always maintain the pattern of "hot in the east and cold in the west", which echoes the overall spatial evolution pattern of China. The hot spots and sub hot spots of China's industrial carbon emission efficiency are mainly concentrated in the southeast coastal areas with relatively superior economic development, and present a "semi enclosed" pattern. Cold spot area and sub cold spot area gradually evolved into a "suppression" pattern dominated by provinces in northwest China, comprehensively suppressing hot spots. This paper conducts an all-round evaluation of China's industrial carbon emission efficiency from the perspective of regional differentiation, and deeply studies the regional differences and spatial evolution pattern of carbon emission efficien cy in various provinces. It is crucial to achieve the goal of carbon emission reduction in China, and has important practical value and practical significance.

An Experiment on Surface Fluctuation of Ga-In-Sn Alloy with a Permanent Magnet Flow Control Mold

To control well the surface fluctuation of liquid metal in a slab mold, a new type of combined permanent magnets braking system, namely a permanent magnet flow control mold (PMFC-Mold) is proposed by our research group, of which its main feature is that the device can control the flow of molten steel in the mold without additional energy. To observe the fluctuation state of the alloy with the PMFC-Mold, instantaneous surface fluctuations were recorded by a laser level meter and camera. To study the effect of various casting speeds and permanent magnet placement on surface fluctuations, the three measurement points, which were 7, 18, and 36 mm away from the narrow surface of the mold, were selected to record the trend of level fluctuation. Three types of permanent magnet placement were designed by setting the differences between the height center of the permanent magnet and the free surface in the slab mold, which were H1 = 0 mm, H2 = −25 mm, and H3 = −75 mm. The experimental results indicated that with the acceleration of the casting speed, the average height and standard deviation of surface fluctuation at the measurement point increased, but the surface fluctuation pattern remained. When the permanent magnets were arranged at H1 = 0 mm and H2 = −25 mm, the position of the magnetic field was reasonable and the surface fluctuation could be effectively suppressed. In contrast, when the permanent magnets were arranged at H3 = −75 mm, the level fluctuation was intensified.

Analysis of the cause of power system inertia generation and decline

Variable renewable energy sources (RES) are becoming more and more common, and traditional power generation plants are rapidly being replaced by them. As RES are used more frequently, power electronics are also utilized more frequently, both to connect RES and as drives for electric motors. As a result, the inertia level of the power system is continuously decreasing, and the frequency stability of the power system is facing severe challenges. Traditional power-generating methods such as thermal, hydroelectric, nuclear, and natural gas use generators to produce electric energy. By utilizing the rotational inertia of the steam turbine unit, the frequency fluctuation trend that occurs in the power grid can be delayed. However, photovoltaic power generation lacks rotating machinery and has no rotational inertia, whereas wind turbines operate at a modest speed and have negligible rotational inertia. The response capability is reduced significantly when the power grid's frequency changes. Any electric power system tends to rely on rotational inertia. The relevant factors impacting the inertia level of the power system are introduced based on the concept of inertia of the power system. The power system experiences inertia from the synchronous grid-connected generation side, the load side, and the grid-connected generation side of the converter. These three sources make up the majority of the inertia in the system. From the aspects of the power generating side, grid side, and load side, approaches and strategies to increase the frequency stability of power systems are introduced.

The Analysis of Vital Food Cost

This paper analyzes the price fluctuation trends of four essential foods in Canada, Australia, Japan, South Africa and Sweden during 2018-2022, so as to explore the factors affecting the price of essential foods and predict the future trend of food prices. According to the sample data, the data cleaning work was carried out to obtain the price growth rate excluding the price factor, and the data visualization chart was established combining the characteristics of cpi index, time change, and national conditions. Combining a variety of data visualization charts to analyze and study the problem, it has good practicability and accuracy.

Evaluating the sustainability of land use integrating SDGs and its driving factors: A case study of the Yangtze River Delta urban agglomeration, China

Achieving the sustainability of land use (SLU) is of significance in the implementation of the Sustainable Development Goals (SDGs). However, limited research has been conducted on the integrating SDGs into land use assessment. This paper constructs a SLU evaluation framework oriented to SDGs to investigate the spatial-temporal characteristics of SLU during 2000–2020 and its driving factors, taking 192 counties in Yangtze River Delta urban agglomeration (YRD), China as a case. Results show that the SLU level in YRD demonstrates an overall decrease trend of fluctuations, along with obvious regional differences. The spatial pattern of the SLU level in YRD is high in the northern region and low in the southern region, but this gap is gradually narrowing. The spatial distribution of SLU has positive agglomeration characteristics, manifested as HH and L-L types. Furthermore, SLU depends more on the combination of natural and socioeconomic factors. Industrial structure, fiscal deficit, urbanization level, vegetation coverage and precipitation characteristics can promote the SLU, while the economic development level, government intervention and population density have a negative impact on SLU.

Carbon emission characteristics of urban trip based on multi-layer network modeling

Multi-layer networks could reveal the carbon emission structure of urban traffic formed after residents choose the means and purpose of trips. In this paper, a multi-layer network model was proposed and the carbon emission characteristics of urban trips were analyzed. In addition, the carbon reduction potential assessment methods based on nodes and edge feature indexes to identify the carbon reduction areas of the trip network. An empirical study was carried out on Shenzhen and the results showed that: 1) The carbon emission in Shenzhen is unbalanced in spatial and is dense in the west and sparse in the east, but the carbon emission of different networks shows a similar fluctuation trend over time; 2) multi-layer network represents community structure, while communities of “residence-enterprise” network and “residence-park” network are internally closely connected; 3) the carbon emission reduction potential of residential nodes is low in the west and high in the east. The mode of the urban trip and the law of geographical space connection expressed by it were understood by establishing a multi-layer network embedded in geographic space in this paper. The conclusions hereof are of supportive significance for the formulation of space emission reduction policies.

Exploration of Vegetation Change Trend in the Greater Khingan Mountains Area of China Based on EEMD Method

Vegetation, especially forest ecosystems, plays an important role in the global energy flow and material cycle. The vegetation index (VI) is an important index reflecting the dynamic change in vegetation and directly reflects the response of ecosystem to global climate change. The Greater Khingan Mountains Forest region is located in the northeast of China. It is the largest primeval forest region in China, which is well preserved and less affected by human activities. It is of great significance to study the driving mechanism of forest vegetation change for future ecological prediction and management. In this study, GIMMS NDVI data were used to explore the characteristics of nonlinear temporal and spatial variation of NDVI in the Greater Khingan Mountains and its relationship with climatic factors. Firstly, the EEMD method was used to analyze the characteristics of vegetation change in the study area from 1982 to 2015. Secondly, the relationship between vegetation change and climate was discussed by using precipitation and temperature data. The results showed that the following: (1) from 1982 to 2015, the interannual change in vegetation in the Greater Khingan Mountains presented a trend of slow fluctuation and gradual decrease (SLOPE = −0.1645/10,000, p < 0.01). (2) The spatial distribution of vegetation change had obvious geographical differences, and in the central region, the overall distribution characteristics had an obvious browning trend, and in the northwest and southeast, the distribution characteristics had a green trend. (3) The correlation analysis results of vegetation change and climate factors showed that NDVI change was significantly positively correlated with temperature and precipitation; additionally, NDVI change was more correlated with temperature with a range of 0.8–1 than precipitation. (4) The results of vegetation attribution analysis in four typical areas of the study area showed that the following: the coniferous forest area has good cold tolerance and drought tolerance, the correlation between vegetation change and climate factors (temperature, precipitation) was not the strongest, which was 0.537 and 0.828, respectively. The ecological transition area and the broad-leaved forest area, which was located at the edge of the study area, have relatively fragile ecosystems, showed a strong correlation with precipitation, and the correlation coefficients reached 0.670 and 0.632, respectively. The surface water resources provide favorable conditions for the growth of vegetation, it showed a weak correlation with precipitation, and the correlation coefficient was 0.5349.

Water Quality Fluctuations in Shrimp Ponds During Dry and Rainy Seasons

Abstract Season and water quality are essential indicators in the life cycle of pond ecosystems. The season is a natural factor affecting the level of water quality dynamics in shrimp cultivation in ponds. This study aims to evaluate the dynamics of differences in water quality parameters in intensive Litopenaeus vannamei ponds during dry and rainy seasons. This current study applied an ex post facto causal design based on actual field conditions. During the rainy season, water quality parameters tended to fluctuate dynamically, with the parameters of phosphate (PO4), nitrite (NO2), and total organic matter (TOM) exceeding the threshold value of water quality standards for aquaculture, with a PO4 value of 0.734 mg/L, a NO2 of 0.180 mg/L, and a TOM of 101.29 mg/L. In the dry season, water quality parameters remained stable, with only the phosphate parameter showing a value above the water quality standard threshold of 0.633 mg/L. Based on the trend of fluctuations in the two seasons, a model of equation Y = 3.979 + 0.814x was made with a significance value <α (0.05), which means that the two seasons positively correlated with the impact on fluctuations of water quality in the ponds. The results of the dynamic modelling analysis showed contradictions in water quality and nutrients during rainy and dry seasons. Water quality parameters in intensive L. vannamei cultivation during dry and rainy seasons fluctuated dynamically and differed according to the type of weather conditions and the current season.

Evaluation of Long Time-Series Soil Moisture Products Using Extended Triple Collocation and In Situ Measurements in China

Currently, satellite-based soil moisture (SM) products and land surface model assimilation techniques are widely utilized. However, the presence of systematic errors in the observation process, algorithmic discrepancies between products, and variations in spatial and temporal scales result in diverse accuracy characteristics and applicability. This study evaluates three prominent SM products in China, namely, the Essential Climate Variable Soil Moisture (ECV), the European Centre for Medium-Range Weather Forecasts’ Fifth-Generation Land Surface Reanalysis Data (ERA5-Land), and the Global Land Surface Data Assimilation System (GLDAS). The evaluation was conducted using extended triple collocation (ETC) analysis and in situ validation methods at a monthly scale from 2000 to 2020. The ETC analysis results show that among the three products, GLDAS exhibits the highest correlation coefficient (CC) and the lowest standard deviation of error (ESD), indicating its superior performance in China. ECV and ERA5-Land follow, with slightly lower performance. In the in situ validation results, ERA5-Land displays the highest correlation, capturing the temporal trend of the ground SM well. Comparatively, in terms of overall accuracy, ECV performs the best, with a slightly smaller mean error (ME) and root mean square error (RMSE) than GLDAS, and ERA5-Land has the lowest accuracy. The discrepancy between the in situ validation results and ETC analysis can be attributed to the limited number of sites and their representativeness errors. Notably, ERA5-Land exhibits a highly consistent trend of interannual fluctuations between ESD and precipitation. Furthermore, a strong association is observed between the ME and RMSE of ECV and GLDAS and precipitation. These findings serve as valuable references for future SM studies in China.

Cutting Force Fluctuation Suppression and Error Homogenization of Noncircular Gear Hobbing Based on the Tool Shifting Method

The current research on noncircular hobbing mainly focuses on the linkage model and motion realization. However, the intermittent cutting characteristics of hobbing would increase uncertainties in the manufacturing process. In this paper, a hobbing machining model with tool-shifting characteristics was proposed to solve the problems of cutting force fluctuation and inconsistency of tooth profile envelope accuracy at different positions of the pitch curve in noncircular gear hobbing. Based on the unit cutting force coefficient method, the undeformed chip volume generated by interrupted cutting was used to characterize the fluctuation trend of the hobbing force. The fluctuation characteristics of the cutting force generated by different hobbing models were compared and analyzed. Using the equivalent gear tooth and hob slotting numbers, an analysis model of the tooth profile envelope error of the noncircular gear was constructed. Subsequently, the tooth profile envelope errors at different positions of the pitch curve were compared and analyzed based on the constructed model. The transmission structure of the electronic gearbox was constructed based on the proposed hobbing model, and the hobbing experiment was conducted based on the self-developed noncircular gear CNC hobbing system. This paper proposes a hobbing method that can effectively suppress the fluctuation of the peak and whole circumference cutting force and reduce the maximum envelope error of the whole circumference gear teeth.

Glucometric Guardianship

It is a well-known fact that the knowledge of their current glucose readings empowered people with diabetes to evaluate and monitor the trends in glucose fluctuations and take informed decisions on adjusting their medicines, food intake, and physical activity. Glucose monitoring technology has undergone a technological evolution and has improved diabetes care in patients living with type 2 diabetes. This has also made the need to efficiently and effectively utilize blood glucose monitoring tools. Given the above, the article has reviewed the significance of glucometric guardianship. Glucometric checklists offer a standardized approach to glucometric guardianship which is necessary to improve the process of drug choice and dose titration. The stepwise factors included in the glucometric guardianship checklist include procurement, distribution, pre-testing hygiene, testing, recording, action, disposal, quality control, and procedure safety.

Forecasting Renewable Energy Generation Based on a Novel Dynamic Accumulation Grey Seasonal Model

With the increasing proportion of electricity in global end-energy consumption, it has become a global consensus that there is a need to develop more environmentally efficient renewable energy generation methods to gradually replace traditional high-pollution fossil energy power generation. Renewable energy generation has become an important method of supplying power across the world. Therefore, the accurate prediction of renewable energy generation plays a vital role in maintaining the security of electricity supply in all countries. Based on this, in our study, a novel dynamic accumulation grey seasonal model is constructed, abbreviated to DPDGSTM(1,1), which is suitable for forecasting mid- to long-term renewable energy generation. Specifically, to overcome the over-accumulation and old information disturbance caused by traditional global accumulation, a dynamic accumulation generation operator is introduced based on a data-driven model, which can adaptively select the optimal partial accumulation number according to the intrinsic characteristics of a sequence. Subsequently, dummy variables and a time trend item are integrated into the model structure, significantly enhancing the adaptability of the new model to the sample sequence with different fluctuation trends. Finally, a series of benchmark models are used to predict renewable energy generation in China, wind power generation in the United States, and hydropower generation in India. The empirical results show that the new model performs better than other benchmark models and is an effective tool for the mid- to long-term prediction of renewable energy generation.

The Construction of a Coordinated Integration System of Rural Tourism and Habitat Environment in China Based on Coupled Coordination Degree Model

Abstract The tourism industry provides the impetus for the development of the habitat environment, while the development of the habitat environment lays the foundation for the development of the tourism industry, and the two develop in a coordinated manner. In rural habitat improvement, rural tourism development should be integrated with rural habitat improvement, and a coordinated integration system of rural tourism and habitat environment should be built to extend the coverage of rural habitat improvement and improve the level of rural tourism development. This study constructs a comprehensive evaluation system and evaluation indexes for the development level of the rural tourism industry, and the analysis of the coupling coordination degree results shows that Fi(x, t) > F2(y, t) from 2017 to 2020, and Fi(x, t) < F2(y, t) from 2014 to 2016 and 2021 to 2022. From the integration coordination degree (D), from 2014 to 2018, the integration coordination degree (D) of rural tourism and habitat environment shows a fluctuation trend, the integration degree shows an upward trend, the coordination area of rural tourism income level shows a spatial polarization gesture, and the integration of cultural industry and tourism industry reaches the initial coordination by 2021. The integration of rural tourism and habitat environment in China is currently in a dysfunctional state, which is very unfavorable to the long-term development of China’s rural tourism industry and threatens the original habitat environment and should adhere to the people-oriented principle, gradually build up a coordinated integration system of rural tourism and habitat environment in China, and realize a win-win situation for the development of rural tourism and habitat environment.

Analiza evoluției pieței funciare agricole prin prisma tranzacțiilor de vânzare-cumpărare

The agricultural land market, as a specific element of the real estate market, was reestablished in the Republic of Moldova by the end of the last century. During the development of the national agricultural land market, there were different fluctuation trends of the main indicators, which reflect the quantitative aspects of land development: the correlation between demand and supply, market price of agricultural land, sold-purchased land areas, etc. The most important indicator is the market price of agricultural land, which, under the conditions of free land market, is formed based on the correlation between supply and demand for land. The sale-purchase type of business predominates in the transaction structure of the land market. In this context, in order to investigate the issues related to the functioning of the agricultural land market, the number of sale-purchase transactions of agricultural land, the area of agricultural land subject to sale, as well as the average sale-purchase price of agricultural land have been analyzed.

Long short-term memory models to quantify long-term evolution of streamflow discharge and groundwater depth in Alabama

Long short-term memory (LSTM) models have been shown to be efficient for rainfall-runoff modeling, and to a lesser extent, for groundwater depth forecasting. In this study, LSTMs were applied to quantify the spatiotemporal evolution of surface and subsurface hydrographs in Alabama in the Southeastern United States, where water sustainability has not been fully quantified across spatiotemporal scales. First, the surface water LSTM model with extensive dynamic (precipitation and other weather variables) and static (basin characteristics) inputs predicted the main characteristics of streamflow for six years at 19 gauged basins in Alabama. The model tended to underestimate extremely high streamflow but adding drainage density as an input feature slightly improved the predictions of extreme events. Second, to predict the groundwater depth evolution, a groundwater LSTM (GW-LSTM) model was proposed and applied using static inputs capturing the aquifers' hydrogeological properties and dynamic inputs of meteorological information. Three precipitation scenarios were also explored to evaluate the groundwater hydrograph evolution in the next two decades. The GW-LSTM model predicted the general trend of daily groundwater depth fluctuations (at 21 wells distributed across Alabama from 1990 to 2021) including most extremely high groundwater levels, and recovered groundwater depth for locations withheld from model training and validation. This study, therefore, extended the application of LSTMs in quantifying the spatiotemporal evolution of surface water and groundwater, two manifestations of a single integrated resource.

Intervention of Dietary Protein Levels on Muscle Quality, Antioxidation, and Autophagy in the Muscles of Triploid Crucian Carp (Carassius carassius Triploid).

The aim of this study is to investigate the effect of dietary protein levels on flesh quality, oxidative stress, and autophagy status in the muscles of triploid crucian carp (Carassius carassius triploid), and the related molecular mechanisms. Six experimental diets with different protein levels (26%, 29%, 32%, 35%, 38%, 41%) were formulated. A total of 540 fish with an initial weight of 11.79 ± 0.09 g were randomly assigned to 18 cages and six treatments with three replicates of 30 fish each for 8 weeks feeding. It could be found that the whole-body ash content significantly increased in high protein level groups (p < 0.05). The 29% dietary protein level group exhibited the highest muscle moisture, although there was an inconspicuous decrease in the chewiness of the muscles when compared with the other groups. The dietary protein level influenced the content of free amino acids and nucleotides, especially the content of flavor amino acids, which exhibited an increasing tendency along with the increasing protein level, such as alanine and glutamic acid, while the flavor nucleotides showed different fluctuation trends. Moreover, the genes related to muscle development were shown to be influenced by the dietary protein level, especially the expression of MRF4, which was up-regulated with the increasing dietary protein levels. The 29% dietary protein level promoted the majority of analyzed muscle genes expression to the highest level when compared to other dietary levels, except the Myostain, whose expression reached its highest at 38% dietary protein levels. Furthermore, the effect of dietary protein levels on antioxidant signaling pathway genes were also examined. High protein levels would boost the expression of GSTα; GPX1 and GPX4α mRNA expression showed the highest level at the 32% dietary protein group. The increasing dietary protein level decreased both mRNA and protein expressions of Nrf2 by up-regulating Keap1. Autophagy-related gene expression levels reached the peak at 32% dietary protein level, as evidenced by a similar change in protein expression of FoxO1. In summary, muscle nutritional composition, antioxidative pathways, and autophagy levels were affected by the dietary protein levels. A total of 29-32% dietary protein level would be the appropriate level range to improve muscle quality and promote the antioxidant and autophagy capacity of triploid crucian carp muscles.

Seasonal and Spatial Variability of Chlorophyll-a in Response to ENSO and Ocean Current in the Maritime Boundary of Bangladesh

Chlorophyll-a (Chl-a) and its correlation with different parameters are one of the major indicators to understand marine ecosystems. This study was conducted to explore the seasonal and spatial variability of Chl-a at three different stations (onshore, midshore, and offshore) across the maritime boundary of Bangladesh in the northern BoB with its response to the surface current speed and recent ENSO (El Niño/La Niña-Southern Oscillation) events by using satellite data. Moderate resolution imaging spectroradiometer (MODIS) aqua satellite level-3 data of Chl-a was used in this study. Ocean currents datasets were obtained from the Asia-Pacific Data Research Center (APDRC) live access service, LAS8.6.13 of NOAA (National Oceanic and Atmospheric Administration), whereas the SST anomalies dataset was collected from NOAA Climate Prediction Center. This study revealed that the onshore region showed the highest (1.121 mgm-3) abundance of Chl-a, whereas the offshore region showed the lowest (0.136 mgm-3). The offshore and midshore regions showed a homogenous distribution of Chl-a, whereas the observed trend of seasonal fluctuation was southwest monsoon &gt; postmonsoon &gt; northeast monsoon &gt; premonsoon. There is a seasonal variation in the relationship between Chl-a and surface current speed, with moderate correlations during northeast (Dec-Feb) and premonsoon (Mar-May). The effect of ENSO on Chl-a was observed as insignificant ( P &gt; 0.05 ) in the northern BoB. However, Chl-a variability in response to ENSO events across the northern region of BoB requires more investigation.