Northwestern Bangladesh Research Articles

Investigating the changing land use patterns and their impacts on ecosystem in the Teesta River Basin

This study investigated the changing land use patterns and their impacts on ecosystem in the Teesta River Basin of northwestern Bangladesh. Although anthropocentric land use patterns, including agricultural land use, settlements, built areas, and waterbody loss, have been increasing in the Nilphamari district, by negatively affecting local ecosystems, they have not been identified by prior research. Limitations of contemporary literature motivated me to work on this crucial ground in the Teesta River Basin in Northwestern Bangladesh. This study applied a mixed research approach to identify the study objectives. Firstly, the land use and land cover (LULC) changes which occurred between 2000 and 2020 were detected using satellite imagery and supervised classification method. In addition to the detection of LULC changes, the study explored the people’s perceptions and experiences about the ecosystem changes resulted from the LULC changes over the last 20 years, conducting stakeholders’ consultations and household surveys utilizing a semi-structured questionnaire. The findings indicated that waterbodies in Nilphamari district have significantly decreased from 378 km2 in 2000 to 181 km2 in 2020. In the same way, the vegetation coverage has reduced 187 km2 between the years 2000 and 2020. On the contrary, agricultural lands (croplands) have increased from 595 km2 to 905 km2 and settlements have increased from 81 km2 to 206 km2 between the years 2000 and 2020. From the chi-square test, it was found a significant association between ecosystem change and biodiversity loss. It was further identified that waterbody decreases have significant impacts on aquatic ecosystems. The results of this study also indicated that due to the introduction of foreign tree species, local and native species have been significantly decreasing over the time. This study emphasizes the non-anthropocentric and inclusive land use policy implications for protecting life on land and preserving the aquatic ecosystem in Bangladesh.

Monitoring wheat area using sentinel-2 imagery and In-situ spectroradiometer data in heterogeneous field conditions

Crop statistics are crucial for developing a demand-based export and import strategy to ensure a country’s sustainable food security. Remote sensing efficiently generates essential crop statistics, while ground-based supplementary sensor data offers sufficient information for crop delineation. This study explored the multispectral satellite imagery using in-situ ground-based hyperspectral reflectance phenology information as training data to delineate wheat from other competitive winter crops in Northwestern Bangladesh as a case study. Wheat spectral signatures were primarily obtained through a hand-held Spectroradiometer at various phenological stages, aligned with Sentinel-2 data availability. Five vegetation indices (VIs), namely Normalized Difference Vegetation Index (NDVI), Red-edge NDVI (RENDVI), Enhanced Vegetation Index (EVI), Greenness Chromatic Coordinate (GCC) and Soil-Adjusted Vegetation Index (SAVI), were derived from Spectroradiometer-data across six wheat growth stages: seedling, tillering, booting, flowering, grain development, and maturity. Maximum and minimum threshold values for the VIs at those six growth stages were determined from regression analysis of the values collected from Spectroradiometer and Sentinel-2. A rule-based classification technique was then used to categorize Sentinel-2 for wheat crop delineation based on those threshold values. The results revealed that maps based on NDVI, EVI, and SAVI showed overall accuracies of 83.33%, 85.18%, and 81.48%, respectively. These accuracies were found to be statistically acceptable (p < 0.05) outcomes. A positive agreement was observed when comparing the remotely sensed area at the union (4th tier administrative level) with the officially reported data of Bangladesh. This innovative method has the potential to be extended for developing phenology and area delineation for other major crops locally and globally.

Investigation on the Distribution of Antibiotic Resistant Bacteria In Dry Fish of Chalan Beel Area From Northwestern Part of Bangladesh

Dried fish, a valuable animal protein source, may pose health risks due to microbial contamination influenced by water quality, hygiene practices, handling, packaging, and transportation. This research focuses on conducting an in-depth analysis of the occurrence and antibiotic resistance patterns of bacteria, identified through 16S rRNA sequencing, in different dried fish varieties obtained from the Chalan beel area in Northwestern Bangladesh. For the purpose of this study, homogenization of collected samples was carried out and resulting homogenates were refrigerated at a temperature of -20°C. Then the samples were subjected to a series of 10-fold dilutions and spread over 1.5% nutrient agar supplemented with Tetracycline. Thereafter, plates were incubated at 37°C for a duration of 24 hours to form bacterial colonies. Twelve aseptically collected dried fish samples had a total viable count ranging from 2.0 × 10² to 6.5 × 10⁵ CFU/ml, with tetracycline influence at 32 µg/ml (7 × 10² to 5.4 × 10³ CFU/ml) and 64 µg/ml (3.0 × 10² to 2.1 × 10³ CFU/ml). Notably, Tengra fish (Mystus sp.) exhibited the highest viable count 6.5 × 105 CFU/ml (Control), while Darikana (Esomus danricus), Chela (Salmostoma phulo), Moa (Amblypharyngodon mola), and Guchi (Mastacembelus pancalus) fish showed the lowest count (3.0 × 10² CFU/ml) at a Tetracycline concentration of 64 µg/ml. Moreover, microbial analysis using 16S rRNA gene sequencing identified twelve unique bacteria belong to genera. The most prevalent genus appears to be Enterobacter, identified by 6 strains. These include Enterobacter hormaechei strains UCHE20, RB13, AUH-ENM30 and 20710, Enterobacter ludwigii strain JCR-38 and Enterobacter sp. M3. Other identified genera included Klebsiella (with Klebsiella variicola and Klebsiella pneumoniae), Proteus (Proteus mirabilis), Macrococcus (Macrococcus caseolyticus), Acinetobacter (Acinetobacter johnsonii), and Bacillus (Bacillus sp.). This study provides valuable insights into the complex microbial dynamics in dried fish, emphasizing the need for enhanced food safety and public health measures. J. Bio-Sci. 32(2): 61-69, 2024

Targeting strategies for balanced energy and protein (BEP) supplementation in pregnancy: study protocol for the TARGET-BEP cluster-randomized controlled trial in rural Bangladesh

BackgroundThe World Health Organization (WHO) recommends balanced energy and protein (BEP) supplementation be provided to all pregnant women living in undernourished populations, usually defined as having a prevalence > 20% of underweight women, to reduce the risk of stillbirths and small-for-gestational-age neonates. Few geographies meet this threshold, however, and a large proportion of undernourished women and those with inadequate gestational weight gain could miss benefiting from BEP. This study compares the effectiveness of individual targeting approaches for supplementation with micronutrient-fortified BEP vs. multiple micronutrient supplements (MMS) alone as control in pregnancy in improving birth outcomes.MethodsThe TARGET-BEP study is a four-arm, cluster-randomized controlled trial conducted in rural northwestern Bangladesh. Eligible participants are married women aged 15–35 years old identified early in pregnancy using a community-wide, monthly, urine-test-based pregnancy detection system. Beginning at 12–14 weeks of gestation, women in the study area comprising 240 predefined sectors are randomly assigned to one of four intervention arms, with sector serving as the unit of randomization. The interventions involving daily supplementation through end of pregnancy are as follows: (1) MMS (control); (2) BEP; (3) targeted BEP for those with pre-pregnancy body mass index (BMI) < 18.5 kg/m2 and MMS for others; (4) targeted BEP for those with pre-pregnancy BMI < 18.5 kg/m2, MMS for others, and women with inadequate gestational weight gain switched from MMS to BEP until the end of pregnancy. Primary outcomes include birth weight, low birth weight (< 2500 g), and small for gestational age, defined using the 10th percentile of the INTERGROWTH-21st reference, for live-born infants measured within 72 h of birth. Project-hired local female staff visit pregnant women monthly to deliver the assigned supplements, monitor adherence biweekly, and assess weight regularly during pregnancy. Trained data collectors conduct pregnancy outcome assessment and measure newborn anthropometry in the facility or home depending on the place of birth.DiscussionThis study will assess the effectiveness of targeted balanced energy and protein supplementation to improve birth outcomes among pregnant women in rural Bangladesh and similar settings.Trial registrationClinicalTrials.gov NCT05576207. Registered on October 5th, 2022.

Analysis of the onset, withdrawal, and variability of monsoon rainfall in the face of climate change

Climate change is affecting the precipitation system in Bangladesh, particularly in the northwestern hydrological zone. This study analyzed the monsoon rainfall variability from 1991 to 2015, revealing a shifting pattern and past trends. This study used the Mann–Kendall test and Sen’s slope (MAKESENS) statistical model to evaluate the annual total rainfall and monsoon rainfall. Approximately 71–78% of the total rainfall occurred during the monsoon season at all stations, with Rangpur being the rainiest and Rajshahi being the driest. The annual rainfall trend decreased, with highly variable arrival and withdrawal days. The monsoon arrived early by 2 to 39 days and late by 1 to 72 days from the reference day. The withdrawal of monsoon rainfall occurred 1 to 38 days early and 1 to 39 days late. These findings can be used to plan and manage agricultural practices at the local level in northwestern Bangladesh.

Empowering real-time flood impact assessment through the integration of machine learning and Google Earth Engine: a comprehensive approach.

Floods cause substantial losses to life and property, especially in flood-prone regions like northwestern Bangladesh. Timely and precise evaluation of flood impacts is critical for effective flood management and decision-making. This research demonstrates an integrated approach utilizing machine learning and Google Earth Engine to enable real-time flood assessment. Synthetic aperture radar (SAR) data from Sentinel-1 and the Google Earth Engine platform were employed to generate near real-time flood maps of the 2020 flood in Kurigram and Lalmonirhat. An automatic thresholding technique quantified flooded areas. For land use/land cover (LULC) analysis, Sentinel-2's high resolution and machine learning models like artificial neural networks (ANN), random forests (RF) and support vector machines (SVM) were leveraged. ANN delivered the best LULC mapping with 0.94 accuracy based on metrics like accuracy, kappa, mean F1 score, mean sensitivity, mean specificity, mean positive predictive value, mean negative value, mean precision, mean recall, mean detection rate and mean balanced accuracy. Results showed over 600,000 people exposed at peak inundation in July-about 17% of the population. The machine learning-enabled LULC maps reliably identified vulnerable areas to prioritize flood management. Over half of croplands flooded in July. This research demonstrates the potential of integrating SAR, machine learning and cloud computing to empower authorities through real-time monitoring and accurate LULC mapping essential for effective flood response. The proposed comprehensive methodology can assist stakeholders in developing data-driven flood management strategies to reduce impacts.

Seasonal Variation of Fe, Mn, and Pb in Groundwater of Northwestern Bangladesh

Groundwater is one of the most significant natural resources on earth and also stands as the largest source of all-purpose water in Bangladesh. The higher concentrations of iron (Fe), manganese (Mn), and lead (Pb) in water constitute a threat to human health and the environment. The research aimed to assess the seasonal variations of heavy metal concentrations, including Fe, Mn, and Pb, and the water type controlling the geochemistry of groundwater. A total of sixty groundwater samples were collected over a year in three seasons and analyzed for several physicochemical parameters using the standard analysis methods The highest concentrations of Fe, Mn, and Pb in investigated groundwater samples were found to be 3.69, 2.50, and 0.17 mg/L, respectively. The study observed that the higher concentrations of Fe and Mn were in the pre-monsoon but Pb was in the post-monsoon. The contaminations of Fe, Mn, and Pb in the groundwater follows the order Fe &gt; Mn &gt; Pb in three seasons, and their concentrations of abundance follow the seasons: PRM &gt; POM &gt; MON. The groundwater samples showed the dominance of Ca++, Mg++, and HCO3-, indicating temporary hardness and the Ca-Mg-HCO3, hydrochemical facies, controlling the groundwater geochemistry in the study area. These findings would provide an in-depth understanding of water quality, potential risks to human health, and coping mechanisms for sustainable drinking water management.

Evaluating arsenic contamination in northwestern Bangladesh: A GIS-Based assessment of groundwater vulnerability and human health impacts

One of the biggest environmental worries in the world today is the risk of arsenic (As) contamination in groundwater. The Atomic Absorption Spectrometer (AAS) was used in this work to assess the As content in groundwater samples from 38 shallow (27 m) tubewells in northwest Bangladesh to determine the existing situation, potential source(s), and likely health risk of As and other important water quality parameters. The range of arsenic concentrations (μgL−1) was troublesome and greater than the WHO recommended level for drinking water, ranging from 0.50 to 164 (mean ± SD: 20.22 ± 36.46). In groundwater, the concentrations of Fe, and Mn vary from 0.04 to 52.75 mgL−1 (mean ± SD: 4.23 ± 9.68), and 0.23 to 3.27 mgL−1 (mean ± SD: 1.10 ± 0.67). The obtained groundwater samples have pH values ranging from 5.9 to 7.1, which indicates a somewhat acidic to neutral character. Major cations have an average abundance that is as follows: Ca2+ > Mg2+ > Na+ > K+, while major anions have an average abundance that is as follows: HCO3− > Cl− > SO42− > NO3−; Ca2+ and HCO3− are the main cation and anion, respectively. The groundwater in the Rajarampur village was deemed unfit for drinking or irrigation based on analyses of water quality performed using the entropy water quality index. The Ca–HCO3 type of water, in which Ca2+ and HCO3− are the main positive ions and negative ions, is suggested by the Piper tri-linear diagram. It was discovered that silicate weathering regulates the hydro-geochemical activities in groundwater using a bi-variate examination of several hydro-chemical variables. Four major clusters were observed for the water sample. According to reductive dissolution processes and principal component analysis, the arsenic in groundwater is geogenic in origin. Arsenic is discharged from sediment to groundwater by reductive dissolution of FeOOH and MnOOH, as shown by the modest connection between As, Fe, and Mn. The United Nations Environmental Protection Agency's (USEPA) suggested value for probable cancer risk assessment was 10−6, however the probable cancer risk assessment found a higher value, indicating that the population in the study region was at high risk for cancer. Remedial measures for arsenic mitigation include removing arsenic from groundwater after it is extracted, searching for alternative aquifers, and implementing various water-supply technologies such as dugwells, deep tubewells, pond-sand filters, and rainwater harvesting systems.

Stock assessment of barred spiny eel, Macrognathus pancalus (Hamilton, 1822) in a wetland ecosystem, northwestern Bangladesh: A fundamental approach to ensure sustainability and conservation

This research delved into the management approach for Macrognathus pancalus within the Gajner Beel of northwestern Bangladesh, employing a comprehensive array of length-based indicators. The study encompassed an investigation into population structure, growth parameters (including asymptotic length (L∞), asymptotic weight (W∞), growth coefficient (K), and age at zero length (t0)), mortality parameters, growth performance indices, recruitment pattern, exploitation rate (E), relative yield per-recruit (Y'/R), optimum catchable length (Lopt), longevity, biomass, and maximum sustainable yield (MSY). The TL and BW ranged from 5.00 to 16.20 cm and 0.49 g–17.20 g for males, and 7.80–18.80 cm and 1.25–29.75 g for females. The overall b value of LWR indicated positive allometric growth for both males and females. The size at first sexual maturity (Lm) was measured 9.74 cm for males and 11.16 cm for females in TL, while calculated age at first sexual maturity (tm) (year) was 0.83 for males and 0.84 for females. The L∞ and W∞ values were determined as 17.15 cm, 23.20 g for males and 19.86 cm, 41.40 g for females. Growth performance indices for males and females were found to be 2.26 and 2.60, respectively. The longevity of males and females was estimated at 4.84 and 4.76 years, respectively. Lopt values were recorded as 9.65 for males and 11.14 cm for females. Calculated M values were 0.95 year−1 for males and 0.97 year−1 for females, while F was determined as 1.29 year−1 and 1.51 year−1 for males and females, respectively. Total mortality (Z) was found to be 2.24 year−1 and 2.48 year−1 for male and female M. pancalus populations. The E were calculated at 58% and 61%, while the MSY indicated 46% and 49%, underscoring the need for a 12% reduction in fishing pressure for both males and females to prevent overexploitation. The findings offer valuable insights for the sustainable management of M. pancalus in the Gajner Beel and its surrounding habitats, underlining the urgency of conservation efforts.

Adoption of Resilient Climate Technologies for Crop Production to Mitigate Drought in Northwestern Bangladesh

Adoption of Resilient Climate Technologies for Crop Production to Mitigate Drought in Northwestern Bangladesh

Rice phenology and water requirements in Northwestern Bangladesh in the face of climate change

Rice phenology and water requirements in Northwestern Bangladesh in the face of climate change

Farmers Adaptation Strategies to Adverse Impacts of Drought on Agriculture of the Central Barind Tract of Bangladesh: An Empirical Study

Drought is a reoccurring phenomenon which is considered as one of the topmost slow-onset disasters in the central Barind Tract of northwestern Bangladesh. Due to the consequences of drought, agriculture of this area is highly impacted as well as the farmers fall in multidimensional livelihoods disruption. The objective of the paper is to investigate the existing adaptive measures practicing by farmers to combat adverse impacts of agricultural drought in two representative drought-prone locations of Rajshahi District of Bangladesh. The present study is mainly based on semi-structured household questionnaire survey. Eventually, the survey was conducted in 2019 among 303 households out of 1421 by using Kothari (2004) sampling formula considering 95% significance level and samples are determined through simple random sampling. Both descriptive and inferential statistics are used to analyze the adoption options of the cultivators of the study areas from geographical perspectives. It is found that most of the farmers adopted several measures rely on their traditional knowledge and experiences, participation in community trainings as well as receiving the facilities and support from different GOs and NGOs. Farmers are cultivating drought tolerant crop varieties, adopting rainwater harvesting, intercropping with rice, temporally changing occupation, using fertilizer and composting to accelerate crop production rate, changing irrigation system, participating in agro-training for coping with modern technologies, seeking to draw the compensation from GOs and microcredit of NGOs etc. to minimize drought impacts. However, the findings of present study are expected to provide useful guidelines to policy makers for facilitating farmers in sustaining their livelihoods against adverse impacts of agricultural drought in Barind Tract of Bangladesh.

Women-Led Climate Change Adaptation: A Study in Northwestern Bangladesh

Climate change has garnered widespread societal concern due to its yawning consequences on both the natural environment and human society. Consequently, the imperative for adaptation to climate change has become intensely entrenched in the collective psyche of humanity. Traditionally, women have played an indispensable role in climate adaptation processes, yet their invaluable contributions remain unfortunately disregarded and underrepresented. While contemporary financial assistance promotes women’s engagement in climate change adaptation, the coping strategies in real situations are widely varied and are significantly important to discuss. This study endeavors to rectify this gap by identifying and revealing the adaptive strategies of women in response to the vulnerabilities engendered by the multidimensional impacts of climate change. Thus, this study was conducted deploying a mixed research methodology combined with qualitative and quantitative approaches, particularly focus group discussions (FGD), household surveys, and key informant interviews (KII) across three villages in the Nilphamari district of Northwestern Bangladesh. The findings of this study reveal that women have made substantial contributions to adapting to the impacts of climate change through the execution of distinctive saving mechanisms. In facing adversities resulting from climate-induced losses, women exhibit a commendable capacity for adaptation by leveraging their accrued financial reserves as a robust and astute coping mechanism. This study suggests a broader replication of this approach to confront the impacts of climate change.

Patriarchal Challenges for Women Empowerment in Neoliberal Agricultural Development: A Study in Northwestern Bangladesh

Women are recognized as proactive catalysts for societal change in rural Bangladesh because of their significant socio-economic contributions to agricultural practices. Historically, they have been closely associated with various agricultural activities ranging from seed preservation to crop harvesting. Despite their vital role in the rural economy, women farmers have encountered a number of obstacles resulting from the adaptation of neoliberal agrarian policies. In recent decades, women’s participation in the agricultural sector has declined, which can be attributed to the influence of capitalist patriarchy on agricultural practices. Grounded on this argument, this present study aims to investigate a research question: What are the major challenges to women’s participation in agricultural practices in Bangladesh? In order to answer this question, data has been collected through in-depth interviews and household surveys from three villages of Jaldhaka Upazila in the Nilphamari district of northwestern Bangladesh. The findings of this paper argue that women’s participation in agriculture is challenged by the effects of the neoliberal policy perspective, such as the mechanization of agriculture, commercial land use, and land inequality, which continue to ratify patriarchy in agriculture. In such a situation, this study suggests women’s empowerment could be effectively facilitated by adopting agricultural policies that are specifically tailored to address gender dynamics, emphasizing the active engagement and meaningful representation of women in the processes of policy formulation and execution.

Early effects of the COVID-19 lockdown on children in north-western Bangladesh

ABSTRACT Using data collected through a structured telephone-based survey in north-western Bangladesh during the height of the pandemic, we present evidence on the effects of household specific shocks on rural children induced by the COVID-19 lockdowns. We focus on three child-related outcomes: time use of children during school closures, plans regarding children’s future schooling, and the incidence of child marriages. We find that respiratory illness and job loss experienced in the household lowered expectations of a child’s future school continuation and increased the probability of marriage-related discussions for girls. The return of a male migrant led to a reduction of children’s time spent doing paid work, while the return of a female migrant led to a reduction in children’s time spent caring for others and doing household chores. Our findings offer a cautionary tale regarding the potential long-term effects of the pandemic and school closures on girls in developing countries.

Implications of Changing Urban Land Use on the Livelihoods of Local People in Northwestern Bangladesh

Bangladesh is one of the emerging economies in the Global South, and rapid urbanization is the driving force behind its economic development. Urban growth and development are closely associated with land use/land cover changes in any area, which sometimes negatively affect the livelihood and wellbeing of local people. We investigated the impacts of urban land use changes on the local people of northwestern Bangladesh using Nilphamari Sadar as a case study site. In order to identify land use patterns and variations in land cover, a 10-year period of land use/land cover changes from 2000 to 2020 was monitored using satellite imagery and the supervised classification method. Primary data were collected through household surveys and focus group discussions. Our analysis suggests that land use has changed over the past 20 years in the study area. As a result, the land area under settlements has substantially increased from 19 square kilometers in 2000 to 48 square kilometers in 2020. Waterbodies were 24 square kilometers in 2010, dropping to 4 square kilometers in 2020, whereas croplands decreased to 218 square kilometers in 2020 from 259 square kilometers in 2000. These changes have proportionately and adversely affected the lives and livelihoods of the local people by altering their longstanding traditional livelihood options, limiting their access to common resources, failing to adapt to new environmental arrangements and economic structures, and creating new forms of vulnerability. We suggest that urban planning processes should consider local people’s interests with the entitlement of local and marginalized people to the benefits generated by urbanization.

A paleo-bioclimatological study on gondwana coal deposits in northwestern Bangladesh and the associated environment reflected by pollen and geochemical analysis

To comprehend the realistic paleo-bioclimate and depositional environment, we need to clearly grasp the methods that can be used to track paleoclimate in the past. The present research has focused on palynological investigation, X-ray Diffraction analysis, and elemental analysis of the core coal samples of the Gondwana coal of the Barapukuria Basin. The palynological study identifies two Palynoassemblage zones (Zone I and Zone II). A non-striate desiccate Scheuringipollenite, Crucisaccites, Parasaccites palynoassemblages are identified as Zone I and denotes as Lower Barakar Palynozone in the Early Permian where Zone II is dominated by striate desiccate Barakarites, Faunipollenites, Callumispora Palynoassemblages in the Late Permian. The Glossopterid plant family ruled the botanical affinity of Zone I and Zone II. It rendered the Gymnosperm group of plants as the rapid deglaciation assisted dissemination of Glossopteris flora. Higher percentages of clay minerals in X-ray diffraction (XRD) analysis and higher amounts of carbon content, lower sulfur, and higher C/S&gt;10 ratio in the elemental analysis have been identified. All evidence from the research suggests that coals were deposited when glaciers retreated in the Early Permian, and the Gymnosperm group of plants prevailed and accumulated in the warm and humid climatic conditions under the braided fluvial influence in the terrestrial environment. J. Asiat. Soc. Bangladesh, Sci. 49(1): 101-119, June 2023

Morpho-meristic characteristics and growth pattern of walking snakehead (Channa orientalis) collected from different locations of Northwestern Bangladesh

This study aimed to reveal the morphometric and meristic variations, length-weight relationships, and condition factor of Channa orientalis collected from three regions (Kurigram, Rangpur, and Lalmonirhat districts) of Northwestern Bangladesh. Fifteen morphometric and six meristic characteristics were selected. Eight morphometric characteristics were significantly different (p&lt;.05) among the regions; three characteristics were highly significant (p&lt;.001) in Kurigram (Pre-orbital distance, PrOD; Lower-jaw length, LJL; Upper-jaw length, UJL) indicating C. orientalis population of Kurigram was significantly different (p&lt;.001) from the other two locations. On the other hand, among six meristic characteristics, number of dorsal fin rays (DFR), pectoral fin rays (PFR), anal fin rays (AFR), and branchiostegal rays (BR) were found to be significantly different among three locations. The values of PFR varied significantly (p&lt;.05) in Kurigram, which distinguishes the other two regions. Likewise, DFR and BR showed significant variations in the Rangpur region, whereas AFR significantly (p&lt;.001) separated the Lalmonirhat population from the others. In length-weight relationships, the generalized relationship between total length (TL) and body weight (BW) were BW=0.007TL3.147 (r2=0.945), BW=0.03TL2.573 (r2=0.916) and BW=0.008TL3.084 (r2=0.899) for Kurigram, Rangpur, and Lalmonirhat, respectively. The growth pattern showed positive allometric in Kurigram (b=3.14) and Lalmonirhat (b=3.08). Negative allometric was observed in Rangpur (b=2.57). The study exhibited a higher condition factor (K) value in Kurigram (1.068) and Rangpur (1.049) whereas the lowest in Lalmonirhat (0.978). The study reveals that the C. orientalis population`s morpho-meristic and growth status were comparatively better in Kurigram region.

Simulation of water productivity of wheat in northwestern Bangladesh using multi-satellite data

Simulation of water productivity of wheat in northwestern Bangladesh using multi-satellite data

Application of novel binary optimized machine learning models for monthly streamflow prediction

Accurate measurements of available water resources play a key role in achieving a sustainable environment of a society. Precise river flow estimation is an essential task for optimal use of hydropower generation, flood forecasting, and best utilization of water resources in river engineering. The current paper presents the development and verification of the prediction abilities of new hybrid extreme learning machine (ELM)-based models coupling with metaheuristic methods, e.g., Particle swarm optimization (PSO), Mayfly optimization algorithm (MOA), Grey wolf optimization (GWO), and simulated annealing (SA) for monthly streamflow prediction. Prediction precision of standalone ELM model was compared with two-phase optimized state-of-the-arts models, e.g., ELM–PSO, ELM–MOA, ELM–PSOGWO, and ELM–SAMOA, respectively. Hydro-meteorological data acquired from Gorai and Padma Hardinge Bridge stations at Padma River Basin, northwestern Bangladesh, were utilized as inputs in this study to employ models in the form of seven different input combinations. The model’s performances are appraised using Nash–Sutcliffe efficiency, root-mean-square-error (RMSE), mean absolute error, mean absolute percentage error and determination coefficient. The tested results of both stations reported that the ELM–SAMOA and ELM–PSOGWO models offered the best accuracy in the prediction of monthly streamflows compared to ELM–PSO, ELM–MOA, and ELM models. Based on the local data, the ELM–SAMOA reduced the RMSE of ELM, ELM–PSO, ELM–MOA, and ELM–PSOGWO by 31%, 27%, 19%, and 14% for the Gorai station and by 29%, 27%, 19%, and 14% for Padma Hardinge bridge station, in the testing stage, respectively. In contrast, based on external data, ELM–PSOGWO improves in RMSE of ELM, ELM–PSO, ELM–MOA, and ELM–SAMOA by 20%, 5.1%, 6.2%, and 4.6% in the testing stage, respectively. The results confirmed the superiority of two-phase optimized ELM–SAMOA and ELM–PSOGWO models over a single ELM model. The overall results suggest that ELM–SAMOA and ELM–PSOGWO models can be successfully applied in modeling monthly streamflow prediction with either local or external hydro-meteorological datasets.