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T."},{"honorificPrefix":"Professor","familyName":"Mashfiqus","givenName":"Salehin","organisationName":"Bangladesh University of Engineering and Technology","organisationIdentifier":"https://ror.org/05a1qpv97","role":"author","email":"msalehin1968@gmail.com","nameIdentifier":"https://orcid.org/0000-0002-1513-7240","fullName":"Mashfiqus, S."},{"honorificPrefix":"Dr","familyName":"Trinh","givenName":"Duc Anh","organisationName":"Vietnam Atomic Energy Instiute","organisationIdentifier":"https://ror.org/04jfns044","role":"author","email":"TRINHANHDUC@VINATOM.GOV.VN","nameIdentifier":"https://orcid.org/0000-0003-4207-8845","fullName":"Trinh, D.A."},{"honorificPrefix":"Dr","familyName":"Van","givenName":"Tri","organisationName":"Can Tho University","organisationIdentifier":"https://ror.org/0071qz696","role":"author","email":"vptri@ctu.edu.vn","fullName":"Van, T."},{"honorificPrefix":"Dr","familyName":"Do","givenName":"Nga Thu","organisationName":"Electric Power 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D.A.","Van, T.","Do, N.T.","Chowdhury, A.I.A.","Chanda, A.","Fielding, J.","Phan, T.","Henderson, A.","McGowan, S.","Brown, J.","Walker-Trivett, C.","Walton, R.","Banerjee, S.","Nguyễn, L.N.","Le, P.Q.T.","Duong, T.T.","Shil, S.","Bass, A.","Majumdar, M.A.","Rafi, N.N.","Shahariar, M.N.K.","Roberts, L.","Salgado Bonnet, J.","Sear, E.","Leadbeater, E.","Taylor, S.","Nam, T.S.","Large, A.","Smith, A."],"bibtex":"https://catalogue.ceh.ac.uk/documents/f311f69d-ecd2-4505-9882-e59d9b56852d/citation?format=bib","day":23,"doi":"10.5285/f311f69d-ecd2-4505-9882-e59d9b56852d","month":6,"publisher":"NERC EDS Environmental Information Data Centre","resourceTypeGeneral":"dataset","ris":"https://catalogue.ceh.ac.uk/documents/f311f69d-ecd2-4505-9882-e59d9b56852d/citation?format=ris","title":"Surface water quality data from rivers and ponds in the Mekong Delta, Red River Delta and Ganges Brahmaputra Meghna Delta, 2018-2024","url":"https://doi.org/10.5285/f311f69d-ecd2-4505-9882-e59d9b56852d","year":2026},"contactPoints":[{"displayName":"Virginia Panizzo","organisationName":"University of Nottingham","organisationIdentifier":"https://ror.org/01ee9ar58","role":"pointOfContact","email":"Virginia.Panizzo@nottingham.ac.uk","fullName":"Virginia Panizzo","pointOfContact":"University of Nottingham"}],"custodians":[{"organisationName":"NERC EDS Environmental Information Data Centre","organisationIdentifier":"https://ror.org/04xw4m193","role":"custodian","email":"info@eidc.ac.uk"}],"datasetReferenceDate":{"publicationDate":"2026-06-23","releasedDate":"2027-01-04"},"description":"This dataset contains water quality data across rivers and ponds in the Vietnamese Mekong River Delta (MRD), Vietnamese Red River Delta (RRD) and Bangladeshi and Indian Ganges Brahmaputra Meghna (GBM) Delta. The main objective of this work was to establish a baseline database for water quality, covering a wide range of water quality parameters to address emerging environmental concerns, such as anti-microbial resistance for the Bangladeshi Ganges Brahmaputra Meghna Delta. The available data are separated by delta, and are listed below.\n\nBangladeshi GBM\nThree datasets are available: river water quality, pond water quality, and phytoplankton biomonitoring.\nOne river water quality dataset is available, containing point measurements from February 2022 to February 2024 at 11 pre-selected locations of four rivers in the coastal areas of the Bangladeshi GBM. Each of the 4 rivers were sampled 5 times over different seasons. Daily measurements (during each of the 5 sampling periods) include 6-7 samples per site (from morning until 19.00).\nTwo separate pond water quality datasets are available:\n(1) The first ponds dataset contains point measurements of 40 ponds in September 2023 and March 2024. Available data and information include the site location and context - including user and use information (occupation, water source, etc.), physical properties (surface area, depth, etc.), context (region, adjacent buildings, urban setting), and treatment regimes. Available water chemistry data include temperature, pH, total suspended solids, total phosphorus, soluble reactive phosphorus, phosphate, ammonium, nitrate, silia, Δ13c, particulate organic carbon, total dissolved nitrogen, C:N, chloride, sulphate, sodium, potassium, calcium, magnesium, dissolved oxygen, SPC, alkalinity, rugged dissolved oxygen, electrical conductivity, turbidity, total coliforms, E. Coli, algal pigments, and sediment chemistry. Additionally, pond depth water chemistry profiles - including water body stratification depths and pycnoclines - are available for 39/40 ponds in September 2023.\n(2) The second ponds dataset contains point measurements of 20 ponds and groundwater tubewells from Gabura, Satkhira and South Bedkashi, Khulna from February 2022 to February 2024. Tubewells were sampled 5 times (once per day) during the same sampling period as the river water quality dataset. Parameters here include water quality variables (pH, conductivity, turbidity), microbial indicators, and selected emerging contaminants.\nOne phytoplankton biomonitoring dataset is available for 8 pond and stream sites from February-March 2022. Each sampling site has a variable number of diatom species. Measurements include concentration (number per ml), biovolume and mean cell biovolume. \n\nIndian GBM\nThree datasets are available: river water quality, pond water quality, and phytoplankton biomonitoring.\nOne river water quality monitoring dataset seasonal water quality measurements collected from multiple sampling stations across the Indian Sundarbans region. The dataset includes physicochemical, biological, and bacteriological parameters, measured under high tide and low tide conditions across nine seasonal campaigns (2021-2024). The data support environmental monitoring, estuarine studies, and biogeochemical assessments.\nOne pond water quality dataset includes point measurements from 29 ponds in the Indian GBM in three sampling periods: July 2024, December 2023 and March 2024. Data include details of the site location, context (i.e. region), user and use information, water chemistry (salinity, temperature, pH, total alkalinity, oxidation-reduction potential, dissolved oxygen, secchi depth, total dissolved solids, total phosphorus, phosphate anions, soluble reactive phosphorus, nitrate anions, total Kjedahl nitrogen, ammoniacal nitrogen, silicate, total suspended solids, conductivity, absolute conductivity, chloride anions, sodium cations, potassium cations, calcium cations, magnesium cations, sulphate anions, dissolved silica, Chl A, Chl B, Chl C, total Chl, carotenoid, total coliform and E Coli.\nOne phytoplankton biomonitoring dataset is available for 20 sites in 3 time periods - both low and high tide for December 2021, July 2022, and March 2023. Data include concentration and biovolumes, concentrations per 1 mL, concentrations per 10 mL, biovolume per 1 mL, and biovolume per 10 mL for 48 diatom species.\n\nRRD\nThree datasets are available for the Vietnamese Red River Delta: two river surface water quality datasets, and one surface pond water quality datasets.\nThe first dataset contains monthly water chemistry data in the RRD from March 2018 to February 2022. The data include pH, TDS, Ca2+, Mg2+, Na+, K+, HCO3-, SiO2, Cl-, and SO42-. Data collected at five stations namely Yen Bai, Vu Quang, Hoa Binh, Gian Khau, and Quyet Chien.\nThe Red River Delta is both a densely populated region and an area of intensive agricultural activity, implying significant potential for pollution. To provide a comprehensive assessment of water quality across the delta and evaluate the impacts of different human activities, we conducted monthly sampling at 22 sites throughout the region. These sites are strategically located across diverse land-use types and at the confluences of major rivers-including the Red, Day, and Nhue rivers-and their tributaries, enabling us to trace potential sources of pollution within the area.\nWithin the second dataset, the following data are available:\n-\tStable isotopes (July 2019-March 2024)\n-\tOrganic content - dissolved organic carbon, dissolved inorganic carbon & particulate organic carbon (July 2019-March 2024)\n-\tPhysiochemistry - temperature, dissolved oxygen, salinity, oxidation reduction potential, pH, turbidity, conductivity, total dissolved solid and total suspended solids (July 2019-March 2024)\n-\tMajor ions (Na, Mg, K, Ca, Cl, SO4, B; July 2019-March 2024)\n-\tNutrients (NO3-N, NO2-N, NH4-N, total nitrogen, soluble reactive phosphorus, TSP, total phosphorus, SIO2 & alkalinity; July 2019-March 2024)\n-\tWater discharge (01-01-2014 to 31-12-2023)\n-\tQuantitative phytoplankton for (1) the Red River (December 2019-March 2024) and (2) the Day River (July 2019-March 2024).\nLastly, one dataset containing water and sediment chemistry of 37 ponds in March 2023 is available. This includes pond user and use information, and water and sediment quality parameters for 37 sampling locations in 36 ponds in the Red River Delta taken in March 2023. The data include details of the site location, pond physical properties (i.e. age, surface area, depth), context (i.e. region, adjacent buildings, urban setting), use information (i.e. agricultural, water source), treatment regimes, water chemistry (i.e. Temp, pH, Secchi depth, Total Suspended Solids, Total Phosphorus, Soluble Reactive Phosphorus, Total Nitrogen, Nitrite, Nitrate, Ammonium, Nitrate δ15N/ δ18O, Aquatic Si, Δ13C, Particulate Organic Carbon, Dissolved Organic Carbon, Total Dissolved Nitrogen, C:N, Chloride anions, Sulphate anion, dissolved oxygen, SPC), algal pigments, and sediment chemistry.\n\nMRD\nTwo datasets are available for the Vietnamese Mekong River Delta. The first includes water quality monitoring of surface water in October 2021 in three provinces: Ca Mau, Soc Trang and Kien Giang.  Parameters include physiochemical and microbiological water quality measurements, including Ammonium (NH4+), BOD5, COD, Chloride (Cl-), DO, E. coli, Nitrate (NO3-), Nitrite (NO2-), pH, Phosphate (PO43-), Temperature (°C), Total Coliform, Total Iron (Fe), TSS, Turbidity (NTU). The total number of sampling sites is 126 across Soc Trang (N = 35), Kien Giang (N = 49) and Ca Mau (N = 42). \nThe second dataset includes further surface water quality monitoring and water quality index metric in Soc Trang and Ca Mau provinces. Cà Mau includes data from 52 stations (NM-01 to NM-52) sampled during dry and wet seasons (coded as Season 1 and Season 2) from 2015 to 2020. Sóc Trăng includes data from 21 stations (coded M1 to M21) sampled annually from 2014 to 2018. The stations cover diverse water environments including freshwater and brackish water systems. Parameters measured include field parameters (pH, temperature, dissolved oxygen, electrical conductivity), organic pollution indicators (BOD5, COD), nutrients (N-NH4, P-PO4), solids (TSS, Turbidity), metals (Fe, Hg, As, Cu etc.), anions (Cl-, SO4-), salinity, total coliform, and petroleum hydrocarbons. A Water Quality Index (WQI) derived from an Artificial Neural Network (ANN), is also calculated for most samples.","distributionFormats":[{"name":"Comma-separated values (CSV)","type":"text/csv","version":"unknown"}],"distributorContacts":[{"organisationName":"NERC EDS Environmental Information Data Centre","organisationIdentifier":"https://ror.org/04xw4m193","role":"distributor","email":"info@eidc.ac.uk"}],"funding":[{"funderName":"Natural Environment Research Council","funderIdentifier":"https://ror.org/02b5d8509","awardTitle":"UKRI GCRF Living Deltas Hub","awardNumber":"NE/S008926/1","awardURI":"https://gtr.ukri.org/projects?ref=NE%2FS008926%2F1","orcid":false,"ror":true}],"hasOnlineServiceAgreement":true,"id":"f311f69d-ecd2-4505-9882-e59d9b56852d","incomingCitationCount":0,"inspireThemes":[{"theme":"Environmental Monitoring Facilities","uri":"http://inspire.ec.europa.eu/theme/ef"}],"keywordsOther":[{"value":"Red River Delta"},{"value":"Vietnam"},{"value":"Mekong River Delta"},{"value":"Ganges Brahmaputra Meghna Delta"},{"value":"India"},{"value":"Bangladesh"},{"value":"river","uri":"http://www.eionet.europa.eu/gemet/concept/7244"},{"value":"pond","uri":"http://www.eionet.europa.eu/gemet/concept/6507"},{"value":"discharge regime","uri":"http://www.eionet.europa.eu/gemet/concept/2227"},{"value":"artificial neural network"},{"value":"surface water"},{"value":"monitoring"},{"value":"Ca Mau"},{"value":"Soc Trang"},{"value":"Kien Giang"},{"value":"nutrient","uri":"http://www.eionet.europa.eu/gemet/concept/5763"},{"value":"heavy metal","uri":"http://www.eionet.europa.eu/gemet/concept/3915"},{"value":"coliform bacterium","uri":"http://www.eionet.europa.eu/gemet/concept/1561"},{"value":"water quality index"},{"value":"time series"},{"value":"major ions"},{"value":"inorganic geochemistry"},{"value":"organic geochemistry"},{"value":"phytoplankton biochemistry"},{"value":"major ion geochemistry"},{"value":"major ions"},{"value":"pH"},{"value":"total dissolved solids"},{"value":"total coliform"},{"value":"physicochemical"},{"value":"BOD"},{"value":"COD"},{"value":"dissoved oxygen"},{"value":"E. coli"},{"value":"nutrient","uri":"http://www.eionet.europa.eu/gemet/concept/5763"},{"value":"Sundarbans"},{"value":"estuarine monitoring"},{"value":"seasonal dataset"},{"value":"tidal sampling"},{"value":"carbon flux"},{"value":"mangrove ecosystem"},{"value":"groundwater","uri":"http://www.eionet.europa.eu/gemet/concept/3780"},{"value":"baseline study"},{"value":"antimicrobial resistance"}],"keywordsTheme":[{"value":"Water quality","uri":"http://onto.nerc.ac.uk/CEHMD/topic/16"},{"value":"Pollution","uri":"http://onto.nerc.ac.uk/CEHMD/topic/15"},{"value":"Environmental survey","uri":"http://onto.nerc.ac.uk/CEHMD/topic/7"},{"value":"Environmental risk","uri":"http://onto.nerc.ac.uk/CEHMD/topic/5"},{"value":"Hydrology","uri":"http://onto.nerc.ac.uk/CEHMD/topic/9"}],"licences":[{"value":"This resource is available under the terms of the Open Government Licence","code":"license","uri":"https://eidc.ac.uk/licences/ogl/plain"}],"lineage":"Bangladeshi GBM\nSamples from the first pond water quality dataset were generated through sonde and laboratory analyses. Pond depth water chemistry profiles were collected through sonde measurements.\nSamples from the second pond water quality dataset and river water quality dataset were collected using standard water sampling protocols for rivers and tubewells - including in-situ measurements of temperature and conductivity and the collection of samples in pre-cleaned sterilised containers for subsequent laboratory analyses. Samples were analysed during standard probes and laboratory equipment. \nPhytoplankton biomonitoring data were obtained using the phytoplankton submerged bottle method, sedimentation chambers were used for analyses using the Utermohl method. Pigment data are currently being processed and the data are forthcoming.\n\nIndian GBM\nThe river water quality dataset samples were collected from Water Sampling Points (WSPs) across the Indian Sundarbans region, extending from Diamond Harbour to Hingalganj. Initially 20 stations (M21-PRM22), later expanded to 23 stations (from M22 onwards). Seasonal sampling incorporates three periods: pre-monsoon, monsoon and post-monsoon and 9 seasonal campaigns between 2021-2024. Each sampling period contains high tide and low tide measurements. Measurements were conducted using a multiparameter probe (pH, DO, conductivity, salinity, temperature, ORP), LI-COR LI-8x0 IRGA (CO₂ flux and pCO₂), anemometer (wind velocity), and Secchi disk (water transparency). Water samples were collected in sealed bottles and preserved immediately using appropriate reagents: HgCl₂ / H₂SO₄ for nutrients; Lugol's iodine for chlorophyll-a. Separate containers were used for bacteriological and chemical analysis. Laboratory analyses were conducted following APHA Standard Methods for nutrients, major ions, and bacteriological parameters (MPN method). Samples from the pond water quality dataset were generated through sonde measurements and standard laboratory analyses. Phytoplankton biomonitoring data were obtained used the filled bottle method, and analysed using Lund cell repeats.\n\nRRD\nWater samples from 22 selected sites across the Red River Delta were collected monthly. The samples were then analysed in the laboratory on the same day or within 24 hours of collection. When immediate analysis was not possible, they were stored under refrigerated or frozen conditions to preserve sample integrity, in accordance with Vietnamese standards. Physico-chemical parameters (pH, total dissolved solids [TDS]) were measured in-situ by a Hydrolab sonde DS5. Each sample was analysed in the laboratory for major cations (Ca2+, Mg2+, Na+, and K+), major anions (Cl- , SO4 2- and HCO3 - ) and dissolved silica (SiO2). Pond water chemistry data were collected with a YSI EXO probe.\n\nMRD\nFor the water quality monitoring dataset, surface water grab samples collected at field sites and transported to Can Tho University laboratory (Dept. of Environmental Sciences) for analysis. Temperature and DO measured in-situ. All analyses conducted per Vietnamese national standards (TCVN) on 25 October 2021 and certified by Head of Laboratory. \nFor the second water quality monitoring and water quality index dataset, the field procedures for surface water sampling, preservation, and transportation strictly adhere to TCVN 6663-3:2016 and associated framework standards (TCVN 6663-1:2011, 6663-4:2018, 6663-6:2018, and 8880:2011) to guarantee sample integrity. Methodologically, this entails the immediate in-situ measurement of physicochemical parameters, filtration of dissolved constituents through 0.45 µm membranes, and the application of parameter-specific chemical preservatives. All collected samples were subsequently stored in dark, insulated conditions at 3°C ± 2°C and transported to the analytical facility within a 24-hour window, accompanied by a comprehensive Chain of Custody (CoC) record. Surface water sampling was conducted in strict accordance with Vietnamese standard TCVN 6663-6:2018. Sampling locations were selected in areas with stable flow, representative of the overall water quality of the water body, with the container opening facing against the current to avoid local contamination. Samples were collected at a depth of 0.2m to 0.5m to eliminate the influence of surface scum and bottom sediments. Immediately after collection, rapidly changing parameters (pH, DO, EC, temperature) were measured in the field. Concurrently, samples were filtered, preserved with specialized chemicals, and stored under cold conditions (1°C to 5°C) during transport to the laboratory.","metadataDate":"2026-07-25T18:05:51","notGEMINI":false,"publicationDate":"2026-06-23T00:00:00.000Z","publishers":[{"organisationName":"NERC EDS Environmental Information Data Centre","organisationIdentifier":"https://ror.org/04xw4m193","role":"publisher","email":"info@eidc.ac.uk"}],"resourceIdentifiers":[{"code":"https://catalogue.ceh.ac.uk/id/f311f69d-ecd2-4505-9882-e59d9b56852d"},{"code":"10.5285/f311f69d-ecd2-4505-9882-e59d9b56852d","codeSpace":"doi"}],"resourceType":{"value":"dataset"},"rightsHolders":[{"organisationName":"Newcastle University","organisationIdentifier":"https://ror.org/01kj2bm70","role":"rightsHolder"}],"spatialReferenceSystems":[{"code":"http://www.opengis.net/def/crs/EPSG/0/4326","title":"WGS 84"},{"code":"https://epsg.io/32648","title":"UTM Zone 48N"}],"spatialRepresentationTypes":["textTable"],"temporalExtents":[{"begin":"2014-01-01","end":"2024-02-29"}],"title":"Surface water quality data from rivers and ponds in the Mekong Delta, Red River Delta and Ganges Brahmaputra Meghna Delta, 2018-2024","topicCategories":[{"value":"environment","uri":"http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/environment"},{"value":"inlandWaters","uri":"http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/inlandWaters"},{"value":"geoscientificInformation","uri":"http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/geoscientificInformation"},{"value":"biota","uri":"http://inspire.ec.europa.eu/metadata-codelist/TopicCategory/biota"}],"topics":["http://onto.nerc.ac.uk/CEHMD/topic/16","http://onto.nerc.ac.uk/CEHMD/topic/15","http://onto.nerc.ac.uk/CEHMD/topic/7","http://onto.nerc.ac.uk/CEHMD/topic/5","http://onto.nerc.ac.uk/CEHMD/topic/9"],"type":"dataset","uri":"https://catalogue.ceh.ac.uk/id/f311f69d-ecd2-4505-9882-e59d9b56852d","useConstraints":[{"value":"This resource is available under the terms of the Open Government Licence","code":"license","uri":"https://eidc.ac.uk/licences/ogl/plain"}]}