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Metrics on usage

As a global database, GEMStat data is regularly requested by a wide range of users from all over the world. In the following you find background information about data requests and our users.

Which countries and parameters are most requested?

The comparison of data requests (i.e. data provided to users by the GEMS/Water Data Centre) shows that in 2023 most data requests referred to data from Europe, followed by Asia and the Pacific, and Latin America and the Caribbean.

With respect to the type of parameters requested, in 2023 mostly chemical parameters were provided. The most requested parameter groups were inorganic compounds and nutrients.

What is the geographical and professional background of our users?

GEMStat data is requested by a wide range of countries and sectors. In 2023, most data requests came from Asia and the Pacific, followed by Europe, and North America. Most inquiries originated from academia and were made by students (including PhD students) and researchers. At regular intervals, however, we also received requests from industry and different types of organisations.

GEMStat citations in the literature:


Fendrich, AN, Ciais, P, Panagos, P et al. (2024). Including land management in a European carbon model with lateral transfer to the oceans. Environmental Research 245, 118014. doi:

Fleischmann, J, Birkel, C, Blechinger P et al. (2024). Guiding the data collection for integrated Water-Energy-Food-Environment systems using a pilot smallholder farm in Costa Rica. Energy Nexus 13, 100259. doi:

Graham, DJ, Bierkens, MFP & van Vliet MTH (2024). Impacts of droughts and heatwaves on river water quality worldwide. Journal of Hydrology 629, 130590. doi:

Jiang, P, Sun, S, Goh, SG et al. (2024). A Rapid Approach with Machine Learning for Quantifying the Relative Burden of Antimicrobial Resistance in Natural Aquatic Environments. Water Research, 122079. doi:

Kelly, MG, Teixeira, H, Lyche Solheim, A et al. (2024). Physico-chemical criteria to support Good Ecological Status in Europe. European Commission, Joint Research Centre, JRC136407. Publications Office of the European Union, Luxembourg. doi:

Kumar, S, Imen, S, Sridharan, VK et al. (2024). Perceived barriers and advances in integrating earth observations with water resources modeling. Remote Sensing Applications: Society and Environment 33, 101119. doi:

Lausch, A, Bannehr, L, Berger, SA et al. (2024). Monitoring Water Diversity and Water Quality with Remote Sensing and Traits. Remote Sensing 16(13), 2425. doi:

Liu, S, Hu, K, Xie, Z et al. (2024). Spatial-temporal change of river thermal environment and anthropogenic impact in China. Science of The Total Environment 929, 172697. doi:

Manfreda, S, Miglino, D, Saddi, KC et al. (2024). Advancing river monitoring using image-based techniques: challenges and opportunities. Hydrological Sciences Journal 69(6), 657-677. doi:

Micella, I, Kroeze, C, Bak, MP et al. (2024). Causes of coastal waters pollution with nutrients, chemicals and plastics worldwide. Marine Pollution Bulletin 198, 115902. doi:

Mukuyu, P, Warner, S, Chapman, DV et al. (2024). Innovations in water quality monitoring and management in Africa: towards developing an African Water Quality Program (AWaQ). International Water Management Institute, IWMI Working Paper 208. Published by the International Water Management Institute in Colombo, Sri Lanka. doi:

Naderian, D, Noori, R, Heggy, E et al. (2024). A water quality database for global lakes. Resources, Conservation and Recycling 202, 107401. doi:

Nkwasa, A, Chawanda, CJ, Nakkazi, MT et al. (2024). One Third of African Rivers Fail to Meet the ‘Good Ambient Water Quality’ Nutrient Targets. Available at Social Science Research Network (SSRN). doi:

Rydgård, M, Jensen, LS, Kroeze, C et al. (2024). Regionalised modelling of recycled fertiliser P in agricultural fields: Development of the life cycle inventory model PLCI 2.0. Journal of Cleaner Production 443, 141088. doi:

Wang, Q, Liu, G, Song, K et al. (2024). Comparison of Machine Learning Algorithms for Estimating Global Lake Clarity With Landsat TOA Data. IEEE Transactions on Geoscience and Remote Sensing 62, 1-14. doi:

Wen, Z, Wang, Q, Ma, Y et al. (2024). Remote estimates of suspended particulate matter in global lakes using machine learning models. International Soil and Water Conservation Research 12(1), 200-216. doi:

Zhou, C, Zhou, M, Peng, Y et al. (2024). Unexpected increase of sulfate concentrations and potential impact on CH4 budgets in freshwater lakes. Water Research 261, 122018. doi:


Arias-Rodriguez, LF, Tüzün, UF, Duan, Z et al. (2023). Global Water Quality of Inland Waters with Harmonized Landsat-8 and Sentinel-2 Using Cloud-Computed Machine Learning. Remote Sensing 15(5), 1390. doi:

Brendel, C, Capell, R & Bartosova, A (2023). To tame a land: Limiting factors in model performance for the multi-objective calibration of a pan-European, semi-distributed hydrological model for discharge and sediments. Journal of Hydrology: Regional Studies 50, 101544. doi:

Cacciatori, C, Mariani, G, Carollo, AM et al. (2023). The Gems of Water – How to become a gem of water? JRC133408, EUR 31486 EN, Publications Office of the European Union, Luxembourg. doi: 10.2760/334925

Chen, T, Liu, T, Wu, Z et al. (2023). Virus–pathogen interactions improve water quality along the Middle Route of the South-to-North Water Diversion Canal. The ISME Journal 17(10), 1719-1732. doi:

Chilton, J & Foster, S (2023). Long datasets for improved understanding, management and protection of groundwater. Hydrogeol J. 32, 347-352. doi:

de Waal, J, Miller, J & van Niekerk, A (2023). The impact of agricultural transformation on water quality in a data-scarce, dryland landscape—a case study in the Bot River, South Africa. Environ Monit Assess 195, 177(2023). doi:

Drechsel, P, Marjani Zadeh, S & Pedrero, F (2023). Water quality in agriculture: Risks and risk mitigation. Rome, FAO & IWMI. doi:

Graham, DJ, Bierkens, MFP & van Vliet, MTH (2023). Impacts of droughts and heatwaves on river water quality worldwide. Journal of Hydrology 629, 130590. doi:

Ibanez, C, Caiola, N, Barquin, J et al. (2023). Ecosystem-level effects of re-oligotrophication and N:P imbalances in rivers and estuaries on a global scale. Global Change Biology 29(5), 1248-1266. doi:

Jones, ER, Bierkens, MFP, van Puijenbroek, PJTM et al. (2023). Sub-Saharan Africa will increasingly become the dominant hotspot of surface water pollution. Nature Water, 1(7), 602-613. doi: 10.1038/s44221-023-00105-5

Jones, ER, Bierkens, MFP, Wanders, N et al. (2023). DynQual v1.0: a high-resolution global surface water quality model. Geosci. Model Dev., 16(15), 4481-4500. doi: 10.5194/gmd-16-4481-2023

Kaushal, SS, Likens, GE, Mayer, PM et al. (2023). The anthropogenic salt cycle. Nature Reviews Earth & Environment 4, 770-784(2023). doi:

Kelly, MG, Free, G, Kolada, A et al. (2023). Warding off freshwater salinization: Do current criteria measure up? WIREs Water, e1694. doi:

Khodamoradi Vatan, N, Mazaheri, M, Vali Samani, JM et al. (2023). Comparative evaluation and comparison of quality monitoring network of Iranʼs rivers with selected countries. Iranian Journal of Soil and Water Research 54(5), 737-751. doi:

Li, C, Smith, P, Bai, X et al. (2023). Effects of carbonate minerals and exogenous acids on carbon flux from the chemical weathering of granite and basalt. Global and Planetary Change 221, 104053. doi:

Maciel, DA, Pahlevan, N, Barbosa, CCF et al. (2023). Towards global long-term water transparency products from the Landsat archive. Remote Sensing of Environment 299, 113889. doi:

Misstear, B, Ruz Vargas, C, Lapworth, D et al. (2023). A global perspective on assessing groundwater quality. Hydrogeol J 31, 11–14 (2023). doi:

Murphy, J & Chanat, J (2023). Leveraging machine learning to automate regression model evaluations for large multi-site water-quality trend studies. Environmental Modelling & Software 170, 105864. doi:

Peker, İB & Gülbaz, S (2023). Examining the open-source datasets for water quantity and quality using the soil and water assessment tool (SWAT). Water Science and Technology, wst2023297. doi: 10.2166/wst.2023.297

Plisnier, PD, Kayada, R, MacIntyre, S et al. (2023). Need for harmonized long-term multi-lake monitoring of African Great Lakes. Journal of Great Lakes Research 49(6), 101988. doi:

Polcher, J, Schrapffer, A, Dupont, E et al. (2023). Hydrological modelling on atmospheric grids: using graphs of sub-grid elements to transport energy and water. Geoscientific Model Development 16, 2583-2606. doi:

Rose, JB, Hofstra, N, Hollmann, E et al. (2023). Global microbial water quality data and predictive analytics: Key to health and meeting SDG 6. PLOS Water 2(8), e0000166. doi:

Roudbari, MV, Dehnavi, A, Jamshidi, S et al. (2023). A multi-pollutant pilot study to evaluate the grey water footprint of irrigated paddy rice. Agricultural Water Management 282, 108291. doi:

Rupp, JM (2023). Trade Liberalization and Environmental Outcomes. MSc thesis at the Department of Social Science, New York University Abu Dhabi

Scanlon, BA, Fakhreddine, S, Rateb, A et al. (2023). Global water resources and the role of groundwater in a resilient water future. Nature Reviews Earth & Environment 4, 87–101 (2023). doi:

Schmidt, C, Bärlund, I, Batool, M et al. (2023). Improving global water quality information by combining in-situ data, remote sensing and modeling. EGU General Assembly 2023, Vienna, Austria, 24–28 Apr 2023, EGU23-13215. doi:


Sheikholeslami, R & Hall, JW (2023). Global patterns and key drivers of stream nitrogen concentration: A machine learning approach. Science of The Total Environment 868: 161623. doi:

Shimony, T, Teitelbaum, Y, Saavedra Cifuentes, E et al. (2023). Kaolinite Deposition Dynamics and Streambed Clogging During Bedform Migration Under Losing and Gaining Flow Conditions. Water Resources Research 59(9), e2023WR034792. doi:

Souza, AP, Oliveira, BA, Andrade, ML et al. (2023). Integrating remote sensing and machine learning to detect turbidity anomalies in hydroelectric reservoirs. Science of The Total Environment, 902, 165964. doi:

Ural-Janssen, A, Kroeze, C, Lesschen, JP et al. (2023). HOTSPOTS OF NUTRIENT LOSSES TO AIR AND WATER: AN INTEGRATED MODELING APPROACH FOR EUROPEAN RIVER BASINS. Front. Agr. Sci. Eng. 10(4), 579–592. doi:

Vlah, MJ, Bernhardt, ES, Rhea, S et al. (2023). Another Step Toward “Big” Catchment Science. Limnology and Oceanography Bulletin 32(4), 147-148. doi:

Wang, J, Liu, X, Beusen, AHW et al. (2023). Surface-Water Nitrate Exposure to World Populations Has Expanded and Intensified during 1970–2010. Environ. Sci. Technol. 2023 57(48), 19395–19406. doi:

Wen, Z, Wang, Q, Ma, Y et. al (2023). Remote estimates of suspended particulate matter in global lakes using machine learning models. International Soil and Water Conservation Research. doi:

Xu, A, Hathorne, E, Laukert, G et al. (2023). Overlooked riverine contributions of dissolved neodymium and hafnium to the Amazon estuary and oceans. Nature Communications 14, 4156 (2023). doi:

Zhou, J, Mogollon, JM, van Bodegom, PM et al. (2023). Effects of Nitrogen Emissions on Fish Species Richness across the World’s Freshwater Ecoregions. Environ. Sci. Technol. 57(22), 8347–8354. doi:


Amora, DJA, Apan, JV, Layosa, DNC, Sarmiento, RC, Tugado, JJ, et al. (2022): Soft Sensing Measurement of Dissolved Ammonia Nitrogen in Tank-Based Eel Aquaculture Systems Utilizing Deep Learning. 2022 IET International Conference on Engineering Technologies and Applications (IET-ICETA), Changhua, Taiwan,

Arora, NK, Mishra, I (2022):  Sustainable development goal 6: Global Water Security. Environmental Sustainability 5(3): 271-275,

Arsenault, J, Talbot, J, Brown, LE, Holden, J, Martinez-Cruz, K, et al. (2022): Biogeochemical Distinctiveness of Peatland Ponds, Thermokarst Waterbodies, and Lakes. Geophysical Research Letters 49(11),

Chapman, DV, Sullivan, T (2022): The role of water quality monitoring in the sustainable use of ambient waters. One Earth 5(2): 132-137,

Colohan, P, Onda, K (2022): Water data for water science and management: Advancing an Internet of Water (IoW). PLOS Water 1(3): e0000017,

Desbureaux, S, Mortier, F, Zaveri, E, van Vliet, MTH, Russ, J, et al. (2022): Mapping global hotspots and trends of water quality (1992–2010): a data driven approach. Environmental Research Letters 17: 114048,

Dzodzomenyo, M, Asamoah, M, Li, C, Kichana, E, Wright, J (2022): Impact of flooding on microbiological contamination of domestic water sources: a longitudinal study in northern Ghana. Applied Water Science 12: 235,

Ebeling, P, Kumar, R, Lutz, SR, Nguyen, T, Sarrazin, F, et al. (2022): QUADICA: water QUAlity, DIscharge and Catchment Attributes for large-sample studies in Germany. Earth System Science Data 14: 3715-3741,

Fendrich, AN, Ciais, P, Lugato, E, Carozzi, M, Guenet, B, et al. (2022): Matrix representation of lateral soil movements: scaling and calibrating CE-DYNAM (v2) at a continental level. Geoscientific Model Development 15: 7835-7857,

Garcia Usaga, JM (2022): Simulacion de la evolucion de los parametros fısico – quimicos del agua en las cuencas del departamento del Quindio, basada en redes complejas y ecuaciones en derivadas parciales. PhD thesis at the Universidad Nacional de Colombia.

Hall, CA, Saia, SM, Popp, AL, Dogulu, N, Schymanski, SJ, et al. (2022): A hydrologist’s guide to open science. Hydrology and Earth System Sciences 26: 647-664,

Jones, ER, Bierkens, MFP, Wanders, N, Sutanudjaja, EH, van Beek, LPH, et al. (2022): Current wastewater treatment targets are insufficient to protect surface water quality. Communications Earth & Environment 3: 1-8,

Kross, A, Kaur, G, Jaeger, JAG (2022): A geospatial framework for the assessment and monitoring of environmental impacts of agriculture. Environmental Impact Assessment Review 97: 106851,

Liu, S, Maavara, T, Brinkerhoff, CB, Raymond, PA (2022): Global Controls on DOC Reaction Versus Export in Watersheds: A Damköhler Number Analysis. Global Biogeochemical Cycles 36: e2021GB007278,

Lytvynenko, V, Yeremeyev, I, Dychko, A (2022): Risk-Oriented Approach to Assessment of Hexamethylenediamine Pollution of Aquatic Ecosystems. Ecological Engineering & Environmental Technology 23: 179-188,

Onda, K (2022): Water Data Infrastructure for Low- and Middle-Income Countries. Water Data Dialogues, Stanford Woods Institute for the Environment.

Pahlevan, N, Greb, S, Decker, A (2022): Earth Observation in Support of SDG 6.3.2/6.6.1: Reporting Surface Water Quality. In: Kavvada, A, Cripe, D, Friedl, L (eds.) Earth Observation Applications and Global Policy Frameworks, Geophysical Monograph 274. John Wiley & Sons, Inc.,

Pandit DN, Kumari, R, Shitanshu, SK (2022): A comparative assessment of the status of Surajkund and Rani Pond, Aurangabad, Bihar, India using overall Index of Pollution and Water Quality Index. Acta Ecologica Sinica 42: 149-155,

Peker, IB, Gülbaz, S (2022): Examining the Use of GEMStat Global Data Source for a Water Quality Model. IWA DIPCON 4th Regional Conference on Diffuse Pollution & Eutrophication, Istanbul, Turkey.

Pizani, FMC, Maillard, P (2022): The determination of water quality parameters by remote sensing: 2000-2020. Universidade Federal de Minas Gerais,

Plisnier, PD, Kayanda, R, MacIntyre, S, Obiero, K, Okello, W, et al. (2022): Need for harmonized long-term multi-lake monitoring of African Great Lakes. Article in Press,

Polcher, J, Schrapffer, A, Dupont, E, Rinchiuso, L, Zhou, X, et al. (2022): Hydrological modelling on atmospheric grids; using graphsof sub-grid elements to transport energy and water. EGUsphere Discussion,

Rajesh, M, Rehana, S (2022): Impact of climate change on river water temperature and dissolved oxygen: Indian riverine thermal regimes. Scientific Reports 12: 9222,

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Rotteveel, L, Sterling, SM (2022): The Surface Water Chemistry (SWatCh) database: A standardized global database of water chemistry to facilitate large-sample hydrological research. Earth System Science Data 14: 4667–4680,

Ruppen, D (2022): Effective Monitoring Strategies for Mining-Related Water Pollution. Doctoral thesis at ETH Zürich,

Russ, J, Zaveri, E, Desbureaux, S, Damania, R, Rodella AS (2022): The impact of water quality of GDP growth: Evidence from around the world. Water Security 17: 100130,

Simpson, G, Jewitt, GPW, Becker, W, Badenhorst, J, Neves, A, et al. (2022): The Water-Energy-Food Nexus Index: A Tool for Integrated Resource Management and Sustainable Development. Frontiers in Water 4: 825854,

Song, K, Wang, Q, Liu, G, Jacinthe, PA, Li, S, et al. (2022): A unified model for high resolution mapping of global lake (>1 ha) clarity using Landsat imagery data. Science of the Total Environment 810: 151188,

Wang, L, Lv, A (2022): Identification and Diagnosis of Transboundary River Basin Water Management in China and Neighboring Countries. Sustainability 14: 12360,

Wang, X, Wen, Z, Liu, G, Tao, H, Song, K, et al. (2022): Remote estimates of total suspended matter in China’s main estuaries using Landsat images and a weight random forest model. ISPRS Journal of Photogrammetry and Remote Sensing 183: 94-110,

Wen, Z, Wang, Q, Liu, G, Jacinthe, PA, Wang, X, et al. (2022): Remote sensing of total suspended matter concentration in lakes across China using Landsat images and Google Earth Engine. ISPRS Journal of Photogrammetry and Remote Sensing 187: 61-78,

Zhang, Y, Shi, K, Sun, X, Zhang, Y, Li, N, et al. (2022): Improving remote sensing estimation of Secchi disk depth for global lakes and reservoirs using machine learning methods. GIScience & Remote Sensing 59: 1367-1383,


Arias-Rodriguez, LF, Duan, Z, Diaz-Torres, JJ, Basilio Hazas, M, Huang, J, et al. (2021): Integration of Remote Sensing and Mexican Water Quality Monitoring System Using an Extreme Learning Machine. Sensors 21: 4118,

Gemmel, A, Sterckx, A, Ruz Vargas, C, Abrahams, E, Flügel, T, et al. (2021): Big Data Analytics and Transboundary Water Collaboration: Consolidation of Data and Application of Big Data Tools to Enhance National and Transboundary Data Sets in Southern Africa that Support Decision-Making for Security of Water Resources. WRC Report K5/2880. Water Research Commission, Pretoria, South Africa.

Heal KV, Bartosova A, Hipsey MR, et al. (2021): Water quality: the missing dimension of water in the water–energy–food nexus. Hydrological Sciences Journal: 1-14,

Hori, M (2021): Near-daily monitoring of surface temperature and channel width of the six largest Arctic rivers from space using GCOM-C/SGLI. Remote Sensing of Environment 263: 112538,

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Mamani Larico AJ, Rendón Dávila VO, Figueroa Tapia ÁM, et al. (2021): Bioenergetic and water quality modeling for eutrophication assessment of El Pañe Reservoir, Peru. Ecohydrology & Hydrobiology 21: 114-128,

Molina, MO (2021): Los datos sobre el agua en México en las plataformas de los organismos internacionales: paradigmas, actores y agendas. Consejo Nacional de Ciencia y Tecnología, Mexico-City, Mexico.

Pickens, A (2021): Dynamics of Global Surface Water 1999-present. PhD thesis, University of Maryland, USA.

Pinheiro, JPS, Windsor, FM, Wilson, RW, Tyler, CR (2021): Global variation in freshwater physico-chemistry and its influence on chemical toxicity in aquatic wildlife. Biological Reviews 96: 1528-1546,

Ridzuan, S (2021): Inequality and water pollution in India. Water Policy, 10,

Ruescas, A, Stelzer, K, Brockmann, K, Taylor, P, Dobel, A, et al. (2021): Lake Water Quality In-Situ Data – Requirements and Availability. Lake Water Quality Report EEA/DIS/R0/20/001 Lot 1, European Environment Agency.

Shukla T, Sen IS, Boral S, et al. (2021): A Time-Series Record during COVID-19 Lockdown Shows the High Resilience of Dissolved Heavy Metals in the Ganga River. Environmental Science & Technology Letters 8: 301-306,

Thorslund, J, Bierkens, MFP, Oude Essink, GHP, et al. (2021): Common irrigation drivers of freshwater salinisation in river basins worldwide. Nature Communications 12: 4232,

Topp, S (2021): Multidecadal Remote Sensing of Inland Water Dynamics. PhD thesis, University of North Carolina, USA.

Vega-Rodríguez MA, Pérez CJ, Reder K, et al. (2021): A stage-based approach to allocating water quality monitoring stations based on the WorldQual model: The Jubba River as a case study. Science of The Total Environment 762: 144162,

Virro H, Amatulli G, Kmoch A, et al. (2021): GRQA: Global River Water Quality Archive. Earth System Science Data Discussions 2021: 1-30,

Wu, J, Xu, N, Wang, Y, Zhang, W, Borthwick, AGL, et al. (2021): Global syndromes induced by changes in solutes of the world’s large rivers. Nature Communications 12: 5940,

Yang, D, Shrestha, RR, Lung, JLY, et al. (2021): Heat flux, water temperature and discharge from 15 northern Canadian rivers draining to Arctic Ocean and Hudson Bay, Global and Planetary Change 204: 103577,


Alvarez-Risco A, Del-Aguila-Arcentales S, Rosen MA (2020): Management of Water. In: Alvarez-Risco A, Rosen M, Del-Aguila-Arcentales S,  Marinova D (eds.) Building Sustainable Cities: Social, Economic and Environmental Factors: 217-230,

Antman, FM (2021): For Want of a Cup: The Rise of Tea in England and the Impact of Water Quality on Mortality. IZA Discussion Papers 15016,

Arreguin-Cortes FI, Saavedra-Horita JR, Rodriguez-Varela JM, et al. (2020): State level water security indices in Mexico. Sustainable Earth 3: 9,

Barik SK, Kar BB, Dixit PR, et al. (2020): Water Quality Index as a critical tool for an assessment of biodiversity of inland water ecosystem. Journal of Water Engineering 1: 44-54,

Carena L, Vione D (2020): Mapping the Photochemistry of European Mid-Latitudes Rivers: An Assessment of Their Ability to Photodegrade Contaminants. Molecules 25: 424,

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Elhag, M, Gitas, I, Othman, A, Bahrawi, J (2020): Effect of water surface area on the remotely sensed water quality parameters of Baysh Dam Lake, Saudi Arabia. Desalination and Water Treatment 194: 369-378,

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McDowell RW, Noble A, Pletnyakov P, et al. (2020): Global database of diffuse riverine nitrogen and phosphorus loads and yields. Geoscience Data Journal 00: 1-12,

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Musonge PSL (2020): Ecological Assessment of Rivers and Streams in the Rwenzori Region, Uganda. PhD thesis, Ghent University, Belgium.

Núñez M, Finkbeiner M (2020): A Regionalised Life Cycle Assessment Model to Globally Assess the Environmental Implications of Soil Salinization in Irrigated Agriculture. Environmental Science & Technology 54: 3082-3090,

Pandit DN, Kumari R, Shitanshu SK (2020): A comparative assessment of the status of Surajkund and Rani Pond, Aurangabad, Bihar, India using overall Index of Pollution and Water Quality Index. Acta Ecologica Sinica,

Polyakova K, Garanis L (2020): Building local indicators for more evidence-based policy making in the water and sanitation sector in Bomet county, Kenya. MSc thesis, University of Geneva, Switzerland.

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Topp SN, Pavelsky TM, Jensen D, et al. (2020): Research Trends in the Use of Remote Sensing for Inland Water Quality Science: Moving Towards Multidisciplinary Applications. Water 12: 169,


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Dallosch MA (2019): Optimal algorithms for deriving estimates of phytoplankton biomass in lakes from LANDSAT satellite imagery. MSc thesis, The University of Western Ontario, Canada.

Damania R, Desbureaux S, Rodella AS, Russ, J, Zaveri, E (2019): Quality Unknown: The Invisible Water Crisis. World Bank, Washington, D.C., USA,

Desbureaux, S, Damania, R, Rodella, AS, Russ, J, Zaveri, E (2019): The Impact of Water Quality on GDP Growth – Evidence from Around the World. World Bank, Washington, D.C., USA,

Evans AEV, Mateo-Sagasta J, Qadir M, Boelee, E, Ippolito, A (2019): Agricultural water pollution: key knowledge gaps and research needs. Current Opinion in Environmental Sustainability 36: 20-27,

Haque SJ, Onodera S-i, Shimizu Y (2019): Surface Water Nitrogen Load Due to Food Production-Supply System in South Asian Megacities: A Model-based Estimation. In: Al-Naggar AMM (ed): Advances and Trends in Agricultural Sciences.

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