From a test case to a trusted tool: Lithuania’s evolving SWAT system for water and agricultural management

Main Article Content

Svajunas Plunge
Mikołaj Piniewski


Keywords : modelling system, model management, water management, institution, decision support
Abstract

Lithuania’s development of the river modelling system (RMS) exemplifies an institutional development and application of integrated modelling for water and agricultural management. What started as a test case, continued to develop focusing on environmental compliance with the EU regulations. Currently, the RMS is a part of decision-making. By incorporating the soil and water assessment tool (SWAT) model and comprehensive data sources, the system facilitates in-depth analysis and policy formulation. Applications in water management plans, pollution assessments, and climate change studies demonstrate the reliability of RMS. Despite data quality and skill retention challenges, institutional commitment and collaboration ensure the RMS’s persistence. This experience emphasizes the value of sustained investment in integrated modelling systems for achieving sustainable environmental governance and signifies Lithuania’s shift towards data driven green transition practices.

Article Details

How to Cite
Plunge, S., & Piniewski, M. (2024). From a test case to a trusted tool: Lithuania’s evolving SWAT system for water and agricultural management. Scientific Review Engineering and Environmental Sciences (SREES), 33(2), 115–130. https://doi.org/10.22630/srees.9790
References

Andersson, A., Brady, M. V., & Pohjola, J. (2022). How unnecessarily high abatement costs and unresolved distributional issues undermine nutrient reductions to the Baltic Sea. Ambio, 51 (1), 51–68. https://doi.org/10.1007/s13280-021-01580-4 (Crossref)

Aplinkos apsaugos agentūra [AAA], (2009). Pažyma dėl SWAT modelio panaudojimo galimybių paviršinio vandens telkinių būklės modeliavimui.

Aplinkos apsaugos agentūra [AAA], (2021). 2022–2027 m. upių baseinų rajonų valdymo planų ir priemonių programų projektai. https://aaa.lrv.lt/lt/veiklos-sritys/vanduo/upes-ezerai-ir-tvenkiniai/vandens-valdymas-upiu-baseinu-rajonu-principu/2022-2027-m-upiu-baseinu-rajonu-valdymo-planai-ir-priemoniu-programos/

Aplinkos apsaugos agentūra [AAA], (2022). Apibendrinta Lietuvos aplinkos būklės ir jos pokyčių ataskaita 2021 m. https://aaa.lrv.lt/uploads/aaa/documents/files/leidinys%20ataskaita_SPAUDA11(1).pdf

Aplinkos apsaugos agentūra [AAA], (2024). Lietuvos Respublikos upių, ežerų ir tvenkinių kadastras. https://uetk.biip.lt/

Arnold, J. G., Bieger, K., White, M. J., Srinivasan, R., Dunbar, J. A., & Allen, P. M. (2018). Use of decision tables to simulate management in SWAT+. Water, 10 (6), 713. https://doi.org/10.3390/w10060713 (Crossref)

Arnold, J., Srinivasan, R., Muttiah, R. S., & Williams, J. R. (1998). Large area hydrologic modeling and assessment part I: model development. JAWRA Journal of the American Water Resources Association, 34 (1), 73–89. https://doi.org/10.1111/j.1752-1688.1998.tb05961.x (Crossref)

Arnold, T., Guillaume, J. H. A., Lahtinen, T. J., & Vervoort, R. W. (2020). From ad-hoc modelling to strategic infrastructure: A manifesto for model management. Environmental Modelling & Software, 123, 104563. https://doi.org/10.1016/j.envsoft.2019.104563 (Crossref)

Bärlund, I., Kirkkala, T., Malve, O., & Kämäri, J. (2007). Assessing SWAT model performance in the evaluation of management actions for the implementation of the Water Framework Directive in a Finnish catchment. Environmental Modelling & Software, 22 (5), 719–724. https://doi.org/10.1016/j.envsoft.2005.12.030 (Crossref)

Bieger, K., Arnold, J. G., Rathjens, H., White, M. J., Bosch, D. D., & Allen, P. M. (2019). Representing the connectivity of upland areas to floodplains and streams in SWAT+. JAWRA Journal of the American Water Resources Association, 55 (3), 578–590. https://doi.org/10.1111/1752-1688.12728 (Crossref)

Bieger, K., Arnold, J. G., Rathjens, H., White, M. J., Bosch, D. D., Allen, P. M., Volk, M., & Srinivasan, R. (2017). Introduction to SWAT+, a completely restructured version of the soil and water assessment tool. JAWRA Journal of the American Water Resources Association, 53 (1), 115–130. https://doi.org/10.1111/1752-1688.12482 (Crossref)

Borah, D. K., Yagow, G., Saleh, A., Barnes, P. L., Rosenthal, W., Krug, E. C., & Hauck, L. M. (2006). Sediment and nutrient modeling for TMDL development and implementation. Transactions of the ASABE, 49 (4), 967–986. https://doi.org/10.13031/2013.20782 (Crossref)

Brady, M. V., Andersen, M. S., Andersson, A., Kilis, E., Saarela, S.-R., & Thorsøe, M. H. (2021). Strengthening the policy framework to resolve lax implementation of the Baltic Sea Action Plan for agriculture. Ambio, 51 (1), 69–83. https://doi.org/10.1007/s13280-021-01573-3 (Crossref)

Carstensen, M. V., Molina-Navarro, E., Hashemi, F., Kronvang, B., & Bieger, K. (2023). Modelling the impact of the Nordic Bioeconomy Pathways and climate change on water quantity and quality in a Danish River Basin. Catena, 222, 106795. https://doi.org/10.1016/j.catena.2022.106795 (Crossref)

Center for Agricultural and Rural Development and Iowa State University (2023). SWAT literature database for peer-reviewed journal articles. https://www.card.iastate.edu/swat_articles

Chataut, G., Bhatta, B., Joshi, D., Subedi, K., & Kafle, K. (2023). Greenhouse gases emission from agricultural soil: a review. Journal of Agriculture and Food Research, 11, 100533. https://doi.org/10.1016/j.jafr.2023.100533 (Crossref)

Council Directive 91/676/EEC of 12 December 1991 concerning the protection of waters against pollution caused by nitrates from agricultural sources (OJ L 375, 31.12.1991, pp. 1–8). https://eur-lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:31991L0676&from=EN

Čerkasova, N. (2019). Nemunas River watershed input to the Curonian Lagoon: discharge, microbiological pollution, nutrient and sediment loads under changing climate (doctoral dissertation). Klaipėda University.

Čerkasova, N., Mėžinė, J., Idzelytė, R., Lesutienė, J., Erturk, A., & Umgiesser, G. (2024). Modeling climate change uncertainty and its impact on the Nemunas River Watershed and Curonian Lagoon Ecosystem. EGUsphere, 2024, 1–28. https://doi.org/10.5194/egusphere-2024-890 (Crossref)

Čerkasova, N., Umgiesser, G., & Ertürk, A. (2018). Development of a hydrology and water quality model for a large transboundary river watershed to investigate the impacts of climate change – A SWAT application. Ecological Engineering, 124, 99–115. https://doi.org/10.1016/j.ecoleng.2018.09.025 (Crossref)

Čerkasova, N., Umgiesser, G., & Ertürk, A. (2021). Modelling framework for flow, sediments and nutrient loads in a large transboundary river watershed: A climate change impact assessment of the Nemunas River watershed. Journal of Hydrology, 598, 126422. https://doi.org/10.1016/j.jhydrol.2021.126422 (Crossref)

Danish Hydraulic Institute Water & Environment (2003). MIKE BASIN 2003. A versatile decision support tools for the integrated water resources management planning. Guide to getting started tutorial. https://www.iemss.org/iemss2006/papers/w5/MB-manual.pdf

Directive 2000/60/EC of The European Parliament and of the Council of 23 October 2000 establishing a framework for community action in the field of water policy (OJ L 327, 22.12.2000, pp. 1–73). https://eur-lex.europa.eu/resource.html?uri=cellar:5c835afb-2ec6-4577-bdf8-756d3d694eeb.0004.02/DOC_1&format=PDF

Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks (OJ L 288, 6.11.2007, pp. 27–34). https://eur-lex.europa.eu/eli/dir/2007/60/oj

Directive 2008/56/EC of the European Parliament and of the Council of 17 June 2008 establishing a framework for community action in the field of marine environmental policy (OJ L 164, 25.6.2008, pp. 19–40). https://eur-lex.europa.eu/eli/dir/2008/56/oj

Directive 2011/92/EU of the European Parliament and of the Council of 13 December 2011 on the assessment of the effects of certain public and private projects on the environment (OJ L 26, 28.1.2012, pp. 1–21). https://eur-lex.europa.eu/eli/dir/2011/92/oj

European Environment Agency [EEA], (2018). European waters. Assessment of status and pressures 2018. EEA Report No 7/2018. Publications Office of the European Union. https://www.eea.europa.eu/publications/state-of-water

European Environment Agency [EEA], (2020). Water and agriculture: towards sustainable solutions. EEA Report No 17/2020. Publications Office of the European Union. https://www.eea.europa.eu/publications/water-and-agriculture-towards-sustainable-solutions/at_download/file

https://www.eea.europa.eu/publications/water-and-agriculture-towards-sustainable-solutions

European Environment Agency [EEA], (2024). WISE SoE – Emissions (WISE-1). https://dd.eionet.europa.eu/datasets/3351

European Commission (2024). Integrated water management in Lithuania. https://webgate.ec.europa.eu/life/publicWebsite/project/LIFE22-IPE-LT-LIFE-SIP-Vanduo-101104645/integrated-water-management-in-lithuania

Evans, A. E., 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. https://doi.org/10.1016/j.cosust.2018.10.003 (Crossref)

Food and Agriculture Organization of the United Nations [FAO], (2013). Guidelines to control water pollution from agriculture in China. https://www.fao.org/3/i3536e/i3536e.pdf

Food and Agriculture Organization of the United Nations [FAO], (2017). Water pollution from agriculture: a global review. https://www.fao.org/3/i7754e/i7754e.pdf

Fu, B., Horsburgh, J. S., Jakeman, A. J., Gualtieri, C., Arnold, T., Marshall, L., Green, T. R., Quinn, N. W. T., Volk, M., Hunt, R. J., Vezzaro, L., Croke, B. F. W., Jakeman, J. D., Snow, V., & Rashleigh, B. (2020). Modeling water quality in watersheds: from here to the next generation. Water Resources Research, 56 (11), e2020WR027721. https://doi.org/10.1029/2020wr027721 (Crossref)

Gassman, P. W., Sadeghi, A. M., & Srinivasan, R. (2014). Applications of the SWAT Model Special Section: overview and insights. Journal of Environmental Quality, 43 (1), 1–8. https://doi.org/10.2134/jeq2013.11.0466 (Crossref)

Gassman, P. W., & Yingkuan, W. (2015). IJABE SWAT Special Issue: Innovative modeling solutions for water resource problems. International Journal of Agricultural and Biological Engineering, 8 (3), 1–8. https://doi.org/10.3965/j.ijabe.20150803.1763

Gudas, M., & Plunge, S. (2021). Klimato kaitos poveikis Lietuvos paviršiniams vandens telkiniams. https://vanduo.old.gamta.lt/files/report.html

Heathwaite, A. L. (2010). Multiple stressors on water availability at global to catchment scales: understanding human impact on nutrient cycles to protect water quality and water availability in the long term. Freshwater Biology, 55 (s1), 241–257. https://doi.org/10.1111/j.1365-2427.2009.02368.x (Crossref)

HELCOM. (2023a). Nutrient Input Ceiling (NIC) assessment 1995–2020 – Technical report. https://helcom.fi/wp-content/uploads/2023/12/Nutrient-Input-Ceilings-assessment-1995-2020-technical-report.pdf

HELCOM. (2023b). The Helsinki Convention. https://helcom.fi/about-us/convention

Holmlund, M., & Hannerz, F. (2007). Project: information management system and infrastructures for the Transboundary Daugava/Zapadnaya Dvina and Nemunas/Neman river basins. Nemunas/Neman and Daugava/Zapadnaya Dvina GIS-database – Layer documentation.

Kronvang, B., Borgvang, S. A., & Barkved, L. J. (2009). Towards European harmonised procedures for quantification of nutrient losses from diffuse sources – the EUROHARP project. Journal of Environmental Monitoring, 11 (3), 503–505. https://doi.org/10.1039/b902869m (Crossref)

Kryshtop, L., Krakovska, S., Chyhareva, A., & Shpytal, T. (2024, April 14–19). Interactive climate atlas of climate change: an application tool for informing practitioners and policy-maker decisions in Ukraine [Conference session]. EGU General Assembly 2024, Vienna, Austria. https://doi.org/10.5194/egusphere-egu24-19674 (Crossref)

Kundzewicz, Z. W., Piniewski, M., Mezghani, A., Okruszko, T., Pińskwar, I., Kardel, I., Hov, Ø., Szcześniak, M., Szwed, M., Benestad, R. E., Marcinkowski, P., Graczyk, D., Dobler, A., Førland, E. J., O’Keefe, J., Choryński, A., Parding, K. M., & Haugen, J. E. (2018). Assessment of climate change and associated impact on selected sectors in Poland. Acta Geophysica, 66 (6), 1509–1523. https://doi.org/10.1007/s11600-018-0220-4 (Crossref)

Laitos, J. G., & Ruckriegle, H. (2012). The clean water act and the challenge of agricultural pollution. Vermont Law Review, 37, 1033.

Lawson, J. (Ed.). (2021). River basin management, progress towards implementation of the European Water Framework Directive. CRC Press. https://doi.org/10.1201/9781003209386 (Crossref)

LIFE GoodWater IP. (2020). Implementation of River Basin Management Plans of Latvian towards good surface water status. https://www.goodwater.lv/en

Lu, N., & Villa, K. M. (2022). Agricultural support and contaminated spillovers: The effects of agricultural water pollution on adult health in China. Applied Economic Perspectives and Policy, 44 (2), 788–821. https://doi.org/10.1002/aepp.13195 (Crossref)

Marcinkowski, P., Kardel, I., Płaczkowska, E., Giełczewski, M., Osuch, P., Okruszko, T., Venegas‐Cordero, N., Ignar, S., & Piniewski, M. (2022). High‐resolution simulated water balance and streamflow data set for 1951–2020 for the territory of Poland. Geoscience Data Journal, 10 (2), 195–207. https://doi.org/10.1002/gdj3.152 (Crossref)

Mer, F., Vervoort, R. W., & Baethgen, W. (2020). Building trust in SWAT model scenarios through a multi-institutional approach in Uruguay. Socio-Environmental Systems Modelling, 2, 17892. https://doi.org/10.18174/sesmo.2020a17892 (Crossref)

Nasr, A., Bruen, M., Jordan, P., Moles, R., Kiely, G., & Byrne, P. (2007). A comparison of SWAT, HSPF and SHETRAN/GOPC for modelling phosphorus export from three catchments in Ireland. Water Research, 41 (5), 1065–1073. https://doi.org/10.1016/j.watres.2006.11.026 (Crossref)

Nõges, T., Vilbaste, S., McCarthy, M. J., Tamm, M., & Nõges, P. (2022). Long-term data reflect nitrogen pollution in Estonian rivers. Hydrology Research, 53 (12), 1468–1479. https://doi.org/10.2166/nh.2022.057 (Crossref)

Osypov, V., Osadcha, N., Bonchkovskyi, A., Kostetskyi, O., Nikoriak, V., Ahafonov, Y., Matviienko, Y., Mossur, H., & Osadchyi, V. (2023). Hydrological model of Ukraine: setup, calibration, and web interface. Book of Abstracts of the International Conference of Young Scientists on Meteorology, Hydrology and Environmental Monitoring (ICYS-MHEM), 2023, 13–13. https://doi.org/10.15407/icys-mhem.2023.013 (Crossref)

Piniewski, M., Tattari, S., Koskiaho, J., Olsson, O., Djodjic, F., Giełczewski, M., Marcinkowski, P., Księżniak, M., & Okruszko, T. (2020). How effective are River Basin Management Plans in reaching the nutrient load reduction targets? Ambio, 50 (3), 706–722. https://doi.org/10.1007/s13280-020-01393-x (Crossref)

Plunge, S. (2009). Risks versus costs: a new approach for assessment of diffuse water pollution abatement. Chalmers University. https://odr.chalmers.se/server/api/core/bitstreams/7d227fbb-a8e8-434e-b74c-828f478566b2/content

Plunge, S. (2011). Advanced decision support methods for solving diffuse water pollution problems. Lund University. https://lup.lub.lu.se/luur/download?func=downloadFile&recordOId=3559183&fileOId=3559187

Plunge, S. (2013). Development of modeling system based on the SWAT model as a tool for water management institution. In International SWAT Conference Proceedings (pp. 26–38). Texas Water Resources Institute. https://swat.tamu.edu/media/114650/2013-swat-conference-proceedings-secured.pdf

Plunge, S. (2020). Žemės ūkio vandens taršos mažinimo priemonių sąvadas. Aplinkos apsaugos agentūra. https://vanduo.old.gamta.lt/files/savadas.html

Plunge, S., Gudas, M., & Povilaitis, A. (2022a). Effectiveness of best management practices for non-point source agricultural water pollution control with changing climate – Lithuania’s case. Agricultural Water Management, 267, 107635. https://doi.org/10.1016/j.agwat.2022.107635 (Crossref)

Plunge, S., Gudas, M., & Povilaitis, A. (2022b). Expected climate change impacts on surface water bodies in Lithuania. Ecohydrology & Hydrobiology, 22 (2), 246–268. https://doi.org/10.1016/j.ecohyd.2021.11.004 (Crossref)

Plunge, S., Gudas, M., Povilaitis, A., & Piniewski, M. (2023a). Evaluation of the costs of agricultural diffuse water pollution abatement in the context of Lithuania’s water protection goals and climate change. Environmental Management, 71 (4), 755–772. https://doi.org/10.1007/s00267-022-01745-1 (Crossref)

Plunge, S., Schürz, C., Čerkasova, N., Strauch, M., & Piniewski, M. (2023b). SWAT+ model setup verification tool: SWATdoctR. Environmental Modelling & Software, 171, 105878. https://doi.org/10.1016/j.envsoft.2023.105878 (Crossref)

Plunge, S., Szabó, B., Strauch, M., Čerkasova, N., Schürz, C., & Piniewski, M. (2024). SWAT + input data preparation in a scripted workflow: SWATprepR. Environmental Sciences Europe, 36 (1), 53. https://doi.org/10.1186/s12302-024-00873-1 (Crossref)

PostGIS PSC & OSGeo. (2024). About PostGIS. https://postgis.net

Procesu analīzes un izpētes centrs [PAIC], (2015). Renewal of a river basin districts management plans and programmes of measures. Annex III – updating SWAT model data and parameters, calibration, validation, and presenting modeling results. Zenodo. https://doi.org/10.5281/zenodo.11092543

Procesu analīzes un izpētes centrs [PAIC], (2022). Water modelling system upgrade and software support services. Zenodo. https://doi.org/10.5281/zenodo.11091661

Procesu analīzes un izpētes centrs [PAIC], & Estonian, & Latvian & Lithuanian Environment. (2012). Development of methodics and modelling system of nitrogen and phosphorus load calculation for surface waters of Lithuania. Zenodo. https://doi.org/10.5281/zenodo.11092022

Python Software Foundation. (2023). Python Language Reference, version 3.11. http://www.python.org (Crossref)

R Foundation. (2024). The R project for statistical computing 4.2. https://www.r-project.org

Saloranta, T. M., Kämäri, J., Rekolainen, S., & Malve, O. (2003). Benchmark criteria: a tool for selecting appropriate models in the field of water management. Environmental Management, 32 (3), 322–333. https://doi.org/10.1007/s00267-003-0069-3 (Crossref)

Tamm, O., Maasikamäe, S., Padari, A., & Tamm, T. (2018). Modelling the effects of land use and climate change on the water resources in the eastern Baltic Sea region using the SWAT model. Catena, 167, 78–89. https://doi.org/10.1016/j.catena.2018.04.029 (Crossref)

Tan, M. L., Gassman, P. W., Srinivasan, R., Arnold, J. G., & Yang, X. (2019). A review of SWAT studies in Southeast Asia: applications, challenges and future directions. Water, 11 (5), 914. https://doi.org/10.3390/w11050914 (Crossref)

Tan, M. L., Gassman, P., Yang, X., & Haywood, J. (2020). A review of SWAT applications, performance and future needs for simulation of hydro-climatic extremes. Advances in Water Resources, 143, 103662. https://doi.org/10.1016/j.advwatres.2020.103662 (Crossref)

The PostgreSQL Global Development Group. (2024). PostgreSQL: the world’s most advanced open source relational database. https://www.postgresql.org

Thorsøe, M. H., Andersen, M. S., Brady, M. V., Graversgaard, M., Kilis, E., Pedersen, A. B., Pitzén, S., & Valve, H. (2021). Promise and performance of agricultural nutrient management policy: lessons from the Baltic Sea. Ambio, 51 (1), 36–50. https://doi.org/10.1007/s13280-021-01549-3 (Crossref)

Tsiafouli, M. A., Thébault, E., Sgardelis, S. P., Ruiter, P. C. de, Putten, W. H. van der, Birkhofer, K., Hemerik, L., Vries, F. T. de, Bardgett, R. D., Brady, M. V., Bjornlund, L., Jørgensen, H. B., Christensen, S., Hertefeldt, T. D., Hotes, S., Hol, W. H. G., Frouz, J., Liiri, M., Mortimer, S. R., Setälä, H., Tzanopoulos, J., Uteseny, K., Pižl, V., Stary, J., Wolters, V., Hedlund, K. (2015). Intensive agriculture reduces soil biodiversity across Europe. Global Change Biology, 21 (2), 973–985. https://doi.org/10.1111/gcb.12752 (Crossref)

Vervoort, R. W., Nervi, E., & Baethgen, W. (2024). Integrated catchment models for policy development and decision making. Agrociencia Uruguay, 27 (NE1), e1194–e1194. https://doi.org/10.31285/agro.27.1194 (Crossref)

Vigiak, O., Udías, A., Grizzetti, B., Zanni, M., Aloe, A., Weiss, F., Hristov, J., Bisselink, B., Roo, A. de, & Pistocchi, A. (2023). Recent regional changes in nutrient fluxes of European surface waters. Science of The Total Environment, 858 (Pt 3), 160063. https://doi.org/10.1016/j.scitotenv.2022.160063 (Crossref)

White, M. J., Arnold, J. G., Bieger, K., Allen, P. M., Gao, J., Čerkasova, N., Gambone, M., Park, S., Bosch, D. D., Yen, H., & Osorio, J. M. (2022). Development of a field scale SWAT+ modeling framework for the contiguous US. JAWRA Journal of the American Water Resources Association, 58 (6), 1545–1560. https://doi.org/10.1111/1752-1688.13056 (Crossref)

White, M. J., Harmel, R. D., Arnold, J. G., & Williams, J. R. (2014). SWAT check: a screening tool to assist users in the identification of potential model application problems. Journal of Environmental Quality, 43 (1), 208–214. https://doi.org/10.2134/jeq2012.0039 (Crossref)

Statistics

Downloads

Download data is not yet available.
Recommend Articles