PL EN


Preferencje help
Widoczny [Schowaj] Abstrakt
Liczba wyników
Tytuł artykułu

Curonian Lagoon drainage basin modelling and assessment of climate change impact

Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The Curonian Lagoon, which is the largest European coastal lagoon with a surface area of 1578 km2 and a drainage area of 100,458 km2, is facing a severe eutrophication problem. With its increasing water management difficulties, the need for a sophisticated hydrological model of the Curonian Lagoon's drainage area arose, in order to assess possible changes resulting from local and global processes. In this study, we developed and calibrated a sophisticated hydrological model with the required accuracy, as an initial step for the future development of a modelling framework that aims to correctly predict the movement of pesticides, sediments or nutrients, and to evaluate water-management practices. The Soil and Water Assessment Tool was used to implement a model of the study area and to assess the impact of climate-change scenarios on the run-off of the Nemunas River and the Minija River, which are located in the Curonian Lagoons drainage basin. The models calibration and validation were performed using monthly streamflow data, and evaluated using the coefficient of determination (R2) and the Nash-Sutcliffe model efficiency coefficient (NSE). The calculated values of the R2 and NSE for the Nemunas and Minija Rivers stations were 0.81 and 0.79 for the calibration, and 0.679 and 0.602 for the validation period. Two potential climate-change scenarios were developed within the general patterns of near-term climate projections, as defined by the Intergovernmental Panel on Climate Change Fifth Assessment Report: both pessimistic (substantial changes in precipitation and temperature) and optimistic (insubstantial changes in precipitation and temperature). Both simulations produce similar general patterns in river-discharge change: a strong increase (up to 22%) in the winter months, especially in February, a decrease during the spring (up to 10%) and summer (up to 18%), and a slight increase during the autumn (up to 10%).
Czasopismo
Rocznik
Strony
90--102
Opis fizyczny
Bibliogr. 29 poz., tab., wykr., mapy
Twórcy
  • Open Access Centre for Marine Research, Klaipeda, Lithuania
autor
  • Open Access Centre for Marine Research, Klaipeda, Lithuania
  • Department of Freshwater Biology, Istanbul University, Istanbul, Turkey
autor
  • Open Access Centre for Marine Research, Klaipeda, Lithuania
autor
  • Faculty of Marine Technology and Natural Sciences, Klaipeda University, Klaipeda, Lithuania
autor
  • Open Access Centre for Marine Research, Klaipeda, Lithuania
  • ISMAR-CNR, Institute of Marine Sciences, Venezia, Italy
Bibliografia
  • 1.Abbaspour, K. C., 2011. SWAT-CUP2: SWAT Calibration and Uncertainty Programs Manual Version 2. User Manual. Department of Systems Analysis, Integrated Assessment and Modelling (SIAM), Eawag. Swiss Federal Institute of Aquatic Science and Technology, Duebendorf, Switzerland.
  • 2.Arnold, J., Allen, P., Bernhardt, G., 1993. A comprehensive surface groundwater flow model. J. Hydrol. 142 (1—4), 47—69.
  • 3.Arnold, J., Kiniry, J., Srinivasan, S., Williams, J., Haney, E., Neitsch, S., 2010. Soil and Water Assessment Tool Input/Output File Documentation, Version 2009. Texas Water Resourc. Inst. Tech. Rep. No. 365, 643 pp.
  • 4.Arnold, J., Moriasi, D., Gassman, P., Abbaspour, K., White, M., Srinivasan, R., Santhi, C., Harmel, R., van Griensven, A., Liew, M. V., Kannan, N., Jha, M., 2012. SWAT: Model use, calibration and validation. Am. Soc. Agric. Biol. Eng. 55 (4), 1419—1508.
  • 5.Balascio, C., Palmeri, D., Gao, H., 1998. Use of a genetic algorithm and multi-objective programming for calibration of a hydrologic model. Am. Soc. Agric. Biol. Eng. 41 (3), 615—619.
  • 6.CGIAR — Consortium for Spatial Information. SRTM Data Search service, http://srtm.csi.cgiar.org/SELECTION/inputCoord.asp (accessed: February 2014).
  • 7.Chaubey, I., Cotter, A., Costello, T., Soerens, T., 2005. Effect of DEM data resolution on SWAT output uncertainty. Hydrol. Process. 19 (3), 621—628.
  • 8.Dubra, J., Červinskas, E., 1968. Freshwater balance of the Curonian Lagoon. Scientific Works of the High Schools. Geogr. Geol. 5, 19— 26, (in Lithuanian).
  • 9.ELLE, PAIC, 2012. Development of methodics and modelling system of nitrogen and phosphorus load calculation for surface waters of Lithuania. The 1st interim report of project, UAB Estonian, Latvian & Lithuanian Environment and SIA Procesu analīzes un izpētes centrs.
  • 10.Gailiušis, B., Kovalenkovienė, M., Jurgelėnaitė, A., 1992. Water balance of the Curonian Lagoon. Energetika 2, 67—73.
  • 11.Gassman, P., Reyes, M., Green, C., Arnold, J., 2007. The Soil and Water Assessment Tool: historical development, applications, and future research directions. Am. Soc. Agric. Biol. Eng. 50 (4), 1211—1250.
  • 12.Ghaffari, G., 2011. The impact of DEM resolution on runoff and sediment modelling results. Res. J. Environ. Sci. 5 (8), 691—702.
  • 13.Jakimavičius, D., 2012. Changes of water balance elements of the Curonian lagoon and their forecast due to anthropogenic and natural factors (Ph.D. thesis). Kaunas Univ. Technol.
  • 14.Jakimavičius, D., Kovalenkovienė, M., 2010. Long-term water balance of the Curonian Lagoon in the context of anthropogenic factors and climate change. Baltica 23 (1), 33—46.
  • 15.Kirtman, B., Power, S., Adedoyin, J., Boer, G., Bojariu, R., Camilloni, I., Doblas-Reyes, F., Fiore, A., Kimoto, M., Meehl, G., Prather, M., Sarr, A., Schar, C., Sutton, R., van Oldenborgh, G., Vecchi, G., Wang, H., 2013. Near-term climate change: projections and predictability. In: Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University.
  • 16.Kontautas, A., Matiukas, K., 2010. Environmental Problems and Challenges of the Minija River Towards a Sustainable Development of the River Basin. Watersketch Project Case Study Report. Coastal Research and Planning Institute, Klaipeda University.
  • 17.Krause, P., Boyle, D. P., Base, F., 2005. Comparison of different efficiency criteria for hydrological model assessment. Adv. Geosci. 5, 89—97.
  • 18.Kriaučiunienė, J., Meilutytė-Barauskienė, D., Rimkus, E., Kažys, J., Vincevičius, A., 2008. Climate change impact on hydrological processes in Lithuanian Nemunas river basin. Baltica 21 (1—2), 51—61.
  • 19.Lin, S., Jing, C., Chaplot, V., Yu, X., Zhang, Z., Moore, N., Wu, J., 2010. Effect of DEM resolution on SWAT outputs of runoff, sediment and nutrients. Hydrol. Earth Syst. Sci. 7, 4411—4435.
  • 20.Meilutytė-Barauskienė, D., Kovalenkovienė, M., 2007. Change of spring flood parameters in Lithuanian rivers. Energetika 53 (2), 26—33.
  • 21.Moriasi, D., Arnold, J., Liew, M. V., Bingner, R., Harmel, R., Veith, T., 2007. Model evaluation guidelines for systematic quantification of accuracy in watershed simulations. Am. Soc. Agric. Biol. Eng. 50 (3), 885—900.
  • 22.National Centers for Environmental Prediction. Climate Forecast System Reanalysis — Global weather database, http:// globalweather.tamu.edu/ (accessed: November 2014).
  • 23.Neitsch, S., Arnold, J., Kiniry, J., Williams, J., 2011. Soil and Water Assessment Tool. Theoretical Documentation. Version 2009. Texas Water Resourc. Inst. Theoretical Doc. 406, 618 pp.
  • 24.Rimkus, E., Stonevčius, E., Korneev, V., Kažys, J., Valiuškevičius, G., Pakhomau, A., 2013. Dynamics of meteorological and hydrological droughts in the Neman river basin. Environ. Res. Lett. 8 (4), 045014.
  • 25.Rogozova, S., 2006. Climate change impacts on hydrological regime in Latvian basins. In: Proceedings of the European Conference on Impacts of Climate Change on Renewable Energy Sources, 137—140.
  • 26.Rouholahnejad, E., Abbaspour, K., Vejdani, M., Srinivasan, R., Schulin, R., Lehmann, A., 2012. A parallelization framework for calibration of hydrological models. Environ. Model. Softw. 31, 28—36.
  • 27.United Nations Economic Commission for Europe, 2011. Second assessment of transboundary rivers, lakes and groundwaters: drainage basin of the Baltic Sea. Assessment report.
  • 28.United Nations University. WaterBase project — Data for SWAT database, http://www.waterbase.org/download_data.html (accessed: November 2014).
  • 29.Žilinskas, G., Jarmalavičius, D., Pupienis, D., Gulbinas, Z., Korotkich, P., Palčiauskaitė, R., Pileckas, M., Raščius, G., 2012. Curonian Lagoon coastal management study. Tech. Rep. Nature Heritage Fund, (in Lithuanian).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9530b60e-325d-4cff-bdad-4376f888d7d8
JavaScript jest wyłączony w Twojej przeglądarce internetowej. Włącz go, a następnie odśwież stronę, aby móc w pełni z niej korzystać.