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  • 1.
    Jaramillo, Fernando
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography. Stockholm University, Faculty of Science, Stockholm Resilience Centre. Stockholm University, Faculty of Science, Stockholm University Baltic Sea Centre.
    Desormeaux, Amanda
    Hedlund, Johanna
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Jawitz, James W.
    Clerici, Nicola
    Piemontese, Luigi
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Alexandra Rodríguez-Rodriguez, Jenny
    Adolfo Anaya, Jesús
    Blanco-Libreros, Juan F.
    Borja, Sonia
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Celi, Jorge
    Chalov, Sergey
    Chun, Kwok Pan
    Cresso, Matilda
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Destouni, Georgia
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Dessu, Shimelis Behailu
    Di Baldassarre, Giuliano
    Downing, Andrea
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Espinosa, Luisa
    Ghajarnia, Navid
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Girard, Pierre
    Gutiérrez, Álvaro G.
    Hansen, Amy
    Hu, Tengfei
    Jarsjö, Jerker
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Kalantary, Zahra
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Labbaci, Adnane
    Licero-Villanueva, Lucia
    Livsey, John
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Machotka, Ewa
    Stockholm University, Faculty of Humanities, Department of Asian, Middle Eastern and Turkish Studies.
    McCurley, Kathryn
    Palomino-Ángel, Sebastián
    Pietron, Jan
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Price, René
    Ramchunder, Sorain J.
    Ricaurte-Villota, Constanza
    Ricaurte, Luisa Fernanda
    Dahir, Lula
    Rodríguez, Erasmo
    Salgado, Jorge
    Sannel, A. Britta K.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Carolina Santos, Ana
    Seifollahi-Aghmiuni, Samaneh
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Sjöberg, Ylva
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Sun, Lian
    Stockholm University, Faculty of Science, Department of Physical Geography. Beijing Normal University, China.
    Thorslund, Josefin
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Vigouroux, Guillaume
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Wang-Erlandsson, Lan
    Stockholm University, Faculty of Science, Stockholm Resilience Centre.
    Xu, Diandian
    Stockholm University, Faculty of Science, Department of Physical Geography. Hohai University, China.
    Zamora, David
    Ziegler, Alan D.
    Åhlén, Imenne
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Priorities and Interactions of Sustainable Development Goals (SDGs) with Focus on Wetlands2019In: Water, ISSN 2073-4441, E-ISSN 2073-4441, Vol. 11, no 3, article id 619Article in journal (Refereed)
    Abstract [en]

    Wetlands are often vital physical and social components of a country's natural capital, as well as providers of ecosystem services to local and national communities. We performed a network analysis to prioritize Sustainable Development Goal (SDG) targets for sustainable development in iconic wetlands and wetlandscapes around the world. The analysis was based on the information and perceptions on 45 wetlandscapes worldwide by 49 wetland researchers of the Global Wetland Ecohydrological Network (GWEN). We identified three 2030 Agenda targets of high priority across the wetlandscapes needed to achieve sustainable development: Target 6.3-Improve water quality; 2.4-Sustainable food production; and 12.2-Sustainable management of resources. Moreover, we found specific feedback mechanisms and synergies between SDG targets in the context of wetlands. The most consistent reinforcing interactions were the influence of Target 12.2 on 8.4-Efficient resource consumption; and that of Target 6.3 on 12.2. The wetlandscapes could be differentiated in four bundles of distinctive priority SDG-targets: Basic human needs, Sustainable tourism, Environmental impact in urban wetlands, and Improving and conserving environment. In general, we find that the SDG groups, targets, and interactions stress that maintaining good water quality and a wise use of wetlandscapes are vital to attaining sustainable development within these sensitive ecosystems.

  • 2.
    Seifollahi-Aghmiuni, Samaneh
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Bozorg-Haddad, Omid
    Simulation-Optimization Tool for Multiattribute Reservoir Systems2019In: Journal of hydrologic engineering, ISSN 1084-0699, E-ISSN 1943-5584, Vol. 24, no 9, article id 04019028Article in journal (Refereed)
    Abstract [en]

    Reservoirs, as the largest water systems for controlling water and supply demands, have been particularly important due to their operational requirements. Applying practical tools to evaluate the performance of reservoir systems plays a key role in their effective operational management. This study focused on developing a simulation-optimization tool for the design and operation of multiattribute reservoir systems (SOMAR), which includes four parts: input data, simulation, optimization, and output results. Its different components can be selectively activated for each problem. SOMAR can use both standard operation policy or given rule curves for reservoir system simulation in accordance with the user's preference. It applies a comprehensive evolutionary algorithm for optimization. In this study, SOMAR was validated in seven types of reservoir system problems, including simulations based on (1) standard operation policy, (2) given rule curves, (3) design optimization, (4) long-term operation optimization, (5) design and long-term operation optimization, (6) rule curve optimization, and (7) design and rule curve optimization. The validations indicated the capabilities of SOMAR in analyzing reservoir systems with high reliability of the final results by considering different aspects of these systems.

  • 3.
    Seifollahi-Aghmiuni, Samaneh
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Haddad, Omid Bozorg
    Multi Objective Optimization with a New Evolutionary Algorithm2018In: Water resources management, ISSN 0920-4741, E-ISSN 1573-1650, Vol. 32, no 12, p. 4013-4030Article in journal (Refereed)
    Abstract [en]

    Various objectives are mainly met through decision making in real world. Achieving desirable condition for all objectives simultaneously is a necessity for conflicting objectives. This concept is called multi objective optimization widely used nowadays. In this study, a new algorithm, comprehensive evolutionary algorithm (CEA), is developed based on general concepts of evolutionary algorithms that can be applied for single or multi objective problems with a fixed structure. CEA is validated through solving several mathematical multi objective problems and the obtained results are compared with the results of the non-dominated sorting genetic algorithm II (NSGA-II). Also, CEA is applied for solving a reservoir operation management problem. Comparisons show that CEA has a desirable performance in multi objective problems. The decision space is accurately assessed by CEA in considered problems and the obtained solutions' set has a great extent in the objective space of each problem. Also, CEA obtains more number of solutions on the Pareto than NSGA-II for each considered problem. Although the total run time of CEA is longer than NSGA-II, solution set obtained by CEA is about 32, 4.4 and 1.6% closer to the optimum results in comparison with NSGA-II in the first, second and third mathematical problem, respectively. It shows the high reliability of CEA's results in solving multi objective problems.

  • 4.
    Seifollahi-Aghmiuni, Samaneh
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Kalantari, Zahra
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Land, Magnus
    Destouni, Georgia
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Change Drivers and Impacts in Arctic Wetland LandscapesLiterature Review and Gap Analysis2019In: Water, ISSN 2073-4441, E-ISSN 2073-4441, Vol. 11, no 4, article id 722Article, review/survey (Refereed)
    Abstract [en]

    Wetlands are essential parts of Arctic landscapes, playing important roles for the sustainable development of the region, and linking to climate change and adaptation, ecosystem services, and the livelihood of local people. The effects of human and natural change drivers on key landscape characteristics of Arctic wetlands may be critical for ecosystem resilience, with some functional aspects still poorly understood. This paper reviews the scientific literature on change drivers for Arctic wetland landscapes, seeking to identify the main studied interactions among different drivers and landscape characteristics and their changes, as well as emerging research gaps in this context. In a total of 2232 studies of various aspects of Arctic wetland landscapes found in the literature, natural drivers and climate change have been the most studied change drivers so far, particularly regarding their impacts on carbon cycling, plant communities and biodiversity. In contrast, management plans, land use changes, and nutrient-pollutant loading, have not been investigated as much as human drivers of Arctic wetland change. This lack of study highlights essential gaps in wetland related research, and between such research and management of Arctic wetlands.

  • 5.
    Seifollahi-Aghmiuni, Samaneh
    et al.
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Nockrach, Minnoka
    Stockholm University, Faculty of Science, Department of Physical Geography.
    Kalantari, Zahra
    Stockholm University, Faculty of Science, Department of Physical Geography.
    The Potential of Wetlands in Achieving the Sustainable Development Goals of the 2030 Agenda2019In: Water, ISSN 2073-4441, E-ISSN 2073-4441, Vol. 11, no 3, article id 609Article in journal (Refereed)
    Abstract [en]

    Wetlands used as cost-effective nature-based solutions provide environmental and socio-economic benefits to people locally and regionally. With significant loss of wetland areas due to expansion of forest, agriculture, and energy production industries, some countries, including Sweden, have begun providing economic support for environmental objectives for wetland conservation and restoration. Targeting such objectives and setting up relevant plans can decrease the risk of losing valuable wetland-related benefits and help achieve the United Nations Sustainable Development Goals (SDGs). Different ranges of wetland ecosystem services are broadly addressed by the SDGs, however, target-based assessments are required to better understand wetland functionality for sustainable development. This study investigates whether and how wetland ecosystems at local and regional scales can contribute to achieving the SDGs and their targets in Sweden. Scientific literature, policy documents, and international reports on Swedish wetland ecosystems are scrutinized to exemplify the SDGs and their targets, applying a scoring framework based on their interactions. This reveals that, overall, Swedish wetland ecosystems and implemented management plans can positively interact with 10 SDGs and 17 targets at different levels. The analysis also highlights synergies that need to be considered for integrated environmental governance and enhanced policy coherence for Swedish wetland management.

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