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Stakeholder interviews with two MAVT preference elicitation philosophies in a Swiss water infrastructure decision: aggregation using SWING-weighting and disaggregation using UTA<sup>GMS</sup>
Zheng, J., & Lienert, J. (2018). Stakeholder interviews with two MAVT preference elicitation philosophies in a Swiss water infrastructure decision: aggregation using SWING-weighting and disaggregation using UTAGMS. European Journal of Operational Research, 267(1), 273-287. https://doi.org/10.1016/j.ejor.2017.11.018
Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning
Scholten, L., Maurer, M., & Lienert, J. (2017). Comparing multi-criteria decision analysis and integrated assessment to support long-term water supply planning. PLoS One, 12(5), e0176663 (30 pp.). https://doi.org/10.1371/journal.pone.0176663
A scenario-based MCDA framework for wastewater infrastructure planning under uncertainty
Zheng, J., Egger, C., & Lienert, J. (2016). A scenario-based MCDA framework for wastewater infrastructure planning under uncertainty. Journal of Environmental Management, 183(3), 895-908. https://doi.org/10.1016/j.jenvman.2016.09.027
Importance of anthropogenic climate impact, sampling error and urban development in sewer system design
Egger, C., & Maurer, M. (2015). Importance of anthropogenic climate impact, sampling error and urban development in sewer system design. Water Research, 73, 78-97. https://doi.org/10.1016/j.watres.2014.12.050
Structured decision-making for sustainable water infrastructure planning and four future scenarios
Lienert, J., Scholten, L., Egger, C., & Maurer, M. (2015). Structured decision-making for sustainable water infrastructure planning and four future scenarios. EURO Journal on Decision Processes, 3, 107-140. https://doi.org/10.1007/s40070-014-0030-0
Tackling uncertainty in multi-criteria decision analysis – an application to water supply infrastructure planning
Scholten, L., Schuwirth, N., Reichert, P., & Lienert, J. (2015). Tackling uncertainty in multi-criteria decision analysis – an application to water supply infrastructure planning. European Journal of Operational Research, 242(1), 243-260. https://doi.org/10.1016/j.ejor.2014.09.044
Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis
Scholten, L., Scheidegger, A., Reichert, P., Mauer, M., & Lienert, J. (2014). Strategic rehabilitation planning of piped water networks using multi-criteria decision analysis. Water Research, 49(1), 124-143. https://doi.org/10.1016/j.watres.2013.11.017
Sewer deterioration modeling with condition data lacking historical records
Egger, C., Scheidegger, A., Reichert, P., & Maurer, M. (2013). Sewer deterioration modeling with condition data lacking historical records. Water Research, 47(17), 6762-6779. https://doi.org/10.1016/j.watres.2013.09.010
Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes
Lienert, J., Schnetzer, F., & Ingold, K. (2013). Stakeholder analysis combined with social network analysis provides fine-grained insights into water infrastructure planning processes. Journal of Environmental Management, 125, 134-148. https://doi.org/10.1016/j.jenvman.2013.03.052
Meeting the challenges of transdisciplinary knowledge production for sustainable water governance
Renner, R., Schneider, F., Hohenwallner, D., Kopeinig, C., Kruse, S., Lienert, J., … Muhar, S. (2013). Meeting the challenges of transdisciplinary knowledge production for sustainable water governance. Mountain Research and Development, 33(3), 234-247. https://doi.org/10.1659/MRD-JOURNAL-D-13-00002.1
Extension of pipe failure models to consider the absence of data from replaced pipes
Scheidegger, A., Scholten, L., Maurer, M., & Reichert, P. (2013). Extension of pipe failure models to consider the absence of data from replaced pipes. Water Research, 47(11), 3696-3705. https://doi.org/10.1016/j.watres.2013.04.017
Combining expert knowledge and local data for improved service life modeling of water supply networks
Scholten, L., Scheidegger, A., Reichert, P., & Maurer, M. (2013). Combining expert knowledge and local data for improved service life modeling of water supply networks. Environmental Modelling and Software, 42, 1-16. https://doi.org/10.1016/j.envsoft.2012.11.013
Identifying biases in deterioration models using synthetic sewer data
Scheidegger, A., & Maurer, M. (2012). Identifying biases in deterioration models using synthetic sewer data. Water Science and Technology, 66(11), 2363-2369. https://doi.org/10.2166/wst.2012.471
Network condition simulator for benchmarking sewer deterioration models
Scheidegger, A., Hug, T., Rieckermann, J., & Maurer, M. (2011). Network condition simulator for benchmarking sewer deterioration models. Water Research, 45(16), 4983-4994. https://doi.org/10.1016/j.watres.2011.07.008