Askari, M., Li, J. and Samali, B. (2017). Cost-effective multi-objective optimal positioning of magnetorheological dampers and active actuators in large nonlinear structures. Intelligent Material Systems and Structures, 28(2), 230-253.
Behzadian, K., Ardeshir, A., Kapelan, Z. and Savic, D. (2008). Stochastic sampling design for water distribution model calibration. International Journal of Civil Engineering, 6(1), 48-57.
Bush, C.A. and Uber, J.G. (1998). Sampling design methods for water distribution model calibration, Water Resources Planning and Management, 124(6), 334-344.
De Schaetzen, W.B.F., Walters, G.A. and Savic, D.A. (2000). Optimal sampling design for model calibration using shortest path, genetic and entropy algorithms. Urban Water, 2(2), 141-152.
Homma, T. and Saltelli, A. (1996). Importance measures in global sensitivity analysis of nonlinear models. Reliability Engineering & System Safety, 52(1), 1-17.
Iooss, B. and Lemaître, P. (2015). A review on global sensitivity analysis methods. In: Dellino, G. and Meloni, C. (eds.), Uncertainty Management in Simulation-Optimization of Complex Systems, 101-122, Springer, Boston.
Kapelan, Z.S., Savic, D.A. and Walters, G.A. (2003). Multiobjective sampling design for water distribution model calibration. Water Resources Planning and Management, 129(6), 466-479.
Ormsbee, L.E. (1989). Implicit network calibration. Water Resources Planning and Management, 115(2), 243-257.
Saltelli, A., Aleksankina, K., Becker, W., Fennell, P., Ferretti, F., Holst, N., Li, S. and Wu, Q. (2019). Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices. Environmental Modelling & Software, 114, 29-39.
Shao, Y., Chu, S., Zhang, T., Yang, Y. J. and Yu, T. (2019). A greedy sampling design algorithm for the model calibration of nodal demand in water distribution systems. Mathematic Problems in Engineering,
https://doi.org/10.1155/2019/3917571.
Soroush, F. and Abedini, M.J. (2019). Optimal selection of number and location of pressure sensors in water distribution systems using geostatistical tools coupled with genetic algorithm. Journal of Hydroinformatics, 21(6), 1030-1047.
Tang, T., Reed, P., Wagener, T. and Van Werkhoven, K. (2006). Comparing sensitivity analysis methods to advance lumped watershed model identification and evaluation. Hydrology and Earth System Sciences Discussions, 3(6), 3333- 3395.
Tang, Y., Reed, P., Van Werkhoven, K. and Wagener, T. (2007). Advancing the identification and evaluation of distributed rainfall‐runoff models using global sensitivity analysis. Water Resources Research, 43(6).
Wagner, J.M., Shamir, U. and Marks, D.H. (1988). Water distribution reliability: simulation methods. Water Resources Planning and Management, 114(3), 276-294.
Walski, T.M., Brill Jr, E.D., Gessler, J., Goulter, I.C., Jeppson, R.M., Lansey, K., Lee, H.L., Liebman, J.C., Mays, L. and Morgan, D.R. (1987). Battle of the network models: Epilogue. Water Resources Planning and Management, 113(2), 191-203.