Multiobjective Optimization of Sensor Placement for Precipitation Station Monitoring Network Design
This article has a reply.
VIEW THE REPLYPublication: Journal of Hydrologic Engineering
Volume 25, Issue 9
Abstract
An optimal sensor placement of a precipitation station network should fulfill different regulations and requirements, such as coverage maximization, easy access, and uniform distribution. However, few studies have focused on an integrated way to optimize the precipitation network design from the perspective of monitoring efficiency in space. In this paper, given the complex requirements and diversified goals for precipitation monitoring, a new multiobjective location model is established for optimizing the network’s monitoring efficiency with a comprehensive weighting scheme. Based on the precipitation station siting regulations, the spatial coverage, accessibility, and dispersion of stations are considered in the model. The Elitist Nondominated Sorting Genetic Algorithm (NSGA-II) is used to obtain a set of Pareto-efficient solutions. The Jinsha River Basin is selected as the study region to test the proposed method. The results show that the proposed method satisfies the complex precipitation monitoring requirements and achieves higher coverage than the real-world deployment. The decision making for siting schemes, comparison of other dispersion models, and the extensibility of the proposed method are also discussed.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
This work was supported by grants from the National Nature Science Foundation of China (NSFC) Program (No. 41701453), the Open Research Fund of State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing (Wuhan University) (No. 17I02), the Fundamental Research Funds for the Central Universities, China University of Geosciences (Wuhan) (No. CUG190616), the Science and Technology Research Project of Hubei Provincial Department of Education (No. B2018053), the Social Science Foundation of Wuhan Institute of Technology (No. R201805), the Science Research Project of Wuhan Institute of Technology (No. K201730), and the Application Fundamental and the Special Fund for Foundation and Frontier of Applications of Wuhan (No. 2018010401011293).
References
Alfonso, L., L. He, A. Lobbrecht, and R. Price. 2013. “Information theory applied to evaluate the discharge monitoring network of the Magdalena River.” J. Hydroinf. 15 (1): 211–228. https://doi.org/10.2166/hydro.2012.066.
Awadallah, A. G. 2012. “Selecting optimum locations of rainfall stations using Kriging and entropy.” Int. J. Civ. Environ. Eng. 12 (1): 36–41.
Baltas, E. A., and M. A. Mimikou. 2009. “GIS-based optimisation of the hydrometeorological network in Greece.” Int. J. Digital Earth 2 (2): 171–185. https://doi.org/10.1080/17538940902818303.
Basalirwa, C. P. K., L. J. Ogallo, and F. M. Mutua. 1993. “The design of a regional minimum raingauge network.” Int. J. Water Resour. Dev. 9 (4): 411–424. https://doi.org/10.1080/07900629308722598.
Camara, M. V. O., G. M. Ribeiro, and M. D. C. R. Tosta. 2018. “A Pareto optimal study for the multi-objective oil platform location problem with NSGA-II.” J. Petrol. Sci. Eng. 169 (Oct): 258–268. https://doi.org/10.1016/j.petrol.2018.05.037.
Chacon-Hurtado, J. C., L. Alfonso, and D. Solomatine. 2017. “Rainfall and streamflow sensor network design: A review of applications, classification, and a proposed framework.” Hydrol. Earth Syst. Sci. Discuss. 21 (6): 3071–3091. https://doi.org/10.5194/hess-21-3071-2017.
Chau, K. W. 2017. “Use of meta-heuristic techniques in rainfall-runoff modeling.” Water 9 (3): 186. https://doi.org/10.3390/w9030186.
Cheng, C. T., J. Y. Lin, Y. G. Sun, and K. W. Chau. 2005. “Long-term prediction of discharges in Manwan Hydropower using adaptive-network-based fuzzy inference systems models.” In Vol. 3612 of Advances in natural computation: Lecture notes in computer science, 1152–1161. Berlin: Springer. https://doi.org/10.1007/11539902_145.10.1007/11539902_145.
Church, R. L. 1984. “The planar maximal covering location problem.” J. Reg. Sci. 24 (2): 185–201. https://doi.org/10.1111/j.1467-9787.1984.tb01031.x.
Church, R. L., and C. S. ReVelle. 1974. “The maximal covering location problem.” Pap. Reg. Sci. Assoc. 32 (1): 101–118. https://doi.org/10.1007/BF01942293.
Coello, C. A. C. 2006. “Evolutionary multi-objective optimization: A historical view of the field.” IEEE Comput. Intell. Mag. 1 (1): 28–36. https://doi.org/10.1109/MCI.2006.1597059.
Collados-Lara, A. J., E. Pardo-Igúzquiza, D. Pulido-Velazquez, and J. Jiménez-Sánchez. 2018. “Precipitation fields in an alpine Mediterranean catchment. Inversion of precipitation gradient with elevation or undercatch of snowfall?” Int. J. Climatol. 38 (9): 3565–3578. https://doi.org/10.1002/joc.5517.
Deb, K. 2007. “Current trends in evolutionary multi-objective optimization.” Int. J. Simul. Multi. Des. Optim. 1 (1): 1–8. https://doi.org/10.1051/ijsmdo:2007001.
Deb, K., A. Pratap, and S. Agarwal. 2002. “A fast and elitist multi-objective genetic algorithm: NSGA-II.” IEEE Trans. Evolut. Comput. 6 (2): 182–197. https://doi.org/10.1109/4235.996017.
Dhar, A., and B. Datta. 2007. “Multiobjective design of dynamic monitoring networks for detection of groundwater pollution.” J. Water Resour. Plann. Manage. 133 (133): 329–338. https://doi.org/10.1061/(ASCE)0733-9496(2007)133:4(329).
Erkut, E., and S. Neuman. 1991. “Comparison of four models for dispersing facilities.” INFOR Inf. Syst. Oper. Res. 29 (2): 68–86. https://doi.org/10.1080/03155986.1991.11732157.
Farahani, R. Z., N. Asgari, N. Heidari, M. Hosseininia, and M. Goh. 2012. “Covering problems in facility location: A review.” Comput. Ind. Eng. 62 (1): 368–407. https://doi.org/10.1016/j.cie.2011.08.020.
Fotovatikhah, F., M. Herrera, S. Shamshirband, K. W. Chau, S. F. Ardabili, and M. J. Piran. 2018. “Survey of computational intelligence as basis to big flood management: Challenges, research directions and future work.” Eng. Appl. Comput. Fluid Mech. 12 (1): 411–437. https://doi.org/10.1080/19942060.2018.1448896.
Ghorbani, M. A., R. Kazempour, K. W. Chau, S. Shamshirband, and P. T. Ghazvinei. 2018. “Forecasting pan evaporation with an integrated artificial neural network quantum-behaved particle swarm optimization model: A case study in Talesh, northern Iran.” Eng. Appl. Comput. Fluid Mech. 12 (1): 724–737. https://doi.org/10.1080/19942060.2018.1517052.
Huang, G., and M. Wang. 2012. “Weight assignment research of improved entropy method in effectiveness evaluation.” Comput. Eng. Appl. 48 (28): 245–248.
Indriasari, V., A. R. Mahmud, N. Ahmad, and A. R. M. Shariff. 2010. “Maximal service area problem for optimal siting of emergency facilities.” Int. J. Geogr. Inf. Sci. 24 (2): 213–230. https://doi.org/10.1080/13658810802549162.
Lei, T. L., and R. L. Church. 2013. “A unified model for dispersing facilities.” Geog. Anal. 45 (4): 401–418. https://doi.org/10.1111/gean.12020.
Li, C., V. P. Singh, and A. K. Mishra. 2012. “Entropy theory-based criterion for hydrometric network evaluation and design: Maximum information minimum redundancy.” Water Resour. Res. 48 (5): W05521. https://doi.org/10.1029/2011WR011251.
Liu, H., H. Lan, Y. Liu, and Y. Zhou. 2011. “Characteristics of spatial distribution of debris flow and the effect of their sediment yield in main downstream of Jinsha River, China.” Environ. Earth Sci. 64 (6): 1653–1666. https://doi.org/10.1007/s12665-009-0409-6.
Martínez, S. I., V. Merwade, and D. Maidment. 2010. “Linking GIS, hydraulic modeling, and tabu search for optimizing a water level-monitoring network in South Florida.” J. Water Resour. Plann. Manage. 136 (2): 167–176. https://doi.org/10.1061/(ASCE)WR.1943-5452.0000024.
Miller, H. J. 1996. “GIS and geometric representation in facility location problems.” Int. J. Geogr. Inf. Syst. 10 (7): 791–816. https://doi.org/10.1080/02693799608902110.
Mishra, A. K., and P. Coulibaly. 2009. “Developments in hydrometric network design: A review.” Rev. Geophys. 47 (2): RG2011. https://doi.org/10.1029/2007RG000243.
Moazenzadeh, R., B. Mohammadi, S. Shamshirband, and K. W. Chau. 2018. “Coupling a firefly algorithm with support vector regression to predict evaporation in northern Iran.” Eng. Appl. Comput. Fluid Mech. 12 (1): 584–597. https://doi.org/10.1080/19942060.2018.1482476.
Moon, I. D., and S. S. Chaudhry. 1984. “An analysis of network location problems with distance constraints.” Manage. Sci. 30 (3): 290–307. https://doi.org/10.1287/mnsc.30.3.290.
Murray, A. T., K. Kim, J. W. Davis, R. Machiraju, and R. Parent. 2007. “Coverage optimization to support security monitoring.” Comput. Environ. Urban Syst. 31 (2): 133–147. https://doi.org/10.1016/j.compenvurbsys.2006.06.002.
Murray, A. T., and D. Tong. 2007. “Coverage optimization in continuous space facility siting.” Int. J. Geog. Inf. Sci. 21 (7): 757–776. https://doi.org/10.1080/13658810601169857.
Pardo-Igúzquiza, E. 1998. “Optimal selection of number and location of rainfall gauges for areal rainfall estimation using geostatistics and simulated annealing.” J. Hydrol. 210 (1–4): 206–220. https://doi.org/10.1016/S0022-1694(98)00188-7.
Shillington, L., and D. Tong. 2011. “Maximizing wireless mesh network coverage.” Int. Reg. Sci. Rev. 34 (4): 419–437. https://doi.org/10.1177/0160017610396011.
Su, H. T., and G. J. Y. You. 2014. “Developing an entropy-based model of spatial information estimation and its application in the design of precipitation gauge networks.” J. Hydrol. 519 (Part D): 3316–3327. https://doi.org/10.1016/j.jhydrol.2014.10.022.
Tapiador, F. J., F. J. Turk, W. Petersen, A. Y. Hou, E. García-Ortega, L. A. T. Machado, C. F. Angelis, P. Salio, and C. Kidd. 2012. “Global precipitation measurement: Methods, datasets and applications.” Atmos. Res. 104–105 (1): 70–97. https://doi.org/10.1016/j.atmosres.2011.10.021.
Tong, D., and A. T. Murray. 2009. “Maximising coverage of spatial demand for service.” Pap. Reg. Sci. 88 (1): 85–97. https://doi.org/10.1111/j.1435-5957.2008.00168.x.
Wang, K., N. Chen, D. Tong, K. Wang, W. Wang, and J. Gong. 2016. “Optimizing precipitation station location: A case study of the Jinsha River Basin.” Int. J. Geogr. Inf. Sci. 30 (6): 1207–1227. https://doi.org/10.1080/13658816.2015.1119280.
Wang, X. D., C. Hirsch, S. Kang, and C. Lacor. 2011. “Multi-objective optimization of turbomachinery using improved NSGA-II and approximation model.” Comput. Methods Appl. Mech. Eng. 200 (9–12): 883–895. https://doi.org/10.1016/j.cma.2010.11.014.
WMO (World Meteorological Organization). 2008. “Guide to hydrological practices, Volume 1, Hydrology—From measurement to hydrological information.” 6th ed. WMO No.168. Accessed May 10, 2019. http://www.hydrology.nl/images/docs/hwrp/WMO_Guide_168_Vol_I_en.pdf.
Yaseen, Z. M., S. O. Sulaiman, R. C. Deo, and K. W. Chau. 2019. “An enhanced extreme learning machine model for river flow forecasting: State-of-the-art, practical applications in water resource engineering area and future research direction.” J. Hydrol. 569 (Feb): 387–408. https://doi.org/10.1016/j.jhydrol.2018.11.069.
Yoo, D. G., G. Chung, A. Sadollah, and J. H. Kim. 2015. “Applications of network analysis and multi-objective genetic algorithm for selecting optimal water quality sensor locations in water distribution networks.” KSCE J. Civ. Eng. 19 (7): 2333–2344. https://doi.org/10.1007/s12205-015-0273-8.
Zade, A. E., A. Sadegheih, and M. M. Lotfi. 2014. “A modified NSGA-II solution for a new multi-objective hub maximal covering problem under uncertain shipments.” J. Ind. Eng. Int. 10 (4): 185–197. https://doi.org/10.1007/s40092-014-0076-4.
Zitzler, E., L. Thiele, M. Laumanns, C. M. Fonseca, and V. G. Da Fonseca. 2003. “Performance assessment of multiobjective optimizers: An analysis and review.” IEEE Trans. Evol. Comput. 7 (2): 117–132. https://doi.org/10.1109/TEVC.2003.810758.
Information & Authors
Information
Published In
Copyright
©2020 American Society of Civil Engineers.
History
Received: Nov 6, 2019
Accepted: Feb 19, 2020
Published online: Jun 19, 2020
Published in print: Sep 1, 2020
Discussion open until: Nov 19, 2020
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.