Integration of hydrological models with entropy and multi-objective optimization based methods for designing specific needs streamflow monitoring networks
•Hydrological Models Can Effectively Guide the Design of Hydrometric Networks.•Using Model Performance Criteria as Design Objectives enables User-Directed Designs.•A novel model-based strategy is proposed that outperforms the traditional approach. Water resource managers depend on the collection of...
Uloženo v:
| Vydáno v: | Journal of hydrology (Amsterdam) Ročník 593; s. 125876 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Elsevier B.V
01.02.2021
|
| Témata: | |
| ISSN: | 0022-1694, 1879-2707 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | •Hydrological Models Can Effectively Guide the Design of Hydrometric Networks.•Using Model Performance Criteria as Design Objectives enables User-Directed Designs.•A novel model-based strategy is proposed that outperforms the traditional approach.
Water resource managers depend on the collection of accurate hydrometric data for various modeling and planning projects. An essential use of hydrometric data includes hydrologic modelling and forecasting to support decision making in water resources planning and management. It is, therefore, essential to design hydrometric monitoring networks while considering the relationship between data collection and model application. A new model-based network design strategy is proposed that embeds hydrological models into a multi-objective evolutionary algorithm, facilitating direct optimization according to the model-based design objectives. This method is compared to the traditional model-based approach used to design hydrometric monitoring networks. The traditional approach is to first conduct optimization using secondary design objectives, that are not model based, to identify a set of optimal networks. Hydrological models are then applied as a post-processing mechanism to identify which of the optimal networks best satisfy the model orientated design objectives or users’ needs. In this investigation, the well-established dual-entropy multi-objective optimization (DEMO) approach was employed to conduct the initial network design based on the principles of information theory, followed by post-processing with rainfall-runoff models. Two case studies are evaluated, a monitoring network reduction in the Fraser River basin and a network augmentation in an upstream subsection of the Churchill River basin. Results show that embedding models in the optimization algorithm consistently yields better network configurations compared to those identified using the traditional method. It is shown that a smaller size optimal network that outperforms larger size networks can be identified directly by the proposed method. The models and model performance criteria used in the design process can be readily adapted, allowing for a user-directed design capable of addressing problem-specific objectives on a case by case basis. |
|---|---|
| AbstractList | •Hydrological Models Can Effectively Guide the Design of Hydrometric Networks.•Using Model Performance Criteria as Design Objectives enables User-Directed Designs.•A novel model-based strategy is proposed that outperforms the traditional approach.
Water resource managers depend on the collection of accurate hydrometric data for various modeling and planning projects. An essential use of hydrometric data includes hydrologic modelling and forecasting to support decision making in water resources planning and management. It is, therefore, essential to design hydrometric monitoring networks while considering the relationship between data collection and model application. A new model-based network design strategy is proposed that embeds hydrological models into a multi-objective evolutionary algorithm, facilitating direct optimization according to the model-based design objectives. This method is compared to the traditional model-based approach used to design hydrometric monitoring networks. The traditional approach is to first conduct optimization using secondary design objectives, that are not model based, to identify a set of optimal networks. Hydrological models are then applied as a post-processing mechanism to identify which of the optimal networks best satisfy the model orientated design objectives or users’ needs. In this investigation, the well-established dual-entropy multi-objective optimization (DEMO) approach was employed to conduct the initial network design based on the principles of information theory, followed by post-processing with rainfall-runoff models. Two case studies are evaluated, a monitoring network reduction in the Fraser River basin and a network augmentation in an upstream subsection of the Churchill River basin. Results show that embedding models in the optimization algorithm consistently yields better network configurations compared to those identified using the traditional method. It is shown that a smaller size optimal network that outperforms larger size networks can be identified directly by the proposed method. The models and model performance criteria used in the design process can be readily adapted, allowing for a user-directed design capable of addressing problem-specific objectives on a case by case basis. Water resource managers depend on the collection of accurate hydrometric data for various modeling and planning projects. An essential use of hydrometric data includes hydrologic modelling and forecasting to support decision making in water resources planning and management. It is, therefore, essential to design hydrometric monitoring networks while considering the relationship between data collection and model application. A new model-based network design strategy is proposed that embeds hydrological models into a multi-objective evolutionary algorithm, facilitating direct optimization according to the model-based design objectives. This method is compared to the traditional model-based approach used to design hydrometric monitoring networks. The traditional approach is to first conduct optimization using secondary design objectives, that are not model based, to identify a set of optimal networks. Hydrological models are then applied as a post-processing mechanism to identify which of the optimal networks best satisfy the model orientated design objectives or users’ needs. In this investigation, the well-established dual-entropy multi-objective optimization (DEMO) approach was employed to conduct the initial network design based on the principles of information theory, followed by post-processing with rainfall-runoff models. Two case studies are evaluated, a monitoring network reduction in the Fraser River basin and a network augmentation in an upstream subsection of the Churchill River basin. Results show that embedding models in the optimization algorithm consistently yields better network configurations compared to those identified using the traditional method. It is shown that a smaller size optimal network that outperforms larger size networks can be identified directly by the proposed method. The models and model performance criteria used in the design process can be readily adapted, allowing for a user-directed design capable of addressing problem-specific objectives on a case by case basis. |
| ArticleNumber | 125876 |
| Author | Ursulak, Jacob Coulibaly, Paulin |
| Author_xml | – sequence: 1 givenname: Jacob surname: Ursulak fullname: Ursulak, Jacob email: ursulajp@mcmaster.ca organization: Department of Civil Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada – sequence: 2 givenname: Paulin surname: Coulibaly fullname: Coulibaly, Paulin organization: Department of Civil Engineering, McMaster University, 1280 Main Street West, Hamilton, ON L8S 4K1, Canada |
| BookMark | eNqFkcFu1DAQhi1UJLaFR0DykUsW23GSjTggVFGoVIkLnC3HHu9OcOxge7taHoWnJUt64tK5jDTz__9I812TqxADEPKWsy1nvH0_bsfD2abot4KJZSaaXde-IBu-6_pKdKy7IhvGhKh428tX5DrnkS1V13JD_tyHAvukC8ZAo6NrUNyj0Z5O0YLP9ITlQCGUFOcz1cHS6egLVnEYwRR8BBrnghP-XkMGnWGRQDlEm6mLiVrIuA8Y9jTPYNChoQFgWeaSQE_Ox9NyKmCJ6SIKUE4x_cyvyUunfYY3T_2G_Lj7_P32a_Xw7cv97aeHytRSlMrVErgBGJgwEvq6ZrIbbN8C17w1trPgGmd7aAcrWw1NJ9pec2NBG2dh19c35N2aO6f46wi5qAmzAe91gHjMSjRCip5J1i3SZpWaFHNO4NSccNLprDhTFxZqVE8s1IWFWlksvg__-QyWf-8qSaN_1v1xdS8w4BEhqWwQggGLaSGgbMRnEv4C7fqySw |
| CitedBy_id | crossref_primary_10_1080_07011784_2023_2242815 crossref_primary_10_3390_w17142160 crossref_primary_10_1007_s13201_023_01992_5 crossref_primary_10_1016_j_jhydrol_2024_130817 crossref_primary_10_5194_hess_28_3099_2024 crossref_primary_10_1016_j_probengmech_2024_103582 crossref_primary_10_1016_j_jhydrol_2023_129806 crossref_primary_10_3389_fevo_2025_1587167 crossref_primary_10_2166_hydro_2024_256 crossref_primary_10_3390_atmos13010143 crossref_primary_10_1177_14727978241299638 crossref_primary_10_1029_2022WR032429 |
| Cites_doi | 10.1175/2011JHM1369.1 10.1016/S0022-1694(98)00188-7 10.1038/s41893-018-0047-7 10.1002/2013WR014058 10.1016/j.jhydrol.2015.03.034 10.1016/j.jhydrol.2019.04.068 10.3390/e21100991 10.1016/j.jhydrol.2018.04.037 10.1029/2011WR011251 10.1147/rd.41.0066 10.1007/BF00872282 10.1029/WR015i006p01791 10.1061/(ASCE)HE.1943-5584.0001508 10.5194/hess-22-989-2018 10.1029/WR010i004p00713 10.1016/S0022-1694(03)00244-0 10.1016/j.jhydrol.2016.01.009 10.3390/rs70100686 10.1016/j.jhydrol.2010.09.018 10.1016/j.jhydrol.2017.07.003 10.1007/BF00174760 10.1111/1752-1688.12611 10.3390/e19110613 10.1016/0022-1694(70)90255-6 10.1016/j.advwatres.2015.01.013 10.1016/j.advwatres.2016.07.006 10.1029/2007RG000243 10.1139/f84-068 10.1016/j.jhydrol.2015.08.048 10.5194/hess-21-3071-2017 10.1623/hysj.50.2.279.61801 10.1016/j.jhydrol.2018.05.058 10.1016/j.advwatres.2011.10.011 10.5194/hess-19-3301-2015 10.1016/j.advwatres.2008.01.017 10.1029/2005WR004723 10.1080/02626660209492977 10.1111/j.1752-1688.1989.tb03088.x 10.1175/JHM-D-14-0191.1 10.1016/j.jhydrol.2013.09.004 10.2166/nh.2010.007 10.2166/nh.2016.344 10.5194/hess-8-1103-2004 10.1002/j.1538-7305.1948.tb01338.x 10.1016/j.envres.2019.108686 10.1016/j.jhydrol.2009.11.015 10.1029/2006GL026962 10.2166/wst.2006.303 10.1029/97WR03495 10.1016/0022-1694(91)90173-F 10.1007/BF02289159 10.1023/A:1015511811686 10.1002/2015WR017137 10.1002/2016WR019981 10.1029/2010WR009194 |
| ContentType | Journal Article |
| Copyright | 2020 Elsevier B.V. |
| Copyright_xml | – notice: 2020 Elsevier B.V. |
| DBID | AAYXX CITATION 7S9 L.6 |
| DOI | 10.1016/j.jhydrol.2020.125876 |
| DatabaseName | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Geography |
| EISSN | 1879-2707 |
| ExternalDocumentID | 10_1016_j_jhydrol_2020_125876 S0022169420313378 |
| GroupedDBID | --K --M -~X .~1 0R~ 1B1 1RT 1~. 1~5 29K 4.4 457 4G. 5GY 5VS 6TJ 7-5 71M 8P~ 9JM 9JN AABNK AABVA AACTN AAEDT AAEDW AAIAV AAIKJ AAKOC AALCJ AALRI AAOAW AAQFI AAQXK AATLK AAXUO ABEFU ABFNM ABGRD ABJNI ABMAC ABQEM ABQYD ABTAH ABXDB ABYKQ ACDAQ ACGFS ACIUM ACLVX ACNCT ACRLP ACSBN ADBBV ADEZE ADMUD ADQTV AEBSH AEKER AENEX AEQOU AFFNX AFKWA AFTJW AFXIZ AGHFR AGUBO AGYEJ AHHHB AIEXJ AIKHN AITUG AJBFU AJOXV ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ ASPBG ATOGT AVWKF AXJTR AZFZN BKOJK BLXMC CBWCG CS3 D-I DU5 EBS EFJIC EFLBG EJD EO8 EO9 EP2 EP3 FA8 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-2 G-Q GBLVA HLV HMA HVGLF HZ~ H~9 IHE IMUCA J1W K-O KOM LW9 LY3 M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SAB SCC SDF SDG SDP SEP SES SEW SPC SPCBC SPD SSA SSE SSZ T5K TN5 UQL VOH WUQ Y6R ZCA ZMT ZY4 ~02 ~G- ~KM 9DU AAHBH AATTM AAXKI AAYWO AAYXX ABUFD ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO ADVLN AEIPS AEUPX AFJKZ AFPUW AGQPQ AIGII AIIUN AKBMS AKRWK AKYEP ANKPU APXCP CITATION EFKBS ~HD 7S9 L.6 |
| ID | FETCH-LOGICAL-c342t-f34e1ceeb02c4e933047bd96e1a16cd7def5fd9e6bd46ae57269a1cdeacfde893 |
| ISICitedReferencesCount | 15 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000639853400061&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 0022-1694 |
| IngestDate | Sun Nov 09 12:05:56 EST 2025 Tue Nov 18 22:18:57 EST 2025 Sat Nov 29 07:27:53 EST 2025 Fri Feb 23 02:45:21 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Hydrometric Monitoring Networks Entropy Hydrological Modelling Optimization |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c342t-f34e1ceeb02c4e933047bd96e1a16cd7def5fd9e6bd46ae57269a1cdeacfde893 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
| PQID | 2524290407 |
| PQPubID | 24069 |
| ParticipantIDs | proquest_miscellaneous_2524290407 crossref_primary_10_1016_j_jhydrol_2020_125876 crossref_citationtrail_10_1016_j_jhydrol_2020_125876 elsevier_sciencedirect_doi_10_1016_j_jhydrol_2020_125876 |
| PublicationCentury | 2000 |
| PublicationDate | February 2021 2021-02-00 20210201 |
| PublicationDateYYYYMMDD | 2021-02-01 |
| PublicationDate_xml | – month: 02 year: 2021 text: February 2021 |
| PublicationDecade | 2020 |
| PublicationTitle | Journal of hydrology (Amsterdam) |
| PublicationYear | 2021 |
| Publisher | Elsevier B.V |
| Publisher_xml | – name: Elsevier B.V |
| References | Leach, Kornelsen, Samuel, Coulibaly (b0170) 2015; 529 Pardo-Igúzquiza (b0255) 1998; 210 Weisse, Bois (b0375) 2002; 47 Nour, M.H., Smit, D.W., Gamal El-Din, M., 2006. Geostatistical mapping of precipitation: Implications for rain gauge network design. Water Sci. Technol. 53, 101–110. https://doi.org/10.2166/wst.2006.303. McGill (b0210) 1954; 19 Alfonso, Lobbrecht, Price (b0005) 2010; 46 Keum, Coulibaly (b0115) 2017; 53 Lindström, G., Pers, C., Rosberg, J., Strömqvist, J., Arheimer, B., 2010. Development and testing of the HYPE (Hydrological Predictions for the Environment) water quality model for different spatial scales. Hydrol. Res. 41, 295–319. https://doi.org/10.2166/nh.2010.007. Northcote, T. G., and P. A. Larkin. 1989. The Fraser River: A major salmonine production system. In D. P. Dodge (ed.). Proceedings of the international large river symposium (LARS). Canadian Special Publication of Fisheries and Aquatic Sciences 106:172–204. Lane, Sykes (b0155) 1982 Tolson, Shoemaker (b0340) 2007; 43 Werstuck, C., Coulibaly, P., 2017. Hydrometric network design using dual entropy multi-objective optimization in the Ottawa River Basin. Hydrol. Res. 48, 1639–1651. https://doi.org/10.2166/nh.2016.344. Keum, Coulibaly (b0120) 2017; 22 Government of Canada, 2010. Land Use 2010. URL https://open.canada.ca/data/en/dataset/9e1efe92-e5a3-4f70-b313-68fb1283eadf (accessed 2.5.19). Wang, Wang, Singh, Wang, Wu, Zhang, Liu, Zou, He, Meng (b0365) 2019; 178 Mishra, Coulibaly (b0220) 2010; 380 Reed, Kollat (b0265) 2012; 35 Werstuck, Coulibaly (b0385) 2018; 54 Krstanovic, Singh (b0145) 1992; 6 Kollat, Reed, Maxwell (b0140) 2011; 47 Chacon-hurtado, Alfonso, Solomatine (b0050) 2017; 21 Markus, Vernon Knapp, Tasker (b0205) 2003; 283 Newbury, McCullough, Hecky (b0240) 1984; 41 Xiao, R., He, X., Zhang, Y., Ferreira, V.G., Chang, L., 2015. Monitoring groundwater variations from satellite gravimetry and hydrological models: A comparison with in-situ measurements in the mid-atlantic region of the United States. Remote Sens. 7, 686–703. https://doi.org/10.3390/rs70100686. Gupta, Sorooshian, Yapo (b0085) 1998; 34 Swenson, Yeh, Wahr, Famiglietti (b0330) 2006; 33 Xu, H., Xu, C.Y., Sælthun, N.R., Xu, Y., Zhou, B., Chen, H., 2015. Entropy theory based multi-criteria resampling of rain gauge networks for hydrological modelling - A case study of humid area in southern China. J. Hydrol. 525, 138–151. https://doi.org/10.1016/j.jhydrol.2015.03.034. Watanabe (b0360) 1960; 4 Dong, Dohmen-Janssen, Booji (b0065) 2005; 50 Keum, Kornelsen, Leach, Coulibaly (b0130) 2017; 19 Tasker, Moss (b0335) 1979; 15 Luo, Wu, Yang, Qian, Wu (b0190) 2016; 534 Fahle, Hohenbrink, Dietrich, Lischeid (b0070) 2015; 51 Weedon, G.P., Gomes, S., Viterbo, P., Shuttleworth, W.J., Blyth, E., ÖSterle, H., Adam, J.C., Bellouin, N., Boucher, O., Best, M., 2011. Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J. Hydrometeorol. 12, 823–848. https://doi.org/10.1175/2011JHM1369.1. Husain (b0100) 1989; 25 Mishra, Coulibaly (b0215) 2009; 47 Ragettli, Pellicciotti, Immerzeel, Miles, Petersen, Heynen, Shea, Stumm, Joshi, Shrestha (b0260) 2015; 78 Stosic, Stosic, Singh (b0325) 2017; 552 François, Schlef, Wi, Brown (b0075) 2019; 574 Nash, Sutcliffe (b0235) 1970; 10 Halverson, M.J., Fleming, S.W., 2015. Complex network theory, streamflow, and hydrometric monitoring system design. Hydrol. Earth Syst. Sci. 19, 3301–3318. https://doi.org/10.5194/hess-19-3301-2015. Laize, C.L.R., 2004. Integration of spatial datasets to support the review of hydrometric networks and the identification of representative catchments. Hydrol. Earth Syst. Sci. 8, 1103–1117. https://doi.org/10.5194/hess-8-1103-2004. World Meteorological Organization, 2008. Guide to Hydrological Practices, Volume I Hydrology – From Measurement to Hydrological Information, WMO-No. 168, Sixth. ed. Keum, Coulibaly, Razavi, Tapsoba, Gobena, Weber, Pietroniro (b0125) 2018; 561 Kollat, Reed, Kasprzyk (b0135) 2008; 31 Shannon, C.E., 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423. Leach, Coulibaly, Guo (b0165) 2016; 96 Samuel, Coulibaly, Kollat (b0280) 2013; 49 Berg, P., Donnelly, C., Gustafsson, D., 2018. Near-real-time adjusted reanalysis forcing data for hydrology. Hydrol. Earth Syst. Sci. 22, 989–1000. https://doi.org/10.5194/hess-22-989-2018. Ruhi, Messager, Olden (b0275) 2018; 1 Joo, Lee, Jun, Kim, Hong, Kim, Kim (b0110) 2019; 21 Benke, Cushing (b0015) 2005 Xu, Xu, Chen, Zhang, Li (b0405) 2013; 505 Burn, Goulter (b0045) 1991; 122 Karnieli (b0105) 1990; 22 Mogheir, Singh (b0230) 2002; 16 Stadnyk, T.; Bajracharya, A.R., 2019. HYPE Model Output for NCRB using Hydro-GFD Reanalysis Dataset. Unpublished work. Lespinas, F., Fortin, V., Roy, G., Rasmussen, P., Stadnyk, T., 2015. Performance evaluation of the canadian precipitation analysis (CaPA). J. Hydrometeorol. 16, 2045–2064. https://doi.org/10.1175/JHM-D-14-0191.1. Li, Singh, Mishra (b0180) 2012; 48 Vaze, Post, Chiew, Perraud, Viney, Teng (b0350) 2010; 394 Zubrycki, Roy, Osman, Lewtas, Gunn, Grosshans (b0425) 2016 Rodríguez-Iturbe, Mejía (b0270) 1974; 10 Zeng, Chen, Xu, Jie, Chen, Guo, Liu (b0420) 2018; 563 10.1016/j.jhydrol.2020.125876_b0320 10.1016/j.jhydrol.2020.125876_b0245 Lane (10.1016/j.jhydrol.2020.125876_b0155) 1982 10.1016/j.jhydrol.2020.125876_b0400 Benke (10.1016/j.jhydrol.2020.125876_b0015) 2005 Zeng (10.1016/j.jhydrol.2020.125876_b0420) 2018; 563 Fahle (10.1016/j.jhydrol.2020.125876_b0070) 2015; 51 Karnieli (10.1016/j.jhydrol.2020.125876_b0105) 1990; 22 Weisse (10.1016/j.jhydrol.2020.125876_b0375) 2002; 47 Vaze (10.1016/j.jhydrol.2020.125876_b0350) 2010; 394 10.1016/j.jhydrol.2020.125876_b0080 Rodríguez-Iturbe (10.1016/j.jhydrol.2020.125876_b0270) 1974; 10 Stosic (10.1016/j.jhydrol.2020.125876_b0325) 2017; 552 Samuel (10.1016/j.jhydrol.2020.125876_b0280) 2013; 49 Ragettli (10.1016/j.jhydrol.2020.125876_b0260) 2015; 78 Joo (10.1016/j.jhydrol.2020.125876_b0110) 2019; 21 Tolson (10.1016/j.jhydrol.2020.125876_b0340) 2007; 43 François (10.1016/j.jhydrol.2020.125876_b0075) 2019; 574 Pardo-Igúzquiza (10.1016/j.jhydrol.2020.125876_b0255) 1998; 210 10.1016/j.jhydrol.2020.125876_b0410 Mogheir (10.1016/j.jhydrol.2020.125876_b0230) 2002; 16 Newbury (10.1016/j.jhydrol.2020.125876_b0240) 1984; 41 Xu (10.1016/j.jhydrol.2020.125876_b0405) 2013; 505 Chacon-hurtado (10.1016/j.jhydrol.2020.125876_b0050) 2017; 21 Gupta (10.1016/j.jhydrol.2020.125876_b0085) 1998; 34 Markus (10.1016/j.jhydrol.2020.125876_b0205) 2003; 283 10.1016/j.jhydrol.2020.125876_b0090 Watanabe (10.1016/j.jhydrol.2020.125876_b0360) 1960; 4 10.1016/j.jhydrol.2020.125876_b0250 Keum (10.1016/j.jhydrol.2020.125876_b0115) 2017; 53 Li (10.1016/j.jhydrol.2020.125876_b0180) 2012; 48 10.1016/j.jhydrol.2020.125876_b0370 10.1016/j.jhydrol.2020.125876_b0175 Husain (10.1016/j.jhydrol.2020.125876_b0100) 1989; 25 Tasker (10.1016/j.jhydrol.2020.125876_b0335) 1979; 15 10.1016/j.jhydrol.2020.125876_b0025 10.1016/j.jhydrol.2020.125876_b0300 Leach (10.1016/j.jhydrol.2020.125876_b0170) 2015; 529 Wang (10.1016/j.jhydrol.2020.125876_b0365) 2019; 178 Zubrycki (10.1016/j.jhydrol.2020.125876_b0425) 2016 Keum (10.1016/j.jhydrol.2020.125876_b0125) 2018; 561 McGill (10.1016/j.jhydrol.2020.125876_b0210) 1954; 19 Keum (10.1016/j.jhydrol.2020.125876_b0120) 2017; 22 Keum (10.1016/j.jhydrol.2020.125876_b0130) 2017; 19 Alfonso (10.1016/j.jhydrol.2020.125876_b0005) 2010; 46 Werstuck (10.1016/j.jhydrol.2020.125876_b0385) 2018; 54 Burn (10.1016/j.jhydrol.2020.125876_b0045) 1991; 122 10.1016/j.jhydrol.2020.125876_b0380 10.1016/j.jhydrol.2020.125876_b0185 Mishra (10.1016/j.jhydrol.2020.125876_b0215) 2009; 47 Leach (10.1016/j.jhydrol.2020.125876_b0165) 2016; 96 Dong (10.1016/j.jhydrol.2020.125876_b0065) 2005; 50 Kollat (10.1016/j.jhydrol.2020.125876_b0140) 2011; 47 Kollat (10.1016/j.jhydrol.2020.125876_b0135) 2008; 31 Nash (10.1016/j.jhydrol.2020.125876_b0235) 1970; 10 Luo (10.1016/j.jhydrol.2020.125876_b0190) 2016; 534 Krstanovic (10.1016/j.jhydrol.2020.125876_b0145) 1992; 6 Ruhi (10.1016/j.jhydrol.2020.125876_b0275) 2018; 1 Mishra (10.1016/j.jhydrol.2020.125876_b0220) 2010; 380 Reed (10.1016/j.jhydrol.2020.125876_b0265) 2012; 35 Swenson (10.1016/j.jhydrol.2020.125876_b0330) 2006; 33 10.1016/j.jhydrol.2020.125876_b0150 10.1016/j.jhydrol.2020.125876_b0395 |
| References_xml | – year: 2016 ident: b0425 article-title: Large Area Planning in the Nelson-Churchill River Basin (NCRB): Laying a foundation in northern Manitoba; International Institute for Sustainable Development (IISD):Winnipeg – volume: 561 start-page: 688 year: 2018 end-page: 701 ident: b0125 article-title: Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design publication-title: J. Hydrol. – volume: 31 start-page: 828 year: 2008 end-page: 845 ident: b0135 article-title: A new epsilon-dominance hierarchical Bayesian optimization algorithm for large multiobjective monitoring network design problems publication-title: Adv. Water Resourc. – volume: 22 start-page: 391 year: 1990 end-page: 398 ident: b0105 article-title: Application of kriging technique to areal precipitation mapping in Arizona publication-title: GeoJournal – start-page: 1 year: 2005 end-page: 18 ident: b0015 article-title: Background and approach publication-title: Rivers of North America – volume: 19 start-page: 97 year: 1954 end-page: 116 ident: b0210 article-title: Multivariate information transmission publication-title: Psychometrika – reference: Shannon, C.E., 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379–423. – reference: Lespinas, F., Fortin, V., Roy, G., Rasmussen, P., Stadnyk, T., 2015. Performance evaluation of the canadian precipitation analysis (CaPA). J. Hydrometeorol. 16, 2045–2064. https://doi.org/10.1175/JHM-D-14-0191.1. – volume: 394 start-page: 447 year: 2010 end-page: 457 ident: b0350 article-title: Climate non-stationarity – Validity of calibrated rainfall–runoff models for use in climate change studies publication-title: J. Hydrol. – volume: 15 start-page: 1791 year: 1979 end-page: 1796 ident: b0335 article-title: Analysis of arizona flood data network for regional information publication-title: Water Resour. Res. – volume: 46 start-page: 1 year: 2010 end-page: 13 ident: b0005 article-title: Optimization of water level monitoring network in polder systems using information theory publication-title: Water Resour. Res. – volume: 34 start-page: 751 year: 1998 end-page: 763 ident: b0085 article-title: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information publication-title: Water Resour. Res. – volume: 534 start-page: 352 year: 2016 end-page: 363 ident: b0190 article-title: Multi-objective optimization of long-term groundwater monitoring network design using a probabilistic Pareto genetic algorithm under uncertainty publication-title: J. Hydrol. – volume: 283 start-page: 107 year: 2003 end-page: 121 ident: b0205 article-title: Entropy and generalized least square methods in assessment of the regional value of streamgages publication-title: J. Hydrol. – reference: Xu, H., Xu, C.Y., Sælthun, N.R., Xu, Y., Zhou, B., Chen, H., 2015. Entropy theory based multi-criteria resampling of rain gauge networks for hydrological modelling - A case study of humid area in southern China. J. Hydrol. 525, 138–151. https://doi.org/10.1016/j.jhydrol.2015.03.034. – volume: 1 start-page: 198 year: 2018 end-page: 203 ident: b0275 article-title: Tracking the pulse of the Earth’s fresh waters publication-title: Nat Sustain – volume: 41 start-page: 548 year: 1984 end-page: 557 ident: b0240 article-title: The southern indian lake impoundment and churchill river diversion publication-title: Can. J. Fish. Aquat. Sci. – reference: Northcote, T. G., and P. A. Larkin. 1989. The Fraser River: A major salmonine production system. In D. P. Dodge (ed.). Proceedings of the international large river symposium (LARS). Canadian Special Publication of Fisheries and Aquatic Sciences 106:172–204. – volume: 50 start-page: 279 year: 2005 end-page: 298 ident: b0065 article-title: Appropriate spatial sampling of rainfall for flow simulation publication-title: Hydrologic. Sci. J. – volume: 51 start-page: 7723 year: 2015 end-page: 7743 ident: b0070 article-title: Temporal variability of the optimal monitoring setup assessed using information theory publication-title: Water Resour. Res. – reference: Werstuck, C., Coulibaly, P., 2017. Hydrometric network design using dual entropy multi-objective optimization in the Ottawa River Basin. Hydrol. Res. 48, 1639–1651. https://doi.org/10.2166/nh.2016.344. – volume: 47 start-page: 739 year: 2002 end-page: 752 ident: b0375 article-title: A comparison of methods for mapping statistical characteristics of heavy rainfall in the French Alps: the use of daily information / Comparaison de méthodes de cartographie de paramètres statistiques des précipitations extrêmes dans les Alpes françaises: apport de l'information journalière publication-title: Hydrol. Sci. J. – volume: 19 start-page: 1 year: 2017 end-page: 21 ident: b0130 article-title: Entropy applications to water monitoring network design: A review publication-title: Entropy – volume: 10 start-page: 713 year: 1974 end-page: 728 ident: b0270 article-title: The design of rainfall networks in time and space publication-title: Water Resour. Res. – volume: 21 start-page: 3071 year: 2017 end-page: 3091 ident: b0050 article-title: Rainfall and streamflow sensor network design: A review of applications, classification, and a proposed framework publication-title: Hydrol. Earth Syst. Sci. – volume: 47 start-page: 1 year: 2011 end-page: 18 ident: b0140 article-title: Many-objective groundwater monitoring network design using bias-aware ensemble Kalman filtering, evolutionary optimization, and visual analytics publication-title: Water Resour. Res. – reference: Weedon, G.P., Gomes, S., Viterbo, P., Shuttleworth, W.J., Blyth, E., ÖSterle, H., Adam, J.C., Bellouin, N., Boucher, O., Best, M., 2011. Creation of the WATCH forcing data and its use to assess global and regional reference crop evaporation over land during the twentieth century. J. Hydrometeorol. 12, 823–848. https://doi.org/10.1175/2011JHM1369.1. – volume: 35 start-page: 55 year: 2012 end-page: 68 ident: b0265 article-title: Save now, pay later? Multi-period many-objective groundwater monitoring design given systematic model errors and uncertainty publication-title: Adv. Water Resour. – reference: Government of Canada, 2010. Land Use 2010. URL https://open.canada.ca/data/en/dataset/9e1efe92-e5a3-4f70-b313-68fb1283eadf (accessed 2.5.19). – reference: Stadnyk, T.; Bajracharya, A.R., 2019. HYPE Model Output for NCRB using Hydro-GFD Reanalysis Dataset. Unpublished work. – year: 1982 ident: b0155 article-title: Nature’s lifeline: Prairie and northern waters – reference: World Meteorological Organization, 2008. Guide to Hydrological Practices, Volume I Hydrology – From Measurement to Hydrological Information, WMO-No. 168, Sixth. ed. – reference: Laize, C.L.R., 2004. Integration of spatial datasets to support the review of hydrometric networks and the identification of representative catchments. Hydrol. Earth Syst. Sci. 8, 1103–1117. https://doi.org/10.5194/hess-8-1103-2004. – volume: 6 start-page: 295 year: 1992 end-page: 314 ident: b0145 article-title: Evaluation of rainfall networks using entropy: II. Application publication-title: Water Resour Manage – reference: Berg, P., Donnelly, C., Gustafsson, D., 2018. Near-real-time adjusted reanalysis forcing data for hydrology. Hydrol. Earth Syst. Sci. 22, 989–1000. https://doi.org/10.5194/hess-22-989-2018. – volume: 78 start-page: 94 year: 2015 end-page: 111 ident: b0260 article-title: Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model publication-title: Adv. Water Resour. – volume: 96 start-page: 108 year: 2016 end-page: 119 ident: b0165 article-title: Entropy based groundwater monitoring network design considering spatial distribution of annual recharge publication-title: Adv. Water Resour. – volume: 47 year: 2009 ident: b0215 article-title: Developments in hydrometric network design: A review publication-title: Rev. Geophys. – volume: 4 start-page: 66 year: 1960 end-page: 82 ident: b0360 article-title: Information theoretical analysis of multivariate correlation publication-title: IBM J. Res. Dev. – volume: 122 start-page: 71 year: 1991 end-page: 91 ident: b0045 article-title: An approach to the rationalization of streamflow data collection networks publication-title: J. Hydrol. – volume: 16 start-page: 37 year: 2002 end-page: 49 ident: b0230 article-title: Application of information theory to groundwater quality monitoring networks publication-title: Water Resour. Manag. – volume: 505 start-page: 1 year: 2013 end-page: 12 ident: b0405 article-title: Assessing the influence of rain gauge density and distribution on hydrological model performance in a humid region of China publication-title: J. Hydrol. – volume: 54 start-page: 275 year: 2018 end-page: 286 ident: b0385 article-title: Assessing spatial scale effects on hydrometric network design using entropy and multi-objective methods publication-title: J. Am. Water Resour. Assoc. – volume: 210 start-page: 206 year: 1998 end-page: 220 ident: b0255 article-title: Optimal selection of number and location of rainfall gauges for areal rainfall estimation using geostatistics and simulated annealing publication-title: J. Hydrol. – volume: 10 start-page: 282 year: 1970 end-page: 290 ident: b0235 article-title: River flow forecasting through conceptual models part I — A discussion of principles publication-title: J. Hydrol. – reference: Halverson, M.J., Fleming, S.W., 2015. Complex network theory, streamflow, and hydrometric monitoring system design. Hydrol. Earth Syst. Sci. 19, 3301–3318. https://doi.org/10.5194/hess-19-3301-2015. – volume: 49 start-page: 8070 year: 2013 end-page: 8089 ident: b0280 article-title: CRDEMO: Combined regionalization and dual entropy-multiobjective optimization for hydrometric network design: Crdemo for Hydrometric Network Design publication-title: Water Resour. Res. – volume: 25 start-page: 527 year: 1989 end-page: 534 ident: b0100 article-title: Hydrologic uncertainty measure and network design publication-title: J. Am. Water Resour. Assoc. – volume: 21 start-page: 991 year: 2019 ident: b0110 article-title: Optimal stream gauge network design using entropy theory and importance of stream gauge stations publication-title: Entropy – volume: 552 start-page: 306 year: 2017 end-page: 312 ident: b0325 article-title: Optimizing streamflow monitoring networks using joint permutation entropy publication-title: J. Hydrol. – volume: 178 start-page: 108686 year: 2019 ident: b0365 article-title: Evaluation of information transfer and data transfer models of rain-gauge network design based on information entropy publication-title: Environ. Res. – volume: 53 start-page: 6239 year: 2017 end-page: 6259 ident: b0115 article-title: Information theory-based decision support system for integrated design of multivariable hydrometric networks publication-title: Water Resour. Res. – volume: 22 start-page: 04017009 year: 2017 ident: b0120 article-title: Sensitivity of entropy method to time series length in hydrometric network design publication-title: J. Hydrol. Eng. – volume: 563 start-page: 106 year: 2018 end-page: 122 ident: b0420 article-title: The effect of rain gauge density and distribution on runoff simulation using a lumped hydrological modelling approach publication-title: J. Hydrol. – reference: Nour, M.H., Smit, D.W., Gamal El-Din, M., 2006. Geostatistical mapping of precipitation: Implications for rain gauge network design. Water Sci. Technol. 53, 101–110. https://doi.org/10.2166/wst.2006.303. – volume: 574 start-page: 557 year: 2019 end-page: 573 ident: b0075 article-title: Design considerations for riverine floods in a changing climate – A review publication-title: J. Hydrol. – reference: Lindström, G., Pers, C., Rosberg, J., Strömqvist, J., Arheimer, B., 2010. Development and testing of the HYPE (Hydrological Predictions for the Environment) water quality model for different spatial scales. Hydrol. Res. 41, 295–319. https://doi.org/10.2166/nh.2010.007. – volume: 33 start-page: 1 year: 2006 end-page: 5 ident: b0330 article-title: A comparison of terrestrial water storage variations from GRACE with in situ measurements from Illinois publication-title: Geophys. Res. Lett. – volume: 48 start-page: 1 year: 2012 end-page: 15 ident: b0180 article-title: Entropy theory-based criterion for hydrometric network evaluation and design: Maximum information minimum redundancy publication-title: Water Resour. Res. – volume: 529 start-page: 1350 year: 2015 end-page: 1359 ident: b0170 article-title: Hydrometric network design using streamflow signatures and indicators of hydrologic alteration publication-title: J. Hydrol. – volume: 43 start-page: 1 year: 2007 end-page: 16 ident: b0340 article-title: Dynamically dimensioned search algorithm for computationally efficient watershed model calibration publication-title: Water Resour. Res. – volume: 380 start-page: 420 year: 2010 end-page: 437 ident: b0220 article-title: Hydrometric network evaluation for Canadian watersheds publication-title: J. Hydrol. – reference: Xiao, R., He, X., Zhang, Y., Ferreira, V.G., Chang, L., 2015. Monitoring groundwater variations from satellite gravimetry and hydrological models: A comparison with in-situ measurements in the mid-atlantic region of the United States. Remote Sens. 7, 686–703. https://doi.org/10.3390/rs70100686. – ident: 10.1016/j.jhydrol.2020.125876_b0370 doi: 10.1175/2011JHM1369.1 – volume: 210 start-page: 206 issue: 1-4 year: 1998 ident: 10.1016/j.jhydrol.2020.125876_b0255 article-title: Optimal selection of number and location of rainfall gauges for areal rainfall estimation using geostatistics and simulated annealing publication-title: J. Hydrol. doi: 10.1016/S0022-1694(98)00188-7 – volume: 1 start-page: 198 issue: 4 year: 2018 ident: 10.1016/j.jhydrol.2020.125876_b0275 article-title: Tracking the pulse of the Earth’s fresh waters publication-title: Nat Sustain doi: 10.1038/s41893-018-0047-7 – volume: 49 start-page: 8070 issue: 12 year: 2013 ident: 10.1016/j.jhydrol.2020.125876_b0280 article-title: CRDEMO: Combined regionalization and dual entropy-multiobjective optimization for hydrometric network design: Crdemo for Hydrometric Network Design publication-title: Water Resour. Res. doi: 10.1002/2013WR014058 – ident: 10.1016/j.jhydrol.2020.125876_b0410 doi: 10.1016/j.jhydrol.2015.03.034 – volume: 574 start-page: 557 year: 2019 ident: 10.1016/j.jhydrol.2020.125876_b0075 article-title: Design considerations for riverine floods in a changing climate – A review publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2019.04.068 – volume: 46 start-page: 1 year: 2010 ident: 10.1016/j.jhydrol.2020.125876_b0005 article-title: Optimization of water level monitoring network in polder systems using information theory publication-title: Water Resour. Res. – volume: 21 start-page: 991 year: 2019 ident: 10.1016/j.jhydrol.2020.125876_b0110 article-title: Optimal stream gauge network design using entropy theory and importance of stream gauge stations publication-title: Entropy doi: 10.3390/e21100991 – volume: 561 start-page: 688 year: 2018 ident: 10.1016/j.jhydrol.2020.125876_b0125 article-title: Application of SNODAS and hydrologic models to enhance entropy-based snow monitoring network design publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2018.04.037 – volume: 48 start-page: 1 year: 2012 ident: 10.1016/j.jhydrol.2020.125876_b0180 article-title: Entropy theory-based criterion for hydrometric network evaluation and design: Maximum information minimum redundancy publication-title: Water Resour. Res. doi: 10.1029/2011WR011251 – volume: 4 start-page: 66 issue: 1 year: 1960 ident: 10.1016/j.jhydrol.2020.125876_b0360 article-title: Information theoretical analysis of multivariate correlation publication-title: IBM J. Res. Dev. doi: 10.1147/rd.41.0066 – year: 1982 ident: 10.1016/j.jhydrol.2020.125876_b0155 – volume: 6 start-page: 295 issue: 4 year: 1992 ident: 10.1016/j.jhydrol.2020.125876_b0145 article-title: Evaluation of rainfall networks using entropy: II. Application publication-title: Water Resour Manage doi: 10.1007/BF00872282 – volume: 15 start-page: 1791 issue: 6 year: 1979 ident: 10.1016/j.jhydrol.2020.125876_b0335 article-title: Analysis of arizona flood data network for regional information publication-title: Water Resour. Res. doi: 10.1029/WR015i006p01791 – volume: 22 start-page: 04017009 issue: 7 year: 2017 ident: 10.1016/j.jhydrol.2020.125876_b0120 article-title: Sensitivity of entropy method to time series length in hydrometric network design publication-title: J. Hydrol. Eng. doi: 10.1061/(ASCE)HE.1943-5584.0001508 – ident: 10.1016/j.jhydrol.2020.125876_b0320 – ident: 10.1016/j.jhydrol.2020.125876_b0025 doi: 10.5194/hess-22-989-2018 – volume: 10 start-page: 713 issue: 4 year: 1974 ident: 10.1016/j.jhydrol.2020.125876_b0270 article-title: The design of rainfall networks in time and space publication-title: Water Resour. Res. doi: 10.1029/WR010i004p00713 – volume: 283 start-page: 107 issue: 1-4 year: 2003 ident: 10.1016/j.jhydrol.2020.125876_b0205 article-title: Entropy and generalized least square methods in assessment of the regional value of streamgages publication-title: J. Hydrol. doi: 10.1016/S0022-1694(03)00244-0 – volume: 534 start-page: 352 year: 2016 ident: 10.1016/j.jhydrol.2020.125876_b0190 article-title: Multi-objective optimization of long-term groundwater monitoring network design using a probabilistic Pareto genetic algorithm under uncertainty publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2016.01.009 – ident: 10.1016/j.jhydrol.2020.125876_b0400 doi: 10.3390/rs70100686 – volume: 394 start-page: 447 issue: 3-4 year: 2010 ident: 10.1016/j.jhydrol.2020.125876_b0350 article-title: Climate non-stationarity – Validity of calibrated rainfall–runoff models for use in climate change studies publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2010.09.018 – volume: 552 start-page: 306 year: 2017 ident: 10.1016/j.jhydrol.2020.125876_b0325 article-title: Optimizing streamflow monitoring networks using joint permutation entropy publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2017.07.003 – volume: 22 start-page: 391 year: 1990 ident: 10.1016/j.jhydrol.2020.125876_b0105 article-title: Application of kriging technique to areal precipitation mapping in Arizona publication-title: GeoJournal doi: 10.1007/BF00174760 – volume: 54 start-page: 275 issue: 1 year: 2018 ident: 10.1016/j.jhydrol.2020.125876_b0385 article-title: Assessing spatial scale effects on hydrometric network design using entropy and multi-objective methods publication-title: J. Am. Water Resour. Assoc. doi: 10.1111/1752-1688.12611 – volume: 19 start-page: 1 year: 2017 ident: 10.1016/j.jhydrol.2020.125876_b0130 article-title: Entropy applications to water monitoring network design: A review publication-title: Entropy doi: 10.3390/e19110613 – volume: 10 start-page: 282 issue: 3 year: 1970 ident: 10.1016/j.jhydrol.2020.125876_b0235 article-title: River flow forecasting through conceptual models part I — A discussion of principles publication-title: J. Hydrol. doi: 10.1016/0022-1694(70)90255-6 – volume: 78 start-page: 94 year: 2015 ident: 10.1016/j.jhydrol.2020.125876_b0260 article-title: Unraveling the hydrology of a Himalayan catchment through integration of high resolution in situ data and remote sensing with an advanced simulation model publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2015.01.013 – volume: 96 start-page: 108 year: 2016 ident: 10.1016/j.jhydrol.2020.125876_b0165 article-title: Entropy based groundwater monitoring network design considering spatial distribution of annual recharge publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2016.07.006 – volume: 47 issue: 2 year: 2009 ident: 10.1016/j.jhydrol.2020.125876_b0215 article-title: Developments in hydrometric network design: A review publication-title: Rev. Geophys. doi: 10.1029/2007RG000243 – volume: 41 start-page: 548 issue: 4 year: 1984 ident: 10.1016/j.jhydrol.2020.125876_b0240 article-title: The southern indian lake impoundment and churchill river diversion publication-title: Can. J. Fish. Aquat. Sci. doi: 10.1139/f84-068 – volume: 529 start-page: 1350 year: 2015 ident: 10.1016/j.jhydrol.2020.125876_b0170 article-title: Hydrometric network design using streamflow signatures and indicators of hydrologic alteration publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2015.08.048 – volume: 21 start-page: 3071 year: 2017 ident: 10.1016/j.jhydrol.2020.125876_b0050 article-title: Rainfall and streamflow sensor network design: A review of applications, classification, and a proposed framework publication-title: Hydrol. Earth Syst. Sci. doi: 10.5194/hess-21-3071-2017 – volume: 50 start-page: 279 year: 2005 ident: 10.1016/j.jhydrol.2020.125876_b0065 article-title: Appropriate spatial sampling of rainfall for flow simulation publication-title: Hydrologic. Sci. J. doi: 10.1623/hysj.50.2.279.61801 – volume: 563 start-page: 106 year: 2018 ident: 10.1016/j.jhydrol.2020.125876_b0420 article-title: The effect of rain gauge density and distribution on runoff simulation using a lumped hydrological modelling approach publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2018.05.058 – volume: 35 start-page: 55 year: 2012 ident: 10.1016/j.jhydrol.2020.125876_b0265 article-title: Save now, pay later? Multi-period many-objective groundwater monitoring design given systematic model errors and uncertainty publication-title: Adv. Water Resour. doi: 10.1016/j.advwatres.2011.10.011 – ident: 10.1016/j.jhydrol.2020.125876_b0090 doi: 10.5194/hess-19-3301-2015 – volume: 31 start-page: 828 issue: 5 year: 2008 ident: 10.1016/j.jhydrol.2020.125876_b0135 article-title: A new epsilon-dominance hierarchical Bayesian optimization algorithm for large multiobjective monitoring network design problems publication-title: Adv. Water Resourc. doi: 10.1016/j.advwatres.2008.01.017 – volume: 43 start-page: 1 year: 2007 ident: 10.1016/j.jhydrol.2020.125876_b0340 article-title: Dynamically dimensioned search algorithm for computationally efficient watershed model calibration publication-title: Water Resour. Res. doi: 10.1029/2005WR004723 – volume: 47 start-page: 739 issue: 5 year: 2002 ident: 10.1016/j.jhydrol.2020.125876_b0375 publication-title: Hydrol. Sci. J. doi: 10.1080/02626660209492977 – volume: 25 start-page: 527 year: 1989 ident: 10.1016/j.jhydrol.2020.125876_b0100 article-title: Hydrologic uncertainty measure and network design publication-title: J. Am. Water Resour. Assoc. doi: 10.1111/j.1752-1688.1989.tb03088.x – ident: 10.1016/j.jhydrol.2020.125876_b0175 doi: 10.1175/JHM-D-14-0191.1 – volume: 505 start-page: 1 year: 2013 ident: 10.1016/j.jhydrol.2020.125876_b0405 article-title: Assessing the influence of rain gauge density and distribution on hydrological model performance in a humid region of China publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2013.09.004 – ident: 10.1016/j.jhydrol.2020.125876_b0245 – ident: 10.1016/j.jhydrol.2020.125876_b0185 doi: 10.2166/nh.2010.007 – ident: 10.1016/j.jhydrol.2020.125876_b0380 doi: 10.2166/nh.2016.344 – ident: 10.1016/j.jhydrol.2020.125876_b0150 doi: 10.5194/hess-8-1103-2004 – ident: 10.1016/j.jhydrol.2020.125876_b0300 doi: 10.1002/j.1538-7305.1948.tb01338.x – year: 2016 ident: 10.1016/j.jhydrol.2020.125876_b0425 – volume: 178 start-page: 108686 year: 2019 ident: 10.1016/j.jhydrol.2020.125876_b0365 article-title: Evaluation of information transfer and data transfer models of rain-gauge network design based on information entropy publication-title: Environ. Res. doi: 10.1016/j.envres.2019.108686 – volume: 380 start-page: 420 issue: 3-4 year: 2010 ident: 10.1016/j.jhydrol.2020.125876_b0220 article-title: Hydrometric network evaluation for Canadian watersheds publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2009.11.015 – start-page: 1 year: 2005 ident: 10.1016/j.jhydrol.2020.125876_b0015 article-title: Background and approach – volume: 33 start-page: 1 year: 2006 ident: 10.1016/j.jhydrol.2020.125876_b0330 article-title: A comparison of terrestrial water storage variations from GRACE with in situ measurements from Illinois publication-title: Geophys. Res. Lett. doi: 10.1029/2006GL026962 – ident: 10.1016/j.jhydrol.2020.125876_b0250 doi: 10.2166/wst.2006.303 – volume: 34 start-page: 751 issue: 4 year: 1998 ident: 10.1016/j.jhydrol.2020.125876_b0085 article-title: Toward improved calibration of hydrologic models: Multiple and noncommensurable measures of information publication-title: Water Resour. Res. doi: 10.1029/97WR03495 – volume: 122 start-page: 71 issue: 1-4 year: 1991 ident: 10.1016/j.jhydrol.2020.125876_b0045 article-title: An approach to the rationalization of streamflow data collection networks publication-title: J. Hydrol. doi: 10.1016/0022-1694(91)90173-F – ident: 10.1016/j.jhydrol.2020.125876_b0395 – volume: 19 start-page: 97 issue: 2 year: 1954 ident: 10.1016/j.jhydrol.2020.125876_b0210 article-title: Multivariate information transmission publication-title: Psychometrika doi: 10.1007/BF02289159 – volume: 16 start-page: 37 year: 2002 ident: 10.1016/j.jhydrol.2020.125876_b0230 article-title: Application of information theory to groundwater quality monitoring networks publication-title: Water Resour. Manag. doi: 10.1023/A:1015511811686 – ident: 10.1016/j.jhydrol.2020.125876_b0080 – volume: 51 start-page: 7723 issue: 9 year: 2015 ident: 10.1016/j.jhydrol.2020.125876_b0070 article-title: Temporal variability of the optimal monitoring setup assessed using information theory publication-title: Water Resour. Res. doi: 10.1002/2015WR017137 – volume: 53 start-page: 6239 issue: 7 year: 2017 ident: 10.1016/j.jhydrol.2020.125876_b0115 article-title: Information theory-based decision support system for integrated design of multivariable hydrometric networks publication-title: Water Resour. Res. doi: 10.1002/2016WR019981 – volume: 47 start-page: 1 year: 2011 ident: 10.1016/j.jhydrol.2020.125876_b0140 article-title: Many-objective groundwater monitoring network design using bias-aware ensemble Kalman filtering, evolutionary optimization, and visual analytics publication-title: Water Resour. Res. doi: 10.1029/2010WR009194 |
| SSID | ssj0000334 |
| Score | 2.4241438 |
| Snippet | •Hydrological Models Can Effectively Guide the Design of Hydrometric Networks.•Using Model Performance Criteria as Design Objectives enables User-Directed... Water resource managers depend on the collection of accurate hydrometric data for various modeling and planning projects. An essential use of hydrometric data... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 125876 |
| SubjectTerms | algorithms data collection Entropy Hydrological Modelling Hydrometric Monitoring Networks mathematical theory model validation Optimization runoff stream flow watersheds |
| Title | Integration of hydrological models with entropy and multi-objective optimization based methods for designing specific needs streamflow monitoring networks |
| URI | https://dx.doi.org/10.1016/j.jhydrol.2020.125876 https://www.proquest.com/docview/2524290407 |
| Volume | 593 |
| WOSCitedRecordID | wos000639853400061&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| journalDatabaseRights | – providerCode: PRVESC databaseName: Elsevier SD Freedom Collection Journals 2021 customDbUrl: eissn: 1879-2707 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0000334 issn: 0022-1694 databaseCode: AIEXJ dateStart: 19950101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Lb9NAEF6FFAkuiKcoLy0St8gBe9fe9TFCBcqh4tBKuVn7stSQ2FEepfwPTvxaZl92lFIVkLhYlqX1Jvm-zIzHM98g9IaZmjJNSEJFYRLwUHkCJyRRinCh4BmDMe2GTbCTEz6dll8Ggx-xF-ZizpqGX16Wy_8KNVwDsG3r7F_A3d0ULsA5gA5HgB2OfwT8cRCAiJHgd73qDJybexMa2mxat116-SVXVpi0cubN36gFQ7IIHZoj6-h0GDXt1BtG2pV9uEyEHV9fn6tRA15w7TpPxKKet99gK2ssXHVf40vN19cEwvETurqDycIqN2hL0y5FcbZab-fiqy_qVa3s3pvYae5S-FnZtsQxqIiHJEaWxrrnmFm70l3TdRqkhR-CPDbeQHNW2h46tmvBcz9k8Yo38ImJ2Xjmv8gYdrZyGjlne-rbzp_b99aZ3S6zepaE8VvoIGN5yYfoYHJ8NP3ce3hCaFShtwv6zrC3v93suphnz_u7kOb0ProXIMATz6EHaGCah-jORxNUzB-hnztcwm2Nd7mEPZew5RIOXMLAJbzHJbzLJey4hAOXMHAJd1zCkUvYcQn3XMI9l3Dk0mN09uHo9P2nJAzzSBSh2SapCTUpRGTyXaaocWk0JnVZmFSkhdJMmzqvdWkKqWkhTM6yohSp0hAY1NpAVP0EDZu2MU8R1lTwQmeScMWpklpCCJwaXReKSCtYd4ho_LkrFZTu7cCVeRVLGmdVQKmyKFUepUM07pYtvdTLTQt4xLIK8aqPQysg4E1LX0fsK7Dn9iWdaEy7XVdZDkFzCa6VPfv32z9Hd_t_2Qs03Ky25iW6rS425-vVq0DnX1KN1hU |
| linkProvider | Elsevier |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Integration+of+hydrological+models+with+entropy+and+multi-objective+optimization+based+methods+for+designing+specific+needs+streamflow+monitoring+networks&rft.jtitle=Journal+of+hydrology+%28Amsterdam%29&rft.au=Ursulak%2C+Jacob&rft.au=Coulibaly%2C+Paulin&rft.date=2021-02-01&rft.pub=Elsevier+B.V&rft.issn=0022-1694&rft.eissn=1879-2707&rft.volume=593&rft_id=info:doi/10.1016%2Fj.jhydrol.2020.125876&rft.externalDocID=S0022169420313378 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0022-1694&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0022-1694&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0022-1694&client=summon |