PRMS-Python: A Python framework for programmatic PRMS modeling and access to its data structures
A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual flux parameterizations and over 100 parameters, the Precipitation-Runoff Modeling System (PRMS) is a perfect example of why it is such a cha...
Uloženo v:
| Vydáno v: | Environmental modelling & software : with environment data news Ročník 114; s. 152 - 165 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
| Vydáno: |
Oxford
Elsevier Ltd
01.04.2019
Elsevier Science Ltd |
| Témata: | |
| ISSN: | 1364-8152, 1873-6726 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual flux parameterizations and over 100 parameters, the Precipitation-Runoff Modeling System (PRMS) is a perfect example of why it is such a challenge to track the history of input and output of complex models. We present a lightweight, object-oriented Python framework with programmatic tools for management and visualization using PRMS as an example platform. Within this framework, a modeler can write intuitive code for a myriad of basic or advanced applications. The framework also includes methods that, for example, apply systematic or stochastic parameter modifications while simultaneously saving metadata on which parameters were varied and with what improvement in performance. We include a case study that uses built in Monte Carlo parameter resampling for global sensitivity analysis of eight PRMS parameters related to estimation of shortwave solar radiation.
•PRMS-Python is a framework for advanced modeling analyses with PRMS hydrologic model.•Tools include modification of model input, visualization, and simulation management.•Framework provides metadata for large model ensembles for sharing and reproducibility.•PRMS-Python is used to conduct a global parameter sensitivity analysis case study. |
|---|---|
| AbstractList | A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual flux parameterizations and over 100 parameters, the Precipitation-Runoff Modeling System (PRMS) is a perfect example of why it is such a challenge to track the history of input and output of complex models. We present a lightweight, object-oriented Python framework with programmatic tools for management and visualization using PRMS as an example platform. Within this framework, a modeler can write intuitive code for a myriad of basic or advanced applications. The framework also includes methods that, for example, apply systematic or stochastic parameter modifications while simultaneously saving metadata on which parameters were varied and with what improvement in performance. We include a case study that uses built in Monte Carlo parameter resampling for global sensitivity analysis of eight PRMS parameters related to estimation of shortwave solar radiation.
•PRMS-Python is a framework for advanced modeling analyses with PRMS hydrologic model.•Tools include modification of model input, visualization, and simulation management.•Framework provides metadata for large model ensembles for sharing and reproducibility.•PRMS-Python is used to conduct a global parameter sensitivity analysis case study. A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual flux parameterizations and over 100 parameters, the Precipitation-Runoff Modeling System (PRMS) is a perfect example of why it is such a challenge to track the history of input and output of complex models. We present a lightweight, object-oriented Python framework with programmatic tools for management and visualization using PRMS as an example platform. Within this framework, a modeler can write intuitive code for a myriad of basic or advanced applications. The framework also includes methods that, for example, apply systematic or stochastic parameter modifications while simultaneously saving metadata on which parameters were varied and with what improvement in performance. We include a case study that uses built in Monte Carlo parameter resampling for global sensitivity analysis of eight PRMS parameters related to estimation of shortwave solar radiation. |
| Author | Turner, Matthew A. Volk, John M. |
| Author_xml | – sequence: 1 givenname: John M. surname: Volk fullname: Volk, John M. email: jmvolk@unr.edu organization: Desert Research Institute, Reno, USA – sequence: 2 givenname: Matthew A. surname: Turner fullname: Turner, Matthew A. email: mturner8@ucmerced.edu organization: Northwest Knowledge Network, University of Idaho, USA |
| BookMark | eNqFkEtLJDEUhYM44GPmJwgBN26qzKsq1boQEV_Qojgz60w6uaVpqxJNUor_ftK0Kze9yiGc73D59tC2Dx4QOqCkpoS2x8sa_HsKfa4ZobOa0JqQdgvt0k7yqpWs3S6Zt6LqaMN20F5KS0JIyWIX_Xt4vPtdPXzm5-BP8DleJ9xHPcJHiC-4DxG_xvBUPkadncErAI_BwuD8E9beYm0MpIRzwC4nbHXWOOU4mTxFSD_Rj14PCX59vfvo79Xln4uban5_fXtxPq8MlyRXoPmsowvD5IIJRoWglnPouJSNNT0xC9bZhvQz3fRCQCNE0y1AciIlN5YB4_voaL1bjn2bIGU1umRgGLSHMCXFGCNdwzlrS_XwW3UZpujLdYrRGeWC8W412KxbJoaUIvTqNbpRx09FiVp5V0v15V2tvCtCVfFeuNNvnHG5mAs-R-2GjfTZmobi6t1BVMk48Aasi2CyssFtWPgPy1qjow |
| CitedBy_id | crossref_primary_10_1016_j_matchemphys_2020_122798 crossref_primary_10_1016_j_envsoft_2025_106618 crossref_primary_10_1016_j_envsoft_2023_105760 crossref_primary_10_3389_feart_2022_907533 crossref_primary_10_1016_j_envsoft_2022_105406 crossref_primary_10_1109_ACCESS_2020_3002164 crossref_primary_10_1016_j_envsoft_2022_105309 crossref_primary_10_1016_j_envsoft_2020_104888 |
| Cites_doi | 10.13031/trans.58.10707 10.1016/j.envsoft.2015.01.004 10.1007/BF00619290 10.1016/j.jhydrol.2015.02.013 10.1111/j.1539-6924.2010.01519.x 10.1175/2010EI370.1 10.1371/journal.pone.0145180 10.1109/MCSE.2007.58 10.1002/2015WR017200 10.1109/MCSE.2011.37 10.1002/2016WR019285 10.1109/MCSE.2007.55 10.1016/j.jhydrol.2013.08.047 10.1002/2015WR017198 10.1016/j.envsoft.2018.07.020 10.1111/j.1752-1688.2006.tb04501.x 10.1038/518125a 10.1016/j.jhydrol.2012.01.034 10.1016/j.jhydrol.2017.12.041 10.1029/WR022i09Sp0046S 10.1002/hyp.7902 10.1002/hyp.10684 10.1002/2014WR015820 10.21105/joss.00097 10.1016/j.cpc.2011.12.020 10.1016/j.envsoft.2016.02.008 10.1016/j.jhydrol.2014.05.026 10.5194/hess-20-4655-2016 10.1016/j.cpc.2009.09.018 10.1111/gwat.12413 |
| ContentType | Journal Article |
| Copyright | 2019 Copyright Elsevier Science Ltd. Apr 2019 |
| Copyright_xml | – notice: 2019 – notice: Copyright Elsevier Science Ltd. Apr 2019 |
| DBID | AAYXX CITATION 7QH 7SC 7ST 7UA 8FD C1K FR3 JQ2 KR7 L7M L~C L~D SOI 7S9 L.6 |
| DOI | 10.1016/j.envsoft.2019.01.006 |
| DatabaseName | CrossRef Aqualine Computer and Information Systems Abstracts Environment Abstracts Water Resources Abstracts Technology Research Database Environmental Sciences and Pollution Management Engineering Research Database ProQuest Computer Science Collection Civil Engineering Abstracts Advanced Technologies Database with Aerospace Computer and Information Systems Abstracts Academic Computer and Information Systems Abstracts Professional Environment Abstracts AGRICOLA AGRICOLA - Academic |
| DatabaseTitle | CrossRef Civil Engineering Abstracts Technology Research Database Computer and Information Systems Abstracts – Academic ProQuest Computer Science Collection Computer and Information Systems Abstracts Engineering Research Database Aqualine Environment Abstracts Advanced Technologies Database with Aerospace Water Resources Abstracts Environmental Sciences and Pollution Management Computer and Information Systems Abstracts Professional AGRICOLA AGRICOLA - Academic |
| DatabaseTitleList | AGRICOLA Civil Engineering Abstracts |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Ecology Computer Science Environmental Sciences |
| EISSN | 1873-6726 |
| EndPage | 165 |
| ExternalDocumentID | 10_1016_j_envsoft_2019_01_006 S1364815218308004 |
| GroupedDBID | --K --M -~X .DC .~1 0R~ 1B1 1RT 1~. 1~5 29G 4.4 457 4G. 53G 5GY 5VS 7-5 71M 8P~ AABNK AACTN AAEDT AAEDW AAHBH AAIKJ AAKOC AALRI AAOAW AAQFI AAQXK AAXKI AAXUO AAYFN AAYOK ABBOA ABFNM ABFYP ABJNI ABLST ABMAC ABXDB ACDAQ ACGFS ACIWK ACNNM ACRLP ACZNC ADBBV ADEZE ADJOM ADMUD AEBSH AEKER AENEX AFJKZ AFKWA AFRAH AFTJW AFXIZ AGHFR AGUBO AGYEJ AHEUO AHZHX AIALX AIEXJ AIKHN AITUG AJOXV AKIFW AKRWK ALMA_UNASSIGNED_HOLDINGS AMFUW AMRAJ AOUOD ASPBG AVWKF AXJTR AZFZN BKOJK BLECG BLXMC CS3 DU5 EBS EFJIC EJD EO8 EO9 EP2 EP3 FDB FEDTE FGOYB FIRID FNPLU FYGXN G-Q GBLVA GBOLZ HVGLF HZ~ IHE J1W KCYFY KOM M41 MO0 N9A O-L O9- OAUVE OZT P-8 P-9 P2P PC. Q38 R2- RIG ROL RPZ SDF SDG SDP SES SEW SPC SPCBC SSJ SSV SSZ T5K UHS ~02 ~G- 9DU AATTM AAYWO AAYXX ABWVN ACLOT ACRPL ACVFH ADCNI ADNMO AEIPS AEUPX AFPUW AGQPQ AIGII AIIUN AKBMS AKYEP ANKPU APXCP CITATION EFKBS EFLBG ~HD 7QH 7SC 7ST 7UA 8FD AGCQF C1K FR3 JQ2 KR7 L7M L~C L~D SOI 7S9 L.6 |
| ID | FETCH-LOGICAL-c370t-ea3981bc27b2421441d33e83775dcf0cb28d50f9a5f44e54458be730773cd2e23 |
| ISICitedReferencesCount | 8 |
| ISICitedReferencesURI | http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=000458135500012&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D |
| ISSN | 1364-8152 |
| IngestDate | Sun Sep 28 10:24:57 EDT 2025 Wed Aug 13 04:41:20 EDT 2025 Tue Nov 18 21:18:07 EST 2025 Sat Nov 29 02:36:24 EST 2025 Thu Nov 14 02:16:25 EST 2024 |
| IsPeerReviewed | true |
| IsScholarly | true |
| Keywords | Parameter sensitivity PRMS PAWN Framework Python |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-c370t-ea3981bc27b2421441d33e83775dcf0cb28d50f9a5f44e54458be730773cd2e23 |
| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 |
| PQID | 2191342382 |
| PQPubID | 2047471 |
| PageCount | 14 |
| ParticipantIDs | proquest_miscellaneous_2220853326 proquest_journals_2191342382 crossref_primary_10_1016_j_envsoft_2019_01_006 crossref_citationtrail_10_1016_j_envsoft_2019_01_006 elsevier_sciencedirect_doi_10_1016_j_envsoft_2019_01_006 |
| PublicationCentury | 2000 |
| PublicationDate | April 2019 2019-04-00 20190401 |
| PublicationDateYYYYMMDD | 2019-04-01 |
| PublicationDate_xml | – month: 04 year: 2019 text: April 2019 |
| PublicationDecade | 2010 |
| PublicationPlace | Oxford |
| PublicationPlace_xml | – name: Oxford |
| PublicationTitle | Environmental modelling & software : with environment data news |
| PublicationYear | 2019 |
| Publisher | Elsevier Ltd Elsevier Science Ltd |
| Publisher_xml | – name: Elsevier Ltd – name: Elsevier Science Ltd |
| References | Hay, Markstrom, Ward-Garrison (bib15) 2011; 15 Leavesley, Markstrom, Brewer, Viger (bib26) 1996; 90 Markstrom, Regan, Hay, Viger, Webb, Payn, LaFontaine (bib28) 2015 Pianosi, Beven, Freer, Hall, Rougier, Stephenson, Wagener (bib34) 2016; 79 Saltelli, Ratto, Andres, Campolongo, Cariboni, Gatelli, Saisana, Tarantola (bib38) 2008 Borgonovo, Castaings, Tarantola (bib2) 2011; 31 Houska, Kraft, Chamorro-Chavez, Breuer (bib18) 2015; 10 Saraswat, Frankenberg, Pai, Ale, Daggupati, Douglas-Mankin, Youssef (bib39) 2015; 58 Tarboton, Idaszak, Horsburgh, Heard, Ames, Goodall, Band, Merwade, Couch, Arrigo, Hooper, Valentine, Maidment (bib43) 2014 Hunter (bib20) 2007; 9 Hutton, Wagener, Freer, Han, Duffy, Arheimer (bib21) 2016; 52 Dooge (bib8) 1986; 22 Hay, Leavesley, Clark, Markstrom, Viger, Umemoto (bib14) 2006; 42 Mendoza, Clark, Barlage, Rajagopalan, Samaniego, Abramowitz, Gupta (bib30) 2015; 51 Volk (bib47) 2014 Wall (bib48) 1996; 37 Harbaugh, Banta, Hill, Mcdonald (bib12) 2000; 121 Hassan, Lubczynski, Niswonger, Su (bib13) 2014; 517 Mendoza, Clark, Mizukami, Gutmann, Arnold, Brekke, Rajagopalan (bib31) 2016; 30 Shin, Guillaume, Croke, Jakeman (bib40) 2013; 503 Clark, Kavetski, Fenicia (bib3) 2011; 47 Herman, Usher (bib17) 2017; 2 Kolmogorov (bib22) 1933; 83–91 Doherty, Hunt (bib7) 2010; 70 Ely (bib9) 2006 Van Der Walt, Colbert, Varoquaux (bib45) 2011; 13 Perkel (bib33) 2015; 518 Clark, McMillan, Collins, Kavetski, Woods (bib4) 2011; 25 Troutman (bib44) 1985 Huang, Kadir, Chung (bib19) 2012; 426–427 Song, Zhang, Zhan, Xuan, Ye, Xu (bib42) 2015; 523 Oliphant (bib32) 2007; 9 Hay, Umemoto (bib16) 2006 Markstrom, Hay, Clark (bib27) 2016; 20 Volk (bib46) 2018 Regan, LaFontaine (bib36) 2017 Pianosi, Wagener (bib35) 2015; 67 Leaf, Brink (bib24) 1973 Leavesley, Lichty, Troutman, Saindon (bib25) 1983 McKinney (bib29) 2013 Feng, Zheng, Mao, Zhang, Wu, Li, Tian, Wu (bib10) 2018; 557 Gardner, Morton, Huntington, Niswonger, Henson (bib11) 2018; 109 Smirnov (bib41) 1939; 2 Clark, Nijssen, Lundquist, Kavetski, Rupp, Woods, Freer, Gutmann, Wood, Brekke, Arnold, Gochis, Rasmussen (bib5) 2015; 51 Bakker, Post, Langevin, Hughes, White, Starn, Fienen (bib1) 2016; 54 Clark, Nijssen, Lundquist, Kavetski, Rupp, Woods, Freer, Gutmann, Wood, Gochis, Rasmussen, Tarboton, Mahat, Flerchinger, Marks (bib6) 2015; 51 Saltelli, Annoni, Azzini, Campolongo, Ratto, Tarantola (bib37) 2010; 181 Kucherenko, Tarantola, Annoni (bib23) 2012; 183 Huang (10.1016/j.envsoft.2019.01.006_bib19) 2012; 426–427 Hunter (10.1016/j.envsoft.2019.01.006_bib20) 2007; 9 Hutton (10.1016/j.envsoft.2019.01.006_bib21) 2016; 52 Doherty (10.1016/j.envsoft.2019.01.006_bib7) 2010; 70 Mendoza (10.1016/j.envsoft.2019.01.006_bib31) 2016; 30 Borgonovo (10.1016/j.envsoft.2019.01.006_bib2) 2011; 31 Markstrom (10.1016/j.envsoft.2019.01.006_bib28) 2015 Regan (10.1016/j.envsoft.2019.01.006_bib36) 2017 Volk (10.1016/j.envsoft.2019.01.006_bib47) 2014 McKinney (10.1016/j.envsoft.2019.01.006_bib29) 2013 Feng (10.1016/j.envsoft.2019.01.006_bib10) 2018; 557 Hay (10.1016/j.envsoft.2019.01.006_bib14) 2006; 42 Herman (10.1016/j.envsoft.2019.01.006_bib17) 2017; 2 Oliphant (10.1016/j.envsoft.2019.01.006_bib32) 2007; 9 Leavesley (10.1016/j.envsoft.2019.01.006_bib26) 1996; 90 Clark (10.1016/j.envsoft.2019.01.006_bib5) 2015; 51 Perkel (10.1016/j.envsoft.2019.01.006_bib33) 2015; 518 Leavesley (10.1016/j.envsoft.2019.01.006_bib25) 1983 Troutman (10.1016/j.envsoft.2019.01.006_bib44) 1985 Clark (10.1016/j.envsoft.2019.01.006_bib4) 2011; 25 Saltelli (10.1016/j.envsoft.2019.01.006_bib38) 2008 Hay (10.1016/j.envsoft.2019.01.006_bib15) 2011; 15 Leaf (10.1016/j.envsoft.2019.01.006_bib24) 1973 Bakker (10.1016/j.envsoft.2019.01.006_bib1) 2016; 54 Harbaugh (10.1016/j.envsoft.2019.01.006_bib12) 2000; 121 Volk (10.1016/j.envsoft.2019.01.006_bib46) Wall (10.1016/j.envsoft.2019.01.006_bib48) 1996; 37 Dooge (10.1016/j.envsoft.2019.01.006_bib8) 1986; 22 Saraswat (10.1016/j.envsoft.2019.01.006_bib39) 2015; 58 Pianosi (10.1016/j.envsoft.2019.01.006_bib34) 2016; 79 Kolmogorov (10.1016/j.envsoft.2019.01.006_bib22) 1933; 83–91 Mendoza (10.1016/j.envsoft.2019.01.006_bib30) 2015; 51 Song (10.1016/j.envsoft.2019.01.006_bib42) 2015; 523 Saltelli (10.1016/j.envsoft.2019.01.006_bib37) 2010; 181 Shin (10.1016/j.envsoft.2019.01.006_bib40) 2013; 503 Hassan (10.1016/j.envsoft.2019.01.006_bib13) 2014; 517 Houska (10.1016/j.envsoft.2019.01.006_bib18) 2015; 10 Gardner (10.1016/j.envsoft.2019.01.006_bib11) 2018; 109 Clark (10.1016/j.envsoft.2019.01.006_bib3) 2011; 47 Tarboton (10.1016/j.envsoft.2019.01.006_bib43) 2014 Hay (10.1016/j.envsoft.2019.01.006_bib16) 2006 Markstrom (10.1016/j.envsoft.2019.01.006_bib27) 2016; 20 Van Der Walt (10.1016/j.envsoft.2019.01.006_bib45) 2011; 13 Pianosi (10.1016/j.envsoft.2019.01.006_bib35) 2015; 67 Ely (10.1016/j.envsoft.2019.01.006_bib9) 2006 Clark (10.1016/j.envsoft.2019.01.006_bib6) 2015; 51 Kucherenko (10.1016/j.envsoft.2019.01.006_bib23) 2012; 183 Smirnov (10.1016/j.envsoft.2019.01.006_bib41) 1939; 2 |
| References_xml | – volume: 518 start-page: 125 year: 2015 end-page: 126 ident: bib33 article-title: Pick up Python publication-title: Nature – year: 2006 ident: bib16 article-title: Multiple-objective stepwise calibration using Luca – volume: 51 start-page: 2515 year: 2015 end-page: 2542 ident: bib6 article-title: A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies publication-title: Water Resour. Res. – volume: 22 start-page: 46S year: 1986 end-page: 58S ident: bib8 article-title: Looking for hydrologic laws publication-title: Water Resour. Res. – volume: 2 year: 1939 ident: bib41 article-title: On the estimation of the discrepancy between empirical curves of distribution for two independent samples publication-title: Bull. Math. Univ. Moscow – volume: 183 start-page: 937 year: 2012 end-page: 946 ident: bib23 article-title: Estimation of global sensitivity indices for models with dependent variables publication-title: Comput. Phys. Commun. – volume: 30 start-page: 1071 year: 2016 end-page: 1095 ident: bib31 article-title: How do hydrologic modeling decisions affect the portrayal of climate change impacts? publication-title: Hydrol. Process. – volume: 51 start-page: 2498 year: 2015 end-page: 2514 ident: bib5 article-title: A unified approach for process-based hydrologic modeling: 1. Modeling concept publication-title: Water Resour. Res. – volume: 9 start-page: 10 year: 2007 end-page: 20 ident: bib32 article-title: Python for scientific computing publication-title: Comput. Sci. Eng. – volume: 52 start-page: 7548 year: 2016 end-page: 7555 ident: bib21 article-title: Most computational hydrology is not reproducible, so is it really science? publication-title: Water Resour. Res. – volume: 20 start-page: 4655 year: 2016 end-page: 4671 ident: bib27 article-title: Towards simplification of hydrologic modeling: identification of dominant processes publication-title: Hydrol. Earth Syst. Sci. – volume: 181 start-page: 259 year: 2010 end-page: 270 ident: bib37 article-title: Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index publication-title: Comput. Phys. Commun. – year: 2018 ident: bib46 article-title: An example template for conducting PAWN global sensitivity analysis on parameters of the PRMS model using the PRMS-Python framework, HydroShare – start-page: 207 year: 1983 ident: bib25 article-title: Precipitation-Runoff Modeling System: Users Manual – volume: 42 start-page: 877 year: 2006 end-page: 890 ident: bib14 article-title: Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin publication-title: J. Am. Water Resour. Assoc. – year: 2013 ident: bib29 article-title: Python for Data Analysis – volume: 51 start-page: 716 year: 2015 end-page: 728 ident: bib30 article-title: Are we unnecessarily constraining the agility of complex process-based models? publication-title: Water Resour. Res. – volume: 79 start-page: 214 year: 2016 end-page: 232 ident: bib34 article-title: Sensitivity analysis of environmental models: A systematic review with practical workflow publication-title: Environ. Model. Softw – volume: 109 start-page: 41 year: 2018 end-page: 53 ident: bib11 article-title: Input data processing tools for the integrated hydrologic model GSFLOW publication-title: Environ. Model. Softw – volume: 31 start-page: 404 year: 2011 end-page: 428 ident: bib2 article-title: Moment Independent importance measures: new results and analytical test cases publication-title: Risk Anal. – volume: 121 year: 2000 ident: bib12 publication-title: MODFLOW-2000, the US Geological Survey modular ground-water model: User guide to modularization concepts and the ground-water flow process – volume: 90 start-page: 303 year: 1996 end-page: 311 ident: bib26 article-title: The modular modeling system (MMS) The physical process modeling component of a database-centered decision support system for water and power management publication-title: Water, Air, Soil Pollut. – volume: 426–427 start-page: 138 year: 2012 end-page: 150 ident: bib19 article-title: Hydrological response to climate warming: The Upper Feather River Watershed publication-title: J. Hydrol. – start-page: 23 year: 2014 end-page: 29 ident: bib43 article-title: Hydro share: Advancing collaboration through hydrologic data and model sharing publication-title: Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014 – volume: 9 start-page: 99 year: 2007 end-page: 104 ident: bib20 article-title: Matplotlib: A 2D graphics environment publication-title: Comput. Sci. Eng. – volume: 557 start-page: 305 year: 2018 end-page: 320 ident: bib10 article-title: An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources publication-title: J. Hydrol. – volume: 37 start-page: 519 year: 1996 ident: bib48 article-title: Practical Statistics for Astronomers - II. Correlation, Data-modelling and Sample Comparison publication-title: Q. J. Roy. Astron. Soc. – year: 2015 ident: bib28 article-title: PRMS-IV , the Precipitation-Runoff Modeling System , Version 4 – volume: 517 start-page: 390 year: 2014 end-page: 410 ident: bib13 article-title: Surfacegroundwater interactions in hard rocks in Sardon Catchment of western Spain: An integrated modeling approach publication-title: J. Hydrol. – year: 1973 ident: bib24 article-title: Hydrologic simulation model of Colorado subalpine forest – year: 2014 ident: bib47 article-title: Potential Effects of a Warming Climate on Water Resources within the Lehman and Baker Creek Drainages , Great Basin National Park , Nevada – volume: 523 start-page: 739 year: 2015 end-page: 757 ident: bib42 article-title: Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications publication-title: J. Hydrol. – year: 2006 ident: bib9 article-title: Analysis of sensitivity of simulated recharge to selected parameters for seven watersheds modeled using the precipitation-runoff modeling system – year: 2017 ident: bib36 article-title: Documentation of the dynamic parameter, water-use, stream and lake flow routing, and two summary output modules and updates to surface-depression storage simulation and initial conditions specification options with the Precipitation-Runoff Modeling System – volume: 58 start-page: 1787 year: 2015 end-page: 1797 ident: bib39 article-title: Hydrologic and Water Quality Models: Documentation and Reporting Procedures for Calibration, Validation, and Use publication-title: Transactions of the ASABE – volume: 83–91 year: 1933 ident: bib22 article-title: Sulla determinazione empirica di una legge di distribuzione publication-title: G. Ist. Ital. Attuari – volume: 15 start-page: 1 year: 2011 end-page: 37 ident: bib15 article-title: Watershed-Scale Response to Climate Change through the Twenty-First Century for Selected Basins across the United States publication-title: Earth Interact. – volume: 47 year: 2011 ident: bib3 publication-title: Pursuing the method of multiple working hypotheses for hydrological modeling – volume: 54 start-page: 733 year: 2016 end-page: 739 ident: bib1 article-title: Scripting MODFLOW model development using python and FloPy publication-title: Gr. Water – year: 2008 ident: bib38 article-title: Global Sensitivity Analysis. The Primer – volume: 10 year: 2015 ident: bib18 article-title: SPOTting Model Parameters Using a Ready-Made Python Package publication-title: PLoS One – volume: 2 year: 2017 ident: bib17 article-title: SALib: An open-source Python library for Sensitivity Analysis publication-title: The Journal of Open Source Software – volume: 25 start-page: 523 year: 2011 end-page: 543 ident: bib4 article-title: Hydrological field data from a modeller's perspective: Part 2: process-based evaluation of model hypotheses publication-title: Hydrol. Process. – volume: 67 start-page: 1 year: 2015 end-page: 11 ident: bib35 article-title: A simple and efficient method for global sensitivity analysis based on cumulative distribution functions publication-title: Environ. Model. Softw – volume: 13 start-page: 22 year: 2011 end-page: 30 ident: bib45 article-title: The NumPy array: A structure for efficient numerical computation publication-title: Comput. Sci. Eng. – year: 1985 ident: bib44 article-title: Errors and Parameter Estimation in Precipitation-Runoff Modeling 2 – volume: 503 start-page: 135 year: 2013 end-page: 152 ident: bib40 article-title: Addressing ten questions about conceptual rainfall-runoff models with global sensitivity analyses in R publication-title: J. Hydrol. – volume: 70 year: 2010 ident: bib7 publication-title: Approaches to highly parameterized inversion: a guide to using PEST for groundwater-model calibration – year: 1985 ident: 10.1016/j.envsoft.2019.01.006_bib44 – volume: 2 year: 1939 ident: 10.1016/j.envsoft.2019.01.006_bib41 article-title: On the estimation of the discrepancy between empirical curves of distribution for two independent samples publication-title: Bull. Math. Univ. Moscow – volume: 58 start-page: 1787 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib39 article-title: Hydrologic and Water Quality Models: Documentation and Reporting Procedures for Calibration, Validation, and Use publication-title: Transactions of the ASABE doi: 10.13031/trans.58.10707 – year: 2008 ident: 10.1016/j.envsoft.2019.01.006_bib38 – year: 2014 ident: 10.1016/j.envsoft.2019.01.006_bib47 – year: 1973 ident: 10.1016/j.envsoft.2019.01.006_bib24 – volume: 67 start-page: 1 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib35 article-title: A simple and efficient method for global sensitivity analysis based on cumulative distribution functions publication-title: Environ. Model. Softw doi: 10.1016/j.envsoft.2015.01.004 – ident: 10.1016/j.envsoft.2019.01.006_bib46 – volume: 90 start-page: 303 year: 1996 ident: 10.1016/j.envsoft.2019.01.006_bib26 article-title: The modular modeling system (MMS) The physical process modeling component of a database-centered decision support system for water and power management publication-title: Water, Air, Soil Pollut. doi: 10.1007/BF00619290 – volume: 121 year: 2000 ident: 10.1016/j.envsoft.2019.01.006_bib12 – volume: 83–91 year: 1933 ident: 10.1016/j.envsoft.2019.01.006_bib22 article-title: Sulla determinazione empirica di una legge di distribuzione publication-title: G. Ist. Ital. Attuari – volume: 523 start-page: 739 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib42 article-title: Global sensitivity analysis in hydrological modeling: Review of concepts, methods, theoretical framework, and applications publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2015.02.013 – volume: 31 start-page: 404 year: 2011 ident: 10.1016/j.envsoft.2019.01.006_bib2 article-title: Moment Independent importance measures: new results and analytical test cases publication-title: Risk Anal. doi: 10.1111/j.1539-6924.2010.01519.x – start-page: 207 year: 1983 ident: 10.1016/j.envsoft.2019.01.006_bib25 – volume: 15 start-page: 1 year: 2011 ident: 10.1016/j.envsoft.2019.01.006_bib15 article-title: Watershed-Scale Response to Climate Change through the Twenty-First Century for Selected Basins across the United States publication-title: Earth Interact. doi: 10.1175/2010EI370.1 – year: 2006 ident: 10.1016/j.envsoft.2019.01.006_bib16 – volume: 10 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib18 article-title: SPOTting Model Parameters Using a Ready-Made Python Package publication-title: PLoS One doi: 10.1371/journal.pone.0145180 – volume: 9 start-page: 10 year: 2007 ident: 10.1016/j.envsoft.2019.01.006_bib32 article-title: Python for scientific computing publication-title: Comput. Sci. Eng. doi: 10.1109/MCSE.2007.58 – volume: 37 start-page: 519 year: 1996 ident: 10.1016/j.envsoft.2019.01.006_bib48 article-title: Practical Statistics for Astronomers - II. Correlation, Data-modelling and Sample Comparison publication-title: Q. J. Roy. Astron. Soc. – volume: 51 start-page: 2515 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib6 article-title: A unified approach for process-based hydrologic modeling: 2. Model implementation and case studies publication-title: Water Resour. Res. doi: 10.1002/2015WR017200 – start-page: 23 year: 2014 ident: 10.1016/j.envsoft.2019.01.006_bib43 article-title: Hydro share: Advancing collaboration through hydrologic data and model sharing – volume: 13 start-page: 22 year: 2011 ident: 10.1016/j.envsoft.2019.01.006_bib45 article-title: The NumPy array: A structure for efficient numerical computation publication-title: Comput. Sci. Eng. doi: 10.1109/MCSE.2011.37 – volume: 52 start-page: 7548 year: 2016 ident: 10.1016/j.envsoft.2019.01.006_bib21 article-title: Most computational hydrology is not reproducible, so is it really science? publication-title: Water Resour. Res. doi: 10.1002/2016WR019285 – volume: 9 start-page: 99 year: 2007 ident: 10.1016/j.envsoft.2019.01.006_bib20 article-title: Matplotlib: A 2D graphics environment publication-title: Comput. Sci. Eng. doi: 10.1109/MCSE.2007.55 – volume: 503 start-page: 135 year: 2013 ident: 10.1016/j.envsoft.2019.01.006_bib40 article-title: Addressing ten questions about conceptual rainfall-runoff models with global sensitivity analyses in R publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2013.08.047 – volume: 51 start-page: 2498 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib5 article-title: A unified approach for process-based hydrologic modeling: 1. Modeling concept publication-title: Water Resour. Res. doi: 10.1002/2015WR017198 – volume: 109 start-page: 41 year: 2018 ident: 10.1016/j.envsoft.2019.01.006_bib11 article-title: Input data processing tools for the integrated hydrologic model GSFLOW publication-title: Environ. Model. Softw doi: 10.1016/j.envsoft.2018.07.020 – year: 2013 ident: 10.1016/j.envsoft.2019.01.006_bib29 – volume: 47 year: 2011 ident: 10.1016/j.envsoft.2019.01.006_bib3 – volume: 42 start-page: 877 year: 2006 ident: 10.1016/j.envsoft.2019.01.006_bib14 article-title: Step wise, multiple objective calibration of a hydrologic model for a snowmelt dominated basin publication-title: J. Am. Water Resour. Assoc. doi: 10.1111/j.1752-1688.2006.tb04501.x – volume: 518 start-page: 125 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib33 article-title: Pick up Python publication-title: Nature doi: 10.1038/518125a – volume: 70 year: 2010 ident: 10.1016/j.envsoft.2019.01.006_bib7 – volume: 426–427 start-page: 138 year: 2012 ident: 10.1016/j.envsoft.2019.01.006_bib19 article-title: Hydrological response to climate warming: The Upper Feather River Watershed publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2012.01.034 – volume: 557 start-page: 305 year: 2018 ident: 10.1016/j.envsoft.2019.01.006_bib10 article-title: An integrated hydrological modeling approach for detection and attribution of climatic and human impacts on coastal water resources publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2017.12.041 – volume: 22 start-page: 46S year: 1986 ident: 10.1016/j.envsoft.2019.01.006_bib8 article-title: Looking for hydrologic laws publication-title: Water Resour. Res. doi: 10.1029/WR022i09Sp0046S – year: 2006 ident: 10.1016/j.envsoft.2019.01.006_bib9 – volume: 25 start-page: 523 year: 2011 ident: 10.1016/j.envsoft.2019.01.006_bib4 article-title: Hydrological field data from a modeller's perspective: Part 2: process-based evaluation of model hypotheses publication-title: Hydrol. Process. doi: 10.1002/hyp.7902 – volume: 30 start-page: 1071 year: 2016 ident: 10.1016/j.envsoft.2019.01.006_bib31 article-title: How do hydrologic modeling decisions affect the portrayal of climate change impacts? publication-title: Hydrol. Process. doi: 10.1002/hyp.10684 – volume: 51 start-page: 716 year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib30 article-title: Are we unnecessarily constraining the agility of complex process-based models? publication-title: Water Resour. Res. doi: 10.1002/2014WR015820 – volume: 2 year: 2017 ident: 10.1016/j.envsoft.2019.01.006_bib17 article-title: SALib: An open-source Python library for Sensitivity Analysis publication-title: The Journal of Open Source Software doi: 10.21105/joss.00097 – year: 2015 ident: 10.1016/j.envsoft.2019.01.006_bib28 – volume: 183 start-page: 937 year: 2012 ident: 10.1016/j.envsoft.2019.01.006_bib23 article-title: Estimation of global sensitivity indices for models with dependent variables publication-title: Comput. Phys. Commun. doi: 10.1016/j.cpc.2011.12.020 – volume: 79 start-page: 214 year: 2016 ident: 10.1016/j.envsoft.2019.01.006_bib34 article-title: Sensitivity analysis of environmental models: A systematic review with practical workflow publication-title: Environ. Model. Softw doi: 10.1016/j.envsoft.2016.02.008 – volume: 517 start-page: 390 year: 2014 ident: 10.1016/j.envsoft.2019.01.006_bib13 article-title: Surfacegroundwater interactions in hard rocks in Sardon Catchment of western Spain: An integrated modeling approach publication-title: J. Hydrol. doi: 10.1016/j.jhydrol.2014.05.026 – volume: 20 start-page: 4655 year: 2016 ident: 10.1016/j.envsoft.2019.01.006_bib27 article-title: Towards simplification of hydrologic modeling: identification of dominant processes publication-title: Hydrol. Earth Syst. Sci. doi: 10.5194/hess-20-4655-2016 – volume: 181 start-page: 259 year: 2010 ident: 10.1016/j.envsoft.2019.01.006_bib37 article-title: Variance based sensitivity analysis of model output. Design and estimator for the total sensitivity index publication-title: Comput. Phys. Commun. doi: 10.1016/j.cpc.2009.09.018 – year: 2017 ident: 10.1016/j.envsoft.2019.01.006_bib36 – volume: 54 start-page: 733 year: 2016 ident: 10.1016/j.envsoft.2019.01.006_bib1 article-title: Scripting MODFLOW model development using python and FloPy publication-title: Gr. Water doi: 10.1111/gwat.12413 |
| SSID | ssj0001524 |
| Score | 2.2958806 |
| Snippet | A persistent problem in numerical hydrologic modeling, is tracking provenance or how particular data came to be. With multiple modules available for individual... |
| SourceID | proquest crossref elsevier |
| SourceType | Aggregation Database Enrichment Source Index Database Publisher |
| StartPage | 152 |
| SubjectTerms | case studies Computer simulation Data structures Framework Hydrologic models Hydrology Mathematical models metadata Parameter estimation Parameter modification Parameter sensitivity PAWN PRMS provenance Python Rainfall-runoff relationships Resampling Runoff Sensitivity analysis Short wave radiation Solar radiation Tracking |
| Title | PRMS-Python: A Python framework for programmatic PRMS modeling and access to its data structures |
| URI | https://dx.doi.org/10.1016/j.envsoft.2019.01.006 https://www.proquest.com/docview/2191342382 https://www.proquest.com/docview/2220853326 |
| Volume | 114 |
| WOSCitedRecordID | wos000458135500012&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: ScienceDirect database customDbUrl: eissn: 1873-6726 dateEnd: 99991231 omitProxy: false ssIdentifier: ssj0001524 issn: 1364-8152 databaseCode: AIEXJ dateStart: 19970101 isFulltext: true titleUrlDefault: https://www.sciencedirect.com providerName: Elsevier |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwtV1Rb9MwELaqDSR4GFCY6BjISLxFKUmc1A5vFSoCxKYKxtQ3kziOtFGlU9uN7Wfwj7mL7SQbg7EHXqIoiS2n9_V8dr77jpBXieYZxrng_Qrlx6Io_azQzI8VU1kpVBDXG26Hn_j-vpjN0mmv99PlwpzNeVWJ8_P05L-aGq6BsTF19hbmbjqFC3AORocjmB2O_2T46ee9L_70AjUBTNq5OfdKR8OqmYWWl2UEW7GJqYnjUhazuo4iBqb4YQFppJ5Rmj1dWtKh281vE-UwDwX7mJvdh5G3Ahf_A5llOI56w7eTVmc67Qb1h4v5d8cO9vaGLfNjaZNybG1ybzzs7lWEaYfiYtwrG8W-CJPL_jeMOx7U3TSTcWgKSfzm582Ww_EQho3vghS9tJZfDa7R1b4y3zUsREdwO5a2G4ndyCCUtYj7ZsSTFBzl5vjDZPaxmd5hgKZSsn2VNi3s9bXj-VPAc2Xqr-OZg4dkyy5E6NgA6BHp6apPHrgiH9T6_D65O6l1zS_65H5Hu7JPti9Z3j2_eky-dQD4ho6pOaMN_CjAj3bhR7EBdfCjAD9q4EfXCwrwo4gU2sLvCfn6bnLw9r1v63j4ivFg7euMpbA6UhHPkYAAAXjBmBaM86RQZaDySBRJUKZZUsaxRnUokWuYeThnqoh0xLbJRrWo9FNCdSaiRCmRRkrFo7LMRFmogmVpmgc5rBMHJHY_tlRW5B5rrczlX409IMOm2YlRebmpgXCWlDZUNSGoBITe1HTXWV5at7GSEDeEqMUpogF52dwGT4-f77JKL07hmQjr6TJYb-3cdrjPyL3277hLNsBi-jm5o87WR6vlC4vwXyik0Pc |
| 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=PRMS-Python%3A+A+Python+framework+for+programmatic+PRMS+modeling+and+access+to+its+data+structures&rft.jtitle=Environmental+modelling+%26+software+%3A+with+environment+data+news&rft.au=Volk%2C+John+M.&rft.au=Turner%2C+Matthew+A.&rft.date=2019-04-01&rft.issn=1364-8152&rft.volume=114&rft.spage=152&rft.epage=165&rft_id=info:doi/10.1016%2Fj.envsoft.2019.01.006&rft.externalDBID=n%2Fa&rft.externalDocID=10_1016_j_envsoft_2019_01_006 |
| thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1364-8152&client=summon |
| thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1364-8152&client=summon |
| thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1364-8152&client=summon |