Global optimization techniques for the calibration of conceptual rainfall-runoff models-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Global optimization techniques for the calibration of conceptual rainfall-runoff models

Published:1998-06 Issue:3 Volume:43 Page:443-458
ISSN:0262-6667
Container-title:Hydrological Sciences Journal
language:en
Short-container-title:Hydrological Sciences Journal

Author:

FRANCHINI MARCO¹,GALEATI GIORGIO²,BERRA SAVERIO³

Affiliation:

1. a DISTART, Costruzioni Idrauliche, Università di Bologna , Viale Risorgimento 2, 1-40136, Bologna, Italy E-mail:

2. b EN EL SpA, Centro di Ricerca Idraulica e Strutturale , Corso del Popolo 245, 1-30172, Mestre, VE, Italy

3. c Facoltà di Ingegneria, Università di Ferrara , Via Saragat 1, 1-44100, Ferrara, Italy

Publisher

Informa UK Limited

Subject

Water Science and Technology

Link

https://www.tandfonline.com/doi/pdf/10.1080/02626669809492137

Reference14 articles.

1. A maximum likelihood criterion for use with data collected at unequal time intervals

2. Shuffled complex evolution approach for effective and efficient global minimization

3. Optimal use of the SCE-UA global optimization method for calibrating watershed models

4. Use of a genetic algorithm combined with a local search method for the automatic calibration of conceptual rainfall-runoff models

Cited by 77 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Improving runoff simulation in the Western United States with Noah-MP and variable infiltration capacity;Hydrology and Earth System Sciences;2024-07-16

2. Harnessing SMAP satellite soil moisture product to optimize soil properties to improve water resource management for agriculture;Agricultural Water Management;2024-07

3. Calibration and Modification of the Hargreaves–Samani Equation for Estimating Daily Reference Evapotranspiration in Iraq;Journal of Hydrologic Engineering;2023-05

4. Hydro-informatics for drainage management in a smart city using artificial intelligent, IoT and machine learning;THE FOURTH SCIENTIFIC CONFERENCE FOR ELECTRICAL ENGINEERING TECHNIQUES RESEARCH (EETR2022);2023

5. Can Gauss‐Newton Algorithms Outperform Stochastic Optimization Algorithms When Calibrating a Highly Parameterized Hydrological Model? A Case Study Using SWAT;Water Resources Research;2022-11

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3