Multiple-response Bayesian calibration of watershed water quality models with significant input and model structure errors-Reference-Cited by-同舟云学术

Multiple-response Bayesian calibration of watershed water quality models with significant input and model structure errors

Published:2016-02 Issue: Volume:88 Page:109-123
ISSN:0309-1708
Container-title:Advances in Water Resources
language:en
Short-container-title:Advances in Water Resources

Author:

Han Feng,Zheng Yi

Funder

National Natural Science Foundation of China

China's National Science & Technology Pillar Program

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference59 articles.

1. Large area hydrologic modeling and assessment part I: model development;Arnold;J Amer Water Resour Assoc,1998

2. Neitsch SL, Arnold JG, Kiniry JR, Williams JR. Soil and water assessment tool theoretical documentation version 2009. Texas Water Resources Institute2011.

3. Decision support system for stakeholder involvement;Chen;J Environ Eng,2004

4. Determining critical water quality conditions for inorganic nitrogen in dry, semi-urbanized watersheds;Keller;J Amer Water Resour Assoc,2004

5. Stochastic watershed water quality simulation for TMDL development - a case study in the Newport Bay watershed;Zheng;J Amer Water Resour Assoc,2008

Cited by 27 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. Assessing ammonium pollution and mitigation measures through a modified watershed non-point source model;Water Research;2024-05

2. Evaluation of Uncertainty in Stream Flow Prediction Using Monte Carlo Simulation for Watershed-Scale Hydrological Modeling;Journal of Hydrologic Engineering;2024-02

3. Comprehensive Evaluation and Distribution Prediction of River Water Quality in One Typical Resource-Depleted City, Central China;Water;2023-08-24

4. Assimilating Low‐Cost High‐Frequency Sensor Data in Watershed Water Quality Modeling: A Bayesian Approach;Water Resources Research;2023-04

5. Parameter sensitivity analysis for a biochemically-based photosynthesis model;Research in Cold and Arid Regions;2023-04