A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds-Reference-Cited by-同舟云学术

A deep learning-based novel approach to generate continuous daily stream nitrate concentration for nitrate data-sparse watersheds

Published:2023-06 Issue: Volume:878 Page:162930
ISSN:0048-9697
Container-title:Science of The Total Environment
language:en
Short-container-title:Science of The Total Environment

Author:

Saha Gourab Kumer,Rahmani Farshid,Shen Chaopeng,Li Li,Cibin Raj

Funder

National Institute of Food and Agriculture

Penn State Institutes of Energy and Environment

Publisher

Elsevier BV

Subject

Pollution,Waste Management and Disposal,Environmental Chemistry,Environmental Engineering

Reference78 articles.

1. Nitrate and biochemical oxygen demand change in a typical midwest stream in the past two decades;Alam;H2Open J.,2020

2. Predicted Nitrate and Arsenic Concentrations in Basin-fill Aquifers of the Southwestern United States: USGS Scientific Investigations Report 2012-5065. Reston, VA;Anning,2012

3. Modeling water quality to improve agricultural practices and land management in a Tunisian Catchment using the soil and water assessment tool;Aouissi;J. Environ. Qual.,2014

4. SWAT: model use, calibration, and validation;Arnold;Trans. ASABE,2012

5. Iowa Ag Review: Living With Hogs in Rural Iowa. Iowa Ag Review;Babcock,2003

Cited by 15 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. Estimating soil mineral nitrogen from data-sparse field experiments using crop model-guided deep learning approach;Computers and Electronics in Agriculture;2024-10

2. Deep learning insights into suspended sediment concentrations across the conterminous United States: Strengths and limitations;Journal of Hydrology;2024-08

3. Metamorphic testing of machine learning and conceptual hydrologic models;Hydrology and Earth System Sciences;2024-06-13

4. A hybrid deep learning approach to predict hourly riverine nitrate concentrations using routine monitored data;Journal of Environmental Management;2024-06

5. Performance evaluation of deep learning based stream nitrate concentration prediction model to fill stream nitrate data gaps at low-frequency nitrate monitoring basins;Journal of Environmental Management;2024-04