A process-based and distributed model for nutrient dynamics in river basin: development, testing and applications

Article

Alam, Md Jahangir and Dutta, Dushmanta. 2012. "A process-based and distributed model for nutrient dynamics in river basin: development, testing and applications." Ecological Modelling. 247, pp. 112-124. https://doi.org/10.1016/j.ecolmodel.2012.07.031
Article Title

A process-based and distributed model for nutrient dynamics in river basin: development, testing and applications

ERA Journal ID3233
Article CategoryArticle
AuthorsAlam, Md Jahangir (Author) and Dutta, Dushmanta (Author)
Journal TitleEcological Modelling
Journal Citation247, pp. 112-124
Number of Pages13
Year2012
PublisherElsevier
Place of PublicationNetherlands
ISSN0304-3800
1872-7026
Digital Object Identifier (DOI)https://doi.org/10.1016/j.ecolmodel.2012.07.031
Web Address (URL)http://www.sciencedirect.com/science/article/pii/S0304380012003808
Abstract

A new grid-based model of nutrient dynamics and transport process has been developed within a distributed hydrological modelling framework and integrated with river network module. The key aspect of this development is a process based description of nutrient generation process on the land surface and its related nutrient release with hydrologic runoff and soil erosion. Whereas the conventional modelling uses the event mean concentration method for nutrient dynamics modelling and estimates nutrient loads from catchments to the rivers this study has introduced an export function based release related with flow capacity. The river module solves the dynamic equation for transport and chemical reaction. The model output is available in high spatial and temporal resolution, which was tested and verified applying in two catchment areas from different hydro-climatic backgrounds. The model was able to simulate short term high intensity flood events as well as long term seasonal patterns. The simulated results for most of the nutrient parameters are within acceptable range as reflected by measures of statistical indices and visual interpretation. For example, the R2 values for different nutrient levels in the Saru River, Japan are within the range of 0.83–0.99 and 0.66–0.87 for calibration and validation, respectively. Similarly, the relative root mean square error (RRMSE) values for different nutrient levels in the Saru River range between 0.06–0.22 and 0.06–0.26 for calibration and validations, respectively. The maximum load of nutrients in each grid was extracted from time series output, analyzed further and presented in two dimensional maps, which showcase the usefulness of the model in decision making process for management of land and maintenance of the in-stream water quality.

Keywordsnutrient pollution; sediment transport; process-based modelling; distributed hydrology; ecosystem; river basin
ANZSRC Field of Research 2020370704. Surface water hydrology
400499. Chemical engineering not elsewhere classified
379999. Other earth sciences not elsewhere classified
400513. Water resources engineering
Public Notes

Files associated with this item cannot be displayed due to copyright restrictions.

Byline AffiliationsMonash University
Institution of OriginUniversity of Southern Queensland
Permalink -

https://research.usq.edu.au/item/q3090/a-process-based-and-distributed-model-for-nutrient-dynamics-in-river-basin-development-testing-and-applications

Log in to edit
  • 1710
    total views
  • 7
    total downloads
  • 1
    views this month
  • 0
    downloads this month

Export as

Related outputs

An Alternative Method for Estimating the Peak Flow for a Regional Catchment Considering the Uncertainty via Continuous Simulation
Brown, Ian, McDougall, Kevin, Chadalavada, Sreeni and Alam, Md Jahangir. 2023. "An Alternative Method for Estimating the Peak Flow for a Regional Catchment Considering the Uncertainty via Continuous Simulation ." Water. 15 (19). https://doi.org/https://doi.org/10.3390/w15193355
Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia
Farzana, Syeda Zehan, Paudyal, Dev Raj, Chadalavada, Sreeni and Alam, Md Jahangir. 2023. "Prediction of Water Quality in Reservoirs: A Comparative Assessment of Machine Learning and Deep Learning Approaches in the Case of Toowoomba, Queensland, Australia." Geosciences. 13 (293). https://doi.org/10.3390/geosciences13100293
A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia
Pakdel, Hadis, Paudyal, Dev Raj, Chadalavada, Sreeni, Alam, Md Jahangir and Vazifedoust, Majid. 2023. "A Multi-Framework of Google Earth Engine and GEV for Spatial Analysis of Extremes in Non-Stationary Condition in Southeast Queensland, Australia." ISPRS International Journal of Geo-Information. 12 (9). https://doi.org/10.3390/ijgi12090370
Calibration of a continuous hydrologic simulation model in the urban Gowrie Creek catchment in Toowoomba, Australia
Brown, I. W., McDougall, K., Alam, Md. Jahangir, Chowdhury, R. and Chadalavada, S.. 2022. "Calibration of a continuous hydrologic simulation model in the urban Gowrie Creek catchment in Toowoomba, Australia." Journal of Hydrology: Regional Studies. 40, pp. 1-16. https://doi.org/10.1016/j.ejrh.2022.101021
Modelling of Nutrient Pollution Dynamics in River Basins: A Review with a Perspective of a Distributed Modelling Approach
Alam, Md Jahangir and Dutta, Dushmanta. 2021. "Modelling of Nutrient Pollution Dynamics in River Basins: A Review with a Perspective of a Distributed Modelling Approach." Geosciences. 11 (9), pp. 1-16. https://doi.org/10.3390/geosciences11090369
Short duration rainfall estimation of Sylhet: IMD and USWB method
Chowdhury, Rezaul Kabir, Alam, Md. J. B., Das, P. and Alam, Md. A.. 2007. "Short duration rainfall estimation of Sylhet: IMD and USWB method." Journal of the Indian Water Works Association. 39 (4), pp. 285-292.
A two-dimensional hydrodynamic model for flood inundation simulation: a case study in the lower Mekong river basin
Dutta, Dushmanta, Alam, Jahangir, Umeda, Kazuo, Hayashi, Masayoshi and Hironaka, Sadayuki. 2007. "A two-dimensional hydrodynamic model for flood inundation simulation: a case study in the lower Mekong river basin." Hydrological Processes. 21 (9), pp. 1223-1237. https://doi.org/10.1002/hyp.6682
A sub-catchment based approach for modelling nutrient dynamics and transport at a river basin scale
Alam, Md Jahangir and Dutta, Dushmanta. 2016. "A sub-catchment based approach for modelling nutrient dynamics and transport at a river basin scale." Water Resources Management. 30 (14), pp. 5455-5478. https://doi.org/10.1007/s11269-016-1500-x
Predicting climate change impact on nutrient pollution in waterways: a case study in the upper catchment of the Latrobe River, Australia
Alam, Md Jahangir and Dutta, Dushmanta. 2013. "Predicting climate change impact on nutrient pollution in waterways: a case study in the upper catchment of the Latrobe River, Australia." Ecohydrology. 6 (1), pp. 73-82. https://doi.org/10.1002/eco.282
Investigating environmental watering options using Source IMS: a case study – the River Murray, Australia
Alam, Md Jahangir, Korn, Alistair and Hardy, Matthew. 2015. "Investigating environmental watering options using Source IMS: a case study – the River Murray, Australia." Weber, T., McPhee, M. J. and Anderssen, R. S. (ed.) 21st International Congress on Modelling and Simulation (MODSIM2015). Gold Coast, Australia 29 Nov - 04 Dec 2015 Australia.
Modelling water demand and trade on the Murray and lower Darling rivers
Alam, Md Jahangir, Bethune, Matthew, Townsend, Phil and Close, Andy. 2014. "Modelling water demand and trade on the Murray and lower Darling rivers." 17th International River Symposium 2014: Excellence Collaboration Integration. Canberra, Australia 15 - 18 Sep 2014 Canberra, Australia.
Investigating environmental watering options using Source IMS: a case study – the River Murray, Australia
Alam, Md Jahangir, Korn, Alistair and Hardy, Matthew. 2015. "Investigating environmental watering options using Source IMS: a case study – the River Murray, Australia ." 21st International Congress on Modelling and Simulation (MODSIM2015). Gold Coast, Australia 29 Nov - 04 Dec 2015 Australia.