Lotka-Volterra analysis of river Ganga pollution in India
Water quality indices (WQI) are a useful tool to assess river water pollution. We defined pollution shares (indicating the relative importance of pollutants) from a WQI and studied their dynamics. Using open data from 2012 to 2020 for 105 monitoring stations along river Ganga in India, we fitted sys...
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| Format: | Article |
| Language: | English |
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Elsevier
2023-06-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X23003436 |
| _version_ | 1797837779981303808 |
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| author | Norbert Brunner Sukanya Das Markus Starkl |
| author_facet | Norbert Brunner Sukanya Das Markus Starkl |
| author_sort | Norbert Brunner |
| collection | DOAJ |
| description | Water quality indices (WQI) are a useful tool to assess river water pollution. We defined pollution shares (indicating the relative importance of pollutants) from a WQI and studied their dynamics. Using open data from 2012 to 2020 for 105 monitoring stations along river Ganga in India, we fitted systems of generalized Lotka-Volterra (LV) differential equations to these shares. We used autonomous LV-systems (the interaction coefficients were constant) and LV-systems with variable (linear) interaction coefficients. 28 of the 105 stations had sufficient data for these models, whereby for 10 stations the autonomous system fitted well to all timeseries of the eight considered pollutants, and for 9 stations the model with linear interaction coefficients. For them we defined three candidates for “importance-growth indicators”: (a) the interaction coefficients of the autonomous LV-system, (b) the leading coefficient of the interaction coefficient of the system with linear coefficients, and (c) the roots of these linear coefficients. We explored the variability of the indicators and applied them to identify stations with a similar temporal evolution of the pollutants. Further, we suggested applications to wastewater management, as at several stations the indicators (a) and (b) forecasted an increasing relative importance of nitrates/nitrites, which currently pose no problems but finally may require an upgrading of existing wastewater treatment. |
| first_indexed | 2024-04-09T15:31:15Z |
| format | Article |
| id | doaj.art-7734a11bcf9848939c0cc83edc6d8bef |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-09T15:31:15Z |
| publishDate | 2023-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-7734a11bcf9848939c0cc83edc6d8bef2023-04-28T08:54:20ZengElsevierEcological Indicators1470-160X2023-06-01150110201Lotka-Volterra analysis of river Ganga pollution in IndiaNorbert Brunner0Sukanya Das1Markus Starkl2University of Natural Resources and Life Sciences, Vienna, Austria; Corresponding author.TERI School of Advanced Studies, New Delhi, IndiaUniversity of Natural Resources and Life Sciences, Vienna, AustriaWater quality indices (WQI) are a useful tool to assess river water pollution. We defined pollution shares (indicating the relative importance of pollutants) from a WQI and studied their dynamics. Using open data from 2012 to 2020 for 105 monitoring stations along river Ganga in India, we fitted systems of generalized Lotka-Volterra (LV) differential equations to these shares. We used autonomous LV-systems (the interaction coefficients were constant) and LV-systems with variable (linear) interaction coefficients. 28 of the 105 stations had sufficient data for these models, whereby for 10 stations the autonomous system fitted well to all timeseries of the eight considered pollutants, and for 9 stations the model with linear interaction coefficients. For them we defined three candidates for “importance-growth indicators”: (a) the interaction coefficients of the autonomous LV-system, (b) the leading coefficient of the interaction coefficient of the system with linear coefficients, and (c) the roots of these linear coefficients. We explored the variability of the indicators and applied them to identify stations with a similar temporal evolution of the pollutants. Further, we suggested applications to wastewater management, as at several stations the indicators (a) and (b) forecasted an increasing relative importance of nitrates/nitrites, which currently pose no problems but finally may require an upgrading of existing wastewater treatment.http://www.sciencedirect.com/science/article/pii/S1470160X23003436Differential equation modelGanges RiverStatistical correlationWater pollutionWater quality index |
| spellingShingle | Norbert Brunner Sukanya Das Markus Starkl Lotka-Volterra analysis of river Ganga pollution in India Ecological Indicators Differential equation model Ganges River Statistical correlation Water pollution Water quality index |
| title | Lotka-Volterra analysis of river Ganga pollution in India |
| title_full | Lotka-Volterra analysis of river Ganga pollution in India |
| title_fullStr | Lotka-Volterra analysis of river Ganga pollution in India |
| title_full_unstemmed | Lotka-Volterra analysis of river Ganga pollution in India |
| title_short | Lotka-Volterra analysis of river Ganga pollution in India |
| title_sort | lotka volterra analysis of river ganga pollution in india |
| topic | Differential equation model Ganges River Statistical correlation Water pollution Water quality index |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X23003436 |
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