Your search found 2 records
1 Mohile, A. D.; Anand, B. K. 2009. Natural flows assessment and creating alternative future scenarios for major river basins of peninsular India. In Amarasinghe, Upali A.; Shah, Tushaar; Malik, R. P. S. (Eds.). Strategic Analyses of the National River Linking Project (NRLP) of India, Series 1: India’s water future: scenarios and issues. Colombo, Sri Lanka: International Water Management Institute (IWMI) pp.381-403.
River basins ; Flow ; Estimation ; Hydrology ; Models ; Water transfer ; Water use ; Runoff ; Evapotranspiration ; Reservoirs ; Water storage ; Environmental flows ; Water balance ; Irrigation efficiency / India / Brahmani Baitarni River Basin / Cauvery River Basin / Godavari River Basin / Krishna River Basin / Mahanadi River Basin / Narmada River Basin
(Location: IWMI HQ Call no: IWMI 333.9162 G635 AMA Record No: H042048)
(279.34 KB)
2 Das, A. 2024. Evaluation of prospective surface water potential zones and their suitability for drinking purposes in Mahanadi River Basin, Odisha (India) AQUA - Water Infrastructure, Ecosystems and Society, jws2024111. (Online first) [doi: https://doi.org/10.2166/aqua.2024.111]
Drinking water ; Surface water ; Water potential ; Water quality ; Decision making ; Machine learning ; Models ; Monitoring ; Geographical information systems ; Water management / India / Odisha / Mahanadi River Basin
(Location: IWMI HQ Call no: e-copy only Record No: H052756)
https://iwaponline.com/aqua/article-pdf/doi/10.2166/aqua.2024.111/1402217/jws2024111.pdf
https://vlibrary.iwmi.org/pdf/H052756.pdf
https://vlibrary.iwmi.org/pdf/H052756.pdf
(1.75 MB) (1.75 MB)
This study presents the usefulness of the water quality index (WQI) based on Fuzzy (F)-analytic hierarchy process (AHP), multi-criteria decision-making technique, namely, weighted sum approach (WSA) and machine learning models such as Borda scoring algorithm (BSA) for its evaluation and were further applied to the datasets on water quality (WQ) of the Mahanadi River (Odisha), generated during 5 years (2018–2023) of monitoring at 19 different sites for 20 parameters. The results render two parameters, namely coliform and TKN, exceeding the WHO standards. The results revealed that 52.63% of surface water samples are excellent in terms of drinking WQ, 26.32% of the samples are categorized under medium, and rest 21.05% are grouped under poor/very poor/unsuitable in terms of the F-AHP WQI. According to the results of WSA, 10 samples (52.63%) are low polluted zones, 6 samples (31.58%) are medium-polluted zones, and around 15.79% (3 samples) are highly polluted. The graphic representations obtained by BSA underline that the calculated value ranged between 15 and 256, stating in a zone of good to poor WQ. The best WQ was observed in T-(1), (5), (14), (15), (16), (17), and (18) because there were no changes in land use.
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