 Subjects -> WATER RESOURCES (Total: 160 journals)
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- Geostatistical analyses empowered with gradient boosting and extra trees
classifier algorithms in the prediction of groundwater quality and
geology-lithology attributes over YSR district, India-
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Authors: Maha Morssi, Andy T.C. Wong, Sahar El-Barky
Pages: 333 - 369
Abstract: Machine learning classifiers are integrated with the geostatistical analyses through interpolation techniques to predict groundwater quality and geology-lithology. Ordinary kriging is used to obtain the optimal interpolation model using RMSSE values. The data extracted from the surface maps were passed onto ML algorithms, resulting in prediction accuracies of 99% for groundwater quality and 96% in predicting the geology-lithology features. There was certain overfitting in the prediction and it was probably due to several classes of geology-lithology variables and limited data available for analysis. The interpolation methods might affect the model performance by producing overfitting and underfitting results. It is to report that the gradient boosting classifier yielded relatively high prediction accuracies in predicting groundwater quality when two classes were used. The extra trees classifier returned better results in predicting geology-lithology features when multiple classes were used in this study.
Keywords: machine learning; geostatistics; groundwater quality; gradient boosting classifier; extra trees classifier; India
Citation: International Journal of Hydrology Science and Technology, Vol. 16, No. 4 (2023) pp. 333 - 369
PubDate: 2023-11-01T23:20:50-05:00
DOI: 10.1504/IJHST.2023.134621
Issue No: Vol. 16, No. 4 (2023)
- Comparison features importance for temporal and spatial-temporal
approaches in GRACE and GRACE-FO signal reconstruction based on GLDAS data
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Authors: Maha Morssi, Andy T.C. Wong, Sahar El-Barky
Pages: 370 - 389
Abstract: Machine learning algorithms can effectively learn the complex relationships between various input variables from the global land data assimilation system (GLDAS) and the total water storage (TWS) observed by gravity recovery and climate experiment (GRACE) and GRACE-FO (follow-on) missions. As the TWS depends on various features, a serious question arises about the importance of used variables for reconstruction. Furthermore, will the variables used for the reconstruction be equally significant for grid-based and basin-based analyses? This work examined the importance of individual predictors for the temporal and spatial-temporal approach over 254 river basins using GRACE and GRACE-FO data as target and GLDAS data as predictors. The extreme gradient boosting (XGBoost) algorithm was used to reconstruct TWS. Results were evaluated with root-mean-square error, normalised root-mean-square error, Pearson correlation coefficient, Nash-Sutcliffe efficiency, and Kolmogorov-Smirnow-test metrics. Model output influence was checked by the model-agnostic version of the feature importance and by Shapley additive explanations (SHAP).
Keywords: total water storage; TWS; global land data assimilation system; GRACE; GRACE-FO; features importance; extreme gradient boosting; XGBoost; Shapley additive explanations; SHAP
Citation: International Journal of Hydrology Science and Technology, Vol. 16, No. 4 (2023) pp. 370 - 389
PubDate: 2023-11-01T23:20:50-05:00
DOI: 10.1504/IJHST.2023.134623
Issue No: Vol. 16, No. 4 (2023)
- Developing rainfall intensity-duration-frequency curves for Dodola
catchment to estimate peak discharge using frequency analysis-
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Authors: Maha Morssi, Andy T.C. Wong, Sahar El-Barky
Pages: 390 - 408
Abstract: The development of intensity-duration-frequency (IDF) curves is one of the most common and useful tools to estimate peak discharge. The purpose of this study was to develop the IDF curves for five selected stations in the Dodola catchment. The Ethiopian Road Authority (ERA) reduction empirical formula was used to estimate the short-duration rainfall intensity from daily rainfall data. The L-moment ratio diagram and three goodness-of-fit tests were used to identify the best-fit probability distribution. The IDF curves that were constructed using regionalised distribution were compared with at-site IDF curves. The difference between the two sets of IDF curves small differences, also, shows the same trend for all selected return periods. These IDF curves will help in the estimation of peak discharge in the catchment.
Keywords: probability distribution; IDF curves; peak discharge; Dodola catchment
Citation: International Journal of Hydrology Science and Technology, Vol. 16, No. 4 (2023) pp. 390 - 408
PubDate: 2023-11-01T23:20:50-05:00
DOI: 10.1504/IJHST.2023.134625
Issue No: Vol. 16, No. 4 (2023)
- Long term trend analysis on precipitation in Ajmer District of Rajasthan
State, India-
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Authors: Jinal H. Pastagia, Darshan J. Mehta
Pages: 409 - 421
Abstract: This research focuses on long-term patterns of climatic variability, such as precipitation. Rainfall trends in the Ajmer region were assessed using the Mann-Kendall (MK) test, Sen's slope estimator, and the innovative trend analysis (ITA) technique on various time scales. Monthly precipitation data were used for the period of 121 years, i.e., 1901-2021. Trends (1901-2021) were assessed at the 5% significant level using a statistical trend analysis method called the Mann-Kendall test. Mann-Kendall trend analysis result reveals an insignificant increase in the region of Ajmer District. At any time, series across the Ajmer District, there is no clear increase or decrease trend. According to the results of the ITA test, all four seasons and annual trends indicate decreasing. Almost all the significant trends identified using the M-K method were excellently recognised by the ITA method. The finding of the study will be useful to understand the risks and vulnerabilities of seasonal and annual precipitation under climate change scenarios in the region.
Keywords: climate change; innovative trend analysis; ITA; Mann-Kendall test; precipitation; Sen's slope estimator
Citation: International Journal of Hydrology Science and Technology, Vol. 16, No. 4 (2023) pp. 409 - 421
PubDate: 2023-11-01T23:20:50-05:00
DOI: 10.1504/IJHST.2023.134624
Issue No: Vol. 16, No. 4 (2023)
- Understanding efficient seawater intrusion assessment in coastal region of
India: a methodological review-
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Authors: Zalak Bhavsar, Jayeshkumar Patel
Pages: 422 - 438
Abstract: India is fortunate to have a long length of coastline. In addition to the numerous villages and industrial communities, many of the country's metropolitan centres are situated along the coastline. Saltwater intrusion is the migration of salty water into freshwater coastal aquifers, resulting in groundwater quality degradation. Land-use changes, climate change, and sea-level rise are the most significant contributing causes to saltwater intrusion in coastal aquifers. Coastal saline water intrusion has a broad range of impacts on the community and financial systems, in addition to the area's overall ecosystem, prompting many studies. According to the research, saline soils cover around 70 thousand square kilometres in India, including about 21,000 square kilometres in coastal regions. It is imperative to understand the extent of seawater intrusion in order to plan and manage mitigation measures towards sustainable development. The objective of this paper is to derive an insightful review of the methods, i.e., hydrogeochemical assessment, geophysical assessment and numerical modelling; used to tackle the pertaining issue of seawater intrusion.
Keywords: coastal aquifer; geophysical method; hydrogeochemical method; seawater intrusion; India
Citation: International Journal of Hydrology Science and Technology, Vol. 16, No. 4 (2023) pp. 422 - 438
PubDate: 2023-11-01T23:20:50-05:00
DOI: 10.1504/IJHST.2023.134626
Issue No: Vol. 16, No. 4 (2023)
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