Analysing flood history and simulating the nature of future floods using Gumbel method and Log-Pearson Type III: the case of the Mayurakshi River Basin, India

Floods of the Mayurakshi River Basin (MRB) have been historically documented since 1860. The high magnitude, low-frequency flood events have drastically changed to low magnitude, high-frequency flood events in the post-dam period, especially after the 1950s, when the major civil structure (Massanjore dam, Tilpara barrage, Brahmani barrage, Deucha barrage, and Bakreshwar dam) were constructed in the MRB. The present study intends to find out the nature flood frequency using the extreme value method of Gumbel and Log-Person type III (LP-III). The results show that the highest flood magnitude (11,327 m3 s˗1) was observed during 1957–2009 for the Tilpara barrage with a return probability of 1.85% and the lowest (708 m3 s˗1) recorded by the Bakreshwar weir during 1956–77 with a return probability of 4.55%. In the present endeavour, we have computed the predicted discharge for the different return periods like 2, 5, 10, 25, 50,100, and 200 years. The quantile-quantile plot shows that the expected discharge calculated using LP-III is more normally distributed than that of Gumbel. Moreover, Kolmogorov–Smirnov (KS) test, Anderson–Darling (AD), x2 distribution show that LP-III distribution is more normally distributed than the Gumbel at 0.01 significance level, implying its greater reliability and acceptance in the flood simulation of the MRB

Groundwater level dynamics in a subtropical fan delta region and its future prediction using machine learning tools: Sustainable groundwater restoration

Study region: The Damodar Fan Delta, West Bengal, India. Study focus: The depletion of groundwater resources worldwide is escalating due to its profuse demand for drinking, irrigation, domestic, and industrial uses. Overexploitation of groundwater in a subtropical fan delta region with rapid population growth like the Damodar Fan Delta in India is of great concern for sustainable mapping, monitoring, and managing water resources. During 2000–2020, the Damodar Fan Delta portrayed an increase in semi-critical community development blocks, implying a decline in groundwater level. To this end, the present study intends to show the groundwater level dynamics including its future prediction, using machine learning algorithms based on the seasonal groundwater level data from 2013‐14 to 2020‐21 for 30 wells. New hydrological insights for the region: Post-monsoon kharif and rabi depicted a higher fall rate in the groundwater level compared to the pre-monsoon and monsoon periods. Future predictions using the best-fit model indicated an increasing trend in the depth of groundwater levels in the future (2025–26). The extreme gradient boost regressor appeared to be the best model, while the decision tree regressor was the worst performer. The major controlling factors of groundwater level dynamics were decreasing rainfall and increasing groundwater abstraction due to population growth and increased demand for irrigation, domestic, and industrial water

Surface Water and Groundwater Suitability for Irrigation Based on Hydrochemical Analysis in the Lower Mayurakshi River Basin, India

The present work investigates the hydrochemical properties of the surface and groundwater of the Mayurakshi River Basin (India) for assessing their irrigation suitability with respect to irrigation hazards. The study involves 72 water samples classified as 48 surface water samples (premonsoon: 24; post-monsoon: 24) and 24 groundwater samples (pre-monsoon:12; post-monsoon: 12). Regarding the specific irrigation hazard, percent of sodium and soluble sodium percentage have demonstrated the groundwater vulnerability to sodium while the surface water is observed to be free from this kind of hazard. Similar findings have also been retained for magnesium hazard and the potential salinity hazard. Moreover, regarding the seasonality of the hazards, the post-monsoon season has depicted a higher level of irrigation hazards compared to the pre-monsoon season. The study found that the general evolution of groundwater hydrochemistry and the suitability of water for irrigation are principally governed by carbonate weathering, sand mining, stone crushing, and the development of brick kiln industries. Our methodology can be a good example for similar contexts, especially in developing and tropical countries.University Grants Commission, Government of IndiaUniversidad de Costa RicaUCR::Vicerrectoría de Docencia::Ciencias Sociales::Facultad de Ciencias Sociales::Escuela de Geografí

Source identification and potential health risks from elevated groundwater nitrate contamination in Sundarbans coastal aquifers, India

Abstract In recent years groundwater contamination through nitrate contamination has increased rapidly in the managementof water research. In our study, fourteen nitrate conditioning factors were used, and multi-collinearity analysis is done. Among all variables, pH is crucial and ranked one, with a value of 0.77, which controls the nitrate concentration in the coastal aquifer in South 24 Parganas. The second important factor is Cl−, the value of which is 0.71. Other factors like—As, F−, EC and Mg2+ ranked third, fourth and fifth position, and their value are 0.69, 0.69, 0.67 and 0.55, respectively. Due to contaminated water, people of this district are suffering from several diseases like kidney damage (around 60%), liver (about 40%), low pressure due to salinity, fever, and headache. The applied method is for other regions to determine the nitrate concentration predictions and for the justifiable alterationof some management strategies

Soil erosion and sediment yield estimation in a tropical monsoon dominated river basin using GIS-based models

The increasing soil erosion (SE) and the associated problems for society, economy, and environment sparked a lot of interest in estimating and mapping SE at different basin scales. The estimation of SE exhibits that SE ranges from 10 to 50 t ha−1 yr−1, with a mean SE of 20 t ha−1 yr−1. The very steep slopes account for 54.21% of total soil loss. The SRB areas where soil loss rates are >10 t ha−1 yr−1 are considered the target areas which account for 27% of the study area and 96% of the soil loss). The high SY is concentrated only in the first-order basins located in a higher slope zone in the northern part of the river. Besides, basin morphometry (basin shape, relative relief) and anthropogenic activities (agricultural land) are retained in the PSLR model as significant factors contributing to SY in the entire river basin.</p