Seasonal and spatial variability in δ18O and δD values in waters of the Godavari River basin: Insights into hydrological processes

Kirkels, Frédérique; Zwart, Huub M.; Basu, Sayak; Usman, Muhammed; Peterse, Francien

doi:10.1016/j.ejrh.2020.100706

Cited by 10 publications

(34 citation statements)

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“…5c, S3), suggesting mixing of 440 freshwater and estuarine/marine phytoplankton in the delta, where the latter has typically less negative δ 13 C org values (i.e., -22.8 to -24.4 ‰;Dehairs et al, 2000;Krishna et al, 2015;Gawade et al, 2018). This result is also consistent with changes in electrical conductivity and water isotopic signature (δ 18 O) that showed seawater intrusion in the delta in the dry season (Kirkels et al, 2020b).…”

Section: Suspended Particulate Mattersupporting

confidence: 63%

“…3c). The negative δ 13 C org values in the upper basin suggest continuous aquatic production, allowed by the limited rainfall and abundant dams in this region that created standing waters and facilitated year-round aquatic productivity (Pradhan et al, 2014;Kirkels et al, 2020b). A few sites in the upper basin had remarkably less negative δ 13 C org values, suggesting that some local soil or C4 450 plant input occurred at locations where agricultural fields with exposed topsoils were situated next to the river (Fig.…”

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confidence: 96%

“…In the lower basin, wet season SPM δ 13 C org values varied from -21. Indravati River in the East Tributaries subbasin as major source areas (Kirkels et al, 2020b). It is generally assumed that the high flow velocity and turbidity in the wet season would limit aquatic production as well as OC degradation during fluvial transport (Balakrishna and Probst, 2005;Acharyya et al, 2012).…”

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confidence: 99%

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Carbon isotopic ratios of modern C3 and C4 vegetation on the Indian Peninsula and changes along the plant–soil–river continuum; implications for (paleo-)vegetation reconstructions

Kirkels

Boer

Hernández

et al. 2022

Preprint

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Abstract. The large difference in the fractionation of stable carbon isotopes between C3 and C4 plants is widely used in vegetation reconstructions, where the predominance of C3 plants suggests wetter and that of C4 plants drier conditions. The isotopic composition of organic carbon (OC) preserved in soils or sediments may be a valuable (paleo-)environmental indicator, based on the assumption that plant-derived material retains the carbon isotopic signature of its photosynthetic pathway during transfer from plant to sediment. In this study, we investigated the carbon isotopic signature of C3 and C4 plants (δ13C) and of organic carbon (δ13Corg) in soils, river Suspended Particulate Matter (SPM) and riverbed sediments, to gain insight in the control of precipitation on C3 and C4 plant δ13C values and to assess changes in δ13Corg values along the plant–soil–river continuum. This information allows us to elucidate the implications of different δ13C end-members on C3/C4 vegetation reconstructions. Our analysis was performed in the Godavari River basin, which has mixed C3 and C4 vegetation and is situated in the Core Monsoon Zone in peninsular India, a region that integrates the hydroclimatic and vegetation changes caused by variation in monsoonal strength. The Godavari C3 and C4 plants revealed more negative δ13C values than global average vegetation values, suggesting region-specific plant δ13C signatures. Godavari C3 plants confirmed a strong control by Mean Annual Precipitation (MAP) on their δ13C values, with an isotopic enrichment of ~2.2 ‰ for the interval between ~500 and 1500 mm y-1. Tracing δ13Corg values from plant to soils and rivers revealed that soils and riverbed sediments reflected the transition from mixed C3 and C4 vegetation in the dry upper basin to more C3 vegetation in the humid lower basin. Soil degradation and stabilisation processes and hydrodynamic sorting within the river altered the plant-derived δ13C signal. Phytoplankton dominated the δ13Corg signal carried by SPM in the dry season and year-round in the upper basin. Our analysis revealed that the reconstructed C3/C4 vegetation composition was sensitive to the plant δ13C end-members used as mixing model input. The %C4 plants in the different subbasins was ~10–19 % higher using Godavari-specific end-members than using global averages, and including a correction for drought enrichment in Godavari C3 plants resulted in a 2–10 % lower estimated C4 plant cover. Hence, incorporating region-specific plant δ13C end-members and drought correction of the C3 end-member in mixing models need to be considered to determine C3 and C4 distributions of modern- and paleo-vegetation in monsoonal regions.

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Section: Suspended Particulate Mattersupporting

confidence: 63%

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confidence: 96%

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confidence: 99%

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Carbon isotopic ratios of modern C3 and C4 vegetation on the Indian Peninsula and changes along the plant–soil–river continuum; implications for (paleo-)vegetation reconstructions

Kirkels

Boer

Hernández

et al. 2022

Preprint

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“…The hydroclimate of the Godavari River basin is characterised by a distinct dry period (October-May) and a monsoon (wet) season (June-September). The Southwest Monsoon, with its main moisture source in the Indian Ocean and Arabian Sea, brings 75-85% of the annual rainfall to the Godavari basin in the wet season (Balakrishna and Probst, 2005;Kirkels et al, 2020b).…”

Section: Study Areamentioning

confidence: 99%

“…Rainfall data from the year of sampling can be found in Kirkels et al (2020b), and discharge data in Appendix 1.The mean annual air temperature in the basin averages around 27°C (Dearing Crampton-Flood et al, 2019a).…”

Section: Study Areamentioning

confidence: 99%

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Peterse

2022

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Quantitative delineation of water sources in the river Ganga using stable water isotopes

Kumar,

Basu,

Ajay

et al. 2023

River Research & Apps

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Quantitative delineation of water sources in a large river system is essential for the sustainable use of water. In the present study, we have tested two different methodologies to estimate the contribution from different water sources in the river Ganga. The first model uses stable isotopes and physicochemical parameters of water to delineate the contribution of glacier‐melt, groundwater, and surface runoff in different stretches of the river Ganga. The end member‐based mixing model provides glacier‐melt contribution of ~31.2%, ~5.5%, and ~0.5% in the upper, middle, and lower stretch of the river Ganga. The model showed maximum contribution from groundwater (~66.3%) in the middle stretch and surface runoff (~57.2%) in the lower stretch of the river Ganga. However, the uncertainties in the estimates from the three‐component mixing model were significantly high due to temporal variability in the end member values. To provide estimates with lower uncertainty, an alternate method (discharge dependent budget estimation [DDBE]) has been proposed which delineates the contribution of groundwater and surface runoff in small segments of the river. The DDBE model confines the calculation for budget estimates to smaller segments of the river and hence leads to lower uncertainties in the results, providing improved systematic estimation of water budget for large river systems. In the present study, estimates from the DDBE model suggest that groundwater contributes ~79% of the additional water whereas the contribution from surface runoff is ~21% in the middle and lower stretch of the river Ganga. The DDBE model was successfully applied in 5 small segments along the stretch of the river Ganga and the methodology used shows great potential for systematic delineation of water sources in large river system.

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Seasonal and spatial variability in δ18O and δD values in waters of the Godavari River basin: Insights into hydrological processes

Cited by 10 publications

References 91 publications

Carbon isotopic ratios of modern C3 and C4 vegetation on the Indian Peninsula and changes along the plant–soil–river continuum; implications for (paleo-)vegetation reconstructions

Carbon isotopic ratios of modern C3 and C4 vegetation on the Indian Peninsula and changes along the plant–soil–river continuum; implications for (paleo-)vegetation reconstructions

Reply on RC1 (David Naafs)

Quantitative delineation of water sources in the river Ganga using stable water isotopes

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