Publications

Latest Publications

Sunder, M. S., Mahto, S. S., & Tyagi, B. (2025). From flames to recovery: ecosystem resilience in Uttarakhand’s 2022 forest fires. MAUSAM, 76(4), 1095-1112. [Link]

Abstract: The foothills of the Himalaya are one of the major hotspots of forest fires in India. Forest fires during the hot-dry summer season (March-June) often cause damage to the Forest ecosystem, one of such events is the Uttarakhand fires in 2022, which seriously impacted the natural vegetation led to economic losses. However, its drivers and ecosystem resilience to vegetation impacts are not well understood. Using hydroclimatic, vegetation, and fire datasets, we thoroughly examined the spatio-temporal variations and recovery of burnt vegetation. High-severity burns were concentrated in the southern regions of Uttarakhand, interpreted based on the dNBR index classes. The burned biomass calculated for the selected high severity area, showed decline (16.75%), post-fire recovery (40.85%) indicated uneven ecosystem resilience. High VPD and low soil moisture, intensified the fire risks but during monsoon onset and fire-induced rainfall helped restore soil moisture and reduce VPD, supported early vegetation recovery. The satellite observation indices observed dynamic restoration immediate after the fire event, showed SAVI (from ~0.23 –0.43) and VCI (from ~40 -80), indicating secondary succession. Overall post-fire burned regions had SH>40% and LH<−20% but showed decline in GPP (~20%) and ET (8-21%), whilePET rose stronger atmospheric demand under weakened surface supply (3-19%), which the explained slow recovery. This study highlights the importance of assessing and understanding the vegetation dynamics with providing key insights into atmospheric conditions and internal characteristics of vegetation recovery offers guidance for adapting to forest fire impacts.

Eldardiry, H., Mahto, S. S., Fatichi, S., & Galelli, S. (2025). VIC-Res Mekong: An open-source hydrological-water management model for the Mekong River basin. Environmental Modelling & Software, 106603. [Link]

Abstract: Decades of research on the Mekong River basin have vastly expanded our knowledge of key hydrological and ecological processes, in part thanks to the development of modelling tools. However, few of these models are openly available to the research community or adhere to FAIR (Findable, Accessible, Interoperable, Reusable) principles, particularly in the domain of hydrology, in turn limiting transparency, reproducibility, and broader scientific engagement. Here, we address this gap and introduce VIC-Res Mekong, an open-source hydrological-water management model for the Mekong River basin. The model is implemented over a spatial domain of ~630,000 km and has a resolution of 0.0625 degrees. Water and energy budgets are simulated with the Variable Infiltration Capacity (VIC) model, while streamflow routing is simulated with VIC-Res, which explicitly accounts for the storage and release dynamics of reservoirs. This is of key importance for a basin like the Mekong, where the active storage capacity of dams has increased from ~20 km to nearly 80 km in the past fifteen years. To this purpose, VIC-Res Mekong integrates information from a database containing reservoir storage time series (inferred from satellite images) for 129 dams that accounts for more than 90% of total storage capacity. These data support both hindcast simulations and the derivation of reservoir operating rules, enabling a flexible and realistic representation of dam operations that allows to characterize in detail dam-induced hydrological alterations.

Journal Articles

2025

[24]. Sunder, M. S., Mahto, S. S., & Tyagi, B. (2025). From flames to recovery: ecosystem resilience in Uttarakhand’s 2022 forest fires. MAUSAM, 76(4), 1095-1112. [Link]

[23]. Eldardiry, H., Mahto, S. S., Fatichi, S., & Galelli, S. (2025). VIC-Res Mekong: An open-source hydrological-water management model for the Mekong River basin. Environmental Modelling & Software, 106603. [Link]

[22]. Mahto, S. S., Fatichi, S., & Galelli, S. (2024). A 1985–2023 time series dataset of absolute reservoir storage in Mainland Southeast Asia (MSEA-Res). Earth System Science Data Discussions, 2024, 1-29. [Link]

[21]. Tripathi, I. M., Mahto, S. S., Sahu, B. K., Mohapatra, P. K., & Jain, V. (2025). Influence of pit geometry and flow conditions on sand pit migration in fluvial systems: insights from flume experiments. ISH Journal of Hydraulic Engineering, 1-16. [Link]

[20]. Rathore, J., Kumari, S., Tripathy, P., Mahto, S. S., & Lal, P. (2025). 2024 Brazil Floods: Mapping the extent and impacts in Eastern Rio Grande do Sul using geospatial techniques. Natural Hazards Research. [Link]

[19]. Tripathi, I. M., Mahto, S. S., Bhagat, C., Modi, A., Jain, V., & Mohapatra, P. K. (2025). A Review of River Sand Mining: Methods, Impacts, and Implications. Next Research, 100149. [Link]

2024

[18]. Kushwaha, A. P., Solanki, H., Vegad, U., Mahto, S. S., & Mishra, V. (2024). Land and atmospheric drivers of the 2023 flood in India. Earth and Space Science, 11(10), e2024EA003750. [Link]

[17]. Maiti, A., Hasan, M. K., Sannigrahi, S., Bar, S., Chakraborti, S., Mahto, S. S., ... & Zhang, Q. (2024). Optimal rainfall threshold for monsoon rice production in India varies across space and time. Communications Earth & Environment, 5(1), 302. [Link]

[16]. Mahto, S. S., & Mishra, V. (2024). Global evidence of rapid flash drought recovery by extreme precipitation. Environmental Research Letters, 19(4), 044031. [Link]

[15]. Tripathi, I. M., Mahto, S. S., Kushwaha, A. P., Kumar, R., Tiwari, A. D., Sahu, B. K., ... & Mohapatra, P. K. (2024). Dominance of soil moisture over aridity in explaining vegetation greenness across global drylands. Science of The Total Environment, 917, 170482. [Link]

2023

[14]. Mahto S.S. and Mishra V. (2023). Increasing risk of simultaneous occurrence of flash drought in major global croplands. Environ. Res. Lett. 18, 044044 (2023). [Link]

[13]. Mahto, S. S., Nayak, M. A., Lettenmaier, D. P., & Mishra, V. (2023). Atmospheric rivers that make landfall in India are associated with flooding. Communications Earth & Environment, 4(1), 120. [Link]

[12]. Mahto S.S. and Mishra V. (2023). Flash drought intensification due to enhanced land-atmospheric coupling in India. J. Clim. 1–31 (2023). [Link]

[11]. Nanditha J.S., Kushwaha A.P., Singh R, Malik I., Solanki H., Chuphal D.S., Vegad U., Dangar S., Mahto, S. S., & Mishra, V. (2023). The Pakistan flood of August 2022: causes and implications. Earth's Future, 11(3), p.e2022EF003230. [Link]

Until 2022

[10]. Rajeev, A., Mahto, S. S., & Mishra, V. (2022). Climate warming and summer monsoon breaks drive compound dry and hot extremes in India. iScience, 105377. [Link]

[9]. Mishra, V., Mujumdar, M., & Mahto, S. S., (2022). Benchmark worst droughts during the summer monsoon in India. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences. https://doi.org/10.1098/rsta.2021-0291. [Link]

[8]. Kushwaha, A. P., Tiwari, A. D., Dangar, S., Shah, H., Mahto, S. S., & Mishra, V. (2021). Multimodel assessment of water budget in Indian sub-continental river basins. Journal of Hydrology, 603, 126977. https://doi.org/10.1016/j.jhydrol.2021.126977. [Link]

[7]. Mishra, V., Aadhar, S., & Mahto, S. S. (2021). Anthropogenic warming and intraseasonal summer monsoon variability amplify the risk of future flash droughts in India. npj Climate and Atmospheric Science, 4(1), 1-10. https://doi.org/10.1038/s41612-020-00158-3. [Link]

[6]. Mahto S.S. and Mishra V. (2020). Dominance of summer monsoon flash droughts in India Environmental Research Letters. https://doi.org/10.1088/1748-9326/abaf1d. [Link]

[5]. Mahto S.S. and Mishra V. (2019). Does ERA-5 outperform other reanalysis products for hydrologic applications in India? Journal of Geophysical Research : Atmospheres. https://doi.org/10.1029/2019JD031155. [Link]

[4]. Nandargi S.S., Mahto S.S. (2019). Frequency and intensity of tropical disturbances over the Indian region and its neighboring seas with associated rainfall during the monsoon season: A perspective. Engineering Reports. 1:e12069. https://doi.org/10.1002/eng2.12069. [Link]

[3]. Kushwaha A.P., Pandey, A.C. and Mahto S.S. (2018). Assessment of Runoff Pattern and Relationship to Sediment Yield of Bhagirathi–Alaknanda River Basin Using Geospatial Techniques. J geovis spat anal. 2: 9. https://doi.org/10.1007/s41651-018-0016-8. [Link]

[2]. Mahto, S. S., & Pandey, A. C. (2018). Satellite Based Temporal Analysis of Local Weather Elements along N–S Transect across Jharkhand, Bihar and Eastern Nepal. In Multidisciplinary Digital Publishing Institute Proceedings (Vol. 2, No. 7, p. 343). https://doi.org/10.3390/ecrs-2-05156. [Link]

[1]. Mahto, S. S., & Kushwaha, A. P. (2018). An assessment of interseasonal surface water level fluctuation of Lonar Crater lake, Maharashtra, India Using multi-temporal Satellite dataset. American Journal of Remote Sensing, 6(1), 6-14. [Link]

Conferences

[9]. Mahto S.S. and Vu Dung., Galelli S., and, Fatichi S. (2023). Inferring reservoir filling strategies and rule curves in Mainland Southeast Asia. H42H-04. AGU Fall Meeting 2023, San Francisco, CA, USA.

[8]. Mahto S.S. and Mishra V. (2022). Flash drought recovery by cascading extreme precipitation in India: role of the atmospheric rivers. NH42B-0423. AGU Fall Meeting 2022, Chicago, IL, USA.

[7]. Mallik I., Mahto S.S. and Mishra V. (2022). Causes of increasing hot and dry compound extremes in India. NH42B-0421. AGU Fall Meeting 2022, Chicago, IL, USA.

[6]. Mahto, S. S., & Mishra, V. (2022). Land-atmospheric coupling amplify the flash drought intensity in India. ID-EGU22-3365. EGU General Assembly, 2022, Vienna, Austria.

[5]. Nanditha JS, Kushwaha AP, Singh, R, Malik I, and Vegad U and Dangar, S, Mahto, S.S. and Solanki H., Chuphal D, and Mishra, V. The Pakistan flood of August 2022: causes and implications. AGU Fall Meeting 2022, Chicago, IL, USA.

[4]. Tripathi I.M., and Mahto S.S., and Mohapatra P. Drought analysis using bivariate copulas in the Indian secondary cities. AGU Fall Meeting 2022, Chicago, IL, USA.

[3]. Mahto S.S. and Mishra V. (2021). Global teleconnections of monsoon season flash drought and its prediction capability in India. ID-GC55H-0503. AGU Fall Meeting 2021, New Orleans, LA, USA.

[2]. Kushwaha, A., Mahto, S. S., & Mishra, V. (2021). Occurrence of contrasting dry and wet extremes in a course of sub-monthly time scale. ID-GC55D-0466. AGU Fall Meeting 2021. New Orleans, LA, USA.

[1]. Mahto S.S. and Mishra V. (2020). Mechanism and Characteristics of Flash Droughts in India and their Evaluation Using Evaporative Soil Moisture Index (ESMI). ID-EGU2020-12616. EGU General Assembly, 2020, Vienna, Austria.

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