Velpuri Manikanta
@nitw.ac.in
Scopus Publications
- Decoding parameter sensitivities across scales: a Wavelet-Sobol framework for hydrological modelling
Vaddadi Sai Suswara, Velpuri Manikanta, Maheswaran Rathinasamy
Journal of Hydrology, 2026 - Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach
Venuthurla Manohar Reddy, Litan Kumar Ray, Velpuri Manikanta
International Journal of Climatology, 2026
The present study investigates the impact of Sea Surface Temperature (SST) extremes on precipitation extremes in India's six homogeneous climate regions from 1981 to 2020. A wavelet‐based complex network analysis was used to explore the connections between precipitation extremes and SST extremes. The Maximum Overlap Discrete Wavelet Transform (MODWT) technique was employed for time series decomposition to identify these links across different temporal scales. Spearman correlation was then used to determine the relationships between SST extremes and precipitation extremes at the grid level. Complex networks were then constructed for each of India's climate regions, focusing on both positive and negative correlations with various global sea regions. Results reveal that precipitation extremes at shorter time scales are predominantly driven by proximal oceanic regions such as the Bay of Bengal (BOB), Arabian Sea (ARS), and Eastern Indian Ocean (EIO), reflecting strong monsoon–SST coupling through moisture convergence and synoptic convection processes. As the time scale increases, remote SST influences from the Atlantic (NAO, EAO), Pacific (EPO, NPO, SPO), and Southern Hemisphere oceans (SIO, SAO, SOO) become increasingly dominant, highlighting the role of atmospheric teleconnections, jet stream modulation, and cross‐equatorial moisture transport. Interannual scales show the widest and most diverse SST control, whilst decadal‐scale influence is generally weak and region‐specific. The regional analysis demonstrates distinct propagation pathways of SST influence, with West Central India showing consistent multiscale sensitivity, Central Northeast and Northeast India transitioning from local to global control, and South Peninsular India retaining strong regional dominance. These insights underscore the necessity of integrating both regional and global SST indices into forecasting frameworks for improved prediction and climate adaptation strategies in India. - Catchment features-based interpretation of performance of the conceptual hydrological and deep learning models using large sample hydrologic data
Daneti Arun Sourya, Velpuri Manikanta, Monzur Alam Imteaz, Maheswaran Rathinasamy
Journal of Hydrology, 2025 - Rising compound heatwave exposure in India: insights from CMIP6 climate model projections
Karlapudi Sahithi, Velpuri Manikanta, Jew Das
Environmental Research Letters, 2025
This study analyses the variability of daytime-only, nighttime-only, and compound heat waves (HWs) and their impact on population exposure across India using shared socioeconomic pathways (SSPs) scenarios (SSP126, SSP245, SSP370, and SSP585) from the Coupled Model Intercomparison Project Phase 6 experiment. The research questions addressed are: (1) what effects might compound heatwaves have under climate change scenarios? (2) How are compound heatwaves expected to impact the population in the future? The outcomes indicate that the compound HWs may increase by 4.6 events annually in Northwest India (NWI) under the SSP585 scenario. In contrast, daytime-only HWs are expected to decline after 2060, except in the Himalayan region, possibly due to changes in monsoon patterns and increased evaporative cooling. It is anticipated that nighttime-only heatwaves will uniformly increase across all regions and scenarios, with the most substantial rises observed in the Central Northeast India (CNI) and NWI. Under the SSP370 scenario during 2061–2100, the population exposure to compound heatwaves and nighttime-only heatwaves is projected to increase substantially across all regions. Specifically, exposure to compound heatwaves is anticipated to exceed historical levels by more than 30 times in most regions. Both the CNI and NWI regions show the highest rise in compound and nighttime-only heatwave extremes. The outcomes provide a substantial scientific foundation for policymakers to inform and enhance heat action plans at the national, state, and local levels. - Deciphering the intra annual dynamics of evolving compound flood-drought interaction in Indian hydrology: insights from a copula-based approach
Salvadi Chetan Kumar, Velpuri Manikanta, Manoj Kumar Jain, Vivek Gupta
Theoretical and Applied Climatology, 2025 - Investigating the Impact of Compound Extremes on Crop Yield Response of Cotton Using DSSAT-CROPGRO-Cotton Crop Simulation Model
Kandula Srikanth, Velpuri Manikanta, N. V. Umamahesh
Journal of Irrigation and Drainage Engineering, 2025
Agricultural productivity is highly vulnerable to weather and climate extremes, including droughts and heatwaves, which can significantly impact crop yields. Despite previous studies addressing the effects of individual and compound extremes on crop productivity, a comprehensive understanding of the critical duration thresholds beyond which a crop yield declines substantially remains limited. This study aims to investigate the duration thresholds of compound and individual extremes for cotton under various scenarios. We utilize the decision support system for agrotechnology transfer-cropping system growth model (DSSAT-CROPGRO)-Cotton crop simulation model, combined with bias-corrected projections from eight climate models, to simulate future cotton yields for rainfed and fully irrigated conditions with varying CO2 concentrations. Our findings indicate an overall decline in cotton yields across all scenarios toward the end of the century, with the highest emissions scenario (SSP585) showing the most significant reduction. The occurrence of coincidental heatwaves and droughts in SSP585 leads to yield declines of approximately 33%, 23%, and 15% in S1, S2, and S3 scenarios, respectively. While rainfed scenarios with increased CO2 show some mitigation of extreme events’ impact, fully irrigated scenarios exhibit only marginal improvements. These results underscore the urgency of developing sustainable practices to mitigate the adverse effects of extreme events on cotton yields amid a changing climate. - Groundwater quality assessment using water quality indices, hydrogeochemical studies and multivariate statistical analysis in Udham Singh Nagar district, Uttarakhand, India
Mayank Singh Bisht, Shiv Kumar, Narendra Kumar Goel, Manohar Arora, Velpuri Manikanta
Environment Development and Sustainability, 2025 - Disaggregation of climatic variables using a novel stochastic approach and its application in building performance simulation studies
Velpuri Manikanta, Titas Ganguly, Shweta Lall, Elangovan Rajasekar, Dhyan Singh Arya
Journal of Building Performance Simulation, 2025
Daily weather data, both observed and synthesized, are available for most locations worldwide but not at the sub-daily temporal scale, which is desirable for building performance analysis. In this context, we introduce a novel stochastic methodology based on pattern mapping for disaggregation of daily data into sub-daily (hourly) time resolution. The methodology has been tested and validated for three weather variables required for energy simulation (temperature, relative humidity and solar radiation). This approach yields better results than existing methodologies for the selected climate variables. Process efficiency is maintained even with the limited input data. Its stochastic nature enables time-invariant pattern mapping to generate future weather files. The annual ‘space conditioning energy’ was simulated to assess building performance accuracy using weather files for the hottest, coldest, average and test reference years (TRY) from disaggregated and observed datasets. Results show that the pattern mapping disaggregation methodology accurately downscales daily to sub-daily data. - Investigating the Limitations of Multi-Model Ensembling of Climate Model Outputs in Capturing Climate Extremes
Velpuri Manikanta, V. Manohar Reddy, Jew Das
International Journal of Climatology, 2024
In the context of climate change, the widespread practice of directly employing Multi‐Model Ensembles (MMEs) for projecting future climate extremes, without prior evaluation of MME performance in historical periods, remains underexplored. This research addresses this gap through a comprehensive analysis of ensemble means derived from CMIP6‐based models, including both simple and weighted averages of precipitation (SEMP and WEMP) and temperature (SEMT and WEMT) time series, as well as simple (SEME) and weighted (WEME) averages of extremes based on model‐by‐model analysis. The study evaluates the efficacy of MMEs in capturing mean annual values of ETCCDI indices over India for the period 1951–2014, utilising the IMD gridded data set as a reference. The results reveal that SEME and WEME consistently align closely with IMD data across various precipitation indices. At the same time, SEMP and WEMP consistently display underestimation biases ranging from 20% to 80% across all precipitation indices, except for CWD, where there is an overestimation bias. Moreover, SEMP and WEMP consistently underestimate CDD and overestimate CWD, indicating a systematic bias in these ensemble means, while WEME and SEME demonstrate satisfactory performance. SEMT and WEMT exhibit notable underestimation in temperature indices. In summary, adopting SEME and SEMT leads to a more robust assessment of precipitation and temperature extremes, respectively. These findings highlight the limitations of traditional MME methodologies in reproducing observed extreme precipitation events across various climatic zones in India, offering essential insights for refining climate models and improving the reliability of climate projections specific to the Indian subcontinent. - Unravelling the impact of spatial discretization and calibration strategies on event-based flood models
Velpuri Manikanta, N. V. Umamahesh
Modeling Earth Systems and Environment, 2024 - Does the performance enhancement through multi-model averaging at the catchment outlet gets translated to the interior ungauged points?
Sravanthi Dusa, Velpuri Manikanta, Jew Das, N.V. Umamahesh
Journal of Hydrology, 2023 - Corrigendum to spatio-temporal compounding of connected extreme events: Projection and hotspot identification Environ. Res. 235 (2023) 116615 (Environmental Research (2023) 235, (S0013935123014196), (10.1016/j.envres.2023.116615))
Manikanta Velpuri, Jew Das, N.V. Umamahesh
Environmental Research, 2023 - Spatio-temporal compounding of connected extreme events: Projection and hotspot identification
Manikanta Velpuri, Jew Das, N.V. Umamahesh
Environmental Research, 2023 - Enhancing the predictability of flood forecasts by combining Numerical Weather Prediction ensembles with multiple hydrological models
Kalakuntla Nikhil Teja, Velpuri Manikanta, Jew Das, N.V. Umamahesh
Journal of Hydrology, 2023 - Performance assessment of methods to estimate initial hydrologic conditions for event-based rainfall-runoff modelling
Velpuri Manikanta, N. V. Umamahesh
Journal of Water and Climate Change, 2023 - Hydrological assessment of the Tungabhadra River Basin based on CMIP6 GCMs and multiple hydrological models
G. K. Rudraswamy, Velpuri Manikanta, Nanduri Umamahesh
Journal of Water and Climate Change, 2023 - A Multi criteria Decision Making based nonparametric method of fragments to disaggregate daily precipitation
Velpuri Manikanta, Titas Ganguly, N.V. Umamahesh
Journal of Hydrology, 2023 - On the verification of ensemble precipitation forecasts over the Godavari River basin
Velpuri Manikanta, K. Nikhil Teja, Jew Das, N.V. Umamahesh
Journal of Hydrology, 2023 - Formulation of Wavelet Based Multi-Scale Multi-Objective Performance Evaluation (WMMPE) Metric for Improved Calibration of Hydrological Models
Velpuri Manikanta, Vamsi Krishna Vema
Water Resources Research, 2022 - Population exposure to compound extreme events in India under different emission and population scenarios
Jew Das, Velpuri Manikanta, N.V. Umamahesh
Science of the Total Environment, 2022 - Two decades of ensemble flood forecasting: a state-of-the-art on past developments, present applications and future opportunities
Jew Das, Velpuri Manikanta, K. Nikhil Teja, N. V. Umamahesh
Hydrological Sciences Journal, 2022 - Unravelling the influence of subjectivity on ranking of CMIP6 based climate models: A case study
Suram Anil, Velpuri Manikanta, Anand Raj Pallakury
International Journal of Climatology, 2021
RECENT SCHOLAR PUBLICATIONS
- Decoding parameter sensitivities across scales: a Wavelet–Sobol framework for hydrological modelling
SS Vaddadi, M Velpuri, M Rathinasamy
Journal of Hydrology, 135482 , 2026
2026 - Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach
VM Reddy, LK Ray, V Manikanta
International Journal of Climatology 46 (1), e70172 , 2026
2026 - Rising compound heatwave exposure in India: insights from CMIP6 climate model projections
K Sahithi, V Manikanta, J Das
Environmental Research Letters 20 (11), 114058 , 2025
2025
Citations: 1 - Catchment features-based interpretation of performance of the conceptual hydrological and deep learning models using large sample hydrologic data
DA Sourya, V Manikanta, MA Imteaz, M Rathinasamy
Journal of Hydrology, 134270 , 2025
2025
Citations: 1 - Groundwater quality assessment using water quality indices, hydrogeochemical studies and multivariate statistical analysis in Udham Singh Nagar district, Uttarakhand, India …
MS Bisht, S Kumar, NK Goel, M Arora, V Manikanta
Environment, Development and Sustainability, 1-40 , 2025
2025
Citations: 4 - Deciphering the intra annual dynamics of evolving compound flood-drought interaction in Indian hydrology: insights from a copula-based approach
SC Kumar, V Manikanta, MK Jain, V Gupta
Theoretical and Applied Climatology 156 (4), 199 , 2025
2025
Citations: 4 - Disaggregation of climatic variables using a novel stochastic approach and its application in building performance simulation studies
V Manikanta, T Ganguly, S Lall, E Rajasekar, DS Arya
Journal of Building Performance Simulation 18 (2), 99-117 , 2025
2025 - Investigating the impact of compound extremes on crop yield response of cotton using DSSAT-CROPGRO-Cotton crop simulation model
K Srikanth, V Manikanta, NV Umamahesh
Journal of Irrigation and Drainage Engineering 151 (1), 04024038 , 2025
2025
Citations: 3 - Investigating the Limitations of Multi‐Model Ensembling of Climate Model Outputs in Capturing Climate Extremes
V Manikanta, VM Reddy, J Das
International Journal of Climatology 44 (16), 5711-5726 , 2024
2024
Citations: 4 - Unravelling the impact of spatial discretization and calibration strategies on event-based flood models
V Manikanta, NV Umamahesh
Modeling Earth Systems and Environment 10 (2), 2887-2903 , 2024
2024
Citations: 3 - Does the performance enhancement through multi-model averaging at the catchment outlet gets translated to the interior ungauged points?
S Dusa, V Manikanta, J Das, NV Umamahesh
Journal of Hydrology 627, 130389 , 2023
2023
Citations: 6 - Spatio-temporal compounding of connected extreme events: Projection and hotspot identification
M Velpuri, J Das, NV Umamahesh
Environmental Research 235, 116615 , 2023
2023
Citations: 28 - Enhancing the predictability of flood forecasts by combining Numerical Weather Prediction ensembles with multiple hydrological models
KN Teja, V Manikanta, J Das, NV Umamahesh
Journal of Hydrology 625, 130176 , 2023
2023
Citations: 25 - Performance assessment of methods to estimate initial hydrologic conditions for event-based rainfall-runoff modelling
V Manikanta, NV Umamahesh
Journal of Water and Climate Change 14 (7), 2277-2293 , 2023
2023
Citations: 19 - Hydrological assessment of the Tungabhadra River Basin based on CMIP6 GCMs and multiple hydrological models
GK Rudraswamy, V Manikanta, N Umamahesh
Journal of Water and Climate Change 14 (5), 1371-1394 , 2023
2023
Citations: 28 - A multi criteria decision making based nonparametric method of fragments to disaggregate daily precipitation
V Manikanta, T Ganguly, NV Umamahesh
Journal of Hydrology 617, 128994 , 2023
2023
Citations: 14 - On the verification of ensemble precipitation forecasts over the Godavari River basin
V Manikanta, KN Teja, J Das, NV Umamahesh
Journal of Hydrology 616, 128794 , 2023
2023
Citations: 19 - Formulation of wavelet based multi‐scale multi‐objective performance evaluation (WMMPE) metric for improved calibration of hydrological models
V Manikanta, VK Vema
Water Resources Research 58 (7), e2020WR029355 , 2022
2022
Citations: 22 - Two decades of ensemble flood forecasting: a state-of-the-art on past developments, present applications and future opportunities
J Das, V Manikanta, K Nikhil Teja, NV Umamahesh
Hydrological Sciences Journal 67 (3), 477-493 , 2022
2022
Citations: 38 - Population exposure to compound extreme events in India under different emission and population scenarios
J Das, V Manikanta, NV Umamahesh
Science of the Total Environment 806, 150424 , 2022
2022
Citations: 92
MOST CITED SCHOLAR PUBLICATIONS
- Population exposure to compound extreme events in India under different emission and population scenarios
J Das, V Manikanta, NV Umamahesh
Science of the Total Environment 806, 150424 , 2022
2022
Citations: 92 - Unravelling the influence of subjectivity on ranking of CMIP6 based climate models: A case study
S Anil, V Manikanta, AR Pallakury
International Journal of Climatology 41 (13), 5998-6016 , 2021
2021
Citations: 55 - Two decades of ensemble flood forecasting: a state-of-the-art on past developments, present applications and future opportunities
J Das, V Manikanta, K Nikhil Teja, NV Umamahesh
Hydrological Sciences Journal 67 (3), 477-493 , 2022
2022
Citations: 38 - Spatio-temporal compounding of connected extreme events: Projection and hotspot identification
M Velpuri, J Das, NV Umamahesh
Environmental Research 235, 116615 , 2023
2023
Citations: 28 - Hydrological assessment of the Tungabhadra River Basin based on CMIP6 GCMs and multiple hydrological models
GK Rudraswamy, V Manikanta, N Umamahesh
Journal of Water and Climate Change 14 (5), 1371-1394 , 2023
2023
Citations: 28 - Enhancing the predictability of flood forecasts by combining Numerical Weather Prediction ensembles with multiple hydrological models
KN Teja, V Manikanta, J Das, NV Umamahesh
Journal of Hydrology 625, 130176 , 2023
2023
Citations: 25 - Formulation of wavelet based multi‐scale multi‐objective performance evaluation (WMMPE) metric for improved calibration of hydrological models
V Manikanta, VK Vema
Water Resources Research 58 (7), e2020WR029355 , 2022
2022
Citations: 22 - Performance assessment of methods to estimate initial hydrologic conditions for event-based rainfall-runoff modelling
V Manikanta, NV Umamahesh
Journal of Water and Climate Change 14 (7), 2277-2293 , 2023
2023
Citations: 19 - On the verification of ensemble precipitation forecasts over the Godavari River basin
V Manikanta, KN Teja, J Das, NV Umamahesh
Journal of Hydrology 616, 128794 , 2023
2023
Citations: 19 - A multi criteria decision making based nonparametric method of fragments to disaggregate daily precipitation
V Manikanta, T Ganguly, NV Umamahesh
Journal of Hydrology 617, 128994 , 2023
2023
Citations: 14 - Does the performance enhancement through multi-model averaging at the catchment outlet gets translated to the interior ungauged points?
S Dusa, V Manikanta, J Das, NV Umamahesh
Journal of Hydrology 627, 130389 , 2023
2023
Citations: 6 - Groundwater quality assessment using water quality indices, hydrogeochemical studies and multivariate statistical analysis in Udham Singh Nagar district, Uttarakhand, India …
MS Bisht, S Kumar, NK Goel, M Arora, V Manikanta
Environment, Development and Sustainability, 1-40 , 2025
2025
Citations: 4 - Deciphering the intra annual dynamics of evolving compound flood-drought interaction in Indian hydrology: insights from a copula-based approach
SC Kumar, V Manikanta, MK Jain, V Gupta
Theoretical and Applied Climatology 156 (4), 199 , 2025
2025
Citations: 4 - Investigating the Limitations of Multi‐Model Ensembling of Climate Model Outputs in Capturing Climate Extremes
V Manikanta, VM Reddy, J Das
International Journal of Climatology 44 (16), 5711-5726 , 2024
2024
Citations: 4 - Investigating the impact of compound extremes on crop yield response of cotton using DSSAT-CROPGRO-Cotton crop simulation model
K Srikanth, V Manikanta, NV Umamahesh
Journal of Irrigation and Drainage Engineering 151 (1), 04024038 , 2025
2025
Citations: 3 - Unravelling the impact of spatial discretization and calibration strategies on event-based flood models
V Manikanta, NV Umamahesh
Modeling Earth Systems and Environment 10 (2), 2887-2903 , 2024
2024
Citations: 3 - Rising compound heatwave exposure in India: insights from CMIP6 climate model projections
K Sahithi, V Manikanta, J Das
Environmental Research Letters 20 (11), 114058 , 2025
2025
Citations: 1 - Catchment features-based interpretation of performance of the conceptual hydrological and deep learning models using large sample hydrologic data
DA Sourya, V Manikanta, MA Imteaz, M Rathinasamy
Journal of Hydrology, 134270 , 2025
2025
Citations: 1 - Decoding parameter sensitivities across scales: a Wavelet–Sobol framework for hydrological modelling
SS Vaddadi, M Velpuri, M Rathinasamy
Journal of Hydrology, 135482 , 2026
2026 - Exploring the Influence of Sea Surface Temperature Extremes on Precipitation Extremes Across India's Climate Zones: A Complex Network Approach
VM Reddy, LK Ray, V Manikanta
International Journal of Climatology 46 (1), e70172 , 2026
2026
