Ashok K. Mishra

ORCID: 0000-0003-2606-4718
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About
Contact & Profiles
Research Areas
  • Climate variability and models
  • Hydrology and Drought Analysis
  • Hydrology and Watershed Management Studies
  • Climate change impacts on agriculture
  • Meteorological Phenomena and Simulations
  • Hydrological Forecasting Using AI
  • Agricultural risk and resilience
  • Plant Water Relations and Carbon Dynamics
  • Precipitation Measurement and Analysis
  • Water resources management and optimization
  • Flood Risk Assessment and Management
  • Rice Cultivation and Yield Improvement
  • Soil Moisture and Remote Sensing
  • Agricultural Innovations and Practices
  • Agricultural Science and Fertilization
  • Agricultural Economics and Policy
  • Water-Energy-Food Nexus Studies
  • Agronomic Practices and Intercropping Systems
  • Tropical and Extratropical Cyclones Research
  • Efficiency Analysis Using DEA
  • Market Dynamics and Volatility
  • Potato Plant Research
  • Agricultural pest management studies
  • Ecosystem dynamics and resilience
  • Agricultural Economics and Practices

Texas A&M University
2007-2025

Arizona State University
2015-2025

Clemson University
2015-2024

Odisha University of Agriculture and Technology
2013-2024

Southern Research Station
2024

Indian Institute of Technology Kharagpur
2009-2023

Indian Agricultural Research Institute
2023

Morrison Tech
2017-2020

Pacific Northwest National Laboratory
2012-2018

ConocoPhillips (Canada)
2018

Both seasonal and annual mean precipitation evaporation influence patterns of water availability impacting society ecosystems. Existing global climate studies rarely consider such from non-parametric statistical standpoint. Here, we employ a analysis framework to analyze hydroclimatic regimes by classifying land regions into nine using late 20th century means seasonality. These are used assess implications for due concomitant changes in CMIP5 model future projections. Out 9 regimes, 4 show...

10.1038/s41467-020-16757-w article EN cc-by Nature Communications 2020-06-23

10.1007/s00477-005-0238-4 article EN Stochastic Environmental Research and Risk Assessment 2005-06-20

Abstract Compound drought and heatwaves can cause significant damage to the environment, economy, society. In this study, we quantify spatio‐temporal changes in compound heatwave (CDHW) events by integrating weekly self‐calibrated Palmer Drought Severity Index (sc_PDSI) daily maximum temperatures during period 1983 2016. Multiple data products are used examine robustness of sc_PDSI event analysis. The results consistently suggest increases drought‐related affected global land area recent...

10.1029/2020gl090617 article EN Geophysical Research Letters 2020-12-10

Compound drought and heatwave (CDHW) events have garnered increased attention due to their significant impacts on agriculture, energy, water resources, ecosystems. We quantify the projected future shifts in CDHW characteristics (such as frequency, duration, severity) continued anthropogenic warming relative baseline recent observed period (1982 2019). combine weekly information for 26 climate divisions across globe, employing historical model output from eight Coupled Model Intercomparison...

10.1073/pnas.2219825120 article EN cc-by-nc-nd Proceedings of the National Academy of Sciences 2023-07-03

10.1007/s00477-021-02152-4 article EN Stochastic Environmental Research and Risk Assessment 2022-01-20

This review provides a broad overview of the current state flood research, challenges, and future directions. Beginning with discussion flood-generating mechanisms, synthesizes literature on forecasting, multivariate nonstationary frequency analysis, urban flooding, remote sensing floods. Challenges research directions are outlined highlight emerging topics where more work is needed to help mitigate risks. It anticipated that systems will likely have significant risk due compounding effects...

10.1061/(asce)he.1943-5584.0002164 article EN Journal of Hydrologic Engineering 2022-03-24

Abstract Quantifying the spatial and interconnected structure of regional to continental scale droughts is one unsolved global hydrology problems, which important for understanding looming risk mega-scale resulting water food scarcity their cascading impact on worldwide economy. Using a Complex Network analysis, this study explores topological characteristics drought events based self-calibrated Palmer Drought Severity Index. Event Synchronization used measure strength association between...

10.1038/s41467-022-35531-8 article EN cc-by Nature Communications 2023-01-10

Abstract The 2022 Compound Drought and Heatwave (CDHW) caused widespread crop damage, water shortages, wildfires across Europe. Our study analyzed this event’s severity return period (RP) compared it with past mega CDHWs in hardest‐hit areas were Iberian Peninsula, France, Italy, where temperatures exceeded 2.5°C above normal, severe droughts persisted from May to August. Using a Bayesian approach, we estimated the RP for CDHW event, which was unprecedented Northern western parts of RPs 354,...

10.1029/2023gl105453 article EN cc-by Geophysical Research Letters 2023-08-08

Abstract The significant impact of flash droughts (FDs) on society can vary based a combination FD characteristics (event counts, mean severity, and rate intensification), which is largely unexplored. We employed root‐zone soil‐moisture for 1980–2018 to calculate the integrated them formulate novel multivariate indicator mapping global hotspot regions. potential influence climate (i.e., anomalies, aridity, evaporative fractions) land‐climate feedbacks evolution investigated. Our results...

10.1029/2021gl096804 article EN publisher-specific-oa Geophysical Research Letters 2022-01-10

Abstract Climate change amplifies dry and hot extremes, yet the mechanism, extent, scope, temporal scale of causal linkages between extremes remain underexplored. Here using concept system dynamics, we investigate cross-scale interactions within dry-to-hot hot-to-dry extreme event networks quantify magnitude, temporal-scale, physical drivers cascading effects (CEs) drying-on-heating vice-versa, across globe. We find that locations exhibiting exceptionally strong CE (hotspots) for generally...

10.1038/s41467-022-35748-7 article EN cc-by Nature Communications 2023-01-17

Treating the occurrence and severity of droughts as random, a hybrid model, combining linear stochastic model nonlinear artificial neural network (ANN) is developed for drought forecasting. The combines advantages both ANN models. Using Standardized Precipitation Index series, well individual models were applied to forecast in Kansabati River basin India, their performances compared. was found with greater accuracy.

10.1061/(asce)1084-0699(2007)12:6(626) article EN Journal of Hydrologic Engineering 2007-10-15

10.1007/s00477-007-0194-2 article EN Stochastic Environmental Research and Risk Assessment 2007-10-26
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