A5100622412- Hydrology and Watershed Management Studies
- Climate variability and models
- Hydrology and Drought Analysis
- Flood Risk Assessment and Management
- Meteorological Phenomena and Simulations
- Hydrological Forecasting Using AI
- Precipitation Measurement and Analysis
- Water resources management and optimization
- Soil Moisture and Remote Sensing
- Geophysics and Gravity Measurements
- demographic modeling and climate adaptation
- Tropical and Extratropical Cyclones Research
- Cryospheric studies and observations
- Climate change impacts on agriculture
- Groundwater flow and contamination studies
- Oceanographic and Atmospheric Processes
- Reservoir Engineering and Simulation Methods
- Plant Water Relations and Carbon Dynamics
- Soil and Water Nutrient Dynamics
- Atmospheric and Environmental Gas Dynamics
- Climate change and permafrost
- Energy Load and Power Forecasting
- Soil and Unsaturated Flow
- Soil erosion and sediment transport
- Neural Networks and Applications
UNSW Sydney
2016-2025
Manipal University Jaipur
2016-2025
ARC Centre of Excellence for Climate System Science
2017-2024
Chandigarh University
2022-2024
Kathmandu University
2024
Roche (Switzerland)
2024
DAV University
2024
Gandhi Medical College & Hospital
2023
Mahatma Gandhi University
2023
University of Washington
2022-2023
A nonparametric method for resampling scalar or vector‐valued time series is introduced. Multivariate nearest neighbor probability density estimation provides the basis scheme developed. The motivation this work comes from a desire to preserve dependence structure of while bootstrapping (resampling it with replacement). data driven and preferred where investigator uncomfortable prior assumptions as form (e.g., linear nonlinear) function Gaussian). Such are often made in an ad hoc manner...
Abstract Despite evidence of increasing precipitation extremes, corresponding for increases in flooding remains elusive. If anything, flood magnitudes are decreasing despite widespread claims by the climate community that if extremes increase, floods must also. In this commentary we suggest reasons why extreme rainfall not resulting flooding. Among possible mechanisms responsible, identify decreases antecedent soil moisture, storm extent, and snowmelt. We argue understanding link between...
Expected changes to future extreme precipitation remain a key uncertainty associated with anthropogenic climate change. Recently, has been proposed scale the precipitable water content in atmosphere, which assuming relative humidity stays constant, will increase at rate of ∼6.8%/°C as indicated by Clausius‐Clapeyron (C‐C) relationship. We examine this scaling empirically using data from 137 long‐record pluviograph and temperature gauges across Australia. find that rates are consistent C‐C...
Climate change impact assessments of water resources systems require simulations precipitation and evaporation that exhibit distributional persistence attributes similar to the historical record. Specifically, there is a need ensure general circulation model (GCM) rainfall for current climate low‐frequency variability consistent with observed data. Inability represent in flow leads biased estimates security offered by warmer climate. This paper presents method postprocess GCM imparting...
There is overwhelming consensus that the intensity of heavy precipitation events increasing in a warming world. It generally expected such increases will translate to corresponding increase flooding. Here, using global data sets for non-urban catchments, we investigate sensitivity extreme daily and streamflow changes temperature. We find little evidence suggest rainfall at higher temperatures result similar streamflow, with most regions throughout world showing decreased temperatures. To...
Abstract. The effects of climate change are causing more frequent extreme rainfall events and an increased risk flooding in developed areas. Quantifying this is critical importance for the protection life property as well infrastructure planning design. updated National Oceanic Atmospheric Administration (NOAA) Atlas 14 intensity–duration–frequency (IDF) relationships temporal patterns widely used hydrologic hydraulic modeling design United States. Current literature shows that rising...
A large number of recent studies have aimed at understanding short-duration rainfall extremes, due to their impacts on flash floods, landslides and debris flows potential for these worsen with global warming. This has been led in a concerted international effort by the INTENSE Crosscutting Project GEWEX (Global Energy Water Exchanges) Hydroclimatology Panel. Here, we summarize main findings so far suggest future directions research, including: benefits convection-permitting climate...
Climate change impact studies commonly use models (such as hydrological or crop models) forced with corrected climate input data from global models. A range of downscaling and bias correction methods have been developed to increase the spatial resolution remove systematic biases in model outputs be applied before Many focused on evaluating such approaches for variables they aim correct. However, due nonlinear error propagation there can large remaining outputs, even when ingesting forcings....
In this paper kernel estimates of the joint and conditional probability density functions are used to generate synthetic streamflow sequences. Streamflow is assumed be a Markov process with time dependence characterized by multivariate function. Kernel methods estimate Simulation proceeds sequentially resampling from function derived underlying This nonparametric method for synthesis that data‐driven avoids prior assumptions as form (e.g., linear or nonlinear) Gaussian). We show, using...
One challenge that faces hydrologists in water resources planning is to predict the catchment's response a given rainfall. Estimation of parameter uncertainty (and model uncertainty) allows assessment risk likely applications hydrological models. Bayesian statistical inference provides an ideal means assessing uncertainty, whereby prior knowledge about combined with information from available data produce probability distribution (the posterior distribution) describes and serves as basis for...
Abstract Simulations from general circulation models are now being used for a variety of studies and purposes. With up to 23 different GCMs available, it is desirable determine whether specific variable particular model representative the ensemble mean, which often assumed indicate likely state that in future. The answers important decision makers researchers using selective outputs follow-on such as statistical downscaling, currently assume all simulated with equal reliability. A skill...
Continuous simulation for design flood estimation is increasingly becoming a viable alternative to traditional event‐based methods. The advantage of continuous approaches that the catchment moisture state prior flood‐producing rainfall event implicitly incorporated within modeling framework, provided model has been calibrated and validated produce reasonable simulations. This contrasts with models in which both information about expected sequence evaporation preceding event, as well storage...
Abstract Extreme precipitation intensity is expected to increase in proportion the water‐holding capacity of atmosphere. However, increases beyond this expectation have been observed, implying that changes storm dynamics may be occurring alongside moisture availability. Such imply shifts spatial organization storms, and we test by analyzing present‐day sensitivities between near‐surface atmospheric temperature. We show both total depth peak with temperature, while storm's extent decreases....
Abstract Assessment of climate change impacts on water resources is extremely challenging, due to the inherent uncertainties in projections using global models (GCMs). Three main sources can be identified GCMs, i.e., model structure, emission scenario, and natural variability. The recently released fifth phase Coupled Model Intercomparison Project (CMIP5) includes a number advances relative its predecessor (CMIP3), terms spatial resolution models, list variables, concept specifying future...
Abstract The consensus in the scientific community is that intensity of extreme precipitation will increase a warmer climate. However, as there limited observational evidence to this effect, growing body research which focuses on directly investigating relationship between temperature and precipitation. This currently performed by binning data bins then trend percentiles each bin with temperature. In paper, we highlight limitations approach present quantile regression an alternative above...