Regional water resources management generally requires knowledge of multisite streamflows which exhibit random, yet spatially and temporally correlated, variabilities. The complexity of such correlated randomness makes decision-making for water resources management a difficult task. With presence of uncertainties in space and time, risk-based decision making using stochastic models is sought after. In this study we propose a spatiotemporal stochastic simulation model for multisite streamflow simulation. The model is composed of three components: (1) stochastic simulation of bivariate non-Gaussian distributions, (2) anisotropic space-time covariance function which characterizes the spatial and temporal variations of multisite ten-day periods...
Pedu-Muda reservoirs responsible to supply sufficient water capacity during paddy cultivation period...
: Simulation has been an important tool for planners in many fields of knowledge. In the field of wa...
High-resolution space-time stochastic models for precipitation are crucial for hydrological applicat...
The main objectives of this research are to propose a general stochastic method for determining anal...
Reservoirs are operated and managed based on a set of rule curves. Given an ob- served time series o...
It is imperative for cities to develop sustainable water management and planning strategies in order...
It is imperative for cities to develop sustainable water management and planning strategies in order...
This study aims to develop a stochastic method (SM_GSTR) for generating short-time (i.e., hourly) ra...
A non-parametric method for generating stationary weekly hydrologic time series at multiple location...
One major acknowledged challenge in daily precipitation is the inability to model extreme events in ...
Stochastic modelling of long-tem hydrological data is one of the tools used to evaluate water supply...
Stochastically generated streamflow time series are widely used in water resource planning and manag...
Synthetic daily streamflow generation requires a critical understanding of the underlying dynamics r...
This study develops a multivariate eco-hydrological risk-assessment framework based on the multivari...
Streamflow simulation gives the major information on water systems to water resources planning and m...
Pedu-Muda reservoirs responsible to supply sufficient water capacity during paddy cultivation period...
: Simulation has been an important tool for planners in many fields of knowledge. In the field of wa...
High-resolution space-time stochastic models for precipitation are crucial for hydrological applicat...
The main objectives of this research are to propose a general stochastic method for determining anal...
Reservoirs are operated and managed based on a set of rule curves. Given an ob- served time series o...
It is imperative for cities to develop sustainable water management and planning strategies in order...
It is imperative for cities to develop sustainable water management and planning strategies in order...
This study aims to develop a stochastic method (SM_GSTR) for generating short-time (i.e., hourly) ra...
A non-parametric method for generating stationary weekly hydrologic time series at multiple location...
One major acknowledged challenge in daily precipitation is the inability to model extreme events in ...
Stochastic modelling of long-tem hydrological data is one of the tools used to evaluate water supply...
Stochastically generated streamflow time series are widely used in water resource planning and manag...
Synthetic daily streamflow generation requires a critical understanding of the underlying dynamics r...
This study develops a multivariate eco-hydrological risk-assessment framework based on the multivari...
Streamflow simulation gives the major information on water systems to water resources planning and m...
Pedu-Muda reservoirs responsible to supply sufficient water capacity during paddy cultivation period...
: Simulation has been an important tool for planners in many fields of knowledge. In the field of wa...
High-resolution space-time stochastic models for precipitation are crucial for hydrological applicat...