Population and climate pressures on global river water quality

Global analysis of population growth and river water quality

Inference of reactive transport model parameters using a Bayesian multivariate approach

Parameter estimation of subsurface transport models from multispecies data requires the definition of an objective function that includes different types of measurements. Common approaches are weighted least squares (WLS), where weights are specified a priori for each measurement, and weighted least squares with weight estimation (WLS(we)) where...

Land subsidence due to groundwater withdrawal detected by InSAR time-series in Tazerbo well field, Libya

The Tazerbo well field is one of the well fields designed within the Great Man-Made River Project (GMMRP), which aims to deliver water to the eastern coast of Libya through an underground pipe network. It consists of 108 wells in three rows, where the wells are separated 1.3 km in longitude and 10 km in latitude. The planned total groundwater...

Scenario-based decision making in water resource management: A case study in the Yellow River Delta; abstract

Bayesian model averaging using particle filtering and Gaussian mixture modeling: Theory, concepts, and simulation experiments

Bayesian model averaging (BMA) is a standard method for combining predictive distributions from different models. In recent years, this method has enjoyed widespread application and use in many fields of study to improve the spread-skill relationship of forecast ensembles. The BMA predictive probability density function (pdf) of any quantity of...

Gamma distribution models for transit time estimation in catchments: Physical interpretation of parameters and implications for time?variant transit time assessment

In hydrological tracer studies, the gamma distribution can serve as an appropriate transit time distribution (TTD) as it allows more flexibility to account for nonlinearities in the behavior of catchment systems than the more commonly used exponential distribution. However, it is unclear which physical interpretation can be ascribed to its two...

A formal likelihood function for parameter and predictive inference of hydrologic models with correlated, heteroscedastic, and non?Gaussian errors

Estimation of parameter and predictive uncertainty of hydrologic models has traditionally relied on several simplifying assumptions. Residual errors are often assumed to be independent and to be adequately described by a Gaussian probability distribution with a mean of zero and a constant variance. Here we investigate to what extent estimates of...

Corruption of accuracy and efficiency of Markov chain Monte Carlo simulation by inaccurate numerical implementation of conceptual hydrologic models

Conceptual rainfall?runoff models have traditionally been applied without paying much attention to numerical errors induced by temporal integration of water balance dynamics. Reliance on first?order, explicit, fixed?step integration methods leads to computationally cheap simulation models that are easy to implement. Computational speed is...

Model complexity control for hydrologic prediction

A common concern in hydrologic modeling is overparameterization of complex models given limited and noisy data. This leads to problems of parameter nonuniqueness and equifinality, which may negatively affect prediction uncertainties. A systematic way of controlling model complexity is therefore needed. We compare three model complexity control...