Carlo DeMarchi

Phosphorus load estimation in the Saginaw River, MI using a Bayesian hierarchical/multilevel model.

We propose the use of Bayesian hierarchical/multilevel ratio approach to estimate the annual riverine phosphorus loads in the Saginaw River, Michigan, from 1968 to 2008. The ratio estimator is known to be an unbiased, precise approach for differing flow-concentration relationships and sampling schemes. A Bayesian model can explicitly address the uncertainty in prediction by using a posterior predictive distribution, while in comparison, a Bayesian hierarchical technique can overcome the limitation of interpreting the estimated annual loads inferred from small sample sizes by borrowing strength from the underlying population shared by the years of interest. Thus, by combining the ratio estimator with the Bayesian hierarchical modeling framework, long-term loads estimation can be addressed with explicit quantification of uncertainty. Our study results indicate a slight decrease in total phosphorus load early in the series. The estimated ratio parameter, which can be interpreted as flow-weighted concentration, shows a clearer decrease, damping the noise that yearly flow variation adds to the load. Despite the reductions, it is not likely that Saginaw Bay meets with its target phosphorus load, 440 tonnes/yr. Throughout the decades, the probabilities of the Saginaw Bay not complying with the target load are estimated as 1.00, 0.50, 0.57 and 0.36 in 1977, 1987, 1997, and 2007, respectively. We show that the Bayesian hierarchical model results in reasonable goodness-of-fits to the observations whether or not individual loads are aggregated. Also, this modeling approach can substantially reduce uncertainties associated with small sample sizes both in the estimated parameters and loads.

Application of a Distributed Large Basin Runoff Model to Lake Erie: Model Calibration and Analysis of Parameter Spatial Variation

The distributed large basin runoff model (DLBRM) was designed to simulate the hydrological processes of the Great Lakes watersheds. As part of its development, the DLBRM was recently applied to 18 watersheds in the Lake Erie basin, where it was first calibrated to reproduce the observed discharge in 1950–1964 and then applied to 1999–2006. Four different calibration objective functions: root mean squared error (RMSE) minimization, mean absolute error (MAE) minimization, correlation maximization, and Nash-Sutcliffe index maximization were tested, revealing RMSE minimization as the most successful method and able to achieve results very close to its global minimum. Further, the distribution of the main DLBRM parameters in the 18 watersheds was consistent with regional patterns, although each watershed was calibrated individually, thus adding credibility to the calibration process. Model performances, while generally good, varied across the basin according to a series of environmental factors, including clim...

Modeling Distribution of Point and Nonpoint Sources Pollution Loadings in the Saginaw Bay Watersheds, Michigan

This study involves developing a physically based, spatially-distributed water quality model to simulate spatial and temporal distributions of point and nonpoint sources in the Saginaw Bay Basin, Michigan. Databases of point sources including combined sewer overflows (CSOs) were acquired from the governmental agencies to map the occurrences and magnitude of the CSOs. Multiple databases of meteorology, land use, topography, hydrography, soils, and agricultural statistics were used to estimate nonpoint source loading potential in the study watersheds. Results indicate that point sources from municipalities, industrial sectors and business entities contribute approximately 25% of the total phosphorous load to Saginaw Bay. While total amount of nutrients (N and P) from animal manure and fertilizer applications and atmospheric deposition declined in the Saginaw Bay Basin, fertilizer applications in non-farmland increased significantly.

Simulation of River Flow for Downstream Water Allocation in the Heihe River Watershed, Northwest China

Multiple demands for water for large agricultural irrigation schemes, increasing industrial development, and rapid urban population growth have depleted downstream flows most of the time in the arid Heihe River Watershed, Northwest China, causing shrinking oases and tensions among different water jurisdictions and ethnic groups. To address this pressing issue, the State Council of the People’s Republic of China has issued an executive order to mandate the release of water downstream for ecosystem restoration. This paper describes the adaptation of the Distributed Large Basin Runoff Model to the Heihe Watershed to gain an understanding of the distribution of glacial/snow melt, groundwater, surface runoff, and evapotranspiration in the upper and middle reaches of the watershed. The simulated daily river flows for 1990–2000 show that Qilian Mountain in the upper reach area was the main source of runoff generation in the Heihe Watershed, and annually, the Heihe River discharged about 1 × 109 m3 of water from the middle reach (at Zhengyixia Gage Station) to the lower reach under the normal climatic conditions (with a likelihood of 50 %). These flows are consistent with the State Council’s mandate of delivering 0.95 × 109 m3 water downstream annually. However, the river flow would be significantly less under the dry climatic conditions, making it much more difficult to deliver the mandated amount of water downstream for ecosystem rehabilitation.

Estimating Phosphorous Load from a Large Watershed in the Great Lakes Basin

Common ways to quantify watershed nutrient loads include estimating the annual or seasonal loads using simple relations between discharge and load, such as the ratio estimator, and fitting complex nutrient transport models to the observed concentrations. The former approach produces quite uncertain estimates even at low temporal resolution, when based on typically infrequent routine monitoring data. The second approach may produce more reliable estimates, even at high temporal resolution, but requires a lot of computing effort and auxiliary data. The approach explored in this paper uses linear combination of river discharge at the time of estimate and for antecedent periods to estimate daily Total Phosphorous (TP) concentration, yielding high resolution load estimates sufficiently reliable for a variety of applications.