Incorporating Uncertainty Into the Ranking of SPARROW Model Nutrient Yields From Mississippi/Atchafalaya River Basin Watersheds1

Abstract: Excessive loads of nutrients transported by tributary rivers have been linked to hypoxia in the Gulf of Mexico. Management efforts to reduce the hypoxic zone in the Gulf of Mexico and improve the water quality of rivers and streams could benefit from targeting nutrient reductions toward watersheds with the highest nutrient yields delivered to sensitive downstream waters. One challenge is that most conventional watershed modeling approaches (e.g., mechanistic models) used in these management decisions do not consider uncertainties in the predictions of nutrient yields and their downstream delivery. The increasing use of parameter estimation procedures to statistically estimate model coefficients, however, allows uncertainties in these predictions to be reliably estimated. Here, we use a robust bootstrapping procedure applied to the results of a previous application of the hybrid statistical/mechanistic watershed model SPARROW (Spatially Referenced Regression On Watershed attributes) to develop a statistically reliable method for identifying “high priority” areas for management, based on a probabilistic ranking of delivered nutrient yields from watersheds throughout a basin. The method is designed to be used by managers to prioritize watersheds where additional stream monitoring and evaluations of nutrient‐reduction strategies could be undertaken. Our ranking procedure incorporates information on the confidence intervals of model predictions and the corresponding watershed rankings of the delivered nutrient yields. From this quantified uncertainty, we estimate the probability that individual watersheds are among a collection of watersheds that have the highest delivered nutrient yields. We illustrate the application of the procedure to 818 eight‐digit Hydrologic Unit Code watersheds in the Mississippi/Atchafalaya River basin by identifying 150 watersheds having the highest delivered nutrient yields to the Gulf of Mexico. Highest delivered yields were from watersheds in the Central Mississippi, Ohio, and Lower Mississippi River basins. With 90% confidence, only a few watersheds can be reliably placed into the highest 150 category; however, many more watersheds can be removed from consideration as not belonging to the highest 150 category. Results from this ranking procedure provide robust information on watershed nutrient yields that can benefit management efforts to reduce nutrient loadings to downstream coastal waters, such as the Gulf of Mexico, or to local receiving streams and reservoirs.     

Serial batch leaching procedure for characterization of coal fly ash

Although many leaching methods have been used for various purposes by research groups, industries, and regulators, there is still a need for a simple but comprehensive approach to leaching coal utilization by-products and other granular materials in order to estimate potential release of heavy metals when these materials are exposed to natural fluids. A serial batch characterization method has been developed at the National Energy Technology Laboratory that can be completed in 2–3 days to serve as a screening tool. The procedure provides an estimate of cumulative metals release under varying pH conditions, and leaching the sample at increasing liquid/solid ratios can indicate the rate at which this process will occur. This method was applied to eight fly ashes, adapted to the acidic or alkaline nature of the ash. The leachates were analyzed for 30 elements. The test was run in quadruplicate, and the relative standard deviation (RSD) was used as a measure of method reproducibility. RSD values are between 0.02 and 0.70, with the majority of the RSD values less than 0.3. The serial batch leaching procedure was developed as a simple, relatively quick, yet comprehensive method of estimating the risk of heavy metal release from fly ash when it is exposed to natural fluids, such as acid rain or groundwater. Tests on a random selection of coal fly ashes have shown it to be a reasonably precise method for estimating the availability and long-term release of cations from fly ash.     

Management options and effects on a marine ecosystem: assessing the future of the Baltic

We are using the coupled models in a decision support system, Nest, to evaluate the response of the marine ecosystem to changes in external loads through various management options. The models address all the seven major marine basins and the entire drainage basin of the Baltic Sea. A series of future scenarios have been developed, in close collaboration with the Helsinki Commission, to see the possible effects of improved wastewater treatment and manure handling, phosphorus-free detergents, and less intensive land use and live stocks. Improved wastewater treatment and the use of phosphorus-free detergents in the entire region would drastically decrease phosphorus loads and improve the marine environment, particularly the occurrence of cyanobacterial blooms. However, the Baltic Sea will remain eutrophic, and to reduce other effects, a substantial reduction of nitrogen emissions must be implemented. This can only be obtained in these scenarios by drastically changing land use. In a final scenario, we have turned 50% of all agricultural lands into grasslands, together with efficient wastewater treatments and a ban of phosphorus in detergents. This scenario will substantially reduce primary production and the extension of hypoxic bottoms, increase water transparency in the most eutrophied basins, and virtually eliminate extensive cyanobacterial blooms.     

The role of periodic boundary forcing in plankton pattern formation

We consider one and two-dimensional minimal models in plankton dynamics. The influence of oscillating boundary forcing functions as agents for triggering pattern formation is discussed. In particular it is found that in these conditions population waves arise for one dimensional models, while for two dimensional models, different amplitudes and frequencies in the boundary forcing generate definite patterns, mimicking the boundary term. This happens even though the model we investigate is very simple. The emergence of these features is an interesting metaphor for the fundamental biological problem of how pattern formation processes may be inevitable in natural heterogeneous ecosystems.     

Estimating the aquatic emissions and fate of perfluorooctane sulfonate (PFOS) into the river Rhine

The sources, distribution, levels and sinks of perfluorooctane sulfonate (PFOS) estimated to be released from areas of high population density, have been explored using the river Rhine as a case study. A comparison between modelled and measured data is presented, along with analysis of the importance of PFOS sorption in riverine systems. PFOS releases into the Rhine were estimated to be 325-690 kg/yr based on per capita emission rates of 27-57 μg day(-1) from a population of 33 million living within a 50 km zone either side of the river. Sorption of PFOS to suspended particles and sediments may alter its fate in the aquatic environment. Therefore available measured and modelled partitioning data was assessed, and K(d) values (sorption coefficient) of 7.5 and 20 were selected. This resulted in sediment-water ratios of 23-76 : 1, which are similar to ratios reported in the literature, and resulted in modelled estimates that <20% of the total PFOS entering the Rhine binds to sediments or suspended particles. The calculated discharge from the Rhine to the North Sea based on measured data was 420-2200 kg/yr; our model predictions are in good agreement with these estimates. Emission trends were accurately predicted, suggesting population density can be effectively used as a surrogate for diffuse PFOS emissions from product use, while predicted concentrations were a factor of 2-4 below measured data showing the importance of other sources. Transfer of PFOS to sediment is estimated to be minimal, and consequently discharges to the North Sea are roughly equal to PFOS releases to river water.     

The BIOTA Biodiversity Observatories in Africa—a standardized framework for large-scale environmental monitoring

The international, interdisciplinary biodiversity research project BIOTA AFRICA initiated a standardized biodiversity monitoring network along climatic gradients across the African continent. Due to an identified lack of adequate monitoring designs, BIOTA AFRICA developed and implemented the standardized BIOTA Biodiversity Observatories, that meet the following criteria (a) enable long-term monitoring of biodiversity, potential driving factors, and relevant indicators with adequate spatial and temporal resolution, (b) facilitate comparability of data generated within different ecosystems, (c) allow integration of many disciplines, (d) allow spatial up-scaling, and (e) be applicable within a network approach. A BIOTA Observatory encompasses an area of 1?km² and is subdivided into 100 1-ha plots. For meeting the needs of sampling of different organism groups, the hectare plot is again subdivided into standardized subplots, whose sizes follow a geometric series. To allow for different sampling intensities but at the same time to characterize the whole square kilometer, the number of hectare plots to be sampled depends on the requirements of the respective discipline. A hierarchical ranking of the hectare plots ensures that all disciplines monitor as many hectare plots jointly as possible. The BIOTA Observatory design assures repeated, multidisciplinary standardized inventories of biodiversity and its environmental drivers, including options for spatial up- and downscaling and different sampling intensities. BIOTA Observatories have been installed along climatic and landscape gradients in Morocco, West Africa, and southern Africa. In regions with varying land use, several BIOTA Observatories are situated close to each other to analyze management effects.     

Using an Allowance Reserve to Manage Uncertain Costs in a Cap-and-Trade Program for Greenhouse Gases

This paper investigates the design and performance of an allowance reserve in the context of a cap-and-trade program for greenhouse gases. We use a Monte Carlo approach in which the parameters of the marginal abatement cost function, and the supply of offsets, are drawn from specified distributions. Our framework focuses on the potential impact of “medium-run shocks” to abatement cost and offset supply, as opposed to either short-run volatility or permanent shifts in the cost curve. Our model suggests that under reasonable (and even fairly conservative) assumptions about abatement cost and offset supply, an allowance reserve broadly similar to recent proposals for US climate legislation can be effective in containing allowance prices. In our core policy scenario, with a trigger price equal to US $32 in 2015, we estimate that the probability of drawing on the allowance reserve is <25% and the probability of requiring more than 7?GT of reserve tons over 20?years is <5%. We also use the model to explore the trade-off among three features of the reserve that are most relevant to policy makers: the total size of the reserve, the trigger price, and the degree of confidence that the reserve will be large enough to limit allowance prices to the target level. Our essential result is that a lower trigger price, or a higher degree of confidence, requires a larger reserve.     

Anticipating Climate Threshold Damages

Several integrated assessment studies have concluded that future learning about the uncertainties involved in climate change has a considerable effect on welfare but only a small effect on optimal short-term emissions. In other words, learning is important but anticipation of learning is not. We confirm this result in the integrated assessment model “model of investment and technological development” for learning about climate sensitivity and climate damages. If learning about an irreversible threshold is included, though, we show that anticipation can become crucial both in terms of necessary adjustments of pre-learning emissions and resulting welfare gains. We specify conditions on the time of learning and the threshold characteristic, for which this is the case. They can be summarized as a narrow “anticipation window.”