Evaluation of the current state of distributed watershed nutrient water quality modeling.

Watershed models have been widely used for creating the scientific basis for management decisions regarding nonpoint source pollution. In this study, we evaluated the current state of watershed scale, spatially distributed, process-based, water quality modeling of nutrient pollution. Beginning from 1992, the year when Beven and Binley published their seminal paper on uncertainty analysis in hydrological modeling, and ending in 2010, we selected 257 scientific publications which (i) employed spatially distributed modeling approaches at a watershed scale; (ii) provided predictions of flow, nutrient/sediment concentrations or loads; and (iii) reported fit to measured data. Most "best practices" (optimization, validation, sensitivity, and uncertainty analysis) are not consistently employed during model development. There are no statistically significant differences in model performance among land uses. Studies which used more than one point in space to evaluate their distributed models had significantly lower median values of the Nash-Sutcliffe Efficiency (0.70 vs 0.56, p<0.005, nonparametric Mann-Whitney test), and r2 (p<0.005). This finding suggests that model calibration only to the basin outlet may mask compensation of positive and negative errors of source and transportation processes. We conclude by advocating a number of new directions for distributed watershed modeling, including in-depth uncertainty analysis and the use of additional information, not necessarily related to model end points, to constrain parameter estimation.

Spatial cyberinfrastructures, ontologies, and the humanities.

We report on research into building a cyberinfrastructure for Chinese biographical and geographic data. Our cyberinfrastructure contains (i) the McGill-Harvard-Yenching Library Ming Qing Women's Writings database (MQWW), the only online database on historical Chinese women's writings, (ii) the China Biographical Database, the authority for Chinese historical people, and (iii) the China Historical Geographical Information System, one of the first historical geographic information systems. Key to this integration is that linked databases retain separate identities as bases of knowledge, while they possess sufficient semantic interoperability to allow for multidatabase concepts and to support cross-database queries on an ad hoc basis. Computational ontologies create underlying semantics for database access. This paper focuses on the spatial component in a humanities cyberinfrastructure, which includes issues of conflicting data, heterogeneous data models, disambiguation, and geographic scale. First, we describe the methodology for integrating the databases. Then we detail the system architecture, which includes a tier of ontologies and schema. We describe the user interface and applications that allow for cross-database queries. For instance, users should be able to analyze the data, examine hypotheses on spatial and temporal relationships, and generate historical maps with datasets from MQWW for research, teaching, and publication on Chinese women writers, their familial relations, publishing venues, and the literary and social communities. Last, we discuss the social side of cyberinfrastructure development, as people are considered to be as critical as the technical components for its success.

Spatial distribution and extent of urban land cover control watershed-scale chloride retention.

In some cold regions up to 97% of the chloride (Cl-) entering rivers and lakes is derived from road salts that are applied to impervious surfaces to maintain safe winter travel conditions. While a portion of the Cl- applied as road salt is quickly flushed into streams during melt events via overland flow and flow through storm sewer pipes, the remainder enters the subsurface. Previous studies of individual watersheds have shown that between 28 and 77% of the applied Cl- is retained on an annual basis, however a systematic evaluation of the spatial variability in Cl- retention and potential driving factors has not been carried out. Here we used a mass balance approach to estimate annual Cl- retention in 11 watersheds located in southern Ontario, Canada, which span a gradient of urbanization. We evaluated the influence of multiple landscape variables on the magnitude of Cl- retention as well as the long-term rate of change in stream Cl-concentration for the same systems. We found that mean annual Cl- retention ranged from 40 to 90% and was higher for less urbanized watersheds and for watersheds with urban areas located farther from the stream outlet. This result suggests that less urbanized watersheds and ones with longer flow pathways have more Cl- partitioned into storage and hence the potential for legacy Cl- effects on aquatic organisms. While we did measure statistically significant increasing trends in stream Cl- concentration in some watersheds, there was no consistent relationship between the long-term rate of change in stream Cl- concentrations and patterns of urbanization and the magnitude of Cl- retention. Based on our results we present a detailed conceptual model of watershed Cl- dynamics that can be used to guide future research into the mechanisms of Cl- retention and release within a watershed.

Increased nutrient concentrations in Lake Erie tributaries influenced by greenhouse agriculture.

Greenhouse production of vegetables is a growing global trade. While greenhouses are typically captured under regulations aimed at farmland, they may also function as a point source of effluent. In this study, the cumulative impacts greenhouse effluents have on riverine macronutrient and trace metal concentrations were examined. Water samples were collected Bi-weekly for five years from 14 rivers in agriculturally dominated watersheds in southwestern Ontario. Nine of the watersheds contained greenhouses with their boundaries. Greenhouse influenced rivers had significantly higher concentrations of macronutrients (nitrogen, phosphorus, and potassium) and trace metals (copper, molybdenum, and zinc). Concentrations within greenhouse influenced rivers appeared to decrease over the 5-year study while concentrations within non-greenhouse influenced river remained constant. The different temporal pattern between river types was attributed to increased precipitation during the study period. Increases in precipitation diluted concentrations in greenhouse influenced rivers; however, non-influenced river runoff proportionally increased nutrient mobility and flow, stabilizing the observed concentrations of non-point sources. Understanding the dynamic nature of environmental releases of point and non-point sources of nutrients and trace metals in mixed agricultural systems using riverine water chemistry is complicated by changes in climatic conditions, highlighting the need for long-term monitoring of nutrients, river flows and weather data in assessing these agricultural sectors.

Representing a large region with few sites: The Quality Index approach for field studies.

Many environmental studies require the characterization of a large geographical region using a range of representative sites amenable to intensive study. A systematic approach to selecting study areas can help ensure that an adequate range of the variables of interest is captured. We present a novel method of selecting study sites representing a larger region, in which the region is divided into subregions, which are characterized with relevant independent variables, and displayed in mathematical variable space. Potential study sites are also displayed this way, and selected to cover the range in variables present in the region. The coverage of sites is assessed with the Quality Index, which compares the range and standard deviation of variables among the sites to that of the larger region, and prioritizes sites that are well-distributed (i.e. not clumped) in variable space. We illustrate the method with a case study examining relationships between agricultural land use, physiography and stream phosphorus (P) export, in which we selected several variables representing agricultural P inputs and landscape susceptibility to P loss. A geographic area of 110,000km2 was represented with 11 study sites with good coverage of four variables representing agricultural P inputs and transport mechanisms taken from commonly-available geospatial datasets. We use a genetic algorithm to select 11 sites with the highest possible QI and compare these, post-hoc, to our sites. This approach reduces subjectivity in site selection, considers practical constraints and easily allows for site reselection if necessary. This site selection approach can easily be adapted to different landscapes and study goals, as we provide an algorithm and computer code to reproduce our approach elsewhere.

A Bayesian approach of high impaired river reaches identification and total nitrogen load estimation in a sparsely monitored basin.

In this study, a modeling framework based on the theory of SPAtially Referenced Regression On Watershed attributes (SPARROW) model was developed to identify impaired river reaches with respect to total nitrogen (TN) and estimate the TN sources in the Xin'anjiang River basin, which had limited monitoring sites. A Bayesian approach was applied to estimate the mean values and uncertainties of parameters, including land use export coefficients and in-stream attention rates. Based on the parameters, the midranges (25-75 %) of annual TN concentrations were assessed by the model and 4.5 % of river reaches in the basin were found to be with higher impaired probabilities (namely [TN] > 1.5 mg/l) than other reaches. The amount and yields of TN discharged from diffuse sources were estimated for each county in the basin. The results suggested that Tunxi City had the highest TN yields from farm land and population, while the highest TN yields in Huangshan City were from tea plantations. The outcomes of this study will guide the implementation of practical management measures to reduce TN loads.

Estimation of nutrient sources and transport using Spatially Referenced Regressions on Watershed Attributes: a case study in Songhuajiang River Basin, China.

We report here the first application of the Spatially Referenced Regressions on Watershed Attributes (SPARROW) model to China, a country naturally and culturally distinct from previous SPARROW applications. The Songhuajiang River Basin (556,700 km(2)) empties into the Tongjiang monitoring section, a shared water resource of great import for both Chinese and Russian citizens. The model was calibrated to annual loads of total nitrogen (TN) at 102 sites and total phosphorus (TP) at 65 sites. We assessed the rates of delivery and loss of nutrients from diffuse sources and also provided reach-level predictions of the percentage of nutrient loads delivered from upstream subbasins to Tongjiang monitoring section. The results indicated that farmland and pasture land were responsible for about 70 % of nutrient inputs to the Tongjiang monitoring section. Point source inputs were not statistically significant sources of TN or TP. We presented evidence that rice paddies delivered less TN to streams per area than other types of cropland. The locations responsible for the highest TN and TP inputs to the Tongjiang monitoring section tended to be located near the mainstream, though the areas of highest TN delivered yield did not correspond to the areas of highest TP delivered yield. This suggests that different management priorities may be needed in different parts of the Songhuajiang River Basin.

Regional scale selenium loading associated with surface coal mining, Elk Valley, British Columbia, Canada.

Selenium (Se) concentrations in surface water downstream of surface mining operations have been reported at levels in excess of water quality guidelines for the protection of wildlife. Previous research in surface mining environments has focused on downstream water quality impacts, yet little is known about the fundamental controls on Se loading. This study investigated the relationship between mining practices, stream flows and Se concentrations using a SPAtially Referenced Regression On Watershed attributes (SPARROW) model. This work is part of a R&D program examining the influence of surface coal mining on hydrological and water quality responses in the Elk Valley, British Columbia, Canada, aimed at informing effective management responses. Results indicate that waste rock volume, a product of mining activity, accounted for roughly 80% of the Se load from the Elk Valley, while background sources accounted for roughly 13%. Wet years were characterized by more than twice the Se load of dry years. A number of variables regarding placement of waste rock within the catchments, length of buried streams, and the construction of rock drains did not significantly influence the Se load. The age of the waste rock, the proportion of waste rock surface reclaimed, and the ratio of waste rock pile side area to top area all varied inversely with the Se load from watersheds containing waste rock. These results suggest operational practices that are likely to reduce the release of Se to surface waters.