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Introduction Hydrologic modeling at daily or sub daily resolution requires accurate precipitation and temperature data, which is particularly important when planning land use changes and live management operations such as irrigation allocation. Weather gage data pose a variety of challenges, including the fact that they are nonexistent in many watersheds of interest. We show that by integrating global forecast products and reanalysis datasets from the atmospheric modeling community into the hydrologic models commonly used, we can circumvent some of the issues with point-of-measure weather gauges. Traditionally in hydrologic forecasting, a precipitation forecast is used from a nearby precipitation station on which the hydrologic model has been calibrated. Here we present the results of two studies. First, we compare calibrating a watershed model (SWAT) using weather forecasts from ensembles of raw gridded atmospheric models interpolated to the center of subbasins against using the closest weather gage measurements. Second, we perform a similar study using global reanalysis datasets. In addition, we look at what scales and radii using direct gridded model output may introduce equal or less error to watershed modeling projects than using the closest station. We demostrate: -There is validity to using reanalysis datasets in place of weather station data to force hydrologic modeling systems when nearby weather stations are not available or have inconsistent records -There is validity to using short term forecast archives in place of weather station data to force hydrologic modeling systems. -The distance to the where the model skill produces the same accuracy as the weather stations is closer than we thought. -Variables from the atmospheric models are physically linked, and we should likely keep them that way. Conclusion This study found that weather forecast archives and CFSR reanalysis data provide a potentially valuable alternative to “nearest weather station” data for hydrological modelers. Indeed, this study found that the CFSR data may actually be a better representation of the weather than point observations, at the scale of small watersheds (Presented Nov. 2011. Third International Forum on Water and Food (IFWF3). Tshwane, South Africa http://waterandfood.org/2012/04/22/third-international-forum-on-water-and-food/

Introduction Hydrologic modeling at daily or sub daily resolution requires accurate precipitation data, which is particularly important when assessing flood risk in small runoff dominated watersheds. Precipitation gage data pose a variety of challenges, including the fact that they are located outside of many watersheds of interest and thus, may not accurately represent the actual rainfall in the watershed. We show that by integrating global forecast products from the atmospheric modeling community into the hydrologic models commonly used that we can circumvent some of the issues with point-of-measure rain gauges. Traditionally in hydrologic forecasting, a precipitation forecast is used from a nearby precipitation station on which the hydrologic model has been calibrated. In this study, we compare and contrast calibrating a watershed model (SWAT) using derived statistical representations of precipitation forecasts from "poorman's" ensembles of raw gridded atmospheric models interpolated to the center of subbasins vs using the closest precipitation gage measurement and NWS forecasts for that gage location. In addition, we look at what scales and radii using direct gridded model output may introduce equal or less error to watershed modeling projects than using the closest station. Discussion -It appears there is validity to using short term forecast archives in place of weather station data to force watershed models. -The distance to the where the model skill produces the same accuracy as the weather stations is closer than we thought. -We need to further investigate the watershed calibrations independent for individual forcing data sets. -We need to be careful when applying this method, and should use statistical summaries of the ensembles sparingly. -Variables from the atmospheric models are physically linked, and we should likely keep them that way. Presented NOAA NWS Eastern Region Flash Flood Conference, 2-4 June 2010, Wilkes-Barre, PA.

Predicting runoff producing areas and their corresponding risks of generating storm runoff is important for developing watershed management strategies to mitigate non-point source pollution. However, few methods for making these predictions have been proposed, especially operational approaches that would be useful in areas where variable source area (VSA) hydrology dominates storm runoff. The objective of this study is to develop a simple approach to estimate spatially-distributed risks of runoff production. By considering the development of overland flow as a bivariate process, we incorporated both rainfall and antecedent soil moisture conditions into a method for predicting VSAs based on the Natural Resource Conservation Service-Curve Number equation. We used base-flow immediately preceding storm events as an index of antecedent soil wetness status. Using nine sub-basins of the Upper Susquehanna River Basin, we demonstrated that our estimated runoff volumes and extent of VSAs agreed with observations. We further demonstrated a method for mapping these areas in a Geographic Information System using a Soil Topographic Index. The proposed methodology provides a new tool for watershed planners for quantifying runoff risks across watersheds, which can be used to target water quality protection strategies.

In the northeastern United States (U.S.), watersheds and ecosystems are impacted by nonpoint source pollution (NPS) from agricultural activity. Where agricultural fields coincide with runoff-producing areas-so called hydrologically sensitive areas (HSA)-there is a potential risk of NPS contaminant transport to streams during rainfall events. Although improvements have been made, water management practices implemented to reduce NPS pollution generally do not account for the highly variable, spatiotemporal dynamics of HSAs and the associated dynamics in NPS pollution risks. This paper presents a prototype for a web-based HSA prediction tool developed for the Salmon Creek watershed in upstate New York to assist producers and planners in quickly identifying areas at high risk of generating storm runoff. These predictions can be used to prioritize potentially polluting activities to parts of the landscape with low risks of generating storm runoff. The tool uses real-time measured data and 24-48 h weather forecasts so that locations and the timing of storm runoff generation are accurately predicted based o present-day and future moisture conditions. Analysis of HSA predictions in Salmon Creek show that 71% of the largest storm events between 2006 and 2009 were correctly predicted based on 48 h forecasted weather data. Real-time forecast of HSAs represents an important paradigm shift for the management of NPS in the northeastern U.S. © 2013 by the authors.

The herbicide atrazine is used extensively throughout the United States, and is a widespread groundwater and surface water contaminant. Biochar has been shown to strongly sorb organic compounds and could be used to reduce atrazine leaching. We used lab and field experiments to determine biochar impacts on atrazine leaching under increasingly heterogeneous soil conditions. Application of pine chip biochar (commercially pyrolyzed between 300 and 550 °C) reduced cumulative atrazine leaching by 52% in homogenized (packed) soil columns ( p = 0.0298). Biochar additions in undisturbed soil columns did not significantly ( p > 0.05) reduce atrazine leaching. Mean peak groundwater atrazine concentrations were 53% lower in a field experiment after additions of 10 t ha −1 acidified biochar ( p = 0.0056) relative to no biochar additions. Equivalent peat applications by dry mass had no effect on atrazine leaching. Plots receiving a peat-biochar mixture showed no reduction, suggesting that the peat organic matter may compete with atrazine for biochar sorption sites. Several individual measurement values outside the 99% confidence interval in perched groundwater concentrations indicate that macropore structure could contribute to rare, large leaching events that are not effectively reduced by biochar. We conclude that biochar application has the potential to decrease peak atrazine leaching, but heterogeneous soil conditions, especially preferential flow paths, may reduce this impact. Long-term atrazine leaching reductions are also uncertain.

The contribution of runoff from various land uses to stream channels in a watershed is often speculated and used to underpin many model predictions. However, these contributions, often based on little or no measurements in the watershed, fail to appropriately consider the influence of the hydrologic location of a particular landscape unit in relation to the stream network. A simple model was developed to predict storm runoff and the phosphorus (P) status of a perennial stream in an urban watershed in New York State using the covariance structure of runoff from different landscape units in the watershed to predict runoff in time. One hundred and twenty-seven storm events were divided into parameterization (n = 85) and forecasting (n = 42) data sets. Runoff, dissolved P (DP), and total P (TP) were measured at nine sites distributed among three land uses (high maintenance, unmaintained, wooded), three positions in the watershed (near the outlet, midwatershed, upper watershed), and in the stream at the watershed outlet. The autocorrelation among runoff and P concentrations from the watershed landscape units (n = 9) and the covariance between measurements from the landscape units and measurements from the stream were calculated and used to predict the stream response. Models, validated using leave-one-out cross-validation and a forecasting method, were able to correctly capture temporal trends in streamflow and stream P chemistry (Nash-Sutcliffe efficiencies, 0.49-0.88). The analysis suggests that the covariance structure was consistent for all models, indicating that the physical processes governing runoff and P loss from these landscape units were stationary in time and that landscapes located in hydraulically active areas have a direct hydraulic link to the stream. This methodology provides insight into the impact of various urban landscape units on stream water quantity and quality.

[1] The Soil Conservation Service curve number (SCS-CN) method is widely used to predict storm runoff for hydraulic design purposes, such as sizing culverts and detention basins. As traditionally used, the probability of calculated runoff is equated to the probability of the causative rainfall event, an assumption that fails to account for the influence of variations in soil moisture on runoff generation. We propose a modification to the SCS-CN method that explicitly incorporates rainfall return periods and the frequency of different soil moisture states to quantify storm runoff risks. Soil moisture status is assumed to be correlated to stream base flow. Fundamentally, this approach treats runoff as the outcome of a bivariate process instead of dictating a 1:1 relationship between causative rainfall and resulting runoff volumes. Using data from the Fall Creek watershed in western New York and the headwaters of the French Broad River in the mountains of North Carolina, we show that our modified SCS-CN method improves frequency discharge predictions in medium-sized watersheds in the eastern United States in comparison to the traditional application of the method.

It is currently not clear how to quantifiably relate pore-scale observations of colloid transportto larger scales, so,we proposed a geometric theory showing that pore-scale-derived rate constants may be appropriate to model a larger scale system. This study considered three different types of colloids: latex microspheres, Escherichia coli, and microspheres made of poly lactic acid (PLA). Colloid attachment and detachment rate constants were calculated using digital microscope images, taken in rapid (1 s) sequences, from which rates of attaching and detaching colloids were readily observed. Average rate constants from >1000 images per colloid-type were used to model Darcy-scale colloid transport breakthrough curves. The modeled and observed breakthrough curves agreed well for all three types of colloids. However, for latex and PLA microspheres, the model systematically under predicted the breakthrough curves' rising limb, which may indicate that the rate "constants" are actually dependent on the amount of attached colloids. Insights into these sorts of complexities are best addressed by research that considers both pore-scale phenomena and larger-scale transport responses.

[1] A reduction in surface water quality in urban watersheds due to nonpoint source phosphorus (P) loading has prompted municipalities to consider management practices to reduce P loss from landscapes. However, locating P source areas can be time consuming and expensive. Use of distributed models allows delineation of P source areas and focused management strategies. Using the spatially distributed soil moisture distribution and routing model, we adapt and validate a dissolved P (DP) loading model for application to an urban watershed, in Ithaca, New York, to identify P source areas. The model calculates DP loss separately for base flow, impervious surfaces, plant-soil complex, and fertilized areas. The load at the outlet is the sum of P loss from the four components distributed throughout the watershed. Both stream and distributed DP loss were well predicted as indicated by comparison with measured data. The model predicted the largest contribution from plant-soil complexes (36%). Impervious surfaces contributed 10% of the total load but as much as 17% in the winter. More important, the impervious surfaces increased DP losses from the adjacent areas due to runoff from the impervious surfaces saturating the soil, thus increasing runoff losses. Fertilizer contributed substantially following application but decreased rapidly thereafter, a result of conversion from soluble to insoluble P. However, fertilization increased soil P levels, and thus DP losses were higher as a whole (19%). Results demonstrate that correctly predicting the coincidence of P and runoff source areas can be a powerful tool to identify and mitigate contamination of surface waters.

Received 30 March 2006; revised 15 September 2006; accepted 10 October 2006; published 10 March 2007. [1] Effective control of nonpoint source contaminants in runoff from urbanized watersheds requires knowledge about the locations of runoff source areas under a variety of conditions. Physical monitoring of spatially variant processes, such as runoff production form variable source areas, is time-consuming and expensive. Thus modeling the processes may provide a valuable cost-effective alternative. In this paper we adapt and validate a variable source model for an urban watershed to predict areas of the landscape prone to elevated soil moisture levels and saturation excess runoff. We modified the soil moisture distribution and routing (SMDR) model to simulate hydrologic processes in an urban upstate New York watershed by considering the impact of impervious surfaces, hydraulic control structures (detention basins), and land use on the water balance. In our model, infiltration excess runoff from impervious surfaces infiltrates in the surrounding soils. Simulated and observed streamflow agreed well, and more importantly, the distribution of soil moisture levels and overland flow throughout the watershed were well predicted. Removing urban features from the model resulted in substantially lower peak stormflows than observed, and the base and interflows increased accordingly. Both modeled and measured distributed results indicated that the more urbanized areas of the study site had both higher soil moistures and runoff losses due to shallower soils, greater upslope contributing areas, and a larger area of impervious surfaces generating runoff. The model results helped identify processes that describe how urbanization impacts integrated and distributed hydrology, which provides useful information for targeted water quality management.

The biotic cycling of potassium (K) in forest systems has been relatively understudied in comparison with nitrogen (N) and phosphorus (P) despite its critical roles in maintaining the nutrition of primary production in forests. We investigated the ecological significance of K in forests from a literature review and data synthesis. We focused on (1) describing patterns of the effects of K availability on aboveground growth and change in foliar tissue of tree species from a variety of forests; and (2) documenting previously unreported relationships between hydrologic losses of K and N in forested watersheds from the Americas. In a review of studies examining tree growth under K manipulations/fertilizations, a high percentage (69% of studies) showed a positive response to increases in K availability in forest soils. In addition, 76% of the tree studies reviewed showed a positive and significant increase in K concentrations in plant tissue after soil K manipulation/fertilization. A meta-analysis on a subset of the reviewed studies was found to provide further evidence that potassium effects tree growth and increased tissue [K] with an effect size of 0.709 for growth and an overall effect size of 0.56. In our review of watershed studies, we observed that concentrations of K typically decreased during growing seasons in streams draining forested areas in the Temperate Zones and were responsive to vegetation disturbance in both temperate and tropical regions. We found a strong relationship (r2 = 0.42-0.99) between concentrations of K and N (another critical plant nutrient) in stream water, suggesting that similar mechanisms of biotic retention may control the flow of these nutrients. Furthermore, K dynamics appear to be unique among the base cations, e.g. calcium, magnesium, and sodium, because the others do not show similar seasonal patterns to K. We suggest that K may be important to the productivity and sustenance of many forests, and its dynamics and ecological significance warrant further study. We suggest that knowledge about the dynamics of this understudied element is imperative for our understanding patterns and processes in forest ecosystems.

the two kinetic equations are the maximum amount of water-extractable phosphorus (WEP) and a characteristic desorption time. Water- nure for total loss per rainfall event. Predicting the timing extractable P can be measured directly but currently the characteristic duringthestormis,however,neededwhentheinfiltration time can only be obtained by fitting experimental data. In addition, rate during the storm varies and part of the released P we evaluated two models usually used to estimate P loss from soil, from the manure enters the soil (Steenhuis et al., 1981). the Elovitch equation and power function, both of which relate P loss Moreover, regression-based models do not give insight to time. The models were tested against previously published data of into the processes and may fail for situations outside P release from different manures under laboratory conditions. All the range for which they were tested. equations fit the data well. Of the two kinetic equations, the second- Thus, our objective was to develop and evaluate relaorder model showed better agreement with the data than the first- tively simple, mechanistically defensible mathematical order model; for example, maximum relative differences between the expressions to predict the release of P from manure in model results and measured data were 2.6 and 4.7%, respectively. rain or other leaching waters. This paper presents four The characteristic times varied between 20 min for dairy manure and analytical models that predict the release of dissolved almost 100 min for poultry manure. The characteristic time did not P from manure with time. We used previously published appear to change with flow rate but decreased with smaller manure laboratorydatabySharpleyandMoyer(2000)totestthe aggregates. The parameters for power-function relationships could models’ ability to predict total dissolved phosphorus not be related to measured manure characteristics. These results pro(TDP) release from a variety of manure types. Total disvide the first step to process-based approximations for predicting solved P is defined as the total P after filtration through P release from manure with time during rainfall shortly after land application, when P losses are the greatest. 0.45-m filter (Haygarth and Sharpley, 2000). Experimentsby Muck(1978) wereemployed tofurther explain the dissolved P loss.

Researchers have noted that current water quality protection strategies, like nutrient management plans, lack a sound hydrological underpinning for pollutant transport processes. This is especially true for areas like the northeastern U.S. where copious research has shown that variable source area hydrology largely governs runoff generation. The goal of this study was to develop a scientifically justified method to identify the locations that generate overland flow. Furthermore, this methodology must be computationally simple enough that it can be utilized or incorporated into nutrient management plans and other established water quality tools. We specifically tested the reliability of the ‘distance from a stream,’ Ds, and the ‘topographic index,’ l, to predict areas with a high propensity for generating overland flow, i.e. hydrologically sensitive areas (HSA). HSAs were defined by their probability of generating runoff, Psat, based on 30 year simulations using a physically based hydrological model. Using GIS, each location’s Psat was correlated with Ds and l. We used three Delaware Co., NY watersheds in the New York City watershed system with areas varying in size from 1.6 to 37 km 2 and with forested and agricultural land uses. The topographic index gave stronger, more regionally consistent correlations with Psat than did Ds. Equations correlating l and Psat for each month are presented and can be used to estimate hydrological sensitivity in the region surrounding our study watersheds, i.e. in Delaware Co. This work is currently being incorporated into an Internet Mapping System to facilitate user-friendly, on-line identification of HSAs. q 2005 Elsevier Ltd. All rights reserved.

In the Arctic and Subarctic, the contribution of Indigenous knowledge to understanding environmental change has been established over the last several decades. This paper explores the role of Indigenous knowledge of water in understanding hydrologic change within complex social-ecological systems. Observations of hydrology in the Yukon River Basin, contributed by 20 community experts from Ruby Village, Alaska, in semi-structured interviews, are compared with findings from scientific literature to illustrate the commonalities and differences. Research findings reveal the contribution of Indigenous knowledge to understandings of hydrologic change in the Yukon River and its tributaries, which includes insights regarding alterations in sediment and river ice regimes. Recommendations for future research that incorporates Indigenous knowledge of water to gain insight into hydrologic changes in the watershed include combining multiple case studies that are distributed geographically. Our findings suggest 1) that using participatory research approaches to research will help ensure that it benefits the communities whose livelihoods are affected by hydrologic changes, and 2) that a multidisciplinary approach that combines qualitative and quantitative methods from the social and biophysical sciences would be most effective to help us understand and respond to hydrologic changes.

Phosphorus (P) risk assessment tools are being developed for New York to address the environmental concerns of P loss to surface waters from the application and accumulation of P nutrients. A qualitative risk-based assessment tool has been developed to assist nutrient management planners and farmers in identifying land areas that may be most vulnerable to P losses. A relatively rapid assessment of a few soil, transport, and nutrient application management factors are used to prioritize field sites into one-of-four relative risk categories. No additional application of manure or inorganic sources of P are recommended on the sites identified as very high risk. The factors evaluated in the qualitative risk assessment tool are discussed in detail, along with discussion regarding the utility of this methodology. A quantitative-based model assessment tool is also currently under development. The quantitative modeling tool should help estimate P loadings from a site based on several spatial soil and transport characteristics. Nutrient management decisions incorporated into this tool may then be more effectively evaluated. The GIS-based quantitative assessment tool should further improve the identification of critical areas of P loss.

Organizing complex information in the form of a map is a powerful and effective way of communication.This is especially true when linking spatially distributed scientific information to [real-world] applications. However, creating an intuitive and easy-touse interface between the user and the data requires a large amount of development time for user feedback and programming. To reduce this development time, it is now possible to couple spatial data with the increasingly popular Google Earth software (http://earth.google.com) package (Figure 1). (The products mentioned in this work do not indicate an endorsement by the authors. Additionally, the authors have no affiliation with the GoogleTM company) This free-to-use package allows users to avoid the costs associated with other high-end geographical information systems (GIS). While other free Internet GIS packages exist, including NASA's World Wind (http://worldwind.arc.nasa.gov) and Microsoft's Virtual Earth (http://local.live.com), one significant advantage of Google Earth is the use of Keyhole Markup Language (KML) for managing three-dimensional geospatial data. KML is an XML-based markup language that can be used to import and overlay user-defined data (vector or image form) and control views and zooming.