Geology topics

David A. Saad

Publications and source records attributed to David A. Saad.

At least 19 recordsLinked to original sources

USGS2026

Seasonal estimates of nutrient loading, sources, and impacts on water availability in streams across the conterminous United States, 2000–2020

Excess riverine nutrients can limit water availability for humans and ecosystems. Nutrient monitoring on individual stream reaches provides important information about current and past conditions, yet most river reaches are unmonitored. Additionally, monitored data integrate effects of upstream sources, sinks, and pathways by which nutrients get into streams, making explicit planning for effective nutrient reduction strategies challenging. We developed and applied dynamic SPAtially Referenced Regression On Watershed attributes (SPARROW) models to quantify total nitrogen (TN) and total phosphorus (TP) delivery and source-specific loading in all stream reaches of the conterminous United States (CONUS) at a seasonal timestep from 2000 through 2020. Between one third and one half of non-point source nutrients lagged more than one season in their delivery to CONUS streams over the study period. The largest sources of nutrients that were applied and delivered to streams within a season were agricultural fertilizers, treated wastewater, atmospheric deposition, and manure. Increases in loads were widespread across the CONUS and predominantly associated with increased loading from lagged delivery of non-point source inputs and current season fertilizer application. Model results also identified extensive areas where predicted seasonal concentrations frequently exceeded the National Rivers and Streams Assessment “poor” criteria. Increased loading occurred in areas with high yields and delivery to downstream receiving waterbodies, particularly across the Midwest, raising the risk of negative impacts to downstream water availability. The modeling approach presented here provides a continental-scale framework for identifying when, where, and why nutrients are generated and how that may ultimately impact receiving waterbodies.

conterminous United States↗

USGS2026

Spatially referenced watershed models for the binational Red–Assiniboine River Basin: Bayesian vs frequentist comparison

Excess nutrient loading remains a leading cause of declining water quality in lakes, estuaries, and coastal waters worldwide, with global economic costs of US$200 billion – US$2 trillion annually from impacts on fisheries, tourism, freshwater resources, and water treatment. Our study focuses on total phosphorus (TP) in Lake Winnipeg and its binational Red-Assiniboine River Basin, where nutrient inputs have degraded water quality and increased cyanobacterial blooms. These changes pose ecological, public health, and economic risks. We applied a spatially referenced watershed model with a hybrid statistical-mechanistic structure partitioning annual nutrient loads into land-use export, land-to-water delivery, and in-reservoir decay. Bayesian and traditional frequentist model calibrations were compared. In the frequentist model, coefficients for agricultural inputs, forests /wetlands, stream channels, precipitation, and reservoir losses were statistically significant, whereas coefficient for wastewater was not. In contrast, all variables were successfully calibrated using the Bayesian approach. Model results delineate TP-export hotspots across the basin, showing that 54–62% of TP originates from the U.S., with agricultural sources ranging 62–72%—highlighting the importance of agriculture-focused Best Management Practices. Given the global relevance of nutrient-driven water-quality challenges, our results highlight Bayesian calibration for robust risk assessment and adaptive nutrient management.

Red–Assiniboine River Basin↗

USGS2025

How do hydrological variability and human activities control the spatiotemporal changes of riverine nitrogen export in the Upper Mississippi River Basin?

Excessive nitrogen export from agricultural watersheds remains a critical water quality challenge, with the Upper Mississippi River Basin (UMRB) significantly contributing to downstream eutrophication and hypoxia in the Gulf. This study investigates the spatiotemporal dynamics of riverine nitrate plus nitrite (NO 3 – + NO 2 – -N) export across the UMRB at high spatial resolution (12-digit Hydrologic Unit Codes or HUC12 subwatershed scale) during 2001–2020 and quantifies the effects of anthropogenic activities and hydrological variability on riverine NO 3 – + NO 2 – -N export changes in the region between 2001–2005 and 2016–2020. Our results revealed hotspots of substantial increases in NO 3 – + NO 2 – -N yields across the UMRB, with distinct regional patterns in driving factors. Over the entire UMRB, NO 3 – + NO 2 – -N yields increased by 9.7 kg/ha/yr on average from 2001–2005 to 2016–2020, with anthropogenic activities contributing 4.8 kg/ha/yr and hydrological variability contributing 4.9 kg/ha/yr. The northern and western UMRB had combined influences from both anthropogenic activities and hydrological variability, while the east-central regions had predominantly hydrologically driven changes. Agricultural sources, including fertilizer, manure, and biological nitrogen fixation, collectively contributed over 80% of NO 3 – + NO 2 – -N loading throughout the basin. This framework for disentangling human and hydrological impacts provides critical insights for developing effective and targeted watershed management strategies to reduce nutrient losses and improve water quality.

Upper Mississippi River Basin↗

USGS2024

Seasonally varying contributions of contemporaneous and lagged sources of instream total nitrogen and phosphorus load across the Illinois River basin

Quantifying nutrient sources in streams, their temporal and spatial variability, and drivers of that variability can support effective water resources management. Yet a lack of data and modeling capabilities has previously prevented comprehensive quantification across both space and time. Here a dynamic SPARROW (Spatially Referenced Regressions on Watershed attributes) model that accounts for a lagged delivery of nutrients to streams was developed and applied to simulate seasonal and source-specific total nitrogen (TN) and total phosphorus (TP) loads in streams across the Illinois River basin (IRB). Dynamic load predictions from 2000 through 2020 revealed that a third of the TN and a quarter of the TP instream load originated from non-point sources that were lagged in their delivery from land-application to streams by more than a season. This lagged mass was the largest overall TN source—which was estimated as a lagged expression of previous seasonal non-point sources including fertilizer, manure, atmospheric deposition and fixation, and urban land use. Treated wastewater effluent was the largest TP source exported from the basin, contributing 39 % of the TP load and 15 % of the TN load, and dominated the load in the upper Illinois River near Chicago. Loads in the lower river during this period, conversely, were attributed primarily to a mix of agricultural sources and their lagged fractions from headwater tributaries. Instream processes removed 10 % of the TN load while only 4 % of the TP load was removed during instream transport. With appropriate datasets, the models could be extended to other basins or time periods and used to forecast future seasonal nutrient loads.

Illinois↗

USGS2024

Evaluating the suitability of large-scale datasets to estimate nitrogen loads and yields across different spatial scales

Decision makers are often confronted with inadequate information to predict nutrient loads and yields in freshwater ecosystems at large spatial scales. We evaluate the potential of using data mapped at large spatial scales (regional to global) and often coarse resolution to predict nitrogen yields at varying smaller scales (e.g., at the catchment and stream reach level). We applied the SPAtially Referenced Regression On Watershed attributes (SPARROW) model in three regions: the Upper Midwest part of the United States, New Zealand, and the Grande River Basin in southeastern Brazil. For each region, we compared predictions of nitrogen delivery between models developed using novel large-scale datasets and those developed using local-scale datasets. Large-scale models tended to underperform the local-scale models in poorly monitored areas. Despite this, large-scale models are well suited to generate hypotheses about relative effects of different nutrient source categories (point and urban, agricultural, native vegetation) and to identify knowledge gaps across spatial scales when data are scarce. Regardless of the spatial resolution of the predictors used in the models, a representative network of water quality monitoring stations is key to improve the performance of large-scale models used to estimate loads and yields. We discuss avenues of research to understand how this large-scale modelling approach can improve decision making for managing catchments at local scales, particularly in data poor regions.

Water Research↗

USGS2022

Effects of return flows on stream water quality and availability in the Upper Colorado, Delaware, and Illinois River Basins

Understanding effects of human water use and subsequent return flows on the availability and suitability of water for downstream uses is critical to efficient and effective watershed management. We compared spatially detailed estimates of stream chemistry within three watersheds in diverse settings to available standards to isolate effects of wastewater and irrigation return flows on the suitability of downstream waters for maintaining healthy aquatic ecosystems and for selected human uses. Mean-annual flow-weighted total and source-specific concentrations of nitrogen and phosphorus in individual stream reaches within the Upper Colorado, Delaware, and Illinois River Basins and of total dissolved solids within stream reaches of the Upper Colorado River Basin were estimated from previously calibrated regional watershed models. Estimated concentrations of both nitrogen and phosphorus in most stream reaches in all three watersheds (at least 78%, by length) exceed recommended standards for the protection of aquatic ecosystems, although concentrations in relatively few streams exceed such standards due to contributions from wastewater return flows, alone. Consequently, efforts to reduce wastewater nutrient effluent may provide important local downstream benefits but would likely have minimal impact on regional ecological conditions. Similarly, estimated mean-annual flow-weighted total dissolved solids concentrations in the Upper Colorado River Basin exceed standards for agricultural water use and (or) the secondary maximum contaminant level (SMCL) for drinking water in 52% of streams (by length), but rarely due to effects of irrigation return flows, alone. Dissolved solids in most tributaries of the Upper Colorado River are attributable primarily to natural sources.

Upper Colorado, Delaware, and Illinois River Basin↗

USGS2022

Estimating urban air pollution contribution to South Platte River nitrogen loads with National Atmospheric Deposition Program data and SPARROW model

Air pollution is commonly disregarded as a source of nutrient loading to impaired surface waters managed under the Clean Water Act per states’ 303(d) list programs. The contribution of air pollution to 2017–2018 South Platte River nitrogen (N) loads was estimated from the headwaters to the gage at Weldona, Colorado, USA (100 km downstream of Denver), using data from the National Atmospheric Deposition Program (NADP) and the SPAtially Referenced Regressions On Watershed attributes (SPARROW) model. The NADP offers wet-deposition raster created by spatial interpolation of data collected from regionally representative monitoring sites, excluding the influences from urban site data. For this study, NADP wet-deposition data obtained from sites within the Denver-Boulder, Colorado, urban corridor were included and excluded in new spatial interpolations of wet-deposition raster, which were used as input for SPARROW to model the influence of urban air pollution sources on South Platte River loads. Because urban air pollution is already incorporated into the NADP Total Deposition modeling methodology, dry N deposition was held constant for each SPARROW modeling scenario when dry deposition was included. By including the urban wet-deposition data in the model, estimated N loading to the South Platte River at Denver increased by 9–11 percent. Factoring in dry deposition at a 1:1.8 dry:wet ratio obtained from the results, urban air pollution was estimated to contribute as much as 20 percent of the nitrate Total Maximum Daily Load for Segment 14 of the South Platte River.

Colorado↗

USGS2022

An extrapolation method for estimating loads from unmonitored areas using watershed model load ratios

It is important to routinely estimate loads from an entire watershed to describe current conditions and evaluate how watershed-wide management efforts have affected the nutrient and sediment export that affect downstream water quality. However, monitoring in most areas, including the Great Lakes watershed, consists of sampling at a limited number of sites that are only periodically used to estimate total watershed loading. Here, we describe a technique to extrapolate loads measured at a limited number of reference sites to the total load from a large watershed using load ratios between monitored sites and unmonitored areas obtained from a watershed model (i.e., model load ratio, MLR, approach). In this study, modeled nonpoint-source load ratios between monitored tributaries (reference sites) and nearby unmonitored areas and point-source delivery factors for all areas were obtained from a Spatially Referenced Regression On Watershed attributes (SPARROW) model and used to extrapolate the measured loads from an ongoing monitoring program (Great Lakes Restoration Initiative Tributary monitoring program) to the entire Great Lakes watershed. The MLR approach incorporates spatial variability in nonpoint- and point-source delivery, watershed characteristics, and hydrology that are often not considered when estimating loads from unmonitored areas, such as using the unit area load (UAL) extrapolation approach. The MLR approach provided smaller watershed loads than the UAL approach because yields from monitored sites, in general, were larger than from unmonitored areas. When both approaches were used to estimate loads at adjacent monitored sites, the MLR approach provided more accurate estimates than the UAL approach.

Great Lakes Basin↗

USGS2021

Quantifying regional effects of best management practices on nutrient losses from agricultural lands

Nitrogen (N) and phosphorus (P) losses from agricultural areas have degraded the water quality of downstream rivers, lakes, and oceans. As a result, investment in the adoption of agricultural best management practices (BMPs) has grown, but assessments of their effectiveness at large spatial scales have lagged. This study applies regional Spatially Referenced Regression On Watershed-attributes (SPARROW) models developed for the Midwest, Northeast, and Southeast United States to quantify potential regional effects of BMPs on nutrient losses from agricultural lands. These models were used because they account for specific BMPs in the prediction of instream nutrient loads. The BMPs included in the models were cover crops, no-till, and conservation tillage. Sensitivity testing for the BMPs on agricultural nutrient loads was done using simulations that varied the intensity of BMPs specified in each region. When the BMP intensity was increased 50% relative to the 2012 intensity, the predicted agricultural load of total P decreased across all regions (4% to 14%). The predicted reduction in average P yields in the Midwest, Northeast, and Southeast was 706, 544, and 26 kg km–2, respectively. Increasing BMPs by 50% decreased predicted agricultural total N loads by 3.5% in the Southeast but increased predicted N loads in the Midwest and Northeast by 4.7% and 1.8%, respectively. Model-predicted average N yields increased by 402 kg km–2 and 302 kg km–2 in the Midwest and Northeast, respectively, and decreased in the Southeast by 329 kg km–2. In model simulations, cover crops were more effective at reducing N and P loads than the tillage BMPs despite lower intensity of implementation in 2012. However, at the regional scale of this investigation, implementation of BMPs result in only moderate predicted effects on agricultural nutrient loads

Journal of Soil and Water Conservation↗

USGS2021

Nitrogen and phosphorus sources and delivery from the Mississippi/Atchafalaya River Basin: An update using 2012 SPARROW models

Nitrogen (N) and phosphorus (P) inputs throughout the Mississippi/Atchafalaya River Basin (MARB) have been linked to the Gulf of Mexico hypoxia and water‐quality problems throughout the MARB. To describe N and P loading throughout the MARB, SPAtially Referenced Regression On Watershed attributes (SPARROW) models were previously developed based on nutrient inputs and management similar to 1992 and 2002. In this study, refined SPARROW models were developed with higher resolution basin delineation, updated (2012) source inputs, improved calibration (load) targets, and additional statistical techniques than used in the previous SPARROW models. Based on the refined models, consistent with past models, N and P loads/yields were the highest from the central part of the MARB (Corn Belt) and along the Mississippi River. Agricultural activities remained the most important N and P source, but more so for N because its input, which could now be distinguished from atmospheric deposition, could be estimated. Natural loss of P from geologic material throughout the MARB was an important source, contributing about 23% of the total P from the MARB, and resulted in specific areas, such as Kentucky and Tennessee, being larger sources of P than previously estimated. This information can help managers decide where efforts will have the largest effects (highest ranked areas) on reducing nutrient loading to the Gulf hypoxia and what are the most important sources of N and P in these areas.

Mississippi/Atchafalaya River Basin↗

USGS2020

Spatially referenced models of streamflow and nitrogen, phosphorus, and suspended-sediment loads in streams of the midwestern United States

In this report, SPAtially Referenced Regression On Watershed attributes (SPARROW) models developed to describe long-term (2000–14) mean-annual streamflow, total nitrogen (TN), total phosphorus (TP), and suspended-sediment (SS) transport in streams of the Midwestern part of the United States (the Mississippi River, Great Lakes, and Red River of the North Basins) are described. The nutrient and suspended-sediment models have a base year of 2012, which means they were developed based on source inputs and management practices similar to those existing during or near 2012 and average hydrological conditions detrended to 2012 (2000–14), whereas the streamflow model has base years of 2000–14, which means it was developed based on the average input precipitation minus actual evapotranspiration from 2000 to 2014. In developing the models, several updates and improvements were made to the data inputs and statistical approaches used to calibrate/develop the models from those used in the previous 2002 SPARROW models. The 2012 SPARROW models were constructed using a higher resolution stream network, which resulted in a mean catchment size of 2.7 square kilometers compared to 480 square kilometers in the 2002 models; more detailed and updated wastewater treatment plant contribution estimates; inputs from background phosphorus sources that were not included in the 2002 model; and more accurate loads for calibration that were computed using a modified Beale ratio-estimator technique whenever no trend in load was determined. Statistical approaches were added to compensate for the unequal effect of each monitoring site during the calibration process by adjusting for the fraction of the basin included in other upstream monitored sites (nested share) and thinning the calibration sites if a negative statistical correlation between nearby sites was determined. Results from 2012 SPARROW models describe how much of each water, TN, TP, and SS source was delivered to the stream network, and the major landscape factors that affected their delivery. Atmospheric deposition and natural (background) sources of TN and TP, respectively, were the dominant sources in anthropogenically unaffected areas (especially in the Rocky Mountains and north-central areas of the Midwest), whereas fertilizers, manure, and fixation were dominant sources in agricultural areas, especially in the Corn Belt and near the Mississippi River. Urban sources of TN and TP were typically localized, but they were still important for some large areas, especially the Lake Erie Basin. All of the land-to-water delivery variables in the nutrient and sediment SPARROW models, such as runoff, soil erodibility, basin slope, and the amount of tile drains, are commonly included in process-driven models. In the SPARROW TN and TP models, best management practices (BMPs) reduced the delivery of these nutrients to streams. Long-term mean-annual flows and nutrient and sediment loads were simulated in streams throughout the Midwest. The simulated flows from the SPARROW flow model were used in the SPARROW TN, TP, and SS models to help describe nutrient and sediment transport from the watershed and through the stream network. Outputs from the TN, TP, and SS models describe loads and yields of these constituents throughout the Midwest, and from major drainage basins throughout the Midwest. Highest TN, TP, and SS yields and delivered yields were from the Lake Erie, Ohio River, Upper Mississippi River, and Lower Mississippi River Basins, whereas lowest yields were spread over most other areas. Losses during downstream delivery resulted in part of the TN, TP, and SS that reach the stream network not reaching the downstream receiving bodies: 14, 15, and 28 percent of the TN, TP, and SS, respectively, are lost during delivery to the Great Lakes and 19, 23, and 52 percent of the TN, TP, and SS, respectively, are lost during delivery to the Gulf of Mexico. The largest losses of nutrients and sediments during transport were in the Missouri and Arkansas River Basins. Information from these SPARROW models can help guide nutrient and sediment reduction strategies throughout the Midwest. Model results provide information on what may be the most appropriate general type of actions to reduce total loading by describing the relative importance of each source, and where to most efficiently place the efforts to reduce loading by describing the distribution of nutrient and sediment loading. By implementing management efforts addressing the major sources of the loads in areas contributing the highest loads, it may be possible to reduce nutrient loading throughout the Mississippi River Basin and thus reduce the size of the hypoxic zone in the Gulf of Mexico; reduce nutrient loading into lakes, and thus reduce the occurrence of harmful algal blooms; and reduce sediment losses, and thus improve the benthic habitat in streams and rivers throughout the Midwest.

Scientific Investigations Report↗

USGS2019

Phosphorus and nitrogen transport in the binational Great Lakes Basin estimated using SPARROW watershed models

Eutrophication problems in the Great Lakes are caused by excessive nutrient inputs (primarily phosphorus, P, and nitrogen, N) from various sources throughout its basin. In developing protection and restoration plans, it is important to know where and from what sources the nutrients originate. As part of a binational effort, Midcontinent SPARROW (SPAtially Referenced Regression On Watershed attributes) models were developed and used to estimate P and N loading from throughout the entire basin based on nutrient inputs similar to 2002; previous SPARROW models only estimated U.S. contributions. The new models have a higher resolution (~2‐km 2 catchments) enabling improved descriptions of where nutrients originate and the sources at various spatial scales. The models were developed using harmonized geospatial datasets describing the stream network, nutrient sources, and environmental characteristics affecting P and N delivery. The models were calibrated using loads from sites estimated with ratio estimator and regression techniques and additional statistical approaches to reduce spatial correlation in the residuals and have all monitoring sites equally influence model development. SPARROW results, along with interlake transfers and direct atmospheric inputs, were used to quantify the entire P and N input to each lake and describe the importance of each nutrient source. Model results can be used to compare loading and yields from various tributaries and jurisdictions.

Great Lakes↗

USGS2019

Estimates of long-term mean daily streamflow and annual nutrient and suspended-sediment loads considered for use in regional SPARROW models of the Conterminous United States, 2012 base year

Streamflow, nutrient, and sediment concentration data needed to estimate long-term mean daily streamflow and annual constituent loads were compiled from Federal, State, Tribal, and regional agencies, universities, and nongovernmental organizations. The streamflow and loads are used to develop Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models help describe the distribution, sources, and transport of streamflow, nutrients, and sediment in streams throughout five regions of the conterminous United States. After the data were screened, approximately 5,200 streamflow, 3,000 sediment, and 3,300 nutrient sites, sampled by 137 agencies and organizations were identified as having suitable data for calculating the long-term mean daily streamflow and annual nutrient and sediment loads required for SPARROW model estimation. These sites are representative of a wide range in terms of watershed size, contaminant source types, and land-use and other important watershed characteristics. The methods used to estimate long-term mean annual loads include the Beale ratio estimator and Fluxmaster regression method with Kalman smoothing.

Conterminous United States↗

USGS2018

Estimates of long-term mean-annual nutrient loads considered for use in SPARROW models of the Midcontinental region of Canada and the United States, 2002 base year

Streamflow and nutrient concentration data needed to compute nitrogen and phosphorus loads were compiled from Federal, State, Provincial, and local agency databases and also from selected university databases. The nitrogen and phosphorus loads are necessary inputs to Spatially Referenced Regressions on Watershed Attributes (SPARROW) models. SPARROW models are a way to estimate the distribution, sources, and transport of nutrients in streams throughout the Midcontinental region of Canada and the United States. After screening the data, approximately 1,500 sites sampled by 34 agencies were identified as having suitable data for calculating the long-term mean-annual nutrient loads required for SPARROW model calibration. These final sites represent a wide range in watershed sizes, types of nutrient sources, and land-use and watershed characteristics in the Midcontinental region of Canada and the United States.

Scientific Investigations Report↗

USGS2018

Geospatial data for developing nutrient SPARROW models for the Midcontinental region of Canada and the United States

Through the International Watersheds Initiative of the International Joint Commission (IJC), the SpatiallyReferenced Regressions on Watershed attributes (SPARROW) model developed by the U.S. Geological Survey (USGS) is being applied to the Great Lakes, Rainy River – Lake of the Woods and Red-Assiniboine basins. The objective of this binational application of the SPARROW model is to better understand and quantify the sources of phosphorus (P) and nitrogen (N) that contribute to regional water-quality issues like algal blooms and eutrophication in Lake Erie and other parts of the Great Lakes, as well as Lake of the Woods. Led by the IJC, a team of researchers from the National Research Council of Canada – Ocean, Coastal and River Engineering Research Centre, USGS, and IJC are extending the SPARROW modelling work previously completed for the Red-Assiniboine basin and the U.S. portions of the Great Lakes, Ohio, Upper Mississippi, and Souris-Red-Rainy river basins to cover all of the Great Lakes, Rainy River – Lake of the Woods and RedAssiniboine basins. The current effort is termed the Midcontinent SPARROW modelling study. This report describes the data used to develop the Midcontinent SPARROW models, specifically the sources of original data, assembling the data, and the processing and harmonization required between the U.S. and Canada data needed to produce these models. Details provided include the: development of a digital stream network and related catchments – most significantly in the Canadian regions of the Great Lakes and Rainy River – Lake of the Woods basins where these data were not available to create a seamless binational network across the model domain; calculation of variables to aid in the determination of in-stream and in-reservoir decay of P and N; quantification of Canadian diversions within the Midcontinental region (i.e., Lake St. Joseph, Long Lake and the Ogoki Reservoir); development of binational input nutrient sources considered for model development (i.e., land cover, inorganic farm fertilizer, manure, atmospheric deposition, point-source pollution from wastewatertreatment plants and contribution from non-modelled watersheds); and development of delivery variables considered to be most predominant (i.e., temperature, precipitation and ensuing runoff, soil permeability and clay content, slope of the catchments, and tile drainage). The majority of the geospatial data collection and processing was required for Canadian datasets because many of the U.S. datasets were already assembled for previous SPARROW model applications in the U.S. The task of harmonizing data between the U.S. and Canada was important to ensure consistency of the datasets used in the models. The harmonized digital stream network, delineated catchments and input data for each catchment (i.e., source and delivery variables), created for the Midcontinent SPARROW models, are available for download at url: https://doi.org/10.4224/300.0001.

Technical Report↗

USGS2016

Simulation of climate change effects on streamflow, groundwater, and stream temperature using GSFLOW and SNTEMP in the Black Earth Creek Watershed, Wisconsin

A groundwater/surface-water model was constructed and calibrated for the Black Earth Creek watershed in south-central Wisconsin. The model was then run to simulate scenarios representing common societal concerns in the basin, focusing on maintaining a cold-water resource in an urbanizing fringe near its upper stream reaches and minimizing downstream flooding. Although groundwater and surface water are considered a single resource, many hydrologic models simplistically simulate feedback loops between the groundwater system and other hydrologic processes. These feedbacks include timing and rates of evapotranspiration, surface runoff, soil-zone flow, and interactions with the groundwater system; however, computer models can now routinely and iteratively couple the surface-water and groundwater systems—albeit with longer model run times. In this study, preliminary calibrations of uncoupled transient surface-water and steady-state groundwater models were used to form the starting point for final calibration of one transient computer simulation that iteratively couples groundwater and surface water. The computer code GSFLOW (Groundwater/Surface-water FLOW) was used to simulate the coupled hydrologic system; a surface-water model represented hydrologic processes in the atmosphere, at land surface, and within the soil zone, and a groundwater-flow model represented the unsaturated zone, saturated zone, and streams. The coupled GSFLOW model was run on a daily time step during water years 1985–2007. Early simulation times (1985–2000) were used for spin-up to make the simulation results less sensitive to initial conditions specified; the spin-up period was not included in the model calibration. Model calibration used observed heads, streamflows, solar radiation, and snowpack measurements from 2000 to 2007 for history matching. Calibration was performed by using the PEST parameter estimation software suite. Simulated streamflows from the calibrated GSFLOW model and other basin characteristics were used as input to the one-dimensional SNTEMP (Stream-Network TEMPerature) model. SNTEMP was used to simulate daily stream temperature in selected stream reaches in the watershed. The temperature model was calibrated to high-resolution stream temperature time-series data measured in 2005. The calibrated GSFLOW and SNTEMP models were then used to simulate effects of potential climate change for the years 2010 through 2100. An ensemble of climate models and emission scenarios was evaluated. Downscaled climate drivers for the simulation period showed increases in maximum and minimum air temperature. Scenarios of future precipitation, however, did not show a monotonic trend like temperature. Uncertainty in the climate drivers increased with time for both temperature and precipitation. Forecasts of potential climate change scenarios showed growing season length increasing by weeks, and both potential and actual evapotranspiration rates increasing appreciably, in response to increasing air temperature. Simulated actual evapotranspiration rates increased less than simulated potential evapotranspiration rates as a result of water limitation in the root zone during the summer high-evapotranspiration period. The hydrologic-system response to climate change was characterized by a reduction in the importance of the snowmelt pulse and an increase in the importance of fall and winter groundwater recharge. The less dynamic hydrologic regime is likely to result in drier soil conditions, with relatively less drying expected in groundwater-fed systems. Groundwater discharge in the current upper cold-water reaches of Black Earth Creek is expected to decrease; flooding in downstream reaches may appreciably increase. The magnitude of changes in forecasted flow and associated groundwater/surface-water interaction is dependent on the General Circulation Model and emission scenario chosen. Potential future changes in air temperature drivers were consistently upward regardless of General Circulation Model and emission scenario selected; thus, simulated stream temperatures are forecast to increase appreciably with future climate. However, the amount of temperature increase was variable. Such uncertainty is reflected in temperature model results, along with uncertainty in the groundwater/surface-water interaction itself. The estimated increase in annual average temperature ranged from approximately 3 to 6 degrees Celsius by 2100 in the upper reaches of Black Earth Creek and 2 to 4 degrees Celsius in reaches farther downstream. As with all forecasts that rely on projections of an unknowable future, the results are best considered to approximate potential outcomes of climate change given the underlying uncertainty.

Wisconsin↗

USGS2016

Nutrient delivery to Lake Winnipeg from the Red-Assiniboine River Basin – A binational application of the SPARROW model

Excessive phosphorus (TP) and nitrogen (TN) inputs from the Red–Assiniboine River Basin (RARB) have been linked to eutrophication of Lake Winnipeg; therefore, it is important for the management of water resources to understand where and from what sources these nutrients originate. The RARB straddles the Canada–United States border and includes portions of two provinces and three states. This study represents the first binationally focused application of SPAtially Referenced Regressions on Watershed attributes (SPARROW) models to estimate loads and sources of TP and TN by jurisdiction and basin at multiple spatial scales. Major hurdles overcome to develop these models included: (1) harmonization of geospatial data sets, particularly construction of a contiguous stream network; and (2) use of novel calibration steps to accommodate limitations in spatial variability across the model extent and in the number of calibration sites. Using nutrient inputs for a 2002 base year, a RARB TP SPARROW model was calibrated that included inputs from agriculture, forests and wetlands, wastewater treatment plants (WWTPs) and stream channels, and a TN model was calibrated that included inputs from agriculture, WWTPs and atmospheric deposition. At the RARB outlet, downstream from Winnipeg, Manitoba, the majority of the delivered TP and TN came from the Red River Basin (90%), followed by the Upper Assiniboine River and Souris River basins. Agriculture was the single most important TP and TN source for each major basin, province and state. In general, stream channels (historically deposited nutrients and from bank erosion) were the second most important source of TP. Performance metrics for the RARB SPARROW model are similarly robust compared to other, larger US SPARROW models making it a potentially useful tool to address questions of where nutrients originate and their relative contributions to loads delivered to Lake Winnipeg.

Manitoba, Minnesota, Saskatchewan↗

USGS2016

Simulated impacts of climate change on phosphorus loading to Lake Michigan

Phosphorus (P) loading to the Great Lakes has caused various types of eutrophication problems. Future climatic changes may modify this loading because climatic models project changes in future meteorological conditions, especially for the key hydrologic driver — precipitation. Therefore, the goal of this study is to project how P loading may change from the range of projected climatic changes. To project the future response in P loading, the HydroSPARROW approach was developed that links results from two spatially explicit models, the SPAtially Referenced Regression on Watershed attributes (SPARROW) transport and fate watershed model and the water-quantity Precipitation Runoff Modeling System (PRMS). PRMS was used to project changes in streamflow throughout the Lake Michigan Basin using downscaled meteorological data from eight General Circulation Models (GCMs) subjected to three greenhouse gas emission scenarios. Downscaled GCMs project a + 2.1 to + 4.0 °C change in average-annual air temperature (+ 2.6 °C average) and a − 5.1% to + 16.7% change in total annual precipitation (+ 5.1% average) for this geographic area by the middle of this century (2045–2065) and larger changes by the end of the century. The climatic changes by mid-century are projected to result in a − 21.2% to + 8.9% change in total annual streamflow (− 1.8% average) and a − 29.6% to + 17.2% change in total annual P loading (− 3.1% average). Although the average projected changes in streamflow and P loading are relatively small for the entire basin, considerable variability exists spatially and among GCMs because of their variability in projected future precipitation.

Lake Michigan↗