Climate and streamflow characteristics for selected streamgages in eastern South Dakota, water years 1945–2013

Hoogestraat, Galen K.; Stamm, John F.

doi:10.3133/sir20155146

Cited by 14 publications

(28 citation statements)

References 16 publications

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“…[2015a] observations match recent USGS findings of increased antecedent soil wetness conditions (increasing well levels) in eastern South Dakota [Hoogestraat and Stamm, 2015]. 3.…”

Section: Influence Of Precipitation On Streamflow Changessupporting

confidence: 78%

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Reply to comment by Keith E. Schilling on “Climate and agricultural land use change impacts on streamflow in the upper Midwestern United States”

Gupta

Kessler

Brown

et al. 2016

Water Resources Research

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“…[2015a] observations match recent USGS findings of increased antecedent soil wetness conditions (increasing well levels) in eastern South Dakota [Hoogestraat and Stamm, 2015]. 3.…”

Section: Influence Of Precipitation On Streamflow Changessupporting

confidence: 78%

“…Then, the question is: how did that affect ET from the landscape? For eastern South Dakota, Hoogestraat and Stamm [2015] mention that ''Although some agricultural land . .…”

Section: Effects Of Lulc Change On Base Flowmentioning

confidence: 99%

Reply to comment by Keith E. Schilling on “Climate and agricultural land use change impacts on streamflow in the upper Midwestern United States”

Gupta

Kessler

Brown

et al. 2016

Water Resources Research

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show abstract

“…By aggregating Q and P data over seasonal to annual timescales, any significant shifts in the slope and intercept of the Q-P relationship can be assumed to arise from the influence of other drivers, such as LULC or water management. Conversely, if one assumes a constant Q-P relationship at a given location, then the residuals can be used to investigate the factors characterizing the residual streamflow variability [44]. Simple process-based models based on the Budyko hypothesis [45] may also be used to evaluate the effects of aridity (P and evapotranspiration) and other drivers (e.g., effects of crop conversions, irrigation, reservoir storage and urbanization) [46,47]; or to apportion changes in water yield into climate and LULC drivers [25].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Drivers of Seasonal Streamflow in the U.S. Midwest

Slater

Villarini

2017

Water

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Streamflows have increased notably across the U.S. Midwest over the past century, fueling a debate on the relative influences of changes in precipitation and land cover on the flow distribution. Here, we propose a simple modeling framework to evaluate the main drivers of streamflow rates. Streamflow records from 290 long-term USGS stream gauges were modeled using five predictors: precipitation, antecedent wetness, temperature, agriculture, and population density. We evaluated which predictor combinations performed best for every site, season and streamflow quantile. The goodness-of-fit of our models is generally high and varies by season (higher in the spring and summer than in the fall and winter), by streamflow quantile (best for high flows in the spring and winter, best for low flows in the fall, and good for all flow quantiles in summer), and by region (better in the southeastern Midwest than in the northwestern Midwest). In terms of predictors, we find that precipitation variability is key for modeling high flows, while antecedent wetness is a crucial secondary driver for low and median flows. Temperature improves model fits considerably in areas and seasons with notable snowmelt or evapotranspiration. Finally, in agricultural and urban basins, harvested acreage and population density are important predictors of changing streamflow, and their influence varies seasonally. Thus, any projected changes in these drivers are likely to have notable effects on future streamflow distributions, with potential implications for basin water management, agriculture, and flood risk management.

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“…Several previous studies have shown reduced surface runoff from improved subsurface drainage across the U.S. Midwest [17,19,20], Canada [21,22], Germany [23], and the U.K. [24]. Similarly, recent studies [25][26][27] also reported altered hydrologic responses from agricultural watersheds with artificial subsurface drainage. A study based on eddy covariance tower installed over the fields with and without subsurface drainage in North Dakota (U.S.) reported an increase in ET by 16% and 7% during corn and soybean growing seasons, respectively [28].…”

Section: Introductionmentioning

confidence: 89%

Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model

et al. 2017

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Agricultural subsurface drainage changes the field hydrology and potentially the amount of water available to the crop by altering the flow path and the rate and timing of water removal. Evapotranspiration (ET) is normally among the largest components of the field water budget, and the changes in ET from the introduction of subsurface drainage are likely to have a greater influence on the overall water yield (surface runoff plus subsurface drainage) from subsurface drained (TD) fields compared to fields without subsurface drainage (UD). To test this hypothesis, we examined the impact of subsurface drainage on ET at two sites located in the Upper Midwest (North Dakota-Site 1 and South Dakota-Site 2) using the Landsat imagery-based METRIC (Mapping Evapotranspiration at high Resolution with Internalized Calibration) model. Site 1 was planted with corn (Zea mays L.) and soybean (Glycine max L.) during the 2009 and 2010 growing seasons, respectively. Site 2 was planted with corn for the 2013 growing season. During the corn growing seasons (2009 and 2013), differences between the total ET from TD and UD fields were less than 5 mm. For the soybean year (2010), ET from the UD field was 10% (53 mm) greater than that from the TD field. During the peak ET period from June to September for all study years, ET differences from TD and UD fields were within 15 mm (<3%). Overall, differences between daily ET from TD and UD fields were not statistically significant (p > 0.05) and showed no consistent relationship.

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Climate and streamflow characteristics for selected streamgages in eastern South Dakota, water years 1945–2013

Cited by 14 publications

References 16 publications

Reply to comment by Keith E. Schilling on “Climate and agricultural land use change impacts on streamflow in the upper Midwestern United States”

Reply to comment by Keith E. Schilling on “Climate and agricultural land use change impacts on streamflow in the upper Midwestern United States”

Evaluating the Drivers of Seasonal Streamflow in the U.S. Midwest

Estimating Impacts of Agricultural Subsurface Drainage on Evapotranspiration Using the Landsat Imagery-Based METRIC Model

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