Reply to comment by Foufoula‐Georgiou et al. on “Climate and agricultural land use change impacts on streamflow in the upper midwestern United States”

Gupta, Satish C.; Kessler, Andrew C.; Brown, Melinda K.; Schuh, W. M.

doi:10.1002/2016wr019003

Cited by 3 publications

(2 citation statements)

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“…The overall influence of agricultural land cover and of changing agricultural practices on streamflows across the Midwest has led to heated debates in recent years [20,[69][70][71][72][73][74][75][76]. In the Upper Mississippi River Basin, LULC has a clear signature on streamflow [77].…”

Section: Agriculturementioning

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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Section: Agriculturementioning

confidence: 99%

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

Slater

Villarini

2017

Water

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“…Foufoula-Georgiou et al (2015) compared daily hydrographs of the Redwood River in southwestern Minnesota for two similar precipitation years (1971 and 2002) and suggested that increased daily streamflow in 2002 was due to the presence of tile drainage and adoption of soybean in the landscape. However, Foufoula-Georgiou et al (2015) overlooked the role of stored soil water in comparing daily hydrographs between these two years (Gupta et al, 2016e). In further analysis of bi-monthly streamflows, Foufoula-Georgiou et al (2015) concluded that increased streamflow from May-June was primarily due to land use changes (adoption of soybean and tile drainage) because there was not much difference in May-June precipitation distributions before and after adoption of the above LULC changes.…”

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confidence: 99%

Increased Precipitation as the Main Driver of Increased Streamflow in Tile-Drained Watersheds of the Upper Midwestern U.S.

Gupta

Baeumler

Kessler

et al. 2018

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Abstract. Recent increased streamflow (Q) and its associated impacts on water quality have frequently been linked to land use and land cover (LULC) changes such as increased tile drainage, cultivation of prairies, and adoption of soybean () in modern-day cropping systems. However, many previous studies have assumed minimal to no change in precipitation during their study period. A recent analysis of streamflow records from 29 HUC 8 (Hydrologic Unit Code 008) watersheds in Iowa and Minnesota showed that increased precipitation instead of LULC change was the main driver of increased streamflow. The analysis was done through hierarchical regression of annual streamflow as a function of annual precipitation for the periods prior to 1975 (pre-change period) and after 1976 (post-change period). A statistical shift in annual relationship from the pre- to post-change period was assumed to be an indication of LULC changes, whereas a lack of statistical shift suggested no change in the relationship and higher flows were mainly driven by increased precipitation. In this article, we further show that annual streamflow and annual baseflow were influenced not only by the current year’s precipitation but also by precipitation in the preceding one to two years, and this effect was manifested through increased or decreased stored soil water. The present analysis was done using backward stepwise hierarchical regression with the natural log of annual streamflow as the predictor variable and three to five years of precipitation, the area under soybean production, a group variable simulating pre- and post-change periods, and its interaction terms with precipitation and soybean area as the explanatory variables. This analysis also showed that precipitation was the main driver of annual streamflow or baseflow; however, for some rivers, the area under soybean production and group differences were also significant variables, although at a much smaller confidence level. Annual streamflow testing was done for the Blue Earth River, Redwood River, Cottonwood River, and Whetstone River watersheds in Minnesota and the Maquoketa River and Raccoon River watersheds in Iowa. Annual baseflow testing was done only on the Redwood River and Raccoon River watersheds. Using similar backward stepwise regressions, the analysis showed that changes in Ln(monthly streamflow) were linked to stored soil water through the preceding months’ and years’ precipitation. On a daily scale, comparison of slopes of the hydrograph’s rising limb for two large precipitation events in 1957 (pre-change period) and 1993 (post-change period) showed less watershed connectivity due to LULC changes such as drainage, a finding that is contrary to what has been suggested in the literature. A similar comparison of the falling limb slopes for a given streamflow condition showed similar slope values in pre-change (1947) and post-change (1991) periods, thus suggesting no changes in storage capacity of the watershed as a result of LULC changes. Further comparisons of high-level streamflows (Q > 100 m3 s-1) as a function of average daily storm precipitation showed no effect of drainage between the pre- and post-change periods. A statistical analysis of the relationship between the falling limb slopes as a function of streamflow for low (dQ/dt < -5 m3 s-1 d-1) and medium (dQ/dt varying from -2 to -5 m3 s-1 d-1) slopes also showed no discernable change in the retentive capacity of the Redwood River watershed between the pre- and post-change periods. The above evaluations at three temporal scales further supported our previous conclusion that increased precipitation in recent years is the main driver of the increased streamflow in tile-drained watersheds of the upper Midwestern U.S., and the impacts of LULC change on streamflow characteristics were minimal. We conclude that any comparison of daily, monthly, or annual streamflow and baseflow to evaluate LULC change impacts must be done at comparable stored soil water conditions or with accounting of precipitation from previous days, months, and years. Keywords: Baseflow, Hydrograph, Land use land cover, Precipitation, Streamflow, Tile drainage.

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