Chapter 21 : Midwest. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II

Angel, James R.; Swanston, Chris; Boustead, Barbara Mayes; Conlon, Kathryn C.; Hall, Kimberly R.; Jorns, J. L.; Kunkel, Kenneth E.; Lemos, Maria Carmen; Lofgren, Brent M.; Ontl, Todd A.; Posey, John; Stone, Kevin; Takle, Gene; Todey, Dennis

doi:10.7930/nca4.2018.ch21

Cited by 54 publications

(85 citation statements)

References 259 publications

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“…Increases in monthly trends for CWW, freeze, and heat during winter months reflect large-scale swings in hot/dry and wet/cold COL impacts on crops in the MW (figure 6; Mishra et al 2010). The regional timing of such COL modulation is in line with expected future impacts of increasing winter/spring precipitation and warmer temperatures (Angel et al 2018).…”

Section: Regional-scale Vulnerabilitiessupporting

confidence: 57%

Spatio-temporal variation of crop loss in the United States from 2001 to 2016

Reyes

Elias

2019

Environ. Res. Lett.

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Crop insurance loss data can illuminate variations in agricultural impacts from exposure to weather and climate-driven events, and can improve our understanding of agricultural vulnerabilities. Here we perform a retrospective analysis of weather and climate-driven reasons for crop loss (i.e. cause of loss) obtained from the Risk Management Agency of the United States Department of Agriculture. The federal crop insurance program has insured over $440 billion in liabilities representing farmers' crops from 2001 to 2016. Specifically, we examine the top ten weather and climate-driven causes of loss from 2001 to 2016 across the nation comprising at least 83% of total indemnities (i.e. insurance payouts provided to farmers after crop loss events). First, we analyzed the relative fraction of indemnities by causes of loss, over different spatial and temporal resolutions. We found that drought and excess precipitation comprised the largest sources of crop loss across the nation. However, these causes varied strongly over space and time. We applied two additional normalization techniques to indemnities using (1) insurance premia and the gross domestic product implicit price deflator, and (2) liabilities to calculate the loss cost. We conducted trend analyses using the Mann-Kendall statistical test on loss cost over time. Differential trends and patterns in loss cost demonstrated the importance of spatio-temporal resolution in assessing causes of loss. The majority of monthly significant trends (p<0.05) showed increasing loss cost (i.e. increasing indemnities or decreasing liabilities) in response to weather events. Finally, we briefly discuss an online portal (AgRisk Viewer) to make these data accessible at multiple spatial scales and sub-annual time steps to support both research and outreach efforts promoting adaptation and resilience in agricultural systems.

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Section: Regional-scale Vulnerabilitiessupporting

confidence: 57%

Spatio-temporal variation of crop loss in the United States from 2001 to 2016

Reyes

Elias

2019

Environ. Res. Lett.

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“…The frequency of intense rainfall and drought are increasing 52 . In major portions of drained temperate humid croplands, crop water use exceeds average precipitation during crop growth 53,54 .…”

Section: Future Drainage System Designmentioning

confidence: 99%

“…Moreover, many systems rely on the original clay pipes installed >100 years ago, and those pipes are crumbling. Land-use change and climate change have combined to generate greater water flow to drains 51,52 . When contemporary drainage systems were installed, a much larger fraction of Midwest cropland was alfalfa, small-grain cereals, and pasture (Supplementary Figure 4).…”

Section: Box 2 │ Drainage In the United States Corn Beltmentioning

confidence: 99%

Sustainable intensification of agricultural drainage

et al. 2019

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Artificial drainage is among the most widespread land improvements for agriculture. Drainage benefits crop production, but also promotes nutrient losses to water resources. Here, we outline how a systems perspective for sustainable intensification of drainage can mitigate nutrient losses, increase fertilizer nitrogen use efficiency (NUE) and reduce greenhouse gas emissions. There is an immediate opportunity to realize these benefits because agricultural intensification and climate change are increasing the extent and intensity of drainage systems. If a systems-based approach to drainage can consistently increase NUE while maintaining or increasing crop production, farmers and the environment will benefit. Disciplines

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“…Studies already demonstrated that detention pond designed based on current climate and landuse are likely to result in peak flows of greater magnitude with subsequent higher damages due to elevated flooding and erosion for future storm events of the same frequency (Semadeni-Davies et al, 2008;Moglen and Rios Vidal, 2014). Especially in the Midwest United States urban stormwater system adaptation to increased frequency and intensity of severe rainfall is anticipated to cost more than $500 million per year (Angel. et al, 2018).…”

Section: Introduction and Literature Reviewmentioning

confidence: 99%

Improved reliability of stormwater detention basin performance through water quality data-informed real-time control

Sharior

McDonald

Parolari

2019

Journal of Hydrology

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The objective of stormwater detention basins is to capture stormwater runoff to reduce and delay peak flow and to improve the water quality. These objectives can be improved upon by actively controlling the outflow of the basins rather than traditional passive outflow structures. There are studies demonstrating the performance of the active controls that respond in real-time to basin hydraulics, detention time, and rainfall forecasts. We hypothesize that the performance of these active controls can be improved upon by incorporating real-time water quality data streams into the control algorithm. Furthermore, we hypothesize that performance of these active controls also depends on hydrologic variability, perturbing the highly dynamic rainfall-runoff process. Here, these hypotheses are tested using a numerical modeling framework evaluating the systemslevel reliability of passive and active control of stormwater basin outflow using a Monte Carlo method. The numerical modeling is performed in EPA-SWMM urban hydrologic model driven by stochastic rainfall time-series generated from the Modified Bartlett-Lewis Rectangular Pulses Model. Water quality-informed real-time active control algorithms are developed, tested, and demonstrated to result in a clear improvement over the traditional passive (no control) systems and other storage-based active controls for water and suspended sediment capture. Duration curve analysis showed that both water level-and water quality-informed control performance varied for different storm return periods and this variability could partly be attributed to the fraction of time the valve is closed. In addition, control performance was sensitive to rainfall variability, generally decreasing as storms become less frequent and more intense. Therefore, control system performance may depend on seasonal and longer timescale variability in climate and rainfall-runoff processes. We anticipate this study to be a starting point to incorporate theories of reliability to assess detention basin and conveyance network performance under more complex real-time control algorithms and failure modes.

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Chapter 21 : Midwest. Impacts, Risks, and Adaptation in the United States: The Fourth National Climate Assessment, Volume II

Cited by 54 publications

References 259 publications

Spatio-temporal variation of crop loss in the United States from 2001 to 2016

Spatio-temporal variation of crop loss in the United States from 2001 to 2016

Sustainable intensification of agricultural drainage

Improved reliability of stormwater detention basin performance through water quality data-informed real-time control

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