Impact of climate change on soil erosion, runoff, and wheat productivity in central Oklahoma
Introduction
Analysis of climatology throughout the contiguous U.S. has revealed an upward trend in total precipitation and a bias toward more intense rainfall events during the last century (SWCS, 2003). More importantly, all general circulation models (GCMs) considered in the SWCS report have projected that globally averaged temperature, precipitation, and intensity of rainfall events will increase in the future with increased greenhouse gases (IPCC (Intergovernmental Panel on Climate Change) Working Group I, 2001, U.S. NAST (National Assessment Synthesis Team), 2001). This trend toward precipitation occurring in more extreme events must be adequately simulated for soil erosion assessment, because most soil loss is caused by infrequent severe storms (Edwards and Owens, 1991). Under climate changes, the potential for such projected changes to increase the risk of soil erosion and related environmental consequences is clear, but the actual damage is not known and needs to be assessed (SWCS, 2003). These insights are needed to determine (i) whether a change in soil and water conservation practices is warranted under changed climate and (ii) what practices should be taken to adequately protect soil and water resources if a change is warranted.
Impacts of projected changes in precipitation, temperature, and CO2 on crop productivity have been evaluated by many researchers (e.g., Rosenzweig and Parry, 1994, Semenov and Porter, 1995, Mearns et al., 1997, Mavromatis and Jones, 1998). Mean and variance changes in both precipitation and temperature were considered in those studies, and some results indicated that changes in climate variability (as measured by variance) could have profound effects on crop productivity.
Impacts of global climate change on soil erosion and surface runoff have been evaluated by considering changes in precipitation intensity or frequency. The change in mean precipitation has been assumed to take place by a change in storm frequency alone, intensity alone, or a combination of the two (Favis-Mortlock et al., 1991, Boardman and Favis-Mortlock, 1993, Savabi et al., 1993, Pruski and Nearing, 2002a, Pruski and Nearing, 2002b). Pruski and Nearing (2002a) compared the effects of changes in storm frequency and/or intensity by allocating mean precipitation changes to changes in storm frequency alone, changes in storm intensity alone, or changes in both. They found that a change in precipitation amount and intensity had a much greater effect on soil erosion and runoff generation than a change in storm frequency. Specifically, a 1% change in precipitation resulted in, on average, a 2.4% change in soil loss and a 2.5% change in runoff if a change in precipitation amount and intensity accounted for all of the change, and resulted in a 0.9% change in soil erosion and a 1.3% change in runoff if a change in frequency accounted for all of the change. Other studies conducted in the U.S. (Savabi et al., 1993) and Great Britain (Favis-Mortlock et al., 1991) showed that average soil erosion increased by 2–4% for a 1% increase in precipitation if changes in storm intensity accounted for all the increase.
Zhang et al. (2004) developed a downscaling method that can be used to directly incorporate changes in monthly precipitation and temperature distributions including mean and variance into daily weather series using a stochastic weather generator (CLIGEN) developed by Nicks and Gander (1994). In the proposed method, future transitional probabilities of precipitation occurrence were estimated from linear relationships developed using historical transitional probability and monthly precipitation at a station of interest. Mean and variance ratios of GCM-projected monthly precipitation between a target and a control period were directly multiplied by mean and variance of daily precipitation at the station for use in daily weather generation. Their simulation results indicated that an increase in precipitation variance, which increased the occurrence frequency of large storms, substantially increased predicted soil loss and surface runoff in conventional tillage winter wheat in Oklahoma. They also reported that an increase in mean temperature significantly reduced wheat yield and therefore considerably increased soil loss and runoff.
Climate change scenarios used in this study were from the recent climate change experiments conducted using a third generation general circulation model (HadCM3) at the Hadley Centre, UK (Wood et al., 1999, Gordon et al., 2000, Pope et al., 2000). The HadCM3 climate change experiments issued monthly forecasts for the next 100 years for the entire globe. The greenhouse gas emissions scenarios of A2a, B2a, and GGa1 were selected to represent a wide range of CO2 increases. Selection of the HadCM3 model was subjective, and other GCM models and emissions scenarios may also be used.
The objectives of this study were to evaluate the potential impacts of HadCM3-projected climate changes during 2070–2099 under A2a, and B2a, and GGa1 forcing on soil loss, surface runoff, and winter wheat productivity under three common tillage systems on a central Oklahoma site using a newly developed downscaling method that incorporates both mean and variance changes in projected monthly precipitation and temperatures into generated daily weather series.
Section snippets
Projected climate change scenarios
Climate change experiments conducted by the UK Meteorological Office's Hadley Centre using the HadCM3 model used the emissions scenarios reported in the Special Report on Emissions Scenarios (SRES, 2000) by the Intergovernmental Panel on Climate Change (IPCC, http://www.cru.uea.ac.uk/link/emissions/sres.html). A set of four families of emissions scenarios was formulated based on future production of greenhouse gases and aerosol precursor emissions. Each scenario described one possible
Results and discussion
Five-year moving averages of historical and projected annual precipitation (average of the two grid cells) at El Reno for the period of 1950–1999 are plotted in Fig. 1. The moving averages of projected annual precipitation in the GGa1 scenario, which was forced using the historical increase in the individual greenhouse gases from 1860 to 1990, agreed well with those of historical data after 1975 except for a projected drier spell near 1995. The simulated patterns after 1980 in the B2a scenario
Implications
The Hadley Centre model (HadCM3) predicts a general decrease in annual precipitation for the region near El-Reno, OK over the century, but those decreases in rainfall may not result in reductions in wheat yields. This may be due to the fact that the decrease in annual rainfall is primarily predicted for the summer months, while the rainfall during the growing season months of September through April is relatively constant or, in some months, increasing, and the fact that the negative impact of
Acknowledgements
The GCM data have been supplied by the Climate Impacts LINK Project (DEFRA Contract EPG I/I/I24) on behalf of the Hadley Centre and U.K. Meteorological Office. The generous support is greatly appreciated.
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