1. Climate-induced changes in erosion during the 21 st century for eight U.S. locations

2. Climate change resulting from greenhouse gas-induced global warming is expected to affect the extent, frequency, and magnitude of soil erosion. Erosional response will occur with changes in plant biomass production, plant residue decomposition rates, soil microbial activity, evapo- transpiration rates, soil surface sealing and crusting, as well as shifts in land use necessary to accommodate new climatic regimes. High-temperature stress is among the least understood of all plant processes, but temperature is known to affect morphology, portioning of photosynthetic products, and the root to shoot ratio (Rosenzweig and Hillel, 1998). Assessments of the impact of CO 2 - induced changes on agricultural productivity are needed for both scientific and policy-making purposes. The complexity of climate-crop production interactions makes simulation a useful and, probably, the only practical approach available for making the needed assessments (Stockle et al., 1992).  INTRODUCTION

3. OBJECTIVE To investigate the changes expected in the runoff and erosion as a function of the climate changes estimated for the 21 st century under corn and wheat management systems at eight locations in the United States.

4. METHODS

5. Model used: WEPP – Water Erosion Prediction Project The WEPP is a erosion prediction technology based on fundamentals of stochastic weather generation, infiltration theory, hydrology, soil physics, plant science, hydraulics, and erosion mechanics. The influence of the temperature in the biomass production is represented in the WEPP model (Flanagan and Nearing, 1995) by the temperature stress factor, which is computed with the equation TS = temperature stress factor (0-1), T a is the average daily temperature (  C); T b is the base temperature for the crop (  C), and T o is the optimum temperature for the crop (  C).

6. Atlanta, GA Cookeville, TN Corvallis, OR Pierre, SD Syracuse, NE Temple, TX West Lafayette, IN Wichita, KS Locations

7. CLIMATE FILES Climate files for each of these locations were generated using the CLIGEN model and data from the WEPP database for these locations. Data of 11 decades (1990 to 2099) were obtained with the HadCM3. Data obtained from HadCM3: total precipitation, mean temperature, and total downward surface short-wave solar radiation flux for each month of the 110 years studied (1990-2099). With these values were obtained the monthly mean values of precip., mean temp. and solar radiation for each location in the 11 decades analyzed. CLIGEN File Generation Precipitation changes Precipitation changes were made considering that half of the total monthly changes were due to the amount of precipitation falling per day and the other half was in the number of precipitation (wet) days.

8. CLIGEN File Generation Temperature changes The Hadley database gives data for a large-scale grid (2.5  latitude by 3.75  longitude), while the CLIGEN files are from the exact location. Solar radiation changes The same procedure used to adjust temperature was used for solar radiation, for similar reasons. Soils, Crops, and Topography Scenarios We selected soils that were most common to each location. The simulated crops were chisel plow corn and no-till winter wheat.

9. CO 2 Scenarios A modified version of the WEPP model (WEPP-CO 2 ) was used to account for the effects of atmospheric CO 2 levels on the erosional system. Simulations More than 550 simulations were conducted. Each erosion simulation was made using a 100-year synthetic, steady- climate weather file. Statistical Analyses For each of the eight locations, linear regression equations were computed to relate the mean annual precipitations, mean annual temperatures, mean annual solar radiations, mean monthly precipitations, and mean monthly temperatures to time. For each combination of location, soil type, and cropping system, linear regression equations were computed to relate mean annual erosion and mean annual runoffs to time.

10. RESULTS AND DISCUSSION

11. Changes predicted in the precipitation and temperature, by month, over the period of 1990-2099

13. Schematic diagram of primary pathways

14. Precipitation, runoff and erosion estimated for 1990, and changes (  ) estimated for the period of 1990-2099

16. Group 1 – Prec ↑ Runoff ↑ Erosion ↑ (20.8%) ↑↑↑

17. Group 2 – Prec ↓ Runoff ↓ Erosion ↓ (25%) ↑↑↑

18. Group 3 – Prec ↑ Runoff ↑ Erosion ↓ (Not found)

19. Group 4 – Prec ↓ Runoff ↓ Erosion ↑ (22.9%) ↑↑↑

20. Group 5 – Prec ↑ Runoff ↓ Erosion ↑ (12.5%) This situation was observed only in West Lafayette and the explanation for these results is related to the seasonal changes in precipitation, runoff, and erosion through the year.

21. Group 6 – Prec ↓ Runoff ↑ Erosion ↓ (2.1%) This situation was observed only in one particular condition (corn, in Corvallis, on the Prince soil), where the significance levels were low.

22. Group 7 – Prec ↑ Runoff ↓ Erosion ↓ (Not found)

23. Group 8 – Prec ↓ Runoff ↑ Erosion ↑ (12.5%) ↑↑↑

24. The changes predicted comprise increases until 41% for runoff and 102% for soil loss. The results of this study suggested that in locations where precipitation increases are significant, we can expect runoff and erosion rates to increases at an even greater rate than the precipitation. The results also point out that erosional response to climate change may be very complex. Where rainfall decreases were predicted, predicted erosion rates were just as likely to increase as to decrease. Given these results, along with the likelihood of overall increases in heavy storms during the next century (Karl et al., 1996), the overall story is one of increased erosion rates under climate change for the coming century. We recognize that our analysis of the plant growth aspects of the system under temperature changes is limited. For example, there appears to be a wide range of resistance to high-temperature stress both within and among crop species what suggests a potential for genetic improvement, but which is very difficult to currently model. To adapt to an environment of higher temperature, plant breeders may select cultivars that exhibit heat tolerance during reproductive development, high harvest indices, high photosynthetic capacities per unit leaf area, small leaves, and low leaf area per unit ground area (to reduce heat load). Smaller leaves may translate to lower canopy and ground cover, even were crop yields to remain level. Implications for the Future

25. PRUSKI, F.F., and NEARING, M.A. Water Resources Research, 38 (12), 1298, doi:10. 1029/2001 WR000493, 2002.