Assessing the Role of Parameter and Input Uncertainty in Ecohydrologic Modeling: Implications for a Semi-arid and Urbanizing Coastal California Catchment
- 437 Downloads
Ecohydrologic models are a key tool in understanding plant–water interactions and their vulnerability to environmental change. Although implications of uncertainty in these models are often assessed within a strictly hydrologic context (for example, runoff modeling), the implications of uncertainty for estimation of vegetation water use are less frequently considered. We assess the influence of commonly used model parameters and inputs on predictions of catchment-scale evapotranspiration (ET) and runoff. By clarifying the implications of uncertainty, we identify strategies for insuring that the quality of data used to drive models is considered in interpretation of model predictions. Our assessment also provides insight into unique features of semi-arid, urbanizing watersheds that shape ET patterns. We consider four sources of uncertainty: soil parameters, irrigation inputs, and spatial extrapolation of both point precipitation and air temperature for an urbanizing, semi-arid coastal catchment in Santa Barbara, CA. Our results highlight a seasonal transition from soil parameters to irrigation inputs as key controls on ET. Both ET and runoff show substantial sensitivity to uncertainty in soil parameters, even after parameters have been calibrated against observed streamflow. Sensitivity to uncertainty in precipitation manifested primarily in winter runoff predictions, whereas sensitivity to irrigation manifested exclusively in modeled summer ET. Neither ET nor runoff was highly sensitive to uncertainty in spatial interpolation of temperature. Results argue that efforts to improve ecohydrologic modeling of vegetation water use and associated water-limited ecological processes in these semi-arid regions should focus on improving estimates of anthropogenic outdoor water use and explicit accounting of soil parameter uncertainty.
KeywordsEcohydrology Modeling Urban ecology Plant–water interactions Semiarid Sensitivity analysis
This research was supported by a National Science Foundation Graduate Research Fellowship, and by the Santa Barbara Coastal Long-Term Ecological Research project, funded by the National Science Foundation (OCE-9982105 and OCE-0620276). We thank the two anonymous reviewers whose extensive and thoughtful comments greatly contributed to the quality of the final manuscript.
- Anderson JR, Hardy EE, Roach JT, Witmer RE. 1976. A land use and land cover classification system for use with remote sensor data. US Geological Survey, Professional Paper 964. Reston, VA: USGS.Google Scholar
- County of Santa Barbara. 2007. Santa Barbara County water purveyors water shortage contingency/drought planning handbook. http://www.countyofsb.org/pwd/water/downloads/HandbookforPurveyorsRevSep2007.pdf.
- Fuentes M, Kittel TGF, Nychka D. 2006. Sensitivity of ecological models to their climate drivers: statistical ensembles for forcing. Contemp Stat Ecol 16:99–116.Google Scholar
- Gleick P, Haasz D, Henges-Jeck C, Srinivasan V, Wolff G, Cushing KK, Mann A. 2003. Waste not, want not: the potential for urban water conservation in California. Pacific Institute for Studies in Development, Environment, and Security, Oakland.Google Scholar
- IPCC. 2007. Contribution of Working Groups I, II, and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Geneva, Switzerland.Google Scholar
- Johnson T. 2005. Predicting residential irrigation amounts using remote sensing in Los Angeles, California. M.S. thesis. San Diego, CA: San Diego State University.Google Scholar
- Jones H. 1992. Plants and microclimate. 2nd edn. Cambridge: Cambridge University Press.Google Scholar
- Kirchner J. 2006. Getting the right answers for the right reasons: Linking measurements, analyses, and models to advance the science of hydrology. Water Resour Res 42:W03S04.Google Scholar
- Mackun P, Wilson S. 2011. Population Distribution and Change: 2000 to 2010, U.S. Census Bureau, U.S. Department of Commerce, Economics and Statistics Administration.Google Scholar
- Metropolitan Water District. 1996. Integrated Water Resources Plan (IRP), MWD report no. 1107.Google Scholar
- Spruill CA, Workman SR, Taraba JL. 2000. Simulation of daily and monthly stream discharge from small watersheds using the SWAT model. Trans ASAE 43:1431–9.Google Scholar
- Tague C, Pohl M. 2008. The utility of physically based hydrologic modeling in ungaged urban streams. Ann Assoc Am Geogr 93:1–16.Google Scholar
- Ward A, Trimble S, Wolman M. 1994. Environmental hydrology. 2nd edn. Boca Raton: CRC Press.Google Scholar