9418147 Sorooshian The reliance on land surface hydrologic models as tools in the study of hydroclimatology is increasing as hydrologists and climatologists examine emerging problems and exploit new data sources. However, hydrologic models can only be as reliable as model assumptions, inputs, and parameter estimates. Field measurements, prior information, and calibration are three techniques used in parameter estimation. While the use of field measurements is gaining in importance, experience has shown that as a practical matter, virtually all models require calibration of at least some parameters. However, extensive experience with model calibration has indicated that it is very often not possible to find a preferred (best) solution. That is, for a given model and calibration data, there are usually sizable regions of the parameter space that appear to give roughly equivalent results. This can gives rise to questions about the reliability and realism of the model, and the confidence in its predictions. The primary objective of this research is to develop techniques for calibrating hydrologic models that improve the prospects for finding preferred solutions. Major objectives are to: 1. Recognize the inherently multi-objective nature of the hydrologic model calibration problem and pose the calibration procedure in the framework of multiple objectives. 2. Explore innovative ways of using multi-criteria, data sub-sets (that emphasize different hydrologic processes or different aspect of model performance), measures of information content and global search algorithms in identifying the non-inferior solution space and preferred solutions. 3. On test cases, determine if a satisfactory and reliable estimate of the non-inferior solution space can be identified, from which a preferred parameter estimate (or set of estimates) can be selected. Develop techniques for estimating confidence intervals on paramete rs and simulated variable, taking into account the non-inferior solution space and data errors. Gain insights into the roles that data error, model error, and parameter interaction play in producing non-inferior solutions. 4. Determine, for test cases, how preferred solutions can be reliably, effectively and efficiently obtained through a systematic computer based exploration of the non-inferior solution space. Implement a systematic workstation based calibration stratigy and compare it with existing single-objective strategies. This research will focus its attention on the emerging generation of land surface hydrologic models being considered as viable land-surface soil-vegetation-atmosphere transfer schemes (SVATS); such models are receiving widespread attention among hydrologists and hydrolmeteorologists but the calibration issues surrounding them have yet to receive systematic attention. It is expected that the proposed techniques will help hydrologists build more reliable and more realistic models. In terms of general scientific knowledge, it is expected that the research will result in insights into problems of hydrologic model identification can calibration, particularly in the area of reliability and uniqueness.
