Calibration of Hydrologic Models Using Multiobjectives and Visualization Techiques

小行星9418147 随着水文学家和气候学家研究新出现的问题和开发新的数据源，在水文气候学研究中越来越依赖陆面水文模型作为工具。 然而，水文模型只能像模型假设、输入和参数估计一样可靠。 现场测量、先验信息和校准是参数估计中使用的三种技术。 虽然使用实地测量越来越重要，但经验表明，实际上，几乎所有模型都需要校准至少一些参数。 然而，模型校准的丰富经验表明，通常不可能找到首选（最佳）解决方案。 也就是说，对于给定的模型和校准数据，通常存在参数空间的相当大的区域，这些区域似乎给出大致相等的结果。 这可能会引起对模型的可靠性和现实性以及对其预测的信心的质疑。 本研究的主要目的是开发校准水文模型的技术，以改善寻找首选解决方案的前景。 主要目标是： 1. 认识到水文模型校准固有的多目标性质 问题，并提出了多目标的框架内的校准程序。 2. 探索使用多标准、数据子集（强调不同的 水文过程或模型性能不同方面）、信息测量 内容和全局搜索算法在识别非劣解空间， 首选解决方案。 3. 在测试用例中，确定非劣解的满意且可靠的估计是否 空间可以被识别，从该空间中优选参数估计（或一组估计） 可以选择。 开发估计参数置信区间的技术 和模拟变量，同时考虑了非劣解空间和数据误差。 深入了解数据误差、模型误差和参数交互作用在 产生非劣解。 4. 为测试用例确定如何可靠、有效和高效地获得首选解决方案 通过系统的基于计算机的非劣解空间的探索。 实施 系统工作站标定策略，并与现有单目标标定策略进行比较 战略布局 这项研究将把注意力集中在新一代的陆面水文模型被认为是可行的陆面土壤植被大气传输计划（SVATS），这样的模型受到水文学家和水文气象学家的广泛关注，但围绕他们的校准问题还没有得到系统的关注。 预计所提出的技术将有助于水文学家建立更可靠，更逼真的模型。 在一般的科学知识方面，预计这项研究将导致对水文模型识别和校准问题的深入了解，特别是在可靠性和唯一性方面。

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.