Integrated Modeling of Precipitation-Recharge-Runoff at the River Basin Scale: The Susquehanna

0310122达菲虽然河流流域是陆地水循环研究的组织主体，但直到最近，将气候、地形、生态和地质的复杂性与水资源预测的特殊需求相结合的模型还没有被认为是实用的。本研究提出了多尺度动态的降水-补给-径流，水和能量的预算在复杂的地形和水文地质条件下的分区调查。该方法保持地表和地下过程之间的自然耦合在每个感兴趣的规模，但认识到，地表水流域和地下水流域可能有不同的划定。建模方法是基于一个有限的体积表示，其中守恒和本构方程的平均超过一个指定的支持规模。该模型是多尺度的，因为对地貌的气候、植被、地形和水文地质要素进行了解析，以便为特定的水资源预测（洪水动态、河流含水层对干旱的反应等）保留必要的时空尺度。该研究解决了计算规模和需要在水资源预测中包括精细尺度材料特性之间的权衡。SRB的长期流量预测必须考虑到流域对气候或土地利用强迫的响应的地表和地下过程的竞争时间尺度。 我们的策略是使用多目标进化算法的快速表面响应以及较慢的地下响应的条件预测。 这个多目标框架将适应模型参数和分辨率，以考虑不同的时间尺度和物理复杂性的表面和地下水流regimes.This研究将首先集中在开发区域概念性地表水模型的组成流域内的SRB。 研究的下一阶段将制定一项战略，将地理空间数据作为整个SRB地表-地下水动态大规模模型的输入，综合区域概念模型。 研究的最后阶段将开发一个决策支持系统，将新的气候数据纳入长期径流预测。 这些长期预测将支持整个SRB制定更好的水管理政策。 研究解决了四个基本问题：1）水文地质在长期和短期径流中发挥什么作用，与气候和土地利用动态有什么关系？ 2)小尺度土壤和地下变化何时控制径流？模型如何“适应”不断变化的外部（气候）和内部条件（土地利用）？3)流域支流动态耦合的时空尺度是什么？ 4)如何将演化计算策略和“定性”概念模型结合起来，以更好地解决模型的维数、参数化和流域尺度的预测？

0310122DuffyAlthough the river basin is the organizing principal of the terrestrial water cycle research, until recently, models which couple the complexity of climate, terrain, ecology, and geology at this scale to the particular needs of a water resource forecast, have not been considered practical. The present research proposes to investigate the multi-scale dynamics of precipitation-recharge-runoff, and the partitioning of water and energy budgets over complex terrain and hydrogeological conditions. The approach maintains the natural coupling between surface and subsurface processes at each scale of interest but recognizes that surface water basins and groundwater basins may have distinct delineations. The modeling approach is based on a finite volume representation, where conservation and constitutive equations are averaged over a specified support scale. The model is multi-scale in the sense that climatic, vegetative, topographic and hydrogeologic elements of the landscape are resolved in such a way as to preserve the necessary space-time scales for a particular water resource forecast (flood dynamics, stream-aquifer response to drought, etc.). The research addresses the tradeoff between the scale of computing and the need to include fine-scale material properties in water resource predictions. Long-term flow forecasts for the SRB must account for the competing time scales of the surface and subsurface processes governing the basin's response to climatologic or landuse forcing. Our strategy is to condition forecasts on both rapid surface responses as well as slower subsurface responses using multiobjective evolutionary algorithms. This multiobjective framework will adapt model parameters and resolution to account for the disparate time-scales and physical complexities of surface and subsurface flow regimes.This research will initially focus on developing regional conceptual surface-groundwater models for component watersheds within the SRB. The next phase of the research will develop a strategy for synthesis of the regional conceptual models with geospatial data as input to a large-scale model for the surface-groundwater dynamics of the entire SRB. The final phase of the research will develop a decision-support system that will assimilate new climatologic data into long-range runoff predictions. These long-range predictions will support the development of improved water management policies for the entire SRB. The research addresses four fundamental questions: 1) What role does hydrogeology play in long-term and short-term runoff and what is the relation to climate and landuse dynamics? 2) When does small-scale soil and subsurface variability control runoff and how can models "adapt" to changing external (climate) and internal conditions (landuse)? 3) What are the space-time scales at which tributaries of the river basin are dynamically coupled? 4) How can evolutionary computing strategies and "qualitative" conceptual models be incorporated to better resolve model dimensionality, parameterization, and prediction at the river basin scale?