CAREER: Climate Informed Uncertainty Analyses for Integrated Water Resources Sustainability

0954405 Arumugam本研究的目的是（1）量化气候变化在调节美国东南部相对未开发流域的季节性径流和水质变化方面的相对作用，(2)调查季节性气候预测在改善供水和水质管理以及制定适应性水管理计划以促进诸如北卡罗来纳州纽斯河流域等地区的水可持续性方面的效用，（3）将研究结果纳入（i）NCSU的校园和远程教育课程，（ii）北卡罗来纳州HCBU的水相关课程，和（iii）初中/高中学生的暑期培训计划，和（4）向联邦和州机构、研究机构和非营利组织演示如何使用气候预报为受损水体（例如，北卡罗来纳州）制定流量和水质预报。 各种措施将被用来量化的因果关系链，关联气候变化与流量和水质变化。 将利用多个大气环流模型（GCM）预测来制定径流和水质预测，这些预测将纳入水分配和水质管理模型。 将利用这些预测进行回顾性分析，以制定综合水管理计划。 这项研究旨在建立一个基本的知识体系，了解气候变化在调节河流流域流量和水质方面的作用。 预计这项研究的结果将提供关于水质属性对气候变化的脆弱性的见解。 使用GCM预测开发的径流预测将减少模型的不确定性，并改善季节性水分配和水质管理计划。 概括这些发现将有助于理解气候预测在促进水资源可持续性方面的潜在效用。

0954405ArumugamThe objectives of this research are to (1) quantify the relative roles of climate variability in modulating seasonal streamflow and water quality variability over relatively undeveloped basins in the southeastern U.S., (2) investigate the utility of seasonal climate forecasts in improving water supply and water quality management and in developing adaptive water management plans for promoting water sustainability in regions such as the Neuse river basin, NC, (3) integrate research findings into (i) on-campus and distance education courses at NCSU, (ii) water-related courses at HCBUs in NC, and (iii) summer training programs for junior/senior high school students, and (4) demonstrate to federal and state agencies, research institutes and non-profits the use of climate forecasts in developing streamflow and water quality forecasts for impaired water bodies, for example, in NC. Various measures will be employed to quantify the causal chain that associates climatic variability with streamflow and water quality variability. Multiple General Circulation Models (GCMs) forecasts will be utilized to develop streamflow and water quality forecasts, which are ingested into water allocation and water quality management models. Retrospective analyses using these forecasts will be performed to develop an integrated water management plan. This research aims to create a fundamental body of knowledge on understanding the role of climate variability in modulating streamflow and water quality in river basins. It is expected that findings from this research will offer insights on the vulnerability of water quality attributes to climatic variability. Streamflow forecasts developed using GCM forecasts will reduce model uncertainty and improve seasonal water allocation and water quality management plans. Generalizing the findings will help in understanding the potential utility of climate forecasts in promoting water resources sustainability.