Excellence in Research: Analyzing the Impact of Landscape Change on the Watershed Dynamics of a Flood-Prone Urban Region

该项目将分析土地利用/土地覆盖变化、城市洪水和水污染之间的关系。 调查人员将考虑如何增加人口增长，广泛的城市发展，以及相关的景观变化改变了自然流域生态系统，强调自然资源和过程，从而促进水污染。 该项目将通过调查导致洪水易发地区脆弱性的基本科学过程来造福社会，以便减轻这些影响。 该项目还将在一所历史悠久的黑人大学发展研究能力，并为来自代表性不足的少数群体的研究生和本科生提供严格的教育、培训和实践研究经验，从而建设科学人力资源能力。 该项目促进了各学科之间的直接合作，并将在分析长期数据和将其与地理空间数据相结合，同时监测自然资源方面产生重大影响。 作为该项目的一部分，将开发的地理空间数据和模型将成为城市和州政府、地方社区和非营利组织决策者的有用资源，以更好地监测和管理这些资源。该项目的具体目标是：（1）描述城市流域景观一级的土地利用和土地覆盖的时空变化;（2）通过开发综合地理空间数据库，确定和分析这些城市流域对生态系统的环境足迹;（3）利用地理空间和系统动态模型调查城市流域当前和未来的环境趋势。 该项目将综合利用各种遥感图像来确定土地使用/土地覆盖物变化的特征，并将利用地理信息系统综合不同比例尺的信息。 它还将开发可用于模拟预期情景的综合水文景观模型。 将对土壤和水中的养分和金属浓度进行空间插值分析，以查明和绘制城市流域的污染情况。该项目将产生新的信息，说明为尽量减少对自然资源的影响而必须进行的最佳流域开发的程度，以及为改善当地流域的质量而可能采取的切实步骤。这项研究将揭示如何利用地理空间数据进行景观分析，以制定改善流域管理的补救路径。 该项目将重点关注大休斯顿地区，该地区有着洪水和水污染的历史挑战。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project will analyze the relationship between land-use/land-cover change, urban flooding, and water pollution. Investigators will consider how increasing population growth, extensive urban development, and related landscape changes have altered natural watershed ecosystems, stressing natural resources and processes, thereby contributing to water pollution. This project will benefit society by investigating basic scientific processes that have contributed to the vulnerability of a flood-prone region, so that these can be mitigated. The project will also develop research capacity at a historically Black university, and by providing rigorous education, training, and hands-on research experiences for graduate and undergraduate students from under-represented minority groups, thereby building scientific human resource capacity. The project promotes direct collaboration among the various disciplines and will have significant impact in analyzing long-term data and integrating it with geospatial data while monitoring natural resources. The geospatial data and models that will be developed as part of this project will be useful resources for decision-makers within city and state governments, local communities, and non-profit organizations to better monitor and manage those resources. The specific objectives of the project are: (1) characterizing the landscape level spatiotemporal land use and land cover changes in the urban watersheds; (2) identifying and analyzing the environmental footprint of these urban watersheds on ecosystems by developing a comprehensive geospatial database; and (3) investigating the current and future environmental trends in urban watersheds using geospatial and system dynamic models. The project will use an integration of various types of remotely sensed imagery to characterize land-use/land-cover change, and will use a GIS to integrate information at different scales. It will also develop integrated hydro-landscape models that can be used to simulate anticipated scenarios. A spatial interpolation analysis of nutrient and metal concentrations in the soil and water will be conducted to identify and map contamination in the urban watersheds. The project will generate new information on the extent of optimum watershed development that is necessary for minimal impact on natural resources and the tangible steps that might be taken to improve the quality of local watersheds. The research will reveal how landscape analysis using geospatial data can be used to develop remediation paths for the improved watershed management. The project will focus on the greater Houston region, a region with a history of flooding and water pollution challenges.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.