Date of Award

May 2019

Degree Type


Degree Name

Doctor of Philosophy



First Advisor

Woonsup Choi

Committee Members

Mark D Schwartz, Alison Donnelly, Changshan Wu, Zengwang Xu


climate change, conceptual framework, ecosystem services modeling, hydrological modeling, LULC change


Ecosystem services (ESs) are used as intermediates for researchers, stakeholders, and the public to understand and deal with the current environmental situation and problems, and ESs-related studies have drawn increasing attention. The quantitative assessments of ESs to calculate how much the ecosystem can benefit human beings and society, are still under development. Hydrological ESs, a subset of ESs that is related to water bodies and the surrounding environment, carry several challenges and opportunities for both hydrological and ESs modeling. Specifically, new quantitative tools with the capability to simulate explicit spatial and temporal scales are desired, and such tools should be comprehensive and include climate, geology, land cover, soil, and topography. Also, studies of the impacts of land use/landcover (LULC) and climate changes on hydrological ESs are limited by the current methods and techniques.

This dissertation study was designed to achieve the following objectives: (1) build a coupled modeling framework so that hydrological information can be converted to hydrological ESs by developing a conceptual connection between three functions: data development, modeling, and results analysis. (2) demonstrate the importance of hydrological ESs at fine temporal scales by simulating hydrological ESs with the framework in the case study. (3) examine impacts of LULC and climate changes on hydrological ESs (water provision, flood regulation, and sediment regulation) with the framework and a series of climate and urban expansion scenarios in the Milwaukee River basin, USA.

The framework was designed (objective 1) with integration of data processing, hydrological and ESs modeling, and output analysis which are supported by national data products. With such procedural streamlining, simulation of hydrological ESs are more straightforward and less time-consuming than the separated processes. This framework resolves the design limitations of both current ES models that cannot simulate at fine temporal scales and hydrological models that cannot convert hydrological information to ESs.

Results from the fine temporal analyses (objective 2) of water provision ES, flood regulation ES, and sediment regulation ES indicate that that annual results alone in ESs simulation and analysis for management plans are not adequate for time-sensitive planning and including results at fine temporal scales is necessary for some ESs that are event-based or have large seasonal variations. Based on such results, more timely relevant policy suggestions can be provided to decision-makers.

Results of objective 3 showed that, compared to LULC, the climate-change scenarios have much larger impacts on hydrological ESs, and results under climate change show quite large variations among different climate models, years, and months. Additionally, the interactions among different ESs have also been identified. This approach with the framework and impact scenarios can better support management plans with different scenarios for decision-makers.

In summary, the framework designed in this study is an innovative tool that resolves the issue of fine temporal scales that cannot be addressed with current tools and methods, and contributes to the impact studies under LULC and climate changes with new insights from multiple variations and interaction analyses.