Date of Award


Degree Type


Degree Name

Doctor of Philosophy in Environmental Sciences


Environmental Sciences

First Advisor

Y. Q. Wang


Among the global Earth system changes, human-induced land-cover and land-use changes (LULCC) play significant roles in sustainability of ecosystems. Suburban sprawl, for example, is one of the major components of LULCC that develops urban impervious surface area (ISA) across the landscapes. Increasing ISA is a major environmental issue that has profound impacts on hydrology and climate. Coastal state of Rhode Island has experienced problems associated with urban runoffs due to the alteration of ISA on the landscape.

Precise and accurate coverage and location of ISA are key parameters in ISA related environmental studies. Due to the limitations of existing coarse spatial resolution ISA data and current methods for extraction of ISA from high spatial resolution remote sensing imageries, this study developed an algorithm of multiple agent segmentation and classification (MASC) to extract ISA information from high spatial resolution remote sensing imageries. The MASC model includes submodels of segmentation, shadow-effect, MANOV A-based classification, and post-classification. Based on the MASC model, this study built the 1-meter high spatial resolution ISA dataset for the state of Rhode Island, and revealed its spatial patterns. The result indicates that, as of 2004, 10% of the state land has been covered by ISA. The major population centers and historical cities, such as the Providence, Woonsocket, and Newport, have ISA over 30%. The heavily settled suburban communities have ISA between 10% and 30%. Only 17 out of 39 towns in the state have less than 10% ISA. The average ISA for the coastal towns is 14%. Because most stream quality indicators are predicted to decline when watershed ISA exceeds 10%, the results from this study serve as an alarming indicator for managing the state's watershed and coastal ecosystems.

It is important to develop scientific basis for observing and modeling watershed hydrologic dynamic with emphasis on how the hydrologic processes are affected by the spatial heterogeneity of ISA, and to improve the understanding of influence of ISA on hydrologic cycle in watersheds. This developed a distributed object-oriented rainfall-runoff simulation (DORS) model that enhances capability and performance of hydrologic modeling with incorporation of high spatial resolution ISA information. With the innovative process of object-oriented spatial units, the DORS model can reduce data volume, increase computational efficiency, strengthen representation of watersheds and utilize the data in variable scales. The DORS model provides a framework to integrate remote sensing data and the derived products in different scale for the simulation of hydrologic process in a watershed. This study used USGS stream gaging data to validate the temporal variation of simulated discharge within two watersheds. Ratio of absolute error to the mean and Nash coefficient for the simulation period are 9.4% and 0.998 for first watershed, and 12.6% and 0.80 for second watershed, respectively. The results indicate that the model performs well for the purpose of modeling the runoff and base flow in the complex watershed and the performance of hydrologic simulation is improved with the incorporation of high spatial resolution ISA.

Change of watershed hydrology is one of the most direct and important impacts from increasing ISA. With the high spatial resolution ISA and developed DORS model this study performed hydrologic simulation in twenty HUC-12 watersheds with various degrees of urbanization in the state of Rhode Island. This study derived indicators of hydrology pattern including ratio of runoff to base flow and discharge per area from hydrologic simulations, and watersheds characteristics including percentage of ISA, distance from ISA to streams and stream density. This study employed spatial error model and spatial lag model, as well as regular regression model, to build the relationship between watersheds characteristics and hydrology pattern. The results demonstrate that ISA plays most important role in watershed hydrology compared with other indicators and the spatial dependence in observations can not be neglected in the analyses.

The research results from this study, such as the developed classification model, statewide ISA dataset, spatial pattern of ISA and relationship between watershed characteristics and hydrology pattern, provide useful information for decision-making activities related to watershed management.



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