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Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model

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ABSTRACT

Monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in urbanized watersheds are essential in land-use and water-resource planning and management. This study applies a novel framework to the urban growth model Slope, Land use, Excluded land, Urban extent, Transportation, and Hillshading (SLEUTH) and land-use change with the Conversion of Land use and its Effects (CLUE-s) model using historical SPOT images to predict urban sprawl in the Paochiao watershed in Taipei County, Taiwan. The historical and predicted land-use data was input into Patch Analyst to obtain landscape metrics. This data was also input to the Generalized Watershed Loading Function (GWLF) model to analyze the effects of future urban sprawl on the land-use patterns and watershed hydrology. The landscape metrics of the historical SPOT images show that land-use patterns changed between 1990–2000. The SLEUTH model accurately simulated historical land-use patterns and urban sprawl in the Paochiao watershed, and simulated future clustered land-use patterns (2001–2025). The CLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTH and CLUE-s models show the significant impact urban sprawl will have on land-use patterns in the Paochiao watershed. The historical and predicted land-use patterns in the watershed tended to fragment, had regular shapes and interspersion patterns, but were relatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared with land-use pattern in 1990. During the study, the variability and magnitude of hydrological components based on the historical and predicted land-use patterns were cumulatively affected by urban sprawl in the watershed; specifically, surface runoff increased significantly by 22.0% and baseflow decreased by 18.0% during 1990–2025. The proposed approach is an effective means of enhancing land-use monitoring and management of urbanized watersheds.

No MeSH data available.


Mean monthly stream flow.
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f3-sensors-08-00658: Mean monthly stream flow.

Mentions: Historical and future land-use patterns were fed into the GWLF model to simulate hydrological components of the Paochiao watershed. Stream flow data was used for 1990–2003 to verify the simulated stream-flow modeled using the GWLF model (Figure 3). Additionally, the R2 value of the linear regression model of the monthly mean stream of simulated and observed data was 0.90, and the difference between simulated and observed data was significant at p ≤ 0.01.


Monitoring and Predicting Land-use Changes and the Hydrology of the Urbanized Paochiao Watershed in Taiwan Using Remote Sensing Data, Urban Growth Models and a Hydrological Model
Mean monthly stream flow.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3927508&req=5

f3-sensors-08-00658: Mean monthly stream flow.
Mentions: Historical and future land-use patterns were fed into the GWLF model to simulate hydrological components of the Paochiao watershed. Stream flow data was used for 1990–2003 to verify the simulated stream-flow modeled using the GWLF model (Figure 3). Additionally, the R2 value of the linear regression model of the monthly mean stream of simulated and observed data was 0.90, and the difference between simulated and observed data was significant at p ≤ 0.01.

View Article: PubMed Central - PubMed

ABSTRACT

Monitoring and simulating urban sprawl and its effects on land-use patterns and hydrological processes in urbanized watersheds are essential in land-use and water-resource planning and management. This study applies a novel framework to the urban growth model Slope, Land use, Excluded land, Urban extent, Transportation, and Hillshading (SLEUTH) and land-use change with the Conversion of Land use and its Effects (CLUE-s) model using historical SPOT images to predict urban sprawl in the Paochiao watershed in Taipei County, Taiwan. The historical and predicted land-use data was input into Patch Analyst to obtain landscape metrics. This data was also input to the Generalized Watershed Loading Function (GWLF) model to analyze the effects of future urban sprawl on the land-use patterns and watershed hydrology. The landscape metrics of the historical SPOT images show that land-use patterns changed between 1990–2000. The SLEUTH model accurately simulated historical land-use patterns and urban sprawl in the Paochiao watershed, and simulated future clustered land-use patterns (2001–2025). The CLUE-s model also simulated land-use patterns for the same period and yielded historical trends in the metrics of land-use patterns. The land-use patterns predicted by the SLEUTH and CLUE-s models show the significant impact urban sprawl will have on land-use patterns in the Paochiao watershed. The historical and predicted land-use patterns in the watershed tended to fragment, had regular shapes and interspersion patterns, but were relatively less isolated in 2001–2025 and less interspersed from 2005–2025 compared with land-use pattern in 1990. During the study, the variability and magnitude of hydrological components based on the historical and predicted land-use patterns were cumulatively affected by urban sprawl in the watershed; specifically, surface runoff increased significantly by 22.0% and baseflow decreased by 18.0% during 1990–2025. The proposed approach is an effective means of enhancing land-use monitoring and management of urbanized watersheds.

No MeSH data available.