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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

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.


The monthly changes in (a) streamflows, (b) surface runoffs, (c) groundwater discharges, and (d) evapotranspiration due to land-use changes in the watershed 3.4. Discussions.
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f9-sensors-08-00658: The monthly changes in (a) streamflows, (b) surface runoffs, (c) groundwater discharges, and (d) evapotranspiration due to land-use changes in the watershed 3.4. Discussions.

Mentions: Figure 9 presents the differences in monthly streamflow, surface runoff, groundwater discharge and evapotranspiration between 1990 and land-use changes in 2005, 2010, 2015, 2020 and 2025. The highest changes in monthly streamflows occurred during May–August 2012, 2016, 2020, and particularly in 2025 when monthly streamflow increased by 7.0% (Figure 9(a)). The peak differences in monthly streamflow between land-use change and no change occurred in June and August of all study years. Peak differences in surface runoff between land use change and no change occurred in March, April and May of each year; in 2025 peak differences were highest (32.0%) (Figure 9(b)). Figure 9(c) shows the differences in monthly groundwater discharge between land-use changes and no change (1990). The greatest decrease (−18.0%) in groundwater discharge occurred in August 2025 (Figure 9(c)). The decrease (−15.0%) in evapotranspiration occurred in all months during 2025, except for June (Figure 9(d)).


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
The monthly changes in (a) streamflows, (b) surface runoffs, (c) groundwater discharges, and (d) evapotranspiration due to land-use changes in the watershed 3.4. Discussions.
© Copyright Policy
Related In: Results  -  Collection

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

f9-sensors-08-00658: The monthly changes in (a) streamflows, (b) surface runoffs, (c) groundwater discharges, and (d) evapotranspiration due to land-use changes in the watershed 3.4. Discussions.
Mentions: Figure 9 presents the differences in monthly streamflow, surface runoff, groundwater discharge and evapotranspiration between 1990 and land-use changes in 2005, 2010, 2015, 2020 and 2025. The highest changes in monthly streamflows occurred during May–August 2012, 2016, 2020, and particularly in 2025 when monthly streamflow increased by 7.0% (Figure 9(a)). The peak differences in monthly streamflow between land-use change and no change occurred in June and August of all study years. Peak differences in surface runoff between land use change and no change occurred in March, April and May of each year; in 2025 peak differences were highest (32.0%) (Figure 9(b)). Figure 9(c) shows the differences in monthly groundwater discharge between land-use changes and no change (1990). The greatest decrease (−18.0%) in groundwater discharge occurred in August 2025 (Figure 9(c)). The decrease (−15.0%) in evapotranspiration occurred in all months during 2025, except for June (Figure 9(d)).

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.