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RSS FeedsSustainability, Vol. 11, Pages 6415: Impact of Land Use/Land Cover Change on Hydrological Components in Chongwe River Catchment (Sustainability)

 
 

14 november 2019 20:03:40

 
Sustainability, Vol. 11, Pages 6415: Impact of Land Use/Land Cover Change on Hydrological Components in Chongwe River Catchment (Sustainability)
 


Chongwe River Catchment, a sub-catchment of the Zambezi River Basin, has been experiencing changes in land use/land cover (LULC) and in its hydrology. This study aims to assess the impact of LULC changes on the catchment’s hydrological components such as streamflow, evapotranspiration and water abstractions. LULC change data, detected from the 1984, 1994, 2014 and 2017 USGS Landsat imagery using a maximum likelihood supervised classifier, were integrated into the WEAP Model along with soil, slope and hydro–climate data. The results showed that between 1984 and 2017 built-up area increased by 382.77% at 6.97 km2/year, irrigated agriculture increased by 745.62% at 1.70 km2/year, rainfed farms/ranch/grassland increased by 14.67% at 14.53 km2/year, forest land decreased by 41.11% at 22.33 km2/year and waterbodies decreased by 73.95% at 0.87 km2/year. Streamflow increased at a rate of 0.13 Mm3 per annum in the wet seasons and showed a high variation with flow volume of 79.68 Mm3 in February and 1.01 Mm3 in September. Annual actual evapotranspiration decreased from 840.6 mm to 796.3 mm while annual water abstraction increased from 8.94 mm to 23.2 mm from the year 1984 to 2017. The pattern of LULC change between 1984 and 2017 has negatively impacted the hydrology of the Chongwe River Catchment. From these findings, an integrated catchment management and protection approach is proposed to mitigate the negative impacts of LULC dynamics on hydrological components in the Chongwe River Catchment.


 
210 viewsCategory: Ecology
 
Sustainability, Vol. 11, Pages 6416: Construction of the Ecological Security Pattern of Urban Agglomeration under the Framework of Supply and Demand of Ecosystem Services Using Bayesian Network Machine Learning: Case Study of the Changsha-Zhuzhou-Xiangtan Urban Agglomeration, China (Sustainability)
Sustainability, Vol. 11, Pages 6414: Use of FTIR Spectroscopy and Chemometrics with Respect to Storage Conditions of Moldavian Dragonhead Oil (Sustainability)
 
 
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