Spatiotemporal analysis of precipitation in the sparsely gauged Zambezi River basin using remote sensing and Google Earth Engine
- Zeng, Hongwei, Zhang, Ning, Tian, Fuyou, Phiri, Elijah, Wu, Bingfang, Musakwa, Walter, Zhang, Miao, Zhu, Liang, Mashonjowa, Emmanuel
- Authors: Zeng, Hongwei , Zhang, Ning , Tian, Fuyou , Phiri, Elijah , Wu, Bingfang , Musakwa, Walter , Zhang, Miao , Zhu, Liang , Mashonjowa, Emmanuel
- Date: 2020
- Subjects: Google Earth Engine , Precipitation pattern , Kendall’s Taub rank correlation
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/415785 , uj:35145 , Citation: Zeng, H. et al. Spatiotemporal analysis of precipitation in the sparsely gauged Zambezi River basin using remote sensing and Google Earth Engine. DOI: 10.3390/rs11242977
- Description: Abstract: , Precipitation plays an important role in the food production of Southern Africa. Understanding the spatial and temporal variations of precipitation is helpful for improving agricultural management and flood and drought risk assessment. However, a comprehensive precipitation pattern analysis is challenging in sparsely gauged and underdeveloped regions. To solve this problem, Version 7 Tropical Rainfall Measuring Mission (TRMM) precipitation products and Google Earth Engine (GEE) were adopted in this study for the analysis of spatiotemporal patterns of precipitation in the Zambezi River Basin. The Kendall’s correlation and sen’s Slop reducers in GEE were used to examine precipitation trends and magnitude, respectively, at annual, seasonal and monthly scales from 1998 to 2017. The results reveal that 10% of the Zambezi River basin showed a significant decreasing trend of annual precipitation, while only 1% showed a significant increasing trend. The rainy-season precipitation appeared to have a dominant impact on the annual precipitation pattern. The rainy-season precipitation was found to have larger spatial, temporal and magnitude variation than the dry-season precipitation. In terms of monthly precipitation, June to September during the dry season were dominated by a significant decreasing trend. However, areas presenting a significant decreasing trend were rare (<12% of study area) and scattered during the rainy-season months (November to April of the subsequent year). Spatially, the highest and lowest rainfall regions were shifted by year, with extreme precipitation events (highest and lowest rainfall) occurring preferentially over the northwest side rather than the northeast area of the Zambezi River Basin. A “dry gets dryer, wet gets wetter” (DGDWGW) pattern was also observed over the study area, and a suggestion on agriculture management according to precipitation patterns is provided in this study for the region. This is the first study to use long-term remote sensing data and GEE for precipitation analysis at various temporal scales in the Zambezi River Basin. The methodology proposed in this study is helpful for the spatiotemporal analysis of precipitation in developing countries with scarce gauge stations, limited analytic skills and insufficient computation resources. The approaches of this study can also be operationally applied to the analysis of other climate variables, such as temperature and solar radiation.
- Full Text:
- Authors: Zeng, Hongwei , Zhang, Ning , Tian, Fuyou , Phiri, Elijah , Wu, Bingfang , Musakwa, Walter , Zhang, Miao , Zhu, Liang , Mashonjowa, Emmanuel
- Date: 2020
- Subjects: Google Earth Engine , Precipitation pattern , Kendall’s Taub rank correlation
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/415785 , uj:35145 , Citation: Zeng, H. et al. Spatiotemporal analysis of precipitation in the sparsely gauged Zambezi River basin using remote sensing and Google Earth Engine. DOI: 10.3390/rs11242977
- Description: Abstract: , Precipitation plays an important role in the food production of Southern Africa. Understanding the spatial and temporal variations of precipitation is helpful for improving agricultural management and flood and drought risk assessment. However, a comprehensive precipitation pattern analysis is challenging in sparsely gauged and underdeveloped regions. To solve this problem, Version 7 Tropical Rainfall Measuring Mission (TRMM) precipitation products and Google Earth Engine (GEE) were adopted in this study for the analysis of spatiotemporal patterns of precipitation in the Zambezi River Basin. The Kendall’s correlation and sen’s Slop reducers in GEE were used to examine precipitation trends and magnitude, respectively, at annual, seasonal and monthly scales from 1998 to 2017. The results reveal that 10% of the Zambezi River basin showed a significant decreasing trend of annual precipitation, while only 1% showed a significant increasing trend. The rainy-season precipitation appeared to have a dominant impact on the annual precipitation pattern. The rainy-season precipitation was found to have larger spatial, temporal and magnitude variation than the dry-season precipitation. In terms of monthly precipitation, June to September during the dry season were dominated by a significant decreasing trend. However, areas presenting a significant decreasing trend were rare (<12% of study area) and scattered during the rainy-season months (November to April of the subsequent year). Spatially, the highest and lowest rainfall regions were shifted by year, with extreme precipitation events (highest and lowest rainfall) occurring preferentially over the northwest side rather than the northeast area of the Zambezi River Basin. A “dry gets dryer, wet gets wetter” (DGDWGW) pattern was also observed over the study area, and a suggestion on agriculture management according to precipitation patterns is provided in this study for the region. This is the first study to use long-term remote sensing data and GEE for precipitation analysis at various temporal scales in the Zambezi River Basin. The methodology proposed in this study is helpful for the spatiotemporal analysis of precipitation in developing countries with scarce gauge stations, limited analytic skills and insufficient computation resources. The approaches of this study can also be operationally applied to the analysis of other climate variables, such as temperature and solar radiation.
- Full Text:
Survey of community livelihoods and landscape change along the Nzhelele and Levuvhu river catchments in the Limpopo Province, South Africa
- Musakwa, Walter, Wang, Shuai, Wei, Fangli, Malapane, Olgah Lerato, Makamule, Thomas Masala, Mavengahama, Sydney, Hongwei, Zeng, Wu, Bingfang, Zhao, Wenwu, Nesisa, Analisa Nyathi, Mashimbye, Zama Eric, Poona, Nitesh, Chakwizira, James, Gumbo, Trynos, Mokoena, Baleseng, Kaitano, Francis, Fundisi, Emmanuel, Yeni-Letsoko, Vuyiswa
- Authors: Musakwa, Walter , Wang, Shuai , Wei, Fangli , Malapane, Olgah Lerato , Makamule, Thomas Masala , Mavengahama, Sydney , Hongwei, Zeng , Wu, Bingfang , Zhao, Wenwu , Nesisa, Analisa Nyathi , Mashimbye, Zama Eric , Poona, Nitesh , Chakwizira, James , Gumbo, Trynos , Mokoena, Baleseng , Kaitano, Francis , Fundisi, Emmanuel , Yeni-Letsoko, Vuyiswa
- Date: 2020
- Subjects: Landscape change , Livelihoods , Sustainable development
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/415914 , uj:35161 , Citation: Musakwa, W. et al. Survey of community livelihoods and landscape change along the Nzhelele and Levuvhu river catchments in the Limpopo Province, South Africa.
- Description: Abstract: , Landscape change studies have attracted increasing interest because of their importance 29 to land management and sustainable livelihoods of rural communities. However, empirical studies 30 on landscape change and its drivers are often poorly understood, particularly, in small rural 31 communities in developing countries such as South Africa. The present study surveyed local 32 community livelihoods and perceptions of landscape change in the Nzhelele and Levuvhu river 33 catchments in Limpopo Province, South Africa. These areas have experienced land reform and are 34 also characterized by environmental degradation, poverty, inequality and environmental justice 35 concerns among other issues. Land cover maps derived from Landsat satellite imagery were used 36 for purposes of correlating and validating the survey data findings and results. The survey results 37 showed that education levels, working status and marital status have statistically significant effects 38 on community livelihoods (indicated by levels of income, p < 0.05). Maize, fruits and vegetables are 39 the main cultivated crop varieties in the study area, and these crops are mainly used for subsistence 40 to meet household self-consumption requirements..
- Full Text:
- Authors: Musakwa, Walter , Wang, Shuai , Wei, Fangli , Malapane, Olgah Lerato , Makamule, Thomas Masala , Mavengahama, Sydney , Hongwei, Zeng , Wu, Bingfang , Zhao, Wenwu , Nesisa, Analisa Nyathi , Mashimbye, Zama Eric , Poona, Nitesh , Chakwizira, James , Gumbo, Trynos , Mokoena, Baleseng , Kaitano, Francis , Fundisi, Emmanuel , Yeni-Letsoko, Vuyiswa
- Date: 2020
- Subjects: Landscape change , Livelihoods , Sustainable development
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/415914 , uj:35161 , Citation: Musakwa, W. et al. Survey of community livelihoods and landscape change along the Nzhelele and Levuvhu river catchments in the Limpopo Province, South Africa.
- Description: Abstract: , Landscape change studies have attracted increasing interest because of their importance 29 to land management and sustainable livelihoods of rural communities. However, empirical studies 30 on landscape change and its drivers are often poorly understood, particularly, in small rural 31 communities in developing countries such as South Africa. The present study surveyed local 32 community livelihoods and perceptions of landscape change in the Nzhelele and Levuvhu river 33 catchments in Limpopo Province, South Africa. These areas have experienced land reform and are 34 also characterized by environmental degradation, poverty, inequality and environmental justice 35 concerns among other issues. Land cover maps derived from Landsat satellite imagery were used 36 for purposes of correlating and validating the survey data findings and results. The survey results 37 showed that education levels, working status and marital status have statistically significant effects 38 on community livelihoods (indicated by levels of income, p < 0.05). Maize, fruits and vegetables are 39 the main cultivated crop varieties in the study area, and these crops are mainly used for subsistence 40 to meet household self-consumption requirements..
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