A Comparison of Local- and Foreign-funded Hydropower Station Construction in Nepal based on Remote Sensing

doi:10.5814/j.issn.1674-764x.2022.06.006

Abstract

Abstract:

International investors in large infrastructure projects face numerous risks. To explore this issue, this paper compares the development of two hydropower stations in Rasuwa District, Nepal: Upper Trishuli 3A, which is fully funded by a Chinese government bank, and Rasuwagadhi, which is fully funded by local government banks. The construction of these two plants was compared between 2012 and 2020 using a visual interpretation method to extract data on roads, buildings, dams, and vehicles from 1-m-resolution remote sensing imagery. Two methods were used to compare the environmental impacts of each plant. Landsat 7/8 30-m imagery was used to monitor changes in the normalized difference vegetation index around the Upper Trishuli 3A hydropower station from 2012 to 2020 and around the Rasuwagadhi hydropower station from 2014 to 2020. Then, 1-m-resolution imagery was used to observe land-cover differences in these areas and time periods. The results indicate that: (1) despite various challenges, such as geological disasters, the COVID-19 pandemic, and a blockade by the Indian government, there was no difference in construction progress between the two hydropower stations. (2) The Upper Trishuli 3A Hydropower Station was associated with better environmental protection work, as there were continuous declines in vegetation growth near Rasuwagadhi and increased overall vegetation growth near Upper Trishuli 3A. (3) Energy projects funded by the Belt and Road Initiative have benefited developing countries enormously. Finally, local conditions should be thoroughly investigated during the construction of foreign-funded power stations.

Key words: the Belt and Road Initiative, remote sensing, hydropower station, Nepal

TIMSINA Ritu Raj, WU Mingquan, NIU Zheng. A Comparison of Local- and Foreign-funded Hydropower Station Construction in Nepal based on Remote Sensing[J]. Journal of Resources and Ecology, 2022, 13(6): 1009-1021.

Figures/Tables 17

References 29

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Satellite	Sensor	Path/Row	Date	Resolution (m)
Landsat-8	OLI	141/40	2020-12-07	30
		141/40	2014-12-07	30
		141/41	2020-12-07	30
Landsat-7	ETM+	141/41	2012-12-07	30

Satellite	Sensor	Path/Row	Date	Resolution (m)
Landsat-8	OLI	141/40	2020-12-07	30
		141/40	2014-12-07	30
		141/41	2020-12-07	30
Landsat-7	ETM+	141/41	2012-12-07	30

Category	Rasuwagadhi area				Upper Trishuli 3A area
Category	2012	2014	2017	2020	2012	2014	2017	2020
Roads	0.51	1.91	1.93	1.74	0.79	0.96	1.28	1.32
Construction and materials		19.75	35.10	6.38		37.23	34.33	38.70
Houses	0.50	14.83	32.65	33.40	2.69	7.63	9.27	7.01
Power station						19.59	18.93	23.07
Sand filtering area		17.24	18.39	11.32
Dam		0	13.37	35.73
Vehicles number		8	48	65		14	16	28

Category	Rasuwagadhi area				Upper Trishuli 3A area
Category	2012	2014	2017	2020	2012	2014	2017	2020
Roads	0.51	1.91	1.93	1.74	0.79	0.96	1.28	1.32
Construction and materials		19.75	35.10	6.38		37.23	34.33	38.70
Houses	0.50	14.83	32.65	33.40	2.69	7.63	9.27	7.01
Power station						19.59	18.93	23.07
Sand filtering area		17.24	18.39	11.32
Dam		0	13.37	35.73
Vehicles number		8	48	65		14	16	28

NDVI range	December 7, 2012		December 7, 2020
NDVI range	Area (ha)	Percentage (%)	Area (ha)	Percentage (%)
NDVI < -0.2	36.9	7.5	7.38	1.51
-0.2 ≤ NDVI < 0	106.56	21.68	46.26	9.41
0 ≤ NDVI < 0.2	244.08	49.67	199.98	40.69
0.2 ≤ NDVI < 0.4	103.68	21.09	221.85	45.14
0.4 ≤ NDVI < 0.6	0.18	0.03	15.93	3.24