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The close relationship between large dams and social development (i.e., water, food, and energy consumption) has been revealed in previous studies, and the vital role of large dams in sustaining societies has been recognized. With population projections indicating continued growth during this century, it is expected that further economic development of society, e.g., Gross Domestic Product (GDP) growth, will be greatly affected by possible challenges, such as water, food, and energy shortages in the future, especially if proper planning, development, and management strategies are not adopted. In our previous study, we have argued that construction of additional large dams will be considered as one of the best available options to meet future increases in water, food, and energy demands, which are all crucial to sustain economic development. In the present study, firstly, we will emphasize the vital role of dams in promoting economic growth through analyzing the relationship between large dam development and GDP growth at both global and national scales. Secondly, based on the projection results of future large dam development, we will preliminarily predict the future economic development represented by GDP. The results show that the impacts of large dams upon GDP are more significant in countries with higher levels of socioeconomic development, which generally supports large dams as the vital factor to promote economic development.
Haiyun Shi; Ji Chen; Suning Liu; Bellie Sivakumar. The Role of Large Dams in Promoting Economic Development under the Pressure of Population Growth. Sustainability 2019, 11, 2965 .
AMA StyleHaiyun Shi, Ji Chen, Suning Liu, Bellie Sivakumar. The Role of Large Dams in Promoting Economic Development under the Pressure of Population Growth. Sustainability. 2019; 11 (10):2965.
Chicago/Turabian StyleHaiyun Shi; Ji Chen; Suning Liu; Bellie Sivakumar. 2019. "The Role of Large Dams in Promoting Economic Development under the Pressure of Population Growth." Sustainability 11, no. 10: 2965.
River discharge, which represents the accumulation of surface water flowing into rivers and ultimately into the ocean or other water bodies, may have great impacts on water quality and the living organisms in rivers. However, the global knowledge of river discharge is still poor and worth exploring. This study proposes an efficient method for mapping high-resolution global river discharge based on the algorithms of drainage network extraction. Using the existing global runoff map and digital elevation model (DEM) data as inputs, this method consists of three steps. First, the pixels of the runoff map and the DEM data are resampled into the same resolution (i.e., 0.01-degree). Second, the flow direction of each pixel of the DEM data (identified by the optimal flow path method used in drainage network extraction) is determined and then applied to the corresponding pixel of the runoff map. Third, the river discharge of each pixel of the runoff map is calculated by summing the runoffs of all the pixels in the upstream of this pixel, similar to the upslope area accumulation step in drainage network extraction. Finally, a 0.01-degree global map of the mean annual river discharge is obtained. Moreover, a 0.5-degree global map of the mean annual river discharge is produced to display the results with a more intuitive perception. Compared against the existing global river discharge databases, the 0.01-degree map is of a generally high accuracy for the selected river basins, especially for the Amazon River basin with the lowest relative error (RE) of 0.3% and the Yangtze River basin within the RE range of ±6.0%. However, it is noted that the results of the Congo and Zambezi River basins are not satisfactory, with RE values over 90%, and it is inferred that there may be some accuracy problems with the runoff map in these river basins.
Jiaye Li; Tiejian Li; Suning Liu; Haiyun Shi. An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction. Water 2018, 10, 533 .
AMA StyleJiaye Li, Tiejian Li, Suning Liu, Haiyun Shi. An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction. Water. 2018; 10 (4):533.
Chicago/Turabian StyleJiaye Li; Tiejian Li; Suning Liu; Haiyun Shi. 2018. "An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction." Water 10, no. 4: 533.