Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains
Water resources from rivers are essential to humans. The discharge of rivers is demonstrated to be significantly affected by climate change in the literature, particularly in the boreal and subboreal climate zones. The Da Hinggan Mountains in subboreal northeast China form the headwaters of the Heil...
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doaj-642d25eb464a469eb2e180e8c4900c5e2020-11-25T03:26:40ZengMDPI AGWater2073-44412020-05-01121565156510.3390/w12061565Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan MountainsZhengxiang Yu0Xiuling Man1Liangliang Duan2Tijiu Cai3Department of Forestry, School of Forestry, Northeast Forestry University, Harbin 150040, ChinaDepartment of Forestry, School of Forestry, Northeast Forestry University, Harbin 150040, ChinaDepartment of Forestry, School of Forestry, Northeast Forestry University, Harbin 150040, ChinaDepartment of Forestry, School of Forestry, Northeast Forestry University, Harbin 150040, ChinaWater resources from rivers are essential to humans. The discharge of rivers is demonstrated to be significantly affected by climate change in the literature, particularly in the boreal and subboreal climate zones. The Da Hinggan Mountains in subboreal northeast China form the headwaters of the Heilongjiang River and the Nenjiang River, which are important water resources for irrigation of downstream agriculture and wetlands. In this study, long-term (44 years) hydrologic, climate and forest dynamics data from the Tahe were analyzed using the soil and water assessment tool (SWAT) model to quantify the effects of climate and forest change on runoff depth. Meanwhile, downscaled precipitation and temperature predictions that arose from global climate models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) were forced using the SWAT model to investigate the climate change impacts on the Tahe River flows in the future. The results indicated that compared with the 1972–1982 period, the forest biomass in the 1984–1994 period was reduced by 17.6%, resulting in an increase of 16.6% in mean annual runoff depth. On the contrary, with reforestation from the 1995–2005 period to the 2006–2016 period, the mean forest biomass was increased by 9.8%, resulting in the mean runoff depth reduction of 11.9%. The tree species composition shift reduced mean annual runoff depth of 13.3% between the 1984–1994 period and the 2006–2016 period. Compared with base years (2006–2016), projections of GCM in the middle of the 21st century indicated that both mean annual temperature and precipitation were expected to increase by −0.50 °C and 43 mm under RCP 2.6, 0.38 °C and 23 mm under RCP 4.5, 0.67 °C and 36 mm under RCP 6.0 and 1.00 °C and 10 mm under RCP 8.5. Simulated results of the SWAT model showed that annual runoff depth would increase by 18.1% (RCP 2.6), 11.8% (RCP 4.5), 23.6% (RCP 6.0), and 11.5% (RCP 8.5), compared to the base years. Such increased runoff was mainly attributed to the increase in April, July, August, September and October, which were consistent with the precipitation prediction. We concluded that the future climate change will increase the water resources from the river, thereby offsetting the possible decline in runoff caused by the forest recovery. The findings of this study might be useful for understanding the impacts of climate and forest change on runoff and provide a reasonable strategy for managers and planners to mitigate the impact of future climate change on water resources in the subboreal forested watersheds.https://www.mdpi.com/2073-4441/12/6/1565climate changeforest changesubboreal forested watershedSWAT modelCMIP5RCPs |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Zhengxiang Yu Xiuling Man Liangliang Duan Tijiu Cai |
spellingShingle |
Zhengxiang Yu Xiuling Man Liangliang Duan Tijiu Cai Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains Water climate change forest change subboreal forested watershed SWAT model CMIP5 RCPs |
author_facet |
Zhengxiang Yu Xiuling Man Liangliang Duan Tijiu Cai |
author_sort |
Zhengxiang Yu |
title |
Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains |
title_short |
Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains |
title_full |
Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains |
title_fullStr |
Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains |
title_full_unstemmed |
Assessments of Impacts of Climate and Forest Change on Water Resources Using SWAT Model in a Subboreal Watershed in Northern Da Hinggan Mountains |
title_sort |
assessments of impacts of climate and forest change on water resources using swat model in a subboreal watershed in northern da hinggan mountains |
publisher |
MDPI AG |
series |
Water |
issn |
2073-4441 |
publishDate |
2020-05-01 |
description |
Water resources from rivers are essential to humans. The discharge of rivers is demonstrated to be significantly affected by climate change in the literature, particularly in the boreal and subboreal climate zones. The Da Hinggan Mountains in subboreal northeast China form the headwaters of the Heilongjiang River and the Nenjiang River, which are important water resources for irrigation of downstream agriculture and wetlands. In this study, long-term (44 years) hydrologic, climate and forest dynamics data from the Tahe were analyzed using the soil and water assessment tool (SWAT) model to quantify the effects of climate and forest change on runoff depth. Meanwhile, downscaled precipitation and temperature predictions that arose from global climate models (GCMs) under four representative concentration pathways (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) were forced using the SWAT model to investigate the climate change impacts on the Tahe River flows in the future. The results indicated that compared with the 1972–1982 period, the forest biomass in the 1984–1994 period was reduced by 17.6%, resulting in an increase of 16.6% in mean annual runoff depth. On the contrary, with reforestation from the 1995–2005 period to the 2006–2016 period, the mean forest biomass was increased by 9.8%, resulting in the mean runoff depth reduction of 11.9%. The tree species composition shift reduced mean annual runoff depth of 13.3% between the 1984–1994 period and the 2006–2016 period. Compared with base years (2006–2016), projections of GCM in the middle of the 21st century indicated that both mean annual temperature and precipitation were expected to increase by −0.50 °C and 43 mm under RCP 2.6, 0.38 °C and 23 mm under RCP 4.5, 0.67 °C and 36 mm under RCP 6.0 and 1.00 °C and 10 mm under RCP 8.5. Simulated results of the SWAT model showed that annual runoff depth would increase by 18.1% (RCP 2.6), 11.8% (RCP 4.5), 23.6% (RCP 6.0), and 11.5% (RCP 8.5), compared to the base years. Such increased runoff was mainly attributed to the increase in April, July, August, September and October, which were consistent with the precipitation prediction. We concluded that the future climate change will increase the water resources from the river, thereby offsetting the possible decline in runoff caused by the forest recovery. The findings of this study might be useful for understanding the impacts of climate and forest change on runoff and provide a reasonable strategy for managers and planners to mitigate the impact of future climate change on water resources in the subboreal forested watersheds. |
topic |
climate change forest change subboreal forested watershed SWAT model CMIP5 RCPs |
url |
https://www.mdpi.com/2073-4441/12/6/1565 |
work_keys_str_mv |
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