Quantitative impacts of climate change and human activities on the runoff evolution process in the Yanhe River Basin

Lian, Yingxin; Sun, Miao; Wang, Jichao; Luan, Qinghua; Jiao, Mengyan; Zhao, Xining; Gao, Xuerui

doi:10.1016/j.pce.2021.102998

Cited by 25 publications

(9 citation statements)

References 22 publications

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“…In this study, accuracy of SWAT simulation is one of the important key factors because many results such as blue water, green water, and hydrological elements (green water flow, green water storage, SURQ, GWQ and LATQ) are all output of the model. R 2 and NSE in this paper are within the accuracy requirement of model establishment, and the accuracy is close to the results of other researches in this river basin[53][54][55]. During the SWAT simulation, land use is classified into 6 types which cannot present the land use type actually and the land use module should be improved.…”

supporting

confidence: 79%

Impact of Grain for Green Project on Water Resources and Ecological Water Stress in Yanhe River Basin

Han

Xia

Huang

et al. 2021

Preprint

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Grain for Green project (GGP) initialed by China government since 1999 has achieved substantial achievements accompanied with surface runoff decrease in the Loess Plateau but impacts of large-scale afforestation on regional water resources are uncertain. Hence, the objective of this study is to explore the impact of land use change on generalized water resources and ecological water stress using blue and green water concept taking Yanhe River Basin as a case study. Soil and Water Assessment Tool (SWAT) is applied to quantify summary of green and blue water which is defined as generalized water resources, ecological water requirement of vegetation (forest and grass), agricultural water footprint and virtual water flow are considered as regional water requirements. Land use types of 1980 (scenario?), 2017 (scenario?) are input in SWAT model while keeps other parameters constant in order to isolate the influence of land use changes. Results show that average annual difference of blue, green and generalized water resources is -72.08 million m 3 , 24.34 million m 3 , -47.74 million m 3 respectively when simulation results of scenario? subtracts scenario?and it presents that land use change caused by GGP leads to decrease in blue and generalized water resources whereas increase in green water resources. SURQ in scenario?is more than that in scenario?in all the study period from 1980-2017, green water storage in scenario?is more than that in scenario? in all the study period except in 1998; whereas LATQ in scenario?is less than that in scenario? except in 2000 and 2015, GWQ in 1992, 2000 and 2015, green water flow in 1998. Blue water, green water storage and green water flow in scenario? is less than that in scenario?in the whole basin, 12.89 percent of the basin and 99.21 percent of the basin respectively. Total WF increases from 1995 to 2010 because forest WF increases significantly in this period though agricultural WF and grass WF decreases. Ecological water stress index has no obvious temporal change trend in both land use scenarios but ecological water stress index in scenario? is more than that in scenario?which illustrates that GGP leads to increase of ecological water stress from perspective of generalized water resources

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supporting

confidence: 79%

Impact of Grain for Green Project on Water Resources and Ecological Water Stress in Yanhe River Basin

Han

Xia

Huang

et al. 2021

Preprint

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“…The data used in this study included the following: (1) daily runoff data for the period of 1991–2020 were collected from the Ganguyi hydrological station, which is the control hydrographic station and the hydrological calibration outlet in the research basin with a control area of 5891 km 2 , accounting for about 76.6% of the basin area [ 38 , 39 ]. All the runoff data came from the hydrological yearbook of the Yellow River Basin provided by the Yellow River Conservancy Commission of the Ministry of Water Resources [ 40 ]; (2) digital elevation model (DEM) data with 30 m resolution, obtained from the Geospatial Data Cloud [ 41 ]; and (3) Yan’an Statistical Yearbook data for 2020, obtained from the Yan’an Bureau of Statistics [ 42 ].…”

Section: Methodsmentioning

confidence: 99%

Multiscale Analysis of Runoff Complexity in the Yanhe Watershed

Liu

Zhao

2022

Entropy

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Runoff complexity is an important indicator reflecting the sustainability of a watershed ecosystem. In order to explore the multiscale characteristics of runoff complexity and analyze its variation and influencing factors in the Yanhe watershed in China during the period 1991–2020, we established a new analysis method for watershed runoff complexity based on the complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) method for the decomposition of multiscale characteristics and the refined composite multiscale entropy (RCMSE) method for the quantification of the system complexity. The results show that runoff and its components all present multiscale complexity characteristics that are different from random signals, and the intermediate frequency modes contribute the most to runoff complexity. The runoff complexity of the Yanhe watershed has decreased gradually since 1991, and 2010 was a turning point of runoff complexity, when it changed from a decline to an increase, indicating that the ecological sustainability of this basin has improved since 2010, which was mainly related to the ecological restoration measures of the Grain for Green Project. This study expands the research perspective for analyzing the variation characteristics of runoff at the multiscale, and provides a reference for the study of watershed ecological sustainability and ecological management.

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“…The annual average precipitation is between 340 and 660 mm across the basin. The primary soil type is loessial soil, accounting for 85% (Lian et al 2021). Besides, the short-duration and high-intensity precipitation led to about 60.5% of the runoff occurring in the wet season, especially in July through September, and caused intensive soil erosion (Miao 2018).…”

Section: Study Areamentioning

confidence: 99%

Spatiotemporal features of pollutant loads in the Yan River Basin, a typical loess hilly and gully watershed in the Chinese Loess Plateau

Song

Sun³

et al. 2022

Geosci. Lett.

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Water quality is the restrictive factor for both ecosystem health and social development in the Chinese Loess Plateau, a unique area with most severe soil erosion, fragile ecology, and water shortage. Understanding the characteristics of the pollutant loads is of vital importance for the sustainability of eco-environment in the Loess Plateau. This study investigated the spatiotemporal changes of chemical oxygen demand (COD), total nitrogen (TN), and total phosphorus (TP) loads by combining the Soil and Water Assessment Tool (SWAT) and regression model Load Estimator (LOADEST) in a typical loess hilly and gully watershed—the Yan River Basin (YanRB). Results showed that the model simulations of monthly streamflow and pollutant loads were in good agreement with those derived from the in situ observations. The temporal variation analysis suggested that the pollutant loads were generally rising in the study period (2001–2018) at four of the five stations and reached the maximum in 2014, and the multi-year (i.e., 2001–2018 with 2013 being excluded due to extreme rainfall) average loads of COD, TN, and TP at the Tanjiahe station, which is close to the outlet of the basin, were 15,021 kg/day, 3835 kg/day, and 168 kg/day, respectively. The spatial distribution of the TN and TP loads along the river seemed to be quite unique because the TP level were obviously higher at the midstream (e.g., Zhujiagou and Ganguyi) than the downstream (e.g., Tanjiahe), and the TN level decreased when the river flowed from Zhujiagou to Ganguyi. Further, the seasonal analysis indicated that the nutrient loads were the highest in summer, followed by autumn, and the loads in these two seasons contributed the most of the annual pollution loads—about 76% and 84% for TN and TP, respectively, indicating the higher flow, the higher pollution load, a similar point based on the inter-annual analysis. In addition, the contribution analysis of point source and non-point source pollutions demonstrated that NPS led to most of the pollutant loads at the whole watershed—70%, 67%, and 71% of the COD, TN, and TP loads, respectively. Overall, this study provided spatiotemporal distributions of the key pollutant loads in the YanRB and can be valuable for water quality protection and pollution control in this area.

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Quantitative impacts of climate change and human activities on the runoff evolution process in the Yanhe River Basin

Cited by 25 publications

References 22 publications

Impact of Grain for Green Project on Water Resources and Ecological Water Stress in Yanhe River Basin

Impact of Grain for Green Project on Water Resources and Ecological Water Stress in Yanhe River Basin

Multiscale Analysis of Runoff Complexity in the Yanhe Watershed

Spatiotemporal features of pollutant loads in the Yan River Basin, a typical loess hilly and gully watershed in the Chinese Loess Plateau

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