Variations in annual water-energy balance and their correlations with vegetation and soil moisture dynamics: A case study in the Wei River Basin, China

Huang, Shengzhi; Huang, Qiang; Leng, Guoyong; Zhao, Mengdie; Meng, Erhao

doi:10.1016/j.jhydrol.2016.12.060

Cited by 44 publications

(26 citation statements)

References 56 publications

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“…Previous studies showed that soil moisture content is an important factor that impacts vegetation (Huang, Huang, Leng, Zhao, & Meng, 2017), but no data that can be used to study soil moisture dynamics are available on a long-term scale. Moreover, this area is a humid area with sufficient precipitation; thus, the influence of soil moisture requires further study.…”

Section: What Other Factors Impact Ndvi?mentioning

confidence: 99%

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

Mengmeng

Xia

2018

Land Degrad Dev

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Since 2000, the gross domestic product (GDP) of the Pearl River Delta (PRD) has increased by more than eight‐fold. Experiences throughout the world indicate that the impacts of economic development on vegetation are particularly important. This study analyzed the variations in vegetation coverage in the PRD from 2000 to 2016. Moderate resolution imaging spectroradiometer normalized difference vegetation index (NDVI) data were employed, whereas climate data, GDP, and population were also used as influencing factors. Topographic factors were introduced to explain the spatial vegetation patterns, and the impacts of human activities on vegetation were explored. The results revealed (a) the overall vegetation coverage in the PRD showed an increasing trend, and the overall average NDVI increased by 0.0033/a. (b) The spatial pattern did not change greatly, but the high and low NDVI values moved to low elevations and shallow topographic slopes where human activities were prevalent. This trend resulted in increased NDVI values in 38% of the area of the PRD (p < 0.01). (c) There was a positive correlation between NDVI and economic growth (GDP, population), with correlation coefficients greater than 0.8 (p < 0.01). NDVI is influenced by climate change and human activities (such as afforestation, resident lifestyles, and economic development policies). This study reveals that with good policies, both rapid economic development and vegetation coverage improvements can be simultaneously achieved in a region. The findings of this study are crucial for the sustainable development of the mega‐urban agglomerations of the PRD and Guangdong‐Hong Kong‐Macau Grand Bay.

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Section: What Other Factors Impact Ndvi?mentioning

confidence: 99%

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

Mengmeng

Xia

2018

Land Degrad Dev

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“…Traditional statistical test methods (e.g., Mann-Kendall test, sliding F-test and sliding t-test, etc.) are difficult to accurately detect the real breakpoints in the nonlinear and nonstationary time series [36][37][38]. However, the heuristic segmentation method developed by Bernaola-Galvan et al [39] could deal with this problem, which is based on the thought of modified sliding t-test to detect the breakpoints of nonlinear and nonstationary time series [36].…”

Section: Detection Of Hydroclimatic Changesmentioning

confidence: 99%

“…are difficult to accurately detect the real breakpoints in the nonlinear and nonstationary time series [36][37][38]. However, the heuristic segmentation method developed by Bernaola-Galvan et al [39] could deal with this problem, which is based on the thought of modified sliding t-test to detect the breakpoints of nonlinear and nonstationary time series [36]. Meanwhile, this method has been widely applied to the breakpoint detection of runoff series, such as in Wei River Basin [40], Hanjiang River Basin [41] and Yellow River Basin [42] in China.…”

Section: Detection Of Hydroclimatic Changesmentioning

confidence: 99%

SWAT-Simulated Streamflow Responses to Climate Variability and Human Activities in the Miyun Reservoir Basin by Considering Streamflow Components

Yan

Bai

Yi³

et al. 2018

Sustainability

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The streamflow into Miyun Reservoir, the only surface drinking water source for Beijing City, has declined dramatically over the past five decades. Thus, the impacts of climate variability and human activities (direct and indirect human activities) on streamflow and its components (baseflow and quickflow) needs to be quantitatively estimated for the sustainability of regional water resources management. Based on a heuristic segmentation algorithm, the chosen study period (1969–2012) was segmented into three subseries: a baseline period (1969–1979) and two impact periods I (1980–1998) and II (1999–2012). The Soil and Water Assessment Tool (SWAT) was adopted to investigate the attributions for streamflow change. Our results indicated that the baseflow accounted for almost 63.5% of the annual streamflow based on baseflow separation. The contributions of climate variability and human activities to streamflow decrease varied with different stages. During impact period I, human activities was accountable for 54.3% of the streamflow decrease. In impact period II, climate variability was responsible for 64.9%, and about 8.3 mm of baseflow was extracted from the stream on average based on the comparison of the observed streamflow and simulated baseflow. The results in this study could provide necessary information for water resources management in the watershed.

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“…Generally, the climate condition for a special region is dominated by both energy balance and water balance [45][46][47]. In the humid regions, the climate is controlled by energy, namely energy The change in T max , T min , ea, U 2 , and R s lead to the changes in AI by 0.0019, 0.0004, 0.0001, 0.0003, and 0.0003 year −1 , respectively.…”

Section: Attribution Of the Variation In Aridity Indexmentioning

confidence: 99%

“…Generally, the climate condition for a special region is dominated by both energy balance and water balance [45][46][47]. In the humid regions, the climate is controlled by energy, namely energy limitation, and can be reflected by ET 0 [48], while it is controlled by water limitation in the arid regions.…”

Section: Attribution Of the Variation In Aridity Indexmentioning

confidence: 99%

Variation of Aridity Index and the Role of Climate Variables in the Southwest China

Feng

Liu

et al. 2017

Water

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Aridity index (AI), defined as the ratio of annual potential evapotranspiration to annual precipitation, has been widely applied in dividing climate regimes and monitoring drought events. Investigating variation of AI and the role of climate variables are thus of great significant for managing agricultural water resource and maintaining regional ecosystem stability. In this study, with the well-corrected precipitation records and the optimized parameters in estimating solar radiation, we investigated the variation of AI and its climatic attribution in the Southwest China using the observed climate records from 135 meteorological stations during the period of 1993-2015. The results showed that the AI increased significantly (0.0053 year −1 , p < 0.05) from 1993 to 2015 and abruptly increasing occurred around 2002. Approximately 85% of stations showed an increasing trend, while 24% of stations reached up to a significant increasing level, which demonstrated that the Southwest China was getting drier for the recent 20 years. Overall, the AI was most sensitive to maximum air temperature and precipitation with values of 1.11 and −1.00, respectively. The following factors are vapor pressure, solar radiation, minimum temperature, and wind speed. The declining precipitation and ascending maximum air temperature were the key variables in dominating the increase in aridity index during the period of 1993-2015, which contribute 38.98% and 36.26% of AI variation, respectively. Our results highlighted the influence of climate variability on aridity in the Southwest China.

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Variations in annual water-energy balance and their correlations with vegetation and soil moisture dynamics: A case study in the Wei River Basin, China

Cited by 44 publications

References 56 publications

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

A significant increase in the normalized difference vegetation index during the rapid economic development in the Pearl River Delta of China

SWAT-Simulated Streamflow Responses to Climate Variability and Human Activities in the Miyun Reservoir Basin by Considering Streamflow Components

Variation of Aridity Index and the Role of Climate Variables in the Southwest China

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