Zhizhu Lai

Dr. Zhizhu Lai

East China normal university
orcid

Research Focus & Metrics

Academic Career Length

14Years (2013-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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1 September 2019 in Renewable Energy
Verified
Journal Article
Closed access
YCYulong Chen
Yulong Chen
JZJincai Zhao
Jincai Zhao
ZLZhizhu Lai
Zhizhu Lai
ZWZheng Wang
Zheng Wang
HXHaibin Xia
Haibin Xia

1 February 2019 in Applied Energy
Verified
Journal Article
Closed access
JZJincai Zhao
Jincai Zhao
GJGuangxing Ji
Guangxing Ji
YYYanLin Yue
YanLin Yue
ZLZhizhu Lai
Zhizhu Lai
YCYulong Chen
Yulong Chen
ZWZheng Wang
Zheng Wang

4 February 2020 in PLOS ONE
Verified
Journal Article
Open access
PDF file
ZLZhizhu Lai
Zhizhu Lai
DGDongmei Ge
Dongmei Ge
HXHaibin Xia
Haibin Xia
YYYanlin Yue
Yanlin Yue
ZWZheng Wang
Zheng Wang
How to achieve the sustainable and coordinated development of the ecological environment, the economy and tourism has already received much attention. In this paper, a comprehensive evaluation index system of the ecological environment, the economy and tourism is established, and the coupling degrees and coordination degrees of the three subsystems of 31 provinces in China from 2003 to 2017 are calculated. The results show that the average coupling degree and average coordination degree have fluctuating upward trends during the period of 2003–2017. According to the spatial distribution of the coupling degrees and coordination degrees, the coastal provinces and Chongqing, with their high ecological environment pressure and good economic development, have low coupling and extremely high coordination levels. The vast central and western provinces with good ecological environment protection and economic backwardness have high coupling and low coordination development level. From the perspective of coordinated development, only seven of the western provinces and three middle-eastern provinces possess basic coordinated development of the ecological environment, the economy and tourism. The remaining 21 provinces are over-utilizing or sacrificing their ecological environments, among which eleven eastern provinces have an advanced economy or advanced tourism and five southwestern provinces with high tourism resource endowments have an advanced tourism.

15 April 2021 in Land
Verified
Journal Article
Open access
PDF file
GJGuangxing Ji
Guangxing Ji
ZLZhizhu Lai
Zhizhu Lai
HXHaibin Xia
Haibin Xia
HLHao Liu
Hao Liu
ZWZheng Wang
Zheng Wang
The purpose of this paper is to simulate the future runoff change of the Yellow River Basin under the combined effect of land use and climate change based on Cellular automata (CA)-Markov and Soil & Water Assessment Tool (SWAT). The changes in the average runoff, high extreme runoff and intra-annual runoff distribution in the middle of the 21st century are analyzed. The following conclusions are obtained: (1) Compared with the base period (1970–1990), the average runoff of Tangnaihai, Toudaoguai, Sanmenxia and Lijin hydrological stations in the future period (2040–2060) all shows an increasing trend, and the probability of flood disaster also tends to increase; (2) Land use/cover change (LUCC) under the status quo continuation scenario will increase the possibility of future flood disasters; (3) The spring runoff proportion of the four hydrological stations in the future period shows a decreasing trend, which increases the risk of drought in spring. The winter runoff proportion tends to increase; (4) The monthly runoff proportion of the four hydrological stations in the future period tends to decrease in April, May, June, July and October. The monthly runoff proportion tends to increase in January, February, August, September and December.

19 May 2021 in Land
Verified
Journal Article
Open access
PDF file
GJGuangxing Ji
Guangxing Ji
LWLeying Wu
Leying Wu
LWLiangdong Wang
Liangdong Wang
DYDan Yan
Dan Yan
ZLZhizhu Lai
Zhizhu Lai
Previous studies mainly focused on quantifying the contribution rate of different factors on annual runoff variation in the source region of the Yellow River (SRYR), while there are few studies on the seasonal runoff variation. In this study, the monthly water storage and monthly actual evaporation of SRYR were calculated by the monthly ABCD model, and then a seasonal Budyko frame was constructed. Finally, the contribution rate of climatic and anthropic factors on the seasonal runoff variation in Tangnaihai hydrological station were quantitatively calculated. It turned out that: (1) The changing point of runoff data at Tangnaihai hydrological station is 1989. (2) The ABCD monthly hydrological model could well simulate the monthly runoff variation of Tangnaihai hydrological station. (3) Anthropic factors play a major role in runoff change in spring, summer, and winter, while climatic factors play a major role in runoff change in autumn.

4 December 2020 in Water
Verified
Journal Article
Open access
PDF file
DYDan Yan
Dan Yan
ZLZhizhu Lai
Zhizhu Lai
GJGuangxing Ji
Guangxing Ji
Assessing the contribution rates of climate change and human activities to the runoff change in the source area of the Yellow River can provide support for water management in the Yellow River Basin. This paper firstly uses a multiple linear regression method to evaluate the contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River. Next, the paper uses the Budyko hypothesis method to calculate the contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change of the Tangnaihai Hydrometric Station. The results showed that: (1) the annual runoff and precipitation in the source area of the Yellow River have a downward trend, while the annual potential evaporation and NDVI (Normalized Difference Vegetation Index) show an increasing trend; (2) The contribution rates of climate change and human activities to the vegetation change in the source area of the Yellow River is 62.79% and 37.21%, respectively; (3) The runoff change became more and more sensitive to changes in climate and underlying surface characteristic parameters; (4) The contribution rates of climatic factors (including precipitation, potential evaporation, and subsequent vegetation changes) and vegetation changes caused by human activities to the runoff change at Tangnaihai Hydrological Station are 75.33% and 24.67%, respectively; (5) The impact of precipitation on runoff reduction is more substantial than that of potential evaporation.