Dagmawi Mulugeta Degefu

Dagmawi Mulugeta Degefu


Research Focus & Metrics

Academic Career Length

3Years (2024-Present)

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

Representative Publications

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27 January 2024 in Water
Verified
Journal Article
Open access
PDF file
JLJiaqi Li
Jiaqi Li
HWHe Weijun
He Weijun
EJEnhui Jiang
Enhui Jiang
BQBo Qu
Bo Qu
Liang YuanLiang Yuan
Liang Yuan
TRThomas Ramsey
Thomas Ramsey
Water resources are crucial for the development of ecosystems and humanity. The Yellow River Basin (YRB), as an important ecological area in China, is facing significant challenges in ecological protection and high-quality development due to global climate change and intense human activities. In order to alleviate the water resources crisis in the YRB, it is necessary to calculate the resilience of the water resources system and identify the main influencing factors. This paper considered the factors of water resources, social economy, and ecological environment, then constructed an evaluation framework of the water resources system resilience (WRSR) from three aspects: resistance, restoration, and adaptability. Taking nine provinces along the YRB as a case study, the WRSR was measured by using the entropy weight TOPSIS model, and its driving factors were analyzed with Geographical Detectors (GD). The results showed that: (1) From 2010 to 2022, the WRSR in the Yellow River Basin and various provinces was showing a fluctuating increasing trend, in which Ningxia had the highest average WRSR (0.646), while Shanxi had the lowest (0.168). (2) From three dimensions, the development trends of resistance, restoration, and adaptability in the YRB and various provinces from 2010 to 2022 were relatively stable. Shandong’s resistance level far exceeded that of other provinces, having the highest average resistance value (0.692), and Ningxia had the highest average value of restoration (0.827) and adaptability (0.711). However, Gansu had the lowest average value of resistance (0.119), Sichuan had the lowest average value of restoration (0.097), and Shandong had the lowest average value of adaptability (0.110). (3) In terms of impact factors, the development and utilization rate of water resources (C13) and the development and utilization rate of surface water resources (C14) in the restoration subsystem consistently ranked in the top two of influencing factors. Similarly, the water consumption per 10,000 yuan of GDP (C26) in the adaptability subsystem consistently ranked within the top ten. On the other hand, the natural population growth rate (C6) in the resistance subsystem, as well as the impact of ammonia nitrogen emissions (C9) and total precipitation (C2) in wastewater, exhibited an upward trend. Based on these, this paper provides relevant suggestions for improving the WRSR in the YRB.

30 November 2025 in Water
Verified
Journal Article
Open access
PDF file
HWHe Weijun
He Weijun
LZLiang Zhao
Liang Zhao
Yang KongYang Kong
Yang Kong
QPQingling Peng
Qingling Peng
Liang YuanLiang Yuan
Liang Yuan
XWXuexue Wu
Xuexue Wu
Water environmental carrying capacity (WECC) is an important support for social and economic development and is closely related to regional production and consumption patterns. Exploring the level of WECC and its evolution trend is very urgent for the scientific formulation of targeted early warning control strategies. Therefore, this study first constructs the index system of WECC with a DPSIR model, and conducts the quantitative evaluation by combining the Kantiray Weighting method and the TOPSIS method. Then, the Kernel Density Estimation method and the Markov Chain model are applied to explore the spatiotemporal variation characteristics of WECC and predict its evolution trend. Finally, a case study of 17 municipal administrative regions in Hubei Province is carried out. The main findings are as follows: (1) The WECC status in Hubei Province during 2013–2022 was generally satisfactory and showed a trend of fluctuating improvement. (2) The spatial agglomeration effect of WECC in Hubei Province was significant, showing a distribution pattern of “high-high” agglomeration and “low-low” agglomeration. The improvement of the WECC in eastern Hubei was obvious, while that in central Hubei was slower, and the cities with a lower level of WECC had a more significant improvement effect. (3) Overall, the WECC of cities in Hubei Province tends to shift to a higher level. In a short period of time, the grade improvement of urban WECC in Hubei Province is more likely to occur between adjacent grades. With the increase in time span, the probability of this transition rises gradually. This study has proposed a set of methods for the evaluation and prediction of WECC status, which can provide important decision-making guidance for the early warning and regulation of regional differentiated WECC.

27 July 2026 in Regional Environmental Change
Verified
Journal Article
Closed access
PDF file
QQQing Qin
Qing Qin
Liang YuanLiang Yuan
Liang Yuan
HWHe Weijun
He Weijun
Dagmawi Mulugeta DegefuDagmawi Mulugeta Degefu
Dagmawi Mulugeta Degefu
XWXia Wu
Xia Wu
TRThomas Ramsey
Thomas Ramsey