Environmental and Human Impacts on Hydrological Drought

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (1 March 2023) | Viewed by 3694

Special Issue Editors


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Guest Editor
College of Water Resources and Architectural Engineering, Northwest A&F University, Yangling 712100, China
Interests: drought severity analysis; climate change; crop modeling; drought projection; statistical down scaling

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Guest Editor
College of Water Resources and Architectural Engineering, Qingdao University, Qingdao, China
Interests: hydrology; climate change modeling; groundwater quality; GIS; Remote Sensing
College of Water Resources and Architectural Engineering, Northwest Agriculture & Forest University, Yangling 712100, China
Interests: water resources operation and management; water resources system theory and sustainable utilization; basin hydrological simulation and uncertainty analysis; optimization method
Special Issues, Collections and Topics in MDPI journals
Faculty of Modern Agricultural Engineering, Kunming University of Science and Technology, Kunming 650500, China
Interests: climate change; agricultural production; adaptation measures; crop modeling
Special Issues, Collections and Topics in MDPI journals
School of Water Resources and Architectural Engineering, Northwest A&F University, Yangling, China
Interests: drought assessment; climate change; DSSAT model; drought risk assessment; spatial and temporal variability
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Climate change and human activities can significantly alter hydrological cycle processes, resulting in more frequent and extensive drought disasters with devastating impacts on the economy, society and environment. Therefore, an increasing number of studies have investigated drought evolution in changing environments.

This Special Issue aims to analyse the impacts of the environment and humans on drought (meteorological drought, agricultural drought and hydrological drought). We encourage researchers to differentiate between the effects of climate change and human activities on drought propagation. Papers should also reveal the potential impact of drought, assess the risk of future droughts, and propose strategies for coping with them. This is of great significance to drought relief, ecological security and food security. 

Original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Temporal and spatial variability of drought;
  • Impact of climate change on drought;
  • Impact of human activities on drought;
  • Effect of climate change and human activities on drought propagation;
  • Separating the effects of climate change and human activities on drought;
  • Assessment of potential impacts of drought;
  • Drought risk assessment and coping strategies.

We look forward to receiving your contributions.

Prof. Dr. Yi Li
Dr. Tehseen Javed
Dr. Zhe Yang
Dr. Na Li
Dr. Ning Yao
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • drought
  • climate change
  • human activity
  • risk assessment
  • spatial and temporal variability

Published Papers (2 papers)

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Research

23 pages, 9809 KiB  
Article
Forecasting Monthly Water Deficit Based on Multi-Variable Linear Regression and Random Forest Models
by Yi Li, Kangkang Wei, Ke Chen, Jianqiang He, Yong Zhao, Guang Yang, Ning Yao, Ben Niu, Bin Wang, Lei Wang, Puyu Feng and Zhe Yang
Water 2023, 15(6), 1075; https://doi.org/10.3390/w15061075 - 10 Mar 2023
Cited by 4 | Viewed by 2426
Abstract
Forecasting water deficit is challenging because it is modulated by uncertain climate, different environmental and anthropic factors, especially in arid and semi-arid northwestern China. The monthly water deficit index D at 44 sites in northwestern China over 1961−2020 were calculated. The key large-scale [...] Read more.
Forecasting water deficit is challenging because it is modulated by uncertain climate, different environmental and anthropic factors, especially in arid and semi-arid northwestern China. The monthly water deficit index D at 44 sites in northwestern China over 1961−2020 were calculated. The key large-scale circulation indices related to D were screened using Pearson’s correlation (r). Subsequently, we predicted monthly D with the multi-variable linear regression (MLR) and random forest (RF) models at certain lagged times after being strictly calibrated and validated. The results showed the following: (1) The r between the monthly D and the screened key circulation indices varied from 0.71 to 0.85 and the lagged time ranged from 1 to 12 months. (2) The calibrated and validated performance of the established MLR and RF models were all good at the 44 sites. Overall, the RF model outperformed the MLR model with a higher coefficient of determination (R2 > 0.8 at 38 sites) and mean absolute percentage error (MAPE < 50% at 30 sites). (3) The Pacific Polar Vortex Intensity (PPVI) had the greatest impact on D in northwestern China, followed by SSRP, WPWPA, NANRP, and PPVA. (4) The forecasted monthly D values based on RF models indicated that the water deficit in northwestern China would be most severe (−239.7 to −62.3 mm) in August 2022. In conclusion, using multiple large-scale climate signals to drive a machine learning model is a promising method for predicting water deficit conditions in northwestern China. Full article
(This article belongs to the Special Issue Environmental and Human Impacts on Hydrological Drought)
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16 pages, 4270 KiB  
Article
Impacts of Different Socioeconomic Development Levels on Extremely Wet/Dry Events in Mainland China
by Qingfeng Zhang, Yi Li, Qiaoyu Hu, Ning Yao, Xiaoyan Song, Fenggui Liu, Bakhtiyor Pulatov, Qingtao Meng and Puyu Feng
Water 2022, 14(23), 3950; https://doi.org/10.3390/w14233950 - 4 Dec 2022
Cited by 1 | Viewed by 1500
Abstract
The impacts of human activity (denoted by population), economic, and social development (denoted by gross domestic product–GDP) on extremely wet/dry (or drought) events are important for humans to tackle extreme hazards. This research aims to investigate the variations in maximum values (SPEI_MAX) and [...] Read more.
The impacts of human activity (denoted by population), economic, and social development (denoted by gross domestic product–GDP) on extremely wet/dry (or drought) events are important for humans to tackle extreme hazards. This research aims to investigate the variations in maximum values (SPEI_MAX) and minimum values (SPEI_MIN) of a 12 month standardized precipitation evapotranspiration index (SPEI12-month) for the selected 525 sites at different socioeconomic development levels (SDLs) (classified by population and GDP) in China between 2000–2018, and to analyze the impacts of increased population/GDP/SDLs on extremely wet/dry events. The linear correlations between SPEI12-month/SPEI_MAX/SPEI_MIN and population/GDP were conducted for all the sites. The relationship between linear slopes of population (PopuLS)/GDP(GDPLS) and SPEI_MAX (SPEI_MAXLS)/SPEI_MIN (SPEI_MINLS) were further studied. The results show that the extremely wet events denoted by SPEI_MAX become worse and the extreme drought events denoted by SPEI_MIN tend to be milder over time. The years 2016 and 2011 were extremely wet and extremely dry in China. There were general increasing trends in SPEI_MAX and decreasing trends in SPEI_MIN as the SDL increased from 1 to 6. This gradual, continuous increase/decrease potentially affected levels 5 and 6. Moreover, extremely wet events were more severe in developed big municipal cities of higher SDLs and extreme drought events were more severe for lower SDLs. This research can supply references for policy makers to prevent extreme disasters. Full article
(This article belongs to the Special Issue Environmental and Human Impacts on Hydrological Drought)
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