Editorial

4 pages, 186 KiB

Open AccessEditorial

Application of Remote Sensing and GIS in Drought and Flood Assessment and Monitoring

by Yaohuan Huang, Yesen Liu, Runhe Shi and Hongyan Ren

Water 2023, 15(3), 541; https://0-doi-org.brum.beds.ac.uk/10.3390/w15030541 - 30 Jan 2023

Cited by 1 | Viewed by 2997

Driven by global change and population pressure, droughts and floods have been two of the most serious natural hazards, leading to crop losses and economic havoc in many areas and ultimately affecting more people globally than any other natural hazard [...] Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

Research

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15 pages, 4577 KiB

Open AccessFeature PaperArticle

Spatial and Temporal Pattern of Rainstorms Based on Manifold Learning Algorithm

by Yuanyuan Liu, Yesen Liu, Hancheng Ren, Longgang Du, Shu Liu, Li Zhang, Caiyuan Wang and Qiang Gao

Water 2023, 15(1), 37; https://0-doi-org.brum.beds.ac.uk/10.3390/w15010037 - 22 Dec 2022

Cited by 1 | Viewed by 1542

Abstract

Identifying the patterns of rainstorms is essential for improving the precision and accuracy of flood forecasts and constructing flood disaster prevention systems. In this study, we used a manifold learning algorithm method of machine learning to analyze rainstorm patterns. We analyzed the spatial–temporal [...] Read more.

Identifying the patterns of rainstorms is essential for improving the precision and accuracy of flood forecasts and constructing flood disaster prevention systems. In this study, we used a manifold learning algorithm method of machine learning to analyze rainstorm patterns. We analyzed the spatial–temporal characteristics of heavy rain in Beijing and Shenzhen. The results showed a strong correlation between the spatial–temporal pattern of rainstorms and underlying topography in Beijing. However, in Shenzhen, the spatial–temporal distribution characteristics of rainstorms were more closely related to the source of water vapor causing the rainfall, and the variation in characteristics was more complex and diverse. This method may be used to quantitatively describe the development and dynamic spatial–temporal patterns of rainfall. In this study, we found that spatial–temporal rainfall distribution characteristics, extracted by machine learning technology could be explained by physical mechanisms consistent with the climatic characteristics and topographic conditions of the region. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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12 pages, 2341 KiB

Open AccessArticle

Analysis of Water Environment Quality Changes and Influencing Factors during the “Thirteenth Five-Year Plan” Period in Heilongjiang Province

by Wei Chen, Yu Bai, Bo Li, Chengcheng Feng and Mi Zhou

Water 2022, 14(15), 2367; https://0-doi-org.brum.beds.ac.uk/10.3390/w14152367 - 31 Jul 2022

Cited by 3 | Viewed by 1684

Abstract

Heilongjiang Province is located in the northeastern part of China and is the province with the highest latitude in China. As Heilongjiang Province is the most important grain production base in China, the Chinese government attaches great importance to the quality of the [...] Read more.

Heilongjiang Province is located in the northeastern part of China and is the province with the highest latitude in China. As Heilongjiang Province is the most important grain production base in China, the Chinese government attaches great importance to the quality of the ecological environment in Heilongjiang Province, especially the analysis of changes in the quality of the water environment and their driving factors. We studied the changes in the environmental quality of surface water in Heilongjiang Province during the “13th Five-Year Plan” period (2016–2020), and analyzed the surface water for four major pollutants including the permanganate index, chemical oxygen demand, ammonia nitrogen and total phosphorus, and the change trends of the proportion of the water quality of class I–III and the proportion of the water quality of inferior class V. The results show that the environmental quality of surface water in Heilongjiang Province has improved significantly during the “13th Five-Year Plan”. The analysis of the driving factors of the change of surface water environment quality shows that the population, the primary industry, the tertiary industry and forestry are the main factors affecting the change of water environment quality in Heilongjiang Province. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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13 pages, 2974 KiB

Open AccessArticle

Long-Term Study of Monitoring History and Change Trends in Surface Water Quality in China

by Fengying Zhang, Lanyu Lin, Wenpan Li, Dekun Fang, Zhuo Lv, Mingsheng Li, Guangwen Ma, Yeyao Wang, Li Wang and Lihuan He

Water 2022, 14(13), 2134; https://0-doi-org.brum.beds.ac.uk/10.3390/w14132134 - 04 Jul 2022

Cited by 7 | Viewed by 2704

Abstract

To investigate the monitoring history and long-term change trends in surface water quality in China since the reform and opening up, the history of surface water environment monitoring is summarized, including monitoring scope, monitoring methods, and technical requirements. Temporal and spatial patterns of [...] Read more.

To investigate the monitoring history and long-term change trends in surface water quality in China since the reform and opening up, the history of surface water environment monitoring is summarized, including monitoring scope, monitoring methods, and technical requirements. Temporal and spatial patterns of surface water quality in China were analyzed based on the monitoring results. In the past 40 years, the monitoring targets for surface water quality have been continuously improved, the frequency of monitoring has become more science-based, and the monitoring indicators are now comprehensive. Overall, the temporal change trend in surface water quality has followed a “fluctuating changes stage—rapid deterioration stage—fluctuations stalemate stage—rapid improvement stage” pattern. However, the current regional surface water quality is still in a polluted status, and there is a gap between surface water quality status and the goal of building a well-off society. At present, China’s surface water pollution is prone to high numbers of incidents and the treatment of surface water pollution has entered a crucial stage. The potential for the continuous reduction of major pollutant discharges has become more challenging, and the marginal cost for pollution control has increased. It is very difficult to comprehensively solve the outstanding water environment problems. In addition to strengthening the existing work on surface water quality control, it is also necessary to strengthen the work of risk identification, early warning, and regulation implementation of the surface water environment. During the 14th year plan period (2021–2025), the overall planning on water resources, water ecology, and water quality will be implemented, and beautiful rivers and lakes will be created. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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13 pages, 8228 KiB

Open AccessArticle

Spatiotemporal Modes of Short Time Rainstorms Based on High-Dimensional Data: A Case Study of the Urban Area of Beijing, China

by Wei Liu, Sheng Chen and Fuchang Tian

Water 2021, 13(24), 3597; https://0-doi-org.brum.beds.ac.uk/10.3390/w13243597 - 14 Dec 2021

Cited by 3 | Viewed by 1773

Abstract

The identification of the characteristics of short time rainstorms in urban areas is a difficult problem. The traditional rainfall definition methods, using rainfall graph or a GIS map, respectively reflect the temporal or spatial variations of a rainfall process, but do not regard [...] Read more.

The identification of the characteristics of short time rainstorms in urban areas is a difficult problem. The traditional rainfall definition methods, using rainfall graph or a GIS map, respectively reflect the temporal or spatial variations of a rainfall process, but do not regard a rainfall as one complete process including its temporal and spatial dimension. In this paper, we present an approach to define typical modes of rainfall from the temporal and spatial dimensions. Firstly, independent rainfall processes are divided based on the continuous monitoring data of multiple rainfall stations. Subsequently, algorithms are applied to identify the typical spatiotemporal modes of rainfall and reconstruction of the process of modes, including dimensionality reduction, clustering, and reconstruction. This approach is used to analyze the monitoring data (5 min intervals) from 2004 to 2016 of 14 rainfall stations in Beijing. The results show that there are three modes of rainstorms in the Beijing urban area, which account for 31.8%, 13.7%, and 54.6% of the total processes. Rainstorm of mode 1 moves from the northwest to the center of Beijing, then spreads to the eastern part of the urban area; rainstorm of mode 2 occurs in the southwestern region of the urban area, and gradually northward, but there is no rainfall in the mountainous northwest; rainstorm of mode 3 is concentrated in the central, eastern, and southern regions. The approach and results of this study can be applied to rainstorm forecasting or flood prevention. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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19 pages, 2495 KiB

Open AccessArticle

Improvement in Ridge Coefficient Optimization Criterion for Ridge Estimation-Based Dynamic System Response Curve Method in Flood Forecasting

by Kexin Liu, Weimin Bao, Yufeng Hu, Yiqun Sun, Dongjing Li, Kuang Li and Lili Liang

Water 2021, 13(24), 3483; https://0-doi-org.brum.beds.ac.uk/10.3390/w13243483 - 07 Dec 2021

Cited by 2 | Viewed by 1968

Abstract

The ridge estimation-based dynamic system response curve (DSRC-R) method, which is an improvement of the dynamic system response curve (DSRC) method via the ridge estimation method, has illustrated its good robustness. However, the optimization criterion for the ridge coefficient in the DSRC-R method [...] Read more.

The ridge estimation-based dynamic system response curve (DSRC-R) method, which is an improvement of the dynamic system response curve (DSRC) method via the ridge estimation method, has illustrated its good robustness. However, the optimization criterion for the ridge coefficient in the DSRC-R method still needs further study. In view of this, a new optimization criterion called the balance and random degree criterion considering the sum of squares of flow errors (BSR) is proposed in this paper according to the properties of model-simulated residuals. In this criterion, two indexes, namely, the random degree of simulated residuals and the balance degree of simulated residuals, are introduced to describe the independence and the zero mean property of simulated residuals, respectively. Therefore, the BSR criterion is constructed by combining the sum of squares of flow errors with the two indexes. The BSR criterion, L-curve criterion and the minimum sum of squares of flow errors (MSSFE) criterion are tested on both synthetic cases and real-data cases. The results show that the BSR criterion is better than the L-curve criterion in minimizing the sum of squares of flow residuals and increasing the ridge coefficient optimization speed. Moreover, the BSR criterion has an advantage over the MSSFE criterion in making the estimated rainfall error more stable. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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12 pages, 4422 KiB

Open AccessFeature PaperArticle

The Impact of Rainfall Movement Direction on Urban Runoff Cannot Be Ignored in Urban Hydrologic Management

by Yesen Liu, Yaohuan Huang, Yuanyuan Liu, Kuang Li and Min Li

Water 2021, 13(20), 2923; https://0-doi-org.brum.beds.ac.uk/10.3390/w13202923 - 17 Oct 2021

Cited by 5 | Viewed by 1709

Abstract

Urban floods have been exacerbated globally, associated with increasing spatial-temporal variations in rainfall. However, compared with rainfall variabilities of intensity and duration, the effect of rainfall movement direction is always ignored. Based on 1313 rainfall scenarios with different combinations of rainfall intensity and [...] Read more.

Urban floods have been exacerbated globally, associated with increasing spatial-temporal variations in rainfall. However, compared with rainfall variabilities of intensity and duration, the effect of rainfall movement direction is always ignored. Based on 1313 rainfall scenarios with different combinations of rainfall intensity and rainfall movement direction in the typically rainy city of Shenzhen in China, we find that the effect of rainfall movement direction on the peak runoff may reach up to 20%, which will decrease to less than 5% under heavy rainfall intensity conditions. In addition, our results show that the impact of rainfall movement direction is almost symmetrical and is associated with the direction of the river. The closer rainfall movement direction is to the Linear Directional Mean of rivers, the larger is the peak runoff of section. Our results reveal that rainfall movement direction is significant to urban peak runoff in the downstream reaches, which should be considered in urban hydrological analysis. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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23 pages, 6593 KiB

Open AccessArticle

Analysis of the Influencing Factors of Drought Events Based on GRACE Data under Different Climatic Conditions: A Case Study in Mainland China

by Lilu Cui, Cheng Zhang, Chaolong Yao, Zhicai Luo, Xiaolong Wang and Qiong Li

Water 2021, 13(18), 2575; https://0-doi-org.brum.beds.ac.uk/10.3390/w13182575 - 18 Sep 2021

Cited by 14 | Viewed by 3120

Abstract

The occurrence of droughts has become more frequent, and their intensity has increased in mainland China. With the aim of better understanding the influence of climate background on drought events in this region, we analyzed the role of the drought-related factors and extreme [...] Read more.

The occurrence of droughts has become more frequent, and their intensity has increased in mainland China. With the aim of better understanding the influence of climate background on drought events in this region, we analyzed the role of the drought-related factors and extreme climate in the formation of droughts by investigating the relationship between the drought severity index (denoted as GRACE-DSI) based on the terrestrial water storage changes (TWSCs) derived from Gravity Recovery and Climate Experiment (GRACE) time-variable gravity fields and drought-related factors/extreme climate. The results show that GRACE-DSI was consistent with the self-calibrating Palmer Drought Severity Index in mainland China, especially for the subtropical monsoon climate, with a correlation of 0.72. Precipitation (PPT) and evapotranspiration (ET) are the main factors causing drought events. However, they play different roles under different climate settings. The regions under temperate monsoon climate and subtropical monsoon climate were more impacted by PPT, while ET played a leading role in the regions under temperate continental climate and plateau mountain climate. Moreover, El Niño–Southern Oscillation (ENSO) and North Atlantic Oscillation (NAO) events mainly caused abnormalities in PPT and ET by affecting the strength of monsoons (East Asian and Indian monsoon) and regional highs (Subtropical High, Siberian High, Central Asian High, etc.). As a result, the various affected regions were prone to droughts during ENSO or NAO events, which disturbed the normal operation of atmospheric circulation in different ways. The results of this study are valuable in the efforts to understand the formation mechanism of drought events in mainland China. Full article

(This article belongs to the Special Issue Application of Remote Sensing and GIS in Droughts and Floods Assessment and Monitoring)

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