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Dr. Yunqing Xuan
Swansea University

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0 Climate Change
0 Hydrology
0 Numerical Weather Prediction
0 Water Resource Management
0 Hydrometeorology

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Journal article
Published: 21 May 2021 in Agriculture
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Non-point source pollution from excessive use of fertilizers in agriculture is a major cause of the eutrophication problem in China. Understanding farmers’ decision-making concerning fertilization and identifying the influencing factors in this process are key to tackling overfertilization and related pollution issues. This paper reports a study on modelling decisions about fertilizer use based on data collected from 200 farmer households in the Three Gorges Reservoir area of China, using a well-fitted artificial neural network (ANN) with incorporated variance-based sensitivity analysis. The rate of fertilizer use estimated from the model is in good agreement with observed data. The model is further validated and tested by comparing the simulated and observed values. Results show that the model is able to identify the influencing factors and their interactions causing the variation in fertilizer use and to help pinpoint the underlying reasons. It is found that the farmers’ fertilization behavior is greatly affected by the area of cultivated land, followed by the interaction among farmers’ education level, annual income, and awareness of the importance of environmental protection. Future land consolidation is one of several ways to achieve more sustainable fertilization strategies.

ACS Style

Lihua Ma; Jiupai Ni; Luuk Fleskens; Han Wang; Yunqing Xuan. Modelling Fertilizer Use in Relation to Farmers’ Household Characteristics in Three Gorges Reservoir Area, China. Agriculture 2021, 11, 472 .

AMA Style

Lihua Ma, Jiupai Ni, Luuk Fleskens, Han Wang, Yunqing Xuan. Modelling Fertilizer Use in Relation to Farmers’ Household Characteristics in Three Gorges Reservoir Area, China. Agriculture. 2021; 11 (6):472.

Chicago/Turabian Style

Lihua Ma; Jiupai Ni; Luuk Fleskens; Han Wang; Yunqing Xuan. 2021. "Modelling Fertilizer Use in Relation to Farmers’ Household Characteristics in Three Gorges Reservoir Area, China." Agriculture 11, no. 6: 472.

Research letter
Published: 28 April 2021 in Geophysical Research Letters
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This paper presents the spatial variation of area‐orientated annual maximum daily rainfall (AMDR), represented by well‐fitted generalized extreme value (GEV) distributions, over the last century in Great Britain (GB) and Australia with respect to three spatial properties: geographic locations, sizes and shapes of the region‐of‐interest (ROI). The results show that the spatial variation of GEV location‐scale parameters is dominated by geographic locations and area sizes. In GB, there is an eastward‐decreasing banded pattern compared with a concentrically‐increasing pattern from the middle to coasts in Australia. The parameters tend to decrease with increased area sizes in both studied regions. Although the impact of the ROI shapes is insignificant, the round‐shaped regions usually have higher‐valued parameters than the elongated ones. The findings provide a new perspective to understanding the heterogeneity of extreme rainfall distribution over space driven by the complex interactions among climate, geographical features, and the practical sampling approaches.

ACS Style

H. Wang; Y. Xuan. Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets. Geophysical Research Letters 2021, 48, 1 .

AMA Style

H. Wang, Y. Xuan. Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets. Geophysical Research Letters. 2021; 48 (8):1.

Chicago/Turabian Style

H. Wang; Y. Xuan. 2021. "Spatial Variation of Extreme Rainfall Observed From Two Century‐Long Datasets." Geophysical Research Letters 48, no. 8: 1.

Article
Published: 09 December 2020
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This paper presents the spatial variation of area-orientated annual maximum daily rainfall (AMDR), represented by well-fitted generalized extreme value (GEV) distributions, from two century-long datasets of Great Britain (GB) and Australia with respect to three spatial properties: geographic locations, sizes and shapes of the region of interest (ROI). The results show that the spatial variation of GEV location-scale parameters are dominated by geographic locations and area sizes. In GB, there is an eastward-decreasing banded pattern compared with a concentrically-increasing pattern from the middle to coasts in Australia. The parameters tend to decrease with increased area sizes in both studied regions. Although the impact of the ROI shapes is insignificant, the round-shaped regions usually have higher-valued parameters than the elongated ones. The findings provide a new perspective to understanding the heterogeneity of extreme rainfall distribution over space driven by the complex interactions among climate, geographical features, and the practical sampling approaches.

ACS Style

Han Wangid; Yunqing XuaniD. Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets. 2020, 1 .

AMA Style

Han Wangid, Yunqing XuaniD. Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets. . 2020; ():1.

Chicago/Turabian Style

Han Wangid; Yunqing XuaniD. 2020. "Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets." , no. : 1.

Accepted manuscript
Published: 09 December 2020 in Environmental Research Letters
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We present a statistical method to quantify the contribution of urbanization to precipitation changes during 1958-2017 across the greater Beijing-Tianjin-Hebei (BTH) metropolitan region in northern China. We find distinct trends in precipitation in the past six decades: decreasing in annual and summer while increasing in other seasons. The spatial patterns of precipitation show discernible terrain-induced characteristics with high values in the buffer zones of plain and mountain areas and low values in the northwestern mountainous regions. Our results indicate that although urbanization has limited impacts on the trends and spatial patterns of precipitation, it has a positive contribution to the changes in precipitation for about 80% of the comparisions conducted, especially in autumn (100%), with the negative contribution being dominant in summer (66.67%). In addition, these results are sensitive to the classifications of urban and rural stations, suggesting that how to classify urban/rural areas is a crucial step to estimate the potential contribution of urbanization to precipitation changes. These findings also support that urbanization can diversify and enhance the variations in precipitation, with urban areas becoming a secondary center along with more increasing or less decreasing trends in precipitation.

ACS Style

Xiaomeng Song; Yuchen Mo; Yunqing Xuan; Quan J. Wang; Wenyan Wu; Jianyun Zhang; Xianju Zou. Impacts of urbanization on precipitation patterns in the greater Beijing–Tianjin–Hebei metropolitan region in northern China. Environmental Research Letters 2020, 16, 014042 .

AMA Style

Xiaomeng Song, Yuchen Mo, Yunqing Xuan, Quan J. Wang, Wenyan Wu, Jianyun Zhang, Xianju Zou. Impacts of urbanization on precipitation patterns in the greater Beijing–Tianjin–Hebei metropolitan region in northern China. Environmental Research Letters. 2020; 16 (1):014042.

Chicago/Turabian Style

Xiaomeng Song; Yuchen Mo; Yunqing Xuan; Quan J. Wang; Wenyan Wu; Jianyun Zhang; Xianju Zou. 2020. "Impacts of urbanization on precipitation patterns in the greater Beijing–Tianjin–Hebei metropolitan region in northern China." Environmental Research Letters 16, no. 1: 014042.

Original paper
Published: 03 November 2020 in Natural Hazards
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This paper presents an improved method of using threshold of peak rainfall intensity for robust flood/flash flood evaluation and warnings in the state of São Paulo, Brazil. The improvements involve the use of two tolerance levels and the delineating of an intermediate threshold by incorporating an exponential curve that relates rainfall intensity and Antecedent Precipitation Index (API). The application of the tolerance levels presents an average increase of 14% in the Probability of Detection (POD) of flood and flash flood occurrences above the upper threshold. Moreover, a considerable exclusion (63%) of non-occurrences of floods and flash floods in between the two thresholds significantly reduce the number of false alarms. The intermediate threshold using the exponential curves also exhibits improvements for almost all time steps of both hydrological hazards, with the best results found for floods correlating 8-h peak intensity and 8 days API, with POD and Positive Predictive Value (PPV) values equal to 81% and 82%, respectively. This study provides strong indications that the new proposed rainfall threshold-based approach can help reduce the uncertainties in predicting the occurrences of floods and flash floods.

ACS Style

Geraldo Moura Ramos Filho; Victor Hugo Rabelo Coelho; Emerson Da Silva Freitas; Yunqing Xuan; Cristiano Das Neves Almeida. An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards. Natural Hazards 2020, 105, 2409 -2429.

AMA Style

Geraldo Moura Ramos Filho, Victor Hugo Rabelo Coelho, Emerson Da Silva Freitas, Yunqing Xuan, Cristiano Das Neves Almeida. An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards. Natural Hazards. 2020; 105 (3):2409-2429.

Chicago/Turabian Style

Geraldo Moura Ramos Filho; Victor Hugo Rabelo Coelho; Emerson Da Silva Freitas; Yunqing Xuan; Cristiano Das Neves Almeida. 2020. "An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards." Natural Hazards 105, no. 3: 2409-2429.

Article
Published: 09 October 2020
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This paper presents the spatial variation of annual maximum daily rainfall (AMDR), represented by the fitted generalized extreme value (GEV) distributions, from two century-long datasets of Great Britain (GB) and Australia with respect to three spatial properties: geographic locations, sizes and shapes of the region of interest (ROI). The results show that the GEV fits well the areal AMDR. The spatial variation of the GEV location-scale parameters, quantified by the generalized linear models, is dominated by geographic locations and area sizes with an eastward-decreasing-banded-pattern in GB and a concentrically-increasing-pattern from the middle to the coasts in Australia. Although the impact of the ROI shapes is insignificant, the round-shaped regions usually have higher-valued parameters than the elongated ones. The findings provide a new perspective to understanding the heterogeneity of extreme rainfall distribution in the space driven by the complex interactions among climate, geographical features and the practical sampling approaches.

ACS Style

Han Wang; Yunqing Xuan. Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets. 2020, 1 .

AMA Style

Han Wang, Yunqing Xuan. Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets. . 2020; ():1.

Chicago/Turabian Style

Han Wang; Yunqing Xuan. 2020. "Spatial Variation of Extreme Rainfall Observed from Two Century-long Datasets." , no. : 1.

Journal article
Published: 05 June 2020 in Journal of Hydrology
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Sub-daily rainfall information is essential for many hydrological applications, but ground-based data availability is still an issue in poorly gauged regions worldwide. Satellite remote sensing missions, such as the Global Precipitation Measurement (GPM) mission, have been playing a key role in estimating sub-daily rainfall data globally. However, the quality of such information needs to be carefully evaluated. Previous studies evaluating sub-daily data from the Integrated multi-satellitE Retrievals for GPM (IMERG) product considered only the rainfall depth over pre-defined periods (e.g., hourly or half-hourly), with no analysis of the ability and quality of the product in defining the actual rainfall events and the associated properties. Thus, the objective of this study is to evaluate the performance of the IMERG Final Run Version 06B (V06B) product in capturing sub-daily rainfall events and their properties (depth, duration and intensity) over Brazil. The analysis consisted of comparing the satellite estimates against the ground-based data from 1757 sub-daily rainfall gauges for a period of three years (2015–2017). This study used the minimum inter-event time (MIT) criterion to define independent rainfall events determined by dry periods: 1, 6 and 24 h. Results show that IMERG can properly estimate the sub-daily rainfall depth for the three MITs considered, with the best results found in the southern part of the country. This means that the IMERG product represents a good source of sub-daily rainfall depth data for hydrological and hydroclimatic applications in Brazil. On the other hand, the evaluation shows large overestimations and underestimations of the IMERG product for rainfall duration and intensity properties, respectively. The results obtained from this study provide a reference for IMERG users who require sub-daily rainfall data based on events and further knowledge about its properties.

ACS Style

Emerson Da S. Freitas; Victor Coelho; Yunqing Xuan; Davi De C.D. Melo; André N. Gadelha; Elias A. Santos; Carlos De O. Galvão; Geraldo M. Ramos Filho; Luís Romero Barbosa; George J. Huffman; Walt A. Petersen; Cristiano Das N. Almeida. The performance of the IMERG satellite-based product in identifying sub-daily rainfall events and their properties. Journal of Hydrology 2020, 589, 125128 .

AMA Style

Emerson Da S. Freitas, Victor Coelho, Yunqing Xuan, Davi De C.D. Melo, André N. Gadelha, Elias A. Santos, Carlos De O. Galvão, Geraldo M. Ramos Filho, Luís Romero Barbosa, George J. Huffman, Walt A. Petersen, Cristiano Das N. Almeida. The performance of the IMERG satellite-based product in identifying sub-daily rainfall events and their properties. Journal of Hydrology. 2020; 589 ():125128.

Chicago/Turabian Style

Emerson Da S. Freitas; Victor Coelho; Yunqing Xuan; Davi De C.D. Melo; André N. Gadelha; Elias A. Santos; Carlos De O. Galvão; Geraldo M. Ramos Filho; Luís Romero Barbosa; George J. Huffman; Walt A. Petersen; Cristiano Das N. Almeida. 2020. "The performance of the IMERG satellite-based product in identifying sub-daily rainfall events and their properties." Journal of Hydrology 589, no. : 125128.

Preprint content
Published: 02 June 2020
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ACS Style

Yunqing Xuan. Responses to Interactive Comments by Julien Worms on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. 2020, 1 .

AMA Style

Yunqing Xuan. Responses to Interactive Comments by Julien Worms on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. . 2020; ():1.

Chicago/Turabian Style

Yunqing Xuan. 2020. "Responses to Interactive Comments by Julien Worms on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”." , no. : 1.

Preprint content
Published: 02 June 2020
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ACS Style

Yunqing Xuan. Responses to Interactive Comments by Geoff Pegram on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. 2020, 1 .

AMA Style

Yunqing Xuan. Responses to Interactive Comments by Geoff Pegram on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. . 2020; ():1.

Chicago/Turabian Style

Yunqing Xuan. 2020. "Responses to Interactive Comments by Geoff Pegram on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”." , no. : 1.

Preprint content
Published: 20 April 2020
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ACS Style

Yunqing Xuan. Responses to Interactive Comments by Paolo De Luca on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. 2020, 1 .

AMA Style

Yunqing Xuan. Responses to Interactive Comments by Paolo De Luca on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”. . 2020; ():1.

Chicago/Turabian Style

Yunqing Xuan. 2020. "Responses to Interactive Comments by Paolo De Luca on “Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain”." , no. : 1.

Journal article
Published: 17 March 2020 in Water
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Effective representation of precipitation inputs is one of the essential components in hydrological model structures, especially when gauge measurements for the modelled catchment are sparse. Assessment of the impact of precipitation pre-processing is often nontrivial as precipitation data are very limited in the first place. In this paper, we demonstrate a study using a semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT) to examine the impact of different precipitation pre-processing methods on model calibration and the overall model performance with regards to the operational use. A river catchment in the UK is modelled to test against the three pre-processing methods: the Centroid Point Estimation Method (CPEM), the Grid Area Method (GAM) and the Grid Point Method (GPM). Cross-calibration and validation are then carried out by using the high-resolution Centre for Ecology & Hydrology–Gridded Estimate Areal Rainfall (CEH-GEAR) dataset. The results show that the proposed methods GAM and GPM can improve the model calibration significantly against the one calibrated with the existing CPEM method used by the model; the performance differences in the validation among the calibrated models, however, remain small and become irrelevant. The findings indicate that it is preferable to always make use of high-quality rainfall data, when available, with a better pre-processing method, even with models that are previously calibrated with low-quality rainfall inputs. It is also shown that such improvements are affected by the size of catchment and become less significant for smaller catchments.

ACS Style

Salam A. Abbas; Yunqing Xuan. Impact of Precipitation Pre-Processing Methods on Hydrological Model Performance using High-Resolution Gridded Dataset. Water 2020, 12, 840 .

AMA Style

Salam A. Abbas, Yunqing Xuan. Impact of Precipitation Pre-Processing Methods on Hydrological Model Performance using High-Resolution Gridded Dataset. Water. 2020; 12 (3):840.

Chicago/Turabian Style

Salam A. Abbas; Yunqing Xuan. 2020. "Impact of Precipitation Pre-Processing Methods on Hydrological Model Performance using High-Resolution Gridded Dataset." Water 12, no. 3: 840.

Preprint content
Published: 24 February 2020
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This paper presents a study on extreme precipitation using both stationary and non-stationary Generalized Extreme Value (GEV) models over a large number of samples distributed over Great Britain (GB) for the last century, aiming to gain insights in the spatial dependency of the GEV distribution. Not only L-Moments (LM) and Maximum Likelihood (ML) estimation methods but a Bayesian Markov-Chain Monte Carlo (B-MCMC) method are incorporated into the GEV models to characterize the uncertainty in the nonstationary risk-based assessment. The samples are generated using a toolbox of spatial random sampling for grid-based data analysis (SRS-GDA). The results show that a markedly large proportion (70 %) of the samples are favour nonstationary assumption GEV models as far as the annual maximum daily rainfall (AMDR) is concerned. The most frequent AMDR, as represented by the location parameter tend to be increasing over the time for more than half of the samples and in contrast, only 8 % have a downward trend. A spatially clustering pattern is also clearly present. For rarer (with 0.1 probability) AMDR, they are shown to have a tendency of becoming more extreme over time, for more than half of the samples. For the three methods, the LM method with stationary GEV maintain best results but for AMDR values with higher probability (5-year return level); the B-MCMC method with nonstationary GEV, however, outperform other combinations by a large margin for more extreme events (50-year return level). The findings suggest that an overhaul of the current engineering design storm practice may be needed in view of environmental change impact on natural processes.

ACS Style

Han Wang; Yunqing Xuan. Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain. 2020, 2020, 1 -24.

AMA Style

Han Wang, Yunqing Xuan. Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain. . 2020; 2020 ():1-24.

Chicago/Turabian Style

Han Wang; Yunqing Xuan. 2020. "Spatial Dependency in Nonstationary GEV Modelling of Extreme Precipitation over Great Britain." 2020, no. : 1-24.

Journal article
Published: 05 December 2019 in Environmental Modelling & Software
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ACS Style

Han Wang; Yunqing Xuan. SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies. Environmental Modelling & Software 2019, 124, 1 .

AMA Style

Han Wang, Yunqing Xuan. SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies. Environmental Modelling & Software. 2019; 124 ():1.

Chicago/Turabian Style

Han Wang; Yunqing Xuan. 2019. "SRS-GDA: A spatial random sampling toolbox for grid-based hydro-climatic data analysis in environmental change studies." Environmental Modelling & Software 124, no. : 1.

Article
Published: 01 September 2019 in Water Resources Management
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Conducting trend analysis of climatic variables is one of the key steps in many climate change impact studies where trend is often checked against aggregated variables. However, there is also a strong need to investigate the trend of the data in different regimes – examples include high flow versus low flow, and heavy precipitation versus prolonged dry period. For this matter, quantile regression (QR) based methods are preferred as they can reveal the temporal dependencies of the variable in question for not only the mean value, but also its quantiles. As such, the tendencies revealed by the QR methods are more informative and helpful in studies where different mitigation methods need to be considered at different severity levels.In this paper, we demonstrate the use of several quantile regressions methods to analyse the long-term trend of rainfall records in two climatically different regions: The Dee River catchment in the United Kingdom, for which daily rainfall data of 1970–2004 are available; and the Beijing Metropolitan Area in China for which monthly rainfall data from 1950 to 2012 are available. Two quantiles are used to represent heavy rainfall condition (0.98 quantile) and severe dry condition (0.02 quantile). The trends of these two quantiles are then estimated using linear quantile regression before being spatially interpolated to demonstrate their spatial distribution (for Dee river only). The method is also compared with traditional indices such as SPI. The results show that the quantile regression method can reveal patterns for both extremely wet and dry conditions of the areas. The clear difference between trends at the chosen quantiles manifests the utility of QR in this context.

ACS Style

Salam A. Abbas; Yunqing Xuan; Xiaomeng Song. Quantile Regression Based Methods for Investigating Rainfall Trends Associated with Flooding and Drought Conditions. Water Resources Management 2019, 33, 4249 -4264.

AMA Style

Salam A. Abbas, Yunqing Xuan, Xiaomeng Song. Quantile Regression Based Methods for Investigating Rainfall Trends Associated with Flooding and Drought Conditions. Water Resources Management. 2019; 33 (12):4249-4264.

Chicago/Turabian Style

Salam A. Abbas; Yunqing Xuan; Xiaomeng Song. 2019. "Quantile Regression Based Methods for Investigating Rainfall Trends Associated with Flooding and Drought Conditions." Water Resources Management 33, no. 12: 4249-4264.

Article
Published: 10 June 2019 in Water Resources Management
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In this paper, we present a study of assessing regional water resources in a highly regulated river basin, the Dee river basin in the UK. The aims of this study include: 1) to address the issue of hydrological simulations for regulated river catchments; 2) to develop a new method revealing the trends of water resources for different scenarios (e.g. dry and wet) and 3) to facilitate water resources assessment under both climate change impacts and regulations. We use the SWAT model to model the hydrological process of the river basin with carefully designed configurations to isolate the impact from the water use regulations and practice. The spatially-distributed model simulations are then analysed with the quantile regression method to reveal the spatial and temporal patterns of regional water resources. The results show that this approach excels in presenting distributed, spatially focused trend information for extremely dry and wet scenarios, which can well address the needs of practitioners and decision-makers in dealing with long-term planning and climate change impact. The representation of the management practice in the modelling process helps identify the impact from both climate change and necessary regulatory practices, and as such lays a foundation for further study on how various management practices can mitigate the impact from other sources such as those from climate change. The novelty of the study lies in three aspects: 1) it devises a new way of isolating and representing management practice in the hydrological modelling process for regulated river basins; 2) it integrates the QR technique to study spatial-temporal trends of catchment water yield in a distributed fashion, for wet and dry scenarios instead of the mean; 3) the combination of the methods are able to reveal the impacts from various sources as well as their interactions with catchment water resources.

ACS Style

Salam A. Abbas; Yunqing Xuan. Development of a New Quantile-Based Method for the Assessment of Regional Water Resources in a Highly-Regulated River Basin. Water Resources Management 2019, 33, 3187 -3210.

AMA Style

Salam A. Abbas, Yunqing Xuan. Development of a New Quantile-Based Method for the Assessment of Regional Water Resources in a Highly-Regulated River Basin. Water Resources Management. 2019; 33 (9):3187-3210.

Chicago/Turabian Style

Salam A. Abbas; Yunqing Xuan. 2019. "Development of a New Quantile-Based Method for the Assessment of Regional Water Resources in a Highly-Regulated River Basin." Water Resources Management 33, no. 9: 3187-3210.

Journal article
Published: 12 December 2018 in Atmospheric Research
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Rainfall data from the Global Precipitation Measurement (GPM) mission provide a new source of information with high spatiotemporal resolution that overcomes the limitations of ground-based rainfall information worldwide. This study evaluates the performance of the Integrated multi-satellitE Retrievals for GPM (IMERG) Final Run product over Brazil by means of multi-temporal and -spatial analyses. The assessment of the IMERG Final Run product is based on six statistics obtained for the period between January–December 2016 (daily, monthly, and annual basis). The analysis consisted of comparing the satellite-based estimates against a ground-based gridded rainfall product created using daily records from 4911 rain gauges distributed throughout Brazil. Overall, the results show that the IMERG product can effectively capture the spatial patterns of rainfall across Brazil. However, the IMERG product presents a slight tendency in overestimating the ground-based rainfall at all timescales. Furthermore, the performance of the satellite product varies throughout the region. The higher errors and biases are found in the North and Central-West regions, but the low density of rain gauges in those regions can be a source of large deviations between IMERG estimates and observations. A large underestimation of the IMERG data is evident along the coastal zone of the North-east region, probably due to the inability of the passive microwave and infrared sensors to detect warm-rain processes over land. This study shows that the IMERG product can be a good source of rainfall data to complement the ground precipitation measurements in most of Brazil, although some uncertainties are found and need to be further studied

ACS Style

André N. Gadelha; Victor Hugo R. Coelho; Alexandre C. Xavier; Luís Romero Barbosa; Davi C.D. Melo; Yunqing Xuan; George J. Huffman; Walt A. Petersen; Cristiano Das N. Almeida. Grid box-level evaluation of IMERG over Brazil at various space and time scales. Atmospheric Research 2018, 218, 231 -244.

AMA Style

André N. Gadelha, Victor Hugo R. Coelho, Alexandre C. Xavier, Luís Romero Barbosa, Davi C.D. Melo, Yunqing Xuan, George J. Huffman, Walt A. Petersen, Cristiano Das N. Almeida. Grid box-level evaluation of IMERG over Brazil at various space and time scales. Atmospheric Research. 2018; 218 ():231-244.

Chicago/Turabian Style

André N. Gadelha; Victor Hugo R. Coelho; Alexandre C. Xavier; Luís Romero Barbosa; Davi C.D. Melo; Yunqing Xuan; George J. Huffman; Walt A. Petersen; Cristiano Das N. Almeida. 2018. "Grid box-level evaluation of IMERG over Brazil at various space and time scales." Atmospheric Research 218, no. : 231-244.

Journal article
Published: 04 April 2018 in Water
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The calculation of hydrologic frequency is an important basic step in the planning and design stage of any water conservancy project. The purpose of the frequency analysis is to deduce the hydrologic variables under different guarantee rates, and to provide hydrologic information for water conservancy project planning and design. The calculation of hydrologic frequency requires that the sample size is large enough, as only then can the statistical characteristics of samples take the place of the total statistical eigenvalues. This means that the samples can reveal the statistical characteristics of hydrologic variables and identify the randomness rule of hydrologic phenomena. Many countries in the East Asian monsoon climate zone (China, Japan and South Korea) have stipulated a sample size of 30 years for hydrologic frequency analysis. In this paper the rationality of the 30-year sample size is proved by analyzing the periodic and random rules of hydrologic phenomenon and the influencing mechanism of solar activity, and by adopting the general conclusion of the sampling theorem. Then, using the wavelet analysis method to examine annual precipitation data in a long series generated from representative precipitation observation stations in China, the strong-weak cycle of solar activity is proved to be 10 years, which is consistent with the wet-dry cycle of the representative precipitation stations (10–12 years). Finally, adopting numerical modeling to analyze the normal distribution of randomly generated samples and long-range annual precipitation data collected from representative stations, hypothesis testing (u, F and t) is used to prove that a 30-year sample size is reasonable. This research provides a reference as to how to prove the necessary sample size for relevant statistical analyses (for example, how large the sample should be for analyzing hydrologic factors trend evolution, hydrologic data consistency and ergodicity of statistical samples), thus ensuring the reliability of the analytical results.

ACS Style

Hongyan Li; Jiaqi Sun; Hongbo Zhang; Jianfeng Zhang; Kwnasue Jung; Joocheol Kim; Yunqing Xuan; Xiaojun Wang; Fengping Li. What Large Sample Size Is Sufficient for Hydrologic Frequency Analysis?—A Rational Argument for a 30-Year Hydrologic Sample Size in Water Resources Management. Water 2018, 10, 430 .

AMA Style

Hongyan Li, Jiaqi Sun, Hongbo Zhang, Jianfeng Zhang, Kwnasue Jung, Joocheol Kim, Yunqing Xuan, Xiaojun Wang, Fengping Li. What Large Sample Size Is Sufficient for Hydrologic Frequency Analysis?—A Rational Argument for a 30-Year Hydrologic Sample Size in Water Resources Management. Water. 2018; 10 (4):430.

Chicago/Turabian Style

Hongyan Li; Jiaqi Sun; Hongbo Zhang; Jianfeng Zhang; Kwnasue Jung; Joocheol Kim; Yunqing Xuan; Xiaojun Wang; Fengping Li. 2018. "What Large Sample Size Is Sufficient for Hydrologic Frequency Analysis?—A Rational Argument for a 30-Year Hydrologic Sample Size in Water Resources Management." Water 10, no. 4: 430.

Preprint content
Published: 09 February 2018
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ACS Style

Yunqing Xuan. Comments on the paper by Liu et al. "Evaluation of Doppler radar and GTS Data Assimilation for NWP Rainfall Prediction of an Extreme Summer Storm in Northern China: from the Hydrological Perspective". 2018, 1 .

AMA Style

Yunqing Xuan. Comments on the paper by Liu et al. "Evaluation of Doppler radar and GTS Data Assimilation for NWP Rainfall Prediction of an Extreme Summer Storm in Northern China: from the Hydrological Perspective". . 2018; ():1.

Chicago/Turabian Style

Yunqing Xuan. 2018. "Comments on the paper by Liu et al. "Evaluation of Doppler radar and GTS Data Assimilation for NWP Rainfall Prediction of an Extreme Summer Storm in Northern China: from the Hydrological Perspective"." , no. : 1.

Journal article
Published: 29 November 2016 in Hydrology and Earth System Sciences
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Impact-focused studies of extreme weather require coupling of accurate simulations of weather and climate systems and impact-measuring hydrological models which themselves demand larger computer resources. In this paper, we present a preliminary analysis of a high-performance computing (HPC)-based hydrological modelling approach, which is aimed at utilizing and maximizing HPC power resources, to support the study on extreme weather impact due to climate change. Here, four case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) with high-resolution simulation suite UKV, alongside a Linux-based hydrological model, Hydrological Predictions for the Environment (HYPE). The results of this study suggest that the coupled hydro-meteorological model was still able to capture the major flood peaks, compared with the conventional gauge- or radar-driving forecast, but with the added value of much extended forecast lead time. The high-resolution rainfall estimation produced by the UKV performs similarly to that of radar rainfall products in the first 2–3 days of tested flood events, but the uncertainties particularly increased as the forecast horizon goes beyond 3 days. This study takes a step forward to identify how the online mode approach can be used, where both numerical weather prediction and the hydrological model are executed, either simultaneously or on the same hardware infrastructures, so that more effective interaction and communication can be achieved and maintained between the models. But the concluding comments are that running the entire system on a reasonably powerful HPC platform does not yet allow for real-time simulations, even without the most complex and demanding data simulation part.

ACS Style

Dehua Zhu; Shirley Echendu; Yunqing Xuan; Mike Webster; Ian Cluckie. Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study. Hydrology and Earth System Sciences 2016, 20, 4707 -4715.

AMA Style

Dehua Zhu, Shirley Echendu, Yunqing Xuan, Mike Webster, Ian Cluckie. Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study. Hydrology and Earth System Sciences. 2016; 20 (12):4707-4715.

Chicago/Turabian Style

Dehua Zhu; Shirley Echendu; Yunqing Xuan; Mike Webster; Ian Cluckie. 2016. "Coupled hydro-meteorological modelling on a HPC platform for high-resolution extreme weather impact study." Hydrology and Earth System Sciences 20, no. 12: 4707-4715.

Preprint content
Published: 24 June 2016
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High performance computing (HPC) has long been used in the disciplines of atmospheric and oceanic sciences, and remains the main tool of choice to extract numerical solutions to complex geophysical problems on the global scale, often accompanied with very large numbers of degrees of freedoms. However, with the growing recognition that the spatially distributed feedback from the land surface is important to weather and the climate system, representation of the land surface is established with increasingly complex (and physically complete) models, which often leads to the coupling of heterogeneous models such as numerical weather prediction (NWP) models and hydrological models. As a result, the spatial grids and the temporal resolutions have become finer and thereby computers with far greater computational and storage capacity are in great demand than those used in the past. Additionally, impact-focused studies that require coupling of accurate simulations of weather/climate systems as well as impact-measuring hydrological models that demand larger computer resources in its own right. In this paper, we present a preliminary analysis of an HPC-based hydrological modelling approach, which is aimed at utilising and maximising HPC power resource, to support the study on extreme weather impact due to climate change. Here, two case studies are presented through implementation on the HPC Wales platform of the UK mesoscale meteorological Unified Model (UM) UKV, alongside a Linux-based hydrological model, HYdrological Predictions for the Environment (HYPE). The results of this study suggest that high resolution rainfall estimation produced by the UKV has similar performance to that of NIMROD radar rainfall products as input in a hydrological model, but with the added-value of much extended forecast lead-time.

ACS Style

Dehua Zhu; Shirley Echendu; Yunqing Xuan; Mike Webster; Ian Cluckie. Coupled hydro-meteorological modelling on HPC platform for high resolution extreme weather impact study. 2016, 2016, 1 -15.

AMA Style

Dehua Zhu, Shirley Echendu, Yunqing Xuan, Mike Webster, Ian Cluckie. Coupled hydro-meteorological modelling on HPC platform for high resolution extreme weather impact study. . 2016; 2016 ():1-15.

Chicago/Turabian Style

Dehua Zhu; Shirley Echendu; Yunqing Xuan; Mike Webster; Ian Cluckie. 2016. "Coupled hydro-meteorological modelling on HPC platform for high resolution extreme weather impact study." 2016, no. : 1-15.