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While reliable drought prediction is fundamental for drought mitigation and water resources management, it is still a challenge to develop robust drought prediction models due to complex local hydro-climatic conditions and various predictors. Sea surface temperature (SST) is considered as the fundamental predictor to develop drought prediction models. However, traditional models usually extract SST signals from one or several specific sea zones within a given time span, which limits full use of SST signals for drought prediction. Here, we introduce a new meteorological drought prediction approach by using the antecedent SST fluctuation pattern (ASFP) and machine learning techniques (e.g., support vector regression (SVR), random forest (RF), and extreme learning machine (ELM)). Three models (i.e., ASFP-SVR, ASFP-ELM, and ASFP-RF) are developed for ensemble, probability, and deterministic drought predictions. The Colorado, Danube, Orange, and Pearl River basins with frequent droughts over different continents are selected, as the cases, where standardized precipitation evapotranspiration index (SPEI) are predicted at the 1° × 1° resolution with 1- and 3-month lead times. Results show that the ASFP-ELM model can effectively predict space-time evolutions of drought events with satisfactory skills, outperforming the ASFP-SVR and ASFP-RF models. Our study has potential to provide a reliable tool for drought prediction, which further supports the development of drought early warning systems.
Jun Li; Zhaoli Wang; Xushu Wu; Chong‐Yu Xu; Shenglian Guo; Xiaohong Chen; Zhenxing Zhang. Robust meteorological drought prediction using antecedent SST fluctuations and machine learning. Water Resources Research 2021, 57, 1 .
AMA StyleJun Li, Zhaoli Wang, Xushu Wu, Chong‐Yu Xu, Shenglian Guo, Xiaohong Chen, Zhenxing Zhang. Robust meteorological drought prediction using antecedent SST fluctuations and machine learning. Water Resources Research. 2021; 57 (8):1.
Chicago/Turabian StyleJun Li; Zhaoli Wang; Xushu Wu; Chong‐Yu Xu; Shenglian Guo; Xiaohong Chen; Zhenxing Zhang. 2021. "Robust meteorological drought prediction using antecedent SST fluctuations and machine learning." Water Resources Research 57, no. 8: 1.
Compound dry and hot conditions frequently cause large impacts on ecosystems and societies worldwide. A suite of indices is available for the assessment of droughts and heatwaves, yet there is no index available for incorporating the joint variability of dry and hot conditions at the sub-monthly scale. Here we introduce a daily-scale index, called the standardized compound drought and heat index (SCDHI), to assess compound dry-hot conditions. The SCDHI is based on a daily drought index (the standardized antecedent precipitation evapotranspiration index – SAPEI), the daily-scale standardized temperature index (STI), and a joint probability distribution method. The new index is verified against real-world compound dry and hot events and associated observed vegetation impacts in China. The SCDHI can not only capture compound dry and hot events at both monthly and sub-monthly scales, but is also a good indicator for associated vegetation impacts. Using the SCDHI, we quantify the frequency, severity, duration, and intensity of compound dry-hot events during the historical period and assess the ability of climate models to reproduce these characteristics in China. We find that compound events whose severity is at least light and which last longer than 2 weeks generally persisted for 20–35 d in China. Southern China suffered from compound events most frequently, and the most severe compound events were mainly detected in this region. Climate models generally overestimate the frequency, duration, severity, and intensity of compound events in China, especially for western regions, which can be attributed to a too strong dependence between the SAPEI and STI in those models. The SCDHI provides a new tool to quantify sub-monthly characteristics of compound dry and hot events and to monitor their initiation, development, and decay. This is important information for decision-makers and stakeholders to release early and timely warnings.
Jun Li; Zhaoli Wang; Xushu Wu; Jakob Zscheischler; Shenglian Guo; Xiaohong Chen. A standardized index for assessing sub-monthly compound dry and hot conditions with application in China. Hydrology and Earth System Sciences 2021, 25, 1587 -1601.
AMA StyleJun Li, Zhaoli Wang, Xushu Wu, Jakob Zscheischler, Shenglian Guo, Xiaohong Chen. A standardized index for assessing sub-monthly compound dry and hot conditions with application in China. Hydrology and Earth System Sciences. 2021; 25 (3):1587-1601.
Chicago/Turabian StyleJun Li; Zhaoli Wang; Xushu Wu; Jakob Zscheischler; Shenglian Guo; Xiaohong Chen. 2021. "A standardized index for assessing sub-monthly compound dry and hot conditions with application in China." Hydrology and Earth System Sciences 25, no. 3: 1587-1601.
Availability of precipitation data at high spatial and temporal resolution is crucial for the understanding of precipitation behaviors that are determinant for environmental aspects such as hydrology, ecology, and social aspects like agriculture, food security, or health issues. This study evaluates the performance of 3B42-V7 satellite-based precipitation product on extreme precipitation estimates in China, by using the Fuzzy C-Means algorithm and L-moment-based regional frequency analysis method. The China Gauge-based Daily Precipitation Analysis (CGDPA) product is employed to measure the estimation biases of 3B42-V7. Results show that: (1) for most regions of China, the Generalized Extreme Value and Generalized Normal distributions are preferable for extreme precipitation estimates; (2) the extreme precipitation estimations of 3B42-V7 for different return periods have a high correlation with those of CGDPA, with biases within 25% for a majority of China on extreme precipitation estimates.
Jiachao Chen; Zhaoli Wang; Xushu Wu; Chengguang Lai; Xiaohong Chen. Evaluation of TMPA 3B42-V7 Product on Extreme Precipitation Estimates. Remote Sensing 2021, 13, 209 .
AMA StyleJiachao Chen, Zhaoli Wang, Xushu Wu, Chengguang Lai, Xiaohong Chen. Evaluation of TMPA 3B42-V7 Product on Extreme Precipitation Estimates. Remote Sensing. 2021; 13 (2):209.
Chicago/Turabian StyleJiachao Chen; Zhaoli Wang; Xushu Wu; Chengguang Lai; Xiaohong Chen. 2021. "Evaluation of TMPA 3B42-V7 Product on Extreme Precipitation Estimates." Remote Sensing 13, no. 2: 209.
Climate change has emerged as a key issue for hydropower management and development in future. This study systematically evaluates the impact of climate change on reservoir inflow, hydropower output, sustainability, and efficiency under the representative concentration pathway (RCP) scenarios (RCP2.6, 4.5 and 8.5) by taking the Pearl River basin in China as the case. The variable infiltration capacity model is coupled with global climate models to project future hydropower changes. It is shown that future reservoir inflow and hydropower output significantly differ from the historical ones. Dry years in future are projected to become drier leading to decrease in hydropower output that in turn reduces hydropower reliability and resiliency and increases the vulnerability. Wet years would get wetter, but the hydropower output does not necessarily increase possibly due to more surplus water released from reservoirs during flood seasons. For normal years, neither of reservoir inflow and hydropower output displays obvious changes. Moreover, water use efficiency of the West River in wet years and that of the North River in wet, normal and dry years would be lower in future, while the East River during non-flood seasons in dry years is expected to have higher water use efficiency. Our study can potentially provide an insight into the response of hydropower to climate change and help policy-makers and stakeholders manage future hydropower generation.
Jun Li; Zhaoli Wang; Xushu Wu; Bo Ming; Lu Chen; Xiaohong Chen. Evident response of future hydropower generation to climate change. Journal of Hydrology 2020, 590, 125385 .
AMA StyleJun Li, Zhaoli Wang, Xushu Wu, Bo Ming, Lu Chen, Xiaohong Chen. Evident response of future hydropower generation to climate change. Journal of Hydrology. 2020; 590 ():125385.
Chicago/Turabian StyleJun Li; Zhaoli Wang; Xushu Wu; Bo Ming; Lu Chen; Xiaohong Chen. 2020. "Evident response of future hydropower generation to climate change." Journal of Hydrology 590, no. : 125385.
Anthropogenic activities have a tremendous impact on water ecosystems worldwide, especially in China. To quantitatively evaluate the hydrological alteration connected with aquatic lives and river ecological risks, we took the Beijiang River located in South China as the case study and used ecosurplus (defined as ecological carrying capacity exceeding ecological consumption)/ecodeficit (defined as ecological consumption exceeding carrying capacity) and Indicators of Hydrological Alterations to evaluate hydrological changes. The Ecologically Relevant Hydrologic Indicators were employed to select the key indices of Indicators of Hydrological Alterations, and the eco-environmental water demand calculation provide an effective way for the reservoir operation. Results showed that: (1) High flows contributed more to the ecodeficit, while low flows contributed more to the ecosurplus; (2) the ecodeficit in some parts of the river basin might exceed the ecosurplus after reservoir construction, especially along the main stream; and (3) the determination of eco-environmental water demand is a feasible way for improving the environment by controlling reservoirs. The current study can help guide the optimization of hydrological operation in the basin toward making the ecosystem healthier and has potential to further provide a reference for other basins in terms of hydrological alterations driven by anthropogenic activities.
Jiakai Du; Xushu Wu; Zhaoli Wang; Jun Li; Xiaohong Chen. Reservoir-Induced Hydrological Alterations Using Ecologically Related Hydrologic Metrics: Case Study in the Beijiang River, China. Water 2020, 12, 2008 .
AMA StyleJiakai Du, Xushu Wu, Zhaoli Wang, Jun Li, Xiaohong Chen. Reservoir-Induced Hydrological Alterations Using Ecologically Related Hydrologic Metrics: Case Study in the Beijiang River, China. Water. 2020; 12 (7):2008.
Chicago/Turabian StyleJiakai Du; Xushu Wu; Zhaoli Wang; Jun Li; Xiaohong Chen. 2020. "Reservoir-Induced Hydrological Alterations Using Ecologically Related Hydrologic Metrics: Case Study in the Beijiang River, China." Water 12, no. 7: 2008.
As atmospheric moisture holding capacity is positively dependent on temperatures, a large intensification of precipitation extremes is projected under foreseeable climate warming. Flooding that is mainly attributed to extreme storms usually accounts for an ambitious target in weather‐related hazard mitigation over China. Previous works seldom focused on flooding evolution patterns under climate change at a national scale, and fewer flooding projections considered the estimation uncertainty sourced from limited samples. This study systematically projected changes in flood quantiles based on annual maximum series and seasonality and also evaluated the variations of sampling uncertainty for 151 catchments over mainland China under the emission scenario of representative concentration pathway (RCP) 8.5. In order to project future streamflow series, the bias‐corrected outputs of six global climate models (GCMs) were input into a best‐performing hydrological model, which was selected from four calibrated hydrological models based on the KGE criteria. The Pearson type‐III (P‐III) distribution and L‐moments (L‐M) method were employed to derive the flood quantiles for different return periods during historical (1961‐2005) and future (2056‐2100) periods, and the bootstrapping method was applied to estimate the sampling uncertainty. A regression trend method was used to track the variations of flood seasonality in the context of climate warming. Our results project earlier flood timing and larger flood quantiles for most catchments in future period than those in historical period, despite being accompanied by substantial spatial variations. We also project that the sampling uncertainty in estimating flood quantiles is increased in a warming future. Many catchments are exposed to dramatic changes in both flood quantile and estimation uncertainty by over 50%, while only few catchments are projected to have decreasing flood risks. These results suggest an urgent need to improve the functionality of early warning systems and increase societal resilience to warming climates over China. This article is protected by copyright. All rights reserved.
Lei Gu; Jiabo Yin; Hongbo Zhang; Hui‐Min Wang; Guang Yang; Xushu Wu. On future flood magnitudes and estimation uncertainty across 151 catchments in mainland China. International Journal of Climatology 2020, 41, 1 .
AMA StyleLei Gu, Jiabo Yin, Hongbo Zhang, Hui‐Min Wang, Guang Yang, Xushu Wu. On future flood magnitudes and estimation uncertainty across 151 catchments in mainland China. International Journal of Climatology. 2020; 41 (S1):1.
Chicago/Turabian StyleLei Gu; Jiabo Yin; Hongbo Zhang; Hui‐Min Wang; Guang Yang; Xushu Wu. 2020. "On future flood magnitudes and estimation uncertainty across 151 catchments in mainland China." International Journal of Climatology 41, no. S1: 1.
Flash drought is a space–time phenomenon with rapid intensification nature that poses a series of challenges for early warning systems and drought relief. Traditional works do not consider the space–time dynamic processes of flash droughts, unable to provide important information such as how fast an event spreads in space that hampers governors and stakeholders from making timely drought mitigation operations. Here we introduced a novel framework for tracking flash droughts that fully accounts of their dynamic space–time behavior, with focus upon the instantaneous intensification/recovery rate (IIR/IRR) and spatial propagation. Flash drought events were defined by a space–time coherent set of grids where pentad-scale standardized evapotranspiration deficit index is below a prescribed threshold. The drought development/recovery stage is identified in terms of intensity, and IIR/IRR between two consecutive drought patches is determined based on the variable motion relationship of speed-time process from the physics perspective. A single space–time drought event is extracted when the duration, averaged intensification rate and IIR all reach prescribed standards. Using daily meteorological station data and daily root zone (0–100 cm) gridded soil moisture data, the framework is demonstrated by analyzing the flash droughts in the Pearl River basin over China from 1960 to 2015. Results indicate that the framework can well capture space–time structure of flash droughts including the severity and dynamic spatial propagation. Most of the identified flash drought events last 5–6 pentads but affect over half of the basin, and the top seven events have affected over 90% of the basin which intensify in two pentads showing rapid intensification nature. Moreover, flash droughts are associated with precipitation, humidity, temperature, and sunshine duration. The framework is conducive to better understanding of flash drought processes that help guide effective monitoring and development of early warning systems.
Jun Li; Zhaoli Wang; Xushu Wu; Jie Chen; Shenglian Guo; Zhenxing Zhang. A new framework for tracking flash drought events in space and time. CATENA 2020, 194, 104763 .
AMA StyleJun Li, Zhaoli Wang, Xushu Wu, Jie Chen, Shenglian Guo, Zhenxing Zhang. A new framework for tracking flash drought events in space and time. CATENA. 2020; 194 ():104763.
Chicago/Turabian StyleJun Li; Zhaoli Wang; Xushu Wu; Jie Chen; Shenglian Guo; Zhenxing Zhang. 2020. "A new framework for tracking flash drought events in space and time." CATENA 194, no. : 104763.
Extreme precipitation can cause disasters such as floods, landslides and crop destruction. A further study on extreme precipitation is essential for enabling reliable projections of future changes. In this study, the trends and frequency distribution changes in extreme precipitation across different major river basins around the world during 1960–2011 were examined based on two of the latest observational data sets respectively collected from 110,000 and 26,592 global meteorological stations. The results showed that approximately a quarter of basins have experienced statistically significant increase in maximum consecutive one-day, three-day and five-day precipitation (RX1day, RX3day and RX5day, respectively). In particular, dramatic increases were found in the recent decade for the Syr Darya River basin (SDR) and Amu Darya River basin (ADR) in the Middle East, while a decrease in RX3day and RX5day were seen over the Amur River basin in East Asia. One third of basins showed remarkable changes in frequency distributions of the three indices, and in most cases the distributions shifted toward larger amounts of extreme precipitation. Relative to the subperiod of 1960–1984, wider range of the three indices over SDR and ADR were detected for 1985–2011, indicating intensification along with larger fluctuations of extreme precipitation. However, some basins have frequency distributions shifting toward smaller amounts of RX3day and RX5day, such as the Columbia River basin and the Yellow River basin. The study has potential to provide the most up-to-date and comprehensive global picture of extreme precipitation, which help guide wiser public policies in future to mitigate the effects of these changes across global river basins.
Xin Feng; Zhaoli Wang; Xushu Wu; Jiabo Yin; Shuni Qian; Jie Zhan. Changes in Extreme Precipitation across 30 Global River Basins. Water 2020, 12, 1527 .
AMA StyleXin Feng, Zhaoli Wang, Xushu Wu, Jiabo Yin, Shuni Qian, Jie Zhan. Changes in Extreme Precipitation across 30 Global River Basins. Water. 2020; 12 (6):1527.
Chicago/Turabian StyleXin Feng; Zhaoli Wang; Xushu Wu; Jiabo Yin; Shuni Qian; Jie Zhan. 2020. "Changes in Extreme Precipitation across 30 Global River Basins." Water 12, no. 6: 1527.
Sunshine duration (SD) is a key index with which to quantitatively measure the intensity and duration of solar radiation. The exploration of spatiotemporal characteristics and potential influential factors for SD could help us better understand solar radiation variability. In this study, we first explore the spatiotemporal variability of SD across mainland China during 1959‐2017, then identify the predominant influential climatic factors and detect their relative influence of temporal dynamic on SD, and finally discuss the relative influential rates of climatic factors and detect the dominating climatic factor on a spatial scale. The results show that: 1) the annual and seasonal SD gradually decreased from the northwest to southeast across mainland China; a significant decreasing trend (P < 0.05) was detected for annual SD at a rate of ‐2.7 h/a, a turning point significantly occurred in 1986 (P< 0.05) in the year SD series, and oscillation periods of 2.4‐3.8 years existed in mainland China and most sub‐regions. 2) The significant (P < 0.05) decrease of wind speed (Win), increase of precipitation (Pre), and increase of vapor pressure (Vp) were responsible for the decreasing trend of SD with relative influential rates of 39.9%, 30.6%, and 29.5%, respectively. 3) Temporally, the relative influential rate of each climatic variable changed over time; spatially, Win dominated most areas of mainland China (55.9%) during 1959‐2017, followed by Pre (24.9%) and Vp (19.2%). Keywords: sunshine duration; spatiotemporal variability; influential climatic factors; random forest.
Jinghua Xiong; Zhaoli Wang; Chengguang Lai; Yaoxing Liao; Xushu Wu. Spatiotemporal variability of sunshine duration and influential climatic factors in mainland China during 1959–2017. International Journal of Climatology 2020, 40, 6282 -6300.
AMA StyleJinghua Xiong, Zhaoli Wang, Chengguang Lai, Yaoxing Liao, Xushu Wu. Spatiotemporal variability of sunshine duration and influential climatic factors in mainland China during 1959–2017. International Journal of Climatology. 2020; 40 (15):6282-6300.
Chicago/Turabian StyleJinghua Xiong; Zhaoli Wang; Chengguang Lai; Yaoxing Liao; Xushu Wu. 2020. "Spatiotemporal variability of sunshine duration and influential climatic factors in mainland China during 1959–2017." International Journal of Climatology 40, no. 15: 6282-6300.
While rapid urbanization promotes social and economic development, it poses a serious threat to the health of rivers, especially the small and medium-scale rivers. Flood control for small and medium-scale rivers in highly urbanized areas is particularly important. The purpose of this study is to explore the most effective flood control strategy for small and medium-scale rivers in highly urbanized areas. MIKE 11 and MIKE 21 were coupled with MIKE FLOOD model to simulate flooding with the flood control standard, after which the best flooding control scheme was determined from a whole region perspective (both the mainstream and tributary conditions were considered). The SheGong River basin located near the Guangzhou Baiyun international airport in Guangzhou city over south China was selected for the case study. The results showed that the flooding area in the basin of interest accounts for 42% of the total, with maximum inundation depth up to 0.93 m under the 20-year return period of the designed flood. The flood-prone areas are the midstream and downstream where urbanization is high; however the downstream of the adjacent TieShan River is still able to bear more flooding. Therefore, the probable cost-effective flood control scheme is to construct two new tributaries transferring floodwater in the mid- and downstream of the SheGong River into the downstream of the TieShan River. This infers that flood control for small and medium-scale rivers in highly urbanized areas should not simply consider tributary flood regimes but, rather, involve both tributary and mainstream flood characters from a whole region perspective.
Zengmei Liu; Yuting Cai; Shangwei Wang; Fupeng Lan; Xushu Wu. Small and Medium-Scale River Flood Controls in Highly Urbanized Areas: A Whole Region Perspective. Water 2020, 12, 182 .
AMA StyleZengmei Liu, Yuting Cai, Shangwei Wang, Fupeng Lan, Xushu Wu. Small and Medium-Scale River Flood Controls in Highly Urbanized Areas: A Whole Region Perspective. Water. 2020; 12 (1):182.
Chicago/Turabian StyleZengmei Liu; Yuting Cai; Shangwei Wang; Fupeng Lan; Xushu Wu. 2020. "Small and Medium-Scale River Flood Controls in Highly Urbanized Areas: A Whole Region Perspective." Water 12, no. 1: 182.
Heat wave flash drought or precipitation deficit flash drought has devastating impacts on society and the environment. This study explored the historical changes (1960–2015) of the two categories of flash drought over the Pearl River Basin (PRB) in China, and revealed how they would change in the future (2016–2100), by coupling the variable infiltration capacity mode with the global climate model under representative concentration pathway (RCP) 2.6, 4.5, and 8.5 scenarios. Our results indicate that during 1960–2015, the mid-northern PRB has experienced heat wave flash drought frequently while the western PRB suffered from precipitation deficit flash drought. In future, heat wave flash drought under RCP2.6 and 4.5 would occur mostly in the western and eastern PRB. Specifically, heat wave flash drought would become severe under RCP8.5, especially for the eastern PRB. However, precipitation deficit flash drought would be concentrated in the western PRB. Except for the central regions, PRB generally exhibits a significant upward trend in heat wave flash drought under RCP4.5. Under RCP8.5, distinct increases in both categories of flash drought across almost the whole PRB are expected. For precipitation deficit flash drought, only a few regions show significant upward trends under RCP2.6 and 4.5.
Jun Li; Zhaoli Wang; Xushu Wu; Shenglian Guo; Xiaohong Chen. Flash droughts in the Pearl River Basin, China: Observed characteristics and future changes. Science of The Total Environment 2019, 707, 136074 .
AMA StyleJun Li, Zhaoli Wang, Xushu Wu, Shenglian Guo, Xiaohong Chen. Flash droughts in the Pearl River Basin, China: Observed characteristics and future changes. Science of The Total Environment. 2019; 707 ():136074.
Chicago/Turabian StyleJun Li; Zhaoli Wang; Xushu Wu; Shenglian Guo; Xiaohong Chen. 2019. "Flash droughts in the Pearl River Basin, China: Observed characteristics and future changes." Science of The Total Environment 707, no. : 136074.
Anthropogenic activities have had a great impact on the characteristics of runoff and sediment load along the Pearl River in China in recent decades. We investigated the spatiotemporal variations, including the trends, abrupt changes, and periodicities of annual runoff and sediment load in the Pearl River by using the datasets from nine hydrological stations for the period of 1953–2017. We found that annual runoff was stable during the study period, with only two stations in the upper reach showing decreasing trends. Annual sediment load has generally experienced a significant decreasing trend, while one of the stations in the middle reach showed an opposite trend due to severe rocky desertification and soil erosion in the local karst terrain. Abrupt changes in sediment load were mainly between the 1990s and 2000s, when many hydraulic projects were conducted, implying the significant impact of anthropogenic activities on river sediment load. Results also indicate 2–4 year and 4–8 year periodicities in both annual runoff and sediment load, with long periodicities less significant than the short ones. Our study is conducive to water and soil resource management in the Pearl River basin, whilst provides a guide for other basins, particularly those characterized by karst terrains where local desertification and soil erosion might likewise cause increase in river sediment load.
Huanyang Zhou; Zhaoli Wang; Xushu Wu; Yuhong Chen; Yixuan Zhong; Zejun Li; Shenglian Guo. Spatiotemporal Variation of Annual Runoff and Sediment Load in the Pearl River during 1953–2017. Sustainability 2019, 11, 5007 .
AMA StyleHuanyang Zhou, Zhaoli Wang, Xushu Wu, Yuhong Chen, Yixuan Zhong, Zejun Li, Shenglian Guo. Spatiotemporal Variation of Annual Runoff and Sediment Load in the Pearl River during 1953–2017. Sustainability. 2019; 11 (18):5007.
Chicago/Turabian StyleHuanyang Zhou; Zhaoli Wang; Xushu Wu; Yuhong Chen; Yixuan Zhong; Zejun Li; Shenglian Guo. 2019. "Spatiotemporal Variation of Annual Runoff and Sediment Load in the Pearl River during 1953–2017." Sustainability 11, no. 18: 5007.