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Article ; Online: Applications of Stacking/Blending ensemble learning approaches for evaluating flash flood susceptibility

Jing Yao / Xiaoxiang Zhang / Weicong Luo / Changjun Liu / Liliang Ren

International Journal of Applied Earth Observations and Geoinformation, Vol 112, Iss , Pp 102932- (2022)

2022

Abstract: Flash floods are a type of catastrophic disasters which cause significant losses of life and property worldwide. In recent years, machine learning techniques have become powerful tools for evaluating flash flood susceptibility. This research applies ... ...

Abstract	Flash floods are a type of catastrophic disasters which cause significant losses of life and property worldwide. In recent years, machine learning techniques have become powerful tools for evaluating flash flood susceptibility. This research applies stacking and blending ensemble learning approaches to assess the flash flood potential in Jiangxi, China. Four base models – linear regression, K-nearest neighbours, support vector machine, and random forest – are adopted to build the two ensemble models. All models are evaluated by three metrics (accuracy, true positive rate, and the area under the receiver operating characteristic curve) and compared with a Bayesian approach. The results suggest that the blending approach is superior to all the other models, which has then been selected to evaluate the vulnerability of flash floods for all the catchments in Jiangxi. The derived maps of flash flood susceptibility suggest that over half of the province, in terms of either area or the number of catchments, are prone to flash floods, in particular the north, northeast and south. These empirical findings can help to develop plans for disaster prevention and control, as well as improving public knowledge of flash flood hazards.
Keywords	Flash floods ; Susceptibility ; Ensemble learning ; Stacking ; Blending ; Physical geography ; GB3-5030 ; Environmental sciences ; GE1-350
Subject code	910 ; 333
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: The patterns, magnitude, and drivers of unprecedented 2022 mega-drought in the Yangtze River Basin, China

Yi Liu / Shanshui Yuan / Ye Zhu / Liliang Ren / Ruiqi Chen / Xiaotong Zhu / Ruize Xia

Environmental Research Letters, Vol 18, Iss 11, p

2023 Volume 114006

Abstract: The Yangtze River Basin in China was hit by an unprecedented extreme drought in 2022. Such a record-breaking event is jointly driven by a few outlier factors and shows abnormal phenomena. The exceptionality of this drought event cannot be fully described ...

Abstract	The Yangtze River Basin in China was hit by an unprecedented extreme drought in 2022. Such a record-breaking event is jointly driven by a few outlier factors and shows abnormal phenomena. The exceptionality of this drought event cannot be fully described by any individual indicator. Therefore, we performed this comprehensive study to highlight the exceptionality of 2022 Yangtze River Basin drought. We evaluated three drought characteristics: onset period (the time interval of moisture condition from normal to extreme), intensity, and affected area and their compound features. Additionally, historical climatology (1950–2022) and four past severe events are used as references. Lastly, we investigated the driving mechanisms of this event from synoptic perspective. Our results indicate the 2022 drought ranked as the most severe event in history. The recurrence interval of the 2022 Yangtze River drought is estimated to be 120–400 years by considering individual and combined drought characteristics. Behind the scenes, the synoptic environment triggered the abnormally high temperatures and abrupt alteration of precipitation, which is the main driver of the event. The 2022 Yangtze River drought is an archetype of an event characterized by both rapid intensification over time and space, which is indicative for drought monitoring and early warning in a warming climate.
Keywords	drought ; Yangtze River Basin ; rapid intensification ; high temperatures ; abrupt alteration of precipitation ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350 ; Science ; Q ; Physics ; QC1-999
Subject code	550 ; 910
Language	English
Publishing date	2023-01-01T00:00:00Z
Publisher	IOP Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: A new non-stationary standardised streamflow index using the climate indices and the optimal anthropogenic indices as covariates in the Wei River Basin, China

Mingming Ren / Shanhu Jiang / Liliang Ren / Baisha Weng / Menghao Wang / Hao Cui / Chong-Yu Xu

Journal of Hydrology: Regional Studies, Vol 51, Iss , Pp 101649- (2024)

2024

Abstract: Study region: Catchment area above the Huaxian station along the Wei River Basin, China. Study focus: This study attempts to construct a new Non-stationary Standardized Streamflow Index (NSSI) applicable to the variable streamflow sequence of the Wei ... ...

Abstract	Study region: Catchment area above the Huaxian station along the Wei River Basin, China. Study focus: This study attempts to construct a new Non-stationary Standardized Streamflow Index (NSSI) applicable to the variable streamflow sequence of the Wei River Basin based on the climate index and the optimal anthropogenic index, and analyse the drought characteristics of the basin. The climate index is used to quantify climate change factors and three anthropogenic indices are used to quantify the factor of human activities, including the reservoir index, the human-induced index calculated based on the Variable Infiltration Capacity (VIC) hydrological model and the Long Short-Term Memory (LSTM) model machine learning approach, respectively. New hydrological insights for the region: The human-induced index based on the LSTM model is more suitable for quantifying anthropogenic factors in the Wei River Basin. The NSSI performs better than the SSI in drought identification. The NSSI based on the LSTM model can capture more frequent severe drought and extreme drought events. The frequency of severe drought and extreme drought is higher in summer and autumn than in the others. The NSSI can better characterize the hydrological drought processes under a non-stationary condition, thus it can provide a more effective reference for regional drought assessment and related policy-making from the perspective of a changing environment.
Keywords	Non-stationary standardized streamflow index ; Hydrological drought ; Climate index ; Anthropogenic index ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	550
Language	English
Publishing date	2024-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: How will drought evolve in global arid zones under different future emission scenarios?

Fan Wu / Xiaoli Yang / Xing Yuan / Liliang Ren / Shanshui Yuan / Fei Yuan / Shanhu Jiang / Yi Liu / Hanshuo Zhang

Journal of Hydrology: Regional Studies, Vol 51, Iss , Pp 101661- (2024)

2024

Abstract: Study region: Global aridity zones. Study focus: Evaluating drought under the impact of climate change is crucial for ensuring sustainable development and ecological security, especially in global arid zones where the environment is vulnerable to global ... ...

Abstract	Study region: Global aridity zones. Study focus: Evaluating drought under the impact of climate change is crucial for ensuring sustainable development and ecological security, especially in global arid zones where the environment is vulnerable to global warming. However, there are large uncertainties in evaluating the future drought risk of arid zones due to uncertainties within climate projections and the use drought-related indices that may not be appropriate for all assessments. Therefore, under the precondition of bias correction applied to CMIP6 data, the drought detection capability of drought indices calculated from multimodel ensemble was evaluated. Based on the drought index with the strongest detection capability and the Reliability-Resilience-Vulnerability (RRV) framework, the future drought risk in global arid zones were predicted. New hydrological insights for the region: Among the drought indices calculated from CMIP6 historical simulations, SPEI offered the best representation of drought patterns. According to the CMIP6 future projections, SSP1–2.6 can effectively mitigate the impact of future drought risk compared with the historical period. In scenarios with higher emissions, the equatorial to northern latitude 30° region will experience more severe drought. For SSP5–8.5, the areas in the arid zones where drought risk deteriorates significantly are several times larger than in other scenarios. To mitigate drought risks, most nations should support a greener, low-emission approach in line with sustainable development goals, reducing the risk of drought-related damage.
Keywords	Climate change ; CMIP6 climate models ; Optimal drought index ; Drought risk ; RRV ; Global arid zones ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	910
Language	English
Publishing date	2024-02-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Assessing the Potential of IMERG and TMPA Satellite Precipitation Products for Flood Simulations and Frequency Analyses over a Typical Humid Basin in South China

Shanhu Jiang / Yu Ding / Ruolan Liu / Linyong Wei / Yating Liu / Mingming Ren / Liliang Ren

Remote Sensing, Vol 14, Iss 4406, p

2022 Volume 4406

Abstract: The availability of the new generation Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06 products facilitates the utility of long-term higher spatial and temporal resolution precipitation data (0.1° × 0.1° and half- ... ...

Abstract	The availability of the new generation Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) V06 products facilitates the utility of long-term higher spatial and temporal resolution precipitation data (0.1° × 0.1° and half-hourly) for monitoring and modeling extreme hydrological events in data-sparse watersheds. This study aims to evaluate the utility of IMERG Final run (IMERG-F), Late run (IMERG-L) and Early run (IMERG-E) products, in flood simulations and frequency analyses over the Mishui basin in Southern China during 2000–2017, in comparison with their predecessors, the Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis (TMPA) products (3B42RT and 3B42V7). First, the accuracy of the five satellite precipitation products (SPPs) for daily precipitation and extreme precipitation events estimation was systematically compared by using high-density gauge station observations. Once completed, the modeling capability of the SPPs in daily streamflow simulations and flood event simulations, using a grid-based Xinanjiang model, was assessed. Finally, the flood frequency analysis utility of the SPPs was evaluated. The assessment of the daily precipitation accuracy shows that IMERG-F has the optimum statistical performance, with the highest CC (0.71) and the lowest RMSE (8.7 mm), respectively. In evaluating extreme precipitation events, among the IMERG series, IMERG-E exhibits the most noticeable variation while IMERG-L and IMERG-F display a relatively low variation. The 3B42RT exhibits a severe inaccuracy and the improvement of 3B42V7 over 3B42RT is comparatively limited. Concerning the daily streamflow simulations, IMERG-F demonstrates a superior performance while 3B42V7 tends to seriously underestimate the streamflow. With regards to the simulations of flood events, IMERG-F has performed optimally, with an average DC of 0.83. Among the near-real-time SPPs, IMERG-L outperforms IMERG-E and 3B42RT over most floods, attaining a mean DC of 0.81. Furthermore, IMERG-L ...
Keywords	satellite precipitation products ; GPM IMERG ; TMPA ; flood simulation ; flood frequency analysis ; Science ; Q
Subject code	550
Language	English
Publishing date	2022-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Interactive influence of climate variability and land-use change on blue and green water resources

Wenting Li / Xiaoli Yang / Liliang Ren / Qianguo Lin / Xiong Zhou / Yujiao Gu

Journal of Water and Climate Change, Vol 13, Iss 1, Pp 158-

a case study from the Ganjiang River Basin, China

2022 Volume 174

Abstract: The response of blue and green water to climate and land-use change in the Ganjiang River Basin (GRB) is evaluated via the SWAT model that combines three scenarios (the land-use/land-cover (LULC), climate change, and integrated climate and LULC change ... ...

Abstract	The response of blue and green water to climate and land-use change in the Ganjiang River Basin (GRB) is evaluated via the SWAT model that combines three scenarios (the land-use/land-cover (LULC), climate change, and integrated climate and LULC change scenarios) in the 2040s (2031–2050) and 2060s (2051–2070). The results indicate that, for the GRB, cropland, woodland, and grassland show a decreasing trend, while build-up and water areas show an increasing trend in terms of future land-use change. The climatic conditions projected using NORESM1-M model data under the RCP4.5 and RCP8.5 scenarios suggest, respectively, increases in precipitation (31.17 and 27.24 mm), maximum temperature (2.25 and 2.69 °C), and minimum temperature (1.96 and 2.58 °C). Under climate change conditions, blue water is estimated to decrease by up to 16.89 and 21.4 mm under RCP4.5 and RCP8.5, while green water is estimated to increase up to 19.14 and 20.22 mm, respectively. Under the LULC changes, blue water is projected to increase by up to 5.50 and 7.57 mm, while green water shows decreases of 4.05 and 7.80 mm for the LULC2035 and LULC2055 scenarios, respectively. Under the four combined LULC and climate change conditions (RCP4.5_2040s, RCP4.5_2060s, RCP8.5_2040s, and RCP8.5_2060s), blue water tends to decrease by 0.67, 7.47, 7.28, and 9.99 mm, while green water increases by 19.24, 20.8, 13.87, and 22.30 mm. The influence of climate variation on blue and green water resources is comparatively higher than that of the integrated impacts of climate and land-use changes. The results of this study offer a scientific reference for the water resources management and planning department responsible for scheduling water resource management plan in the GRB. HIGHLIGHTS This study investigates the effects of climate changes and land-use changes on blue/green water.; The NORESM1-M model data from the CMIP5 are combined with the SWAT model to analyse the influence of future climate changes on blue/green water.; The CA–Markov model is applied to ...
Keywords	blue water ; climate change ; ganjiang river ; green water ; land-use change ; swat model ; Environmental technology. Sanitary engineering ; TD1-1066 ; Environmental sciences ; GE1-350
Language	English
Publishing date	2022-01-01T00:00:00Z
Publisher	IWA Publishing
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dynamics and potential synchronization of regional precipitation concentration and drought-flood abrupt alternation under the influence of reservoir climate

Hao Cui / Shanhu Jiang / Liliang Ren / Weihua Xiao / Fei Yuan / Menghao Wang / Linyong Wei

Journal of Hydrology: Regional Studies, Vol 42, Iss , Pp 101147- (2022)

2022

Abstract: Study region: Three Gorges Reservoir area, the largest reservoir area in China Study focus: The frequency and intensity of extreme weather events increase with climate warming, and the local climate effects in the large reservoir area may also change the ...

Abstract	Study region: Three Gorges Reservoir area, the largest reservoir area in China Study focus: The frequency and intensity of extreme weather events increase with climate warming, and the local climate effects in the large reservoir area may also change the local precipitation structure. Therefore, based on the precipitation sequence data in the Three Gorges Reservoir (TGR) area from 1959 to 2019, the proposed multi-time-scale mutual information entropy (MTSMIE) method was used to reveal the cyclic synchronous changes of drought-flood abrupt alternation and precipitation concentration. New hydrological insights: The results demonstrate that (1) the spatial distribution of the precipitation concentration index in the TGR area has obvious regional variability. On the temporal scale, the precipitation concentration increased by 5.5% and decreased by 8.2% after impoundment at the head and tail of the TGR, respectively. (2) The frequency of drought-to-flood (DTF) events from the head of the reservoir area to the tail of the reservoir area presents a ''more-less'' feature. The frequency of DTF events after impoundment was less than that before the impoundment of the reservoir. However, the flood-to-drought (FTD) events are the opposite. (3) The period of reliable research and monitoring of DFAA and precipitation concentration in the Three Gorges region is about 15–17 years through the MTSMIE method.
Keywords	Precipitation concentration ; Spatiotemporal distribution ; Drought-flood abrupt alternation ; MTSMIE ; Three Gorges Reservoir ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	910 ; 550
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Dynamic multi-dimensional identification of Yunnan droughts and its seasonal scale linkages to the El Niño-Southern Oscillation

Linyan Zhang / Xiaoli Yang / Liliang Ren / Justin Sheffield / Linqi Zhang / Shanshui Yuan / Mengru Zhang

Journal of Hydrology: Regional Studies, Vol 42, Iss , Pp 101128- (2022)

2022

Abstract: Study region: Yunnan Province, China. Study focus: Yunnan Province (YP) is affected by frequent droughts that severely affect local agriculture and the ecological environment. Therefore, the identification of droughts and an analysis of their driving ... ...

Abstract	Study region: Yunnan Province, China. Study focus: Yunnan Province (YP) is affected by frequent droughts that severely affect local agriculture and the ecological environment. Therefore, the identification of droughts and an analysis of their driving factors are of significant importance for mitigating local drought losses and guiding agricultural practices. This study identified the spatiotemporal distribution and dynamic changes in drought events over YP (period 1961–2018) using the severity-area-duration method. The impact of El Niño-Southern Oscillation (ENSO) on seasonal droughts and their lag period were also quantified by employing the sliding correlation coefficient and cross-wavelet analysis method. New hydrological insights for the region: 74 drought events were identified during 1961–2018 in YP, which were mainly short-duration that occurred in the 1980 s and 2000 s, and most drought centers are located over the northern and eastern parts of YP. We found that a significant correlation and different lag periods exist between Oceanic Niño Index (ONI) and seasonal precipitation in YP. Spring droughts mainly occurred in El Niño years during the 1980 s and the 1990 s, whilst winter droughts mainly occurred in La Niña years during the 1990 s and the 2000 s with a lag period of up to 12 months.
Keywords	Drought ; SAD method ; SPI3 ; ENSO ; Yunnan Province ; Physical geography ; GB3-5030 ; Geology ; QE1-996.5
Subject code	910
Language	English
Publishing date	2022-08-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: Non-Ignorable Differences in NIRv-Based Estimations of Gross Primary Productivity Considering Land Cover Change and Discrepancies in Multisource Products

Jiaxin Jin / Weiye Hou / Longhao Wang / Songhan Wang / Ying Wang / Qiuan Zhu / Xiuqin Fang / Liliang Ren

Remote Sensing, Vol 15, Iss 4693, p

2023 Volume 4693

Abstract: The accurate estimation of gross primary productivity (GPP) plays an important role in accurately projecting the terrestrial carbon cycle and climate change. Satellite-driven near-infrared reflectance (NIRv) can be used to estimate GPP based on their ... ...

Abstract	The accurate estimation of gross primary productivity (GPP) plays an important role in accurately projecting the terrestrial carbon cycle and climate change. Satellite-driven near-infrared reflectance (NIRv) can be used to estimate GPP based on their nearly linear relationship. Notably, previous studies have reported that the relationship between NIRv and GPP seems to be biome-specific (or land cover) at the ecosystem scale due to both biotic and abiotic effects. Hence, the NIRv-based estimation of GPP may be influenced by land cover changes (LCC) and the discrepancies in multisource products (DMP). However, these issues have not been well understood until now. Therefore, this study took the Yellow River basin (YRB) as the study area. This area has experienced remarkable land cover changes in recent decades. We used Moderate-Resolution Imaging Spectroradiometer (MODIS) and European Space Agency (ESA) Climate Change Initiative (CCI) land cover products (termed MCD12C1 and ESACCI, respectively) during 2001–2018 to explore the impact of land cover on NIRv-estimated GPP. Paired comparisons between the static and dynamic schemes of land cover using the two products were carried out to investigate the influences of LCC and DMP on GPP estimation by NIRv. Our results showed that the dominant land cover types in the YRB were grassland, followed by cropland and forest. Meanwhile, the main transfer was characterized by the conversion from other land cover types (e.g., barren) to grassland in the northwest of the YRB and from grassland and shrubland to cropland in the southeast of the YRB during the study period. Moreover, the temporal and spatial pattern of GPP was highly consistent with that of NIRv, and the average increase in GPP was 2.14 gCm −2 yr −1 across the YRB. Nevertheless, it is shown that both LCC and DMP had significant influences on the estimation of GPP by NIRv. That is, the areas with obvious differences in NIRv-based GPP closely correspond to the areas where land cover types dramatically changed. The ...
Keywords	NIRv ; GPP ; land cover ; MCD12C1 ; ESA CCI LC maps ; Yellow River basin ; Science ; Q
Subject code	333
Language	English
Publishing date	2023-09-01T00:00:00Z
Publisher	MDPI AG
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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Article ; Online: An integrated approach for identification and quantification of ecological drought in rivers from an ecological streamflow perspective

Shanhu Jiang / Menghao Wang / Liliang Ren / Yating Liu / Le Zhou / Hao Cui / Chong-Yu Xu

Ecological Indicators, Vol 143, Iss , Pp 109410- (2022)

2022

Abstract: Although various studies have investigated the impacts of climate variability and human activities on drought, researches specifically analysing the impact on ecological drought are still limited. A deep understanding of the climatic and anthropogenic ... ...

Abstract	Although various studies have investigated the impacts of climate variability and human activities on drought, researches specifically analysing the impact on ecological drought are still limited. A deep understanding of the climatic and anthropogenic effects on ecological drought processes is crucial for ecological regulation and management in the changing environments. In the present study, an integrated approach for comprehensive understanding and quantification of ecological drought in rivers was proposed which first applied the nonparametric kernel density estimation (KDE) method to calculate the most suitable ecological streamflow (MSES) for a river ecosystem. Then, the variable threshold level method based on the MSES for each month and the run theory method were applied to identify the ecological drought duration and deficit volumes. Finally, a quantification approach based on hydrological model simulation was proposed to attribute the impacts of climate variability and human activities on ecological drought. The proposed approach was applied on two catchments, Xianyang (XY) and Huaxian (HX) within the Weihe River Basin (WRB) in northern China. Comparison results obtained using the two empirical methods revealed that the MSES calculated using the KDE method was reasonable and can be used for ecological drought identification. The identification results showed that both the median and upper quartile values of the drought duration and deficit volumes during the disturbed period (1991–2017) were greater than those during the undisturbed period (1961–1990). Quantification results showed that human activities were the dominant factor aggravating ecological drought in the WRB after 1990. The contribution rates of climate variability and human activities toward ecological drought variations were 25.6% and 74.4%, respectively, for the XY station and 42.7% and 57.3%, respectively, for the HX station. Although the WRB was selected as a case study, the proposed approach can also be applied to other regions to ...
Keywords	Ecological streamflow ; Variable threshold method ; Ecological drought ; Climate change ; Human activities ; Ecology ; QH540-549.5
Subject code	910
Language	English
Publishing date	2022-10-01T00:00:00Z
Publisher	Elsevier
Document type	Article ; Online
Database	BASE - Bielefeld Academic Search Engine (life sciences selection)

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