scholarly journals Drought Characteristics and Its Response to the Global Climate Variability in the Yangtze River Basin, China

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 13 ◽  
Author(s):  
Tao Huang ◽  
Ligang Xu ◽  
Hongxiang Fan

The frequent occurrence of drought events in humid and semi-humid regions is closely related to the global climate variability (GCV). In this study, the Standard Precipitation Evapotranspiration Index (SPEI) was taken as an index to investigate the drought in the Yangtze River Basin (YRB), a typical humid and semi-humid region in China. Furthermore, nine GCV indices, such as North Atlantic Oscillation (NAO) were taken to characterize the GCV. Correlation analysis and a joint probability distribution model were used to explore the relationship between the drought events and the GCV. The results demonstrated that there were six significant spatiotemporal modes revealed by SPEI3 (i.e., seasonal drought), which were consistent with the distribution of the main sub basins in the YRB, indicating a heterogeneity of drought regime. However, the SPEI12 (i.e., annual drought) can only reveal five modes. Precipitation Indices and El Niño/Southern Oscillation (ENSO) Indices were more closely related to the drought events. A causal relationship existed between ENSO precipitation index (ESPI), NAO, East Central Tropical Pacific Sea Surface Temperature (Nino3.4) and Northern Oscillation Index (NOI) and drought in the YRB, respectively. Drought events were most sensitive to the low NAO and high NOI events. This study shows a great significance for the understanding of spatiotemporal characteristics of meteorological drought and will provide a reference for the further formulation of water resources policy and the prevention of drought disasters.

Water ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 2960
Author(s):  
Hao Huang ◽  
Bo Zhang ◽  
Yanqiang Cui ◽  
Shangqian Ma

As China’s main grain producing region, the Yangtze River basin is vulnerable to changes in wet and dry conditions. In this study, the monthly scale of standardized precipitation evapotranspiration index (SPEI) was calculated, based on the Penman–Monteith equation from 239 meteorological stations in the Yangtze River basin, from 1960 to 2017. Water regime characteristic areas of the Yangtze River basin were extracted and divided using the rotating empirical orthogonal function (REOF). The linear trend of the drought and wetness indicators, the abrupt changes of the rotated principal component time series (RPCs), and the change periods of the drought/wetness intensity (DI/WI) in each subregion were analyzed and discussed. Subsequently, the effects of El Niño-southern oscillation (ENSO) and arctic oscillation (AO) on drought and wetness events were discussed. The results showed that the Yangtze River basin has the characteristic of coexistence of drought and wetness, and drought and wetness of similar severity tend to occur in the same region. There were six subregions extracted through REOF, based on the monthly scale of SPEI, of which the northwestern pattern had an aridization tendency. The stations with significantly increased wetness were located in the middle and eastern basin. The stations in the south of the northwestern pattern, and the west of the southern pattern, had a tendency of wetting in the first 29 years, however, there has been a significant tendency of drying in this region in the last 29 years, which was caused by an abrupt change in 1994. In addition, other patterns had multiple abrupt changes, resulting in multiple transitions between dry and wet states. The principal periods of WI in the southern pattern and northern pattern were longer than the DI, but in other subregions DI was longer than WI. ENSO and AO had the most obvious influence on DI and WI. Compared with the cold phase of ENSO, the DI/WI in the warm phase were higher/lower; compared with the negative phase of AO, both DI and WI were higher in the positive phase. The Hurst index showed that the current dry and wet conditions in the Yangtze River basin have persistent characteristics, the dry conditions in each subregion will continue in the future, and there were a few wetness indicators with weak anti-persistence.


2012 ◽  
Vol 63 (5) ◽  
pp. 478 ◽  
Author(s):  
Sha Wang ◽  
Enli Wang ◽  
Fei Wang ◽  
Liang Tang

Canola is a major oil crop in the Yangtze River Basin of China, and its yield and oil content vary significantly from year to year due to changes in sowing time and inter-annual climate variability. However, there have been no studies to quantify the impacts of sowing time and climate variability. Experimental data to analyse the response of canola growth to sowing date are limited to a few seasons; however, combining these data with modelling provides an efficient means to study the impact of sowing date and historical climate variation. The APSIM-Canola model was calibrated and tested using data from three field experimental sites in the Yangtze River Basin. These experiments included different cultivars and sowing dates, and recorded major phenological stages, biomass, and grain yield. After calibration of the phenological parameters and maximum harvest index, the model was able to simulate the onset of phenological stages with different sowing dates, and to explain 75% of the variation in biomass and yield caused by late sowings. However, the model overestimated canola yield under late sowing dates. The results revealed that canola yield declined linearly with late sowing time, mainly due to shortened vegetative growth stages, and varied significantly due to inter-annual climate variability. The yield potential at the study region is ~3 t/ha, on average. However, this potential cannot be achieved in the rice–canola double-cropping system due to later sowing time after rice harvest in mid–later October. Transplanting canola may still be an effective measure against the constraint of season length to achieving higher yields of both rice and canola.


Forests ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 731
Author(s):  
Zhuoqing Hao ◽  
Jixia Huang ◽  
Yantao Zhou ◽  
Guofei Fang

The Yangtze River Basin is among the river basins with the strongest strategic support and developmental power in China. As an invasive species, the pinewood nematode (PWN) Bursaphelenchus xylophilus has introduced a serious obstacle to the high-quality development of the economic and ecological synchronization of the Yangtze River Basin. This study analyses the occurrence and spread of pine wilt disease (PWD) with the aim of effectively managing and controlling the spread of PWD in the Yangtze River Basin. In this study, statistical data of PWD-affected areas in the Yangtze River Basin are used to analyse the occurrence and spread of PWD in the study area using spatiotemporal visualization analysis and spatiotemporal scanning statistics technology. From 2000 to 2018, PWD in the study area showed an “increasing-decreasing-increasing” trend, and PWD increased explosively in 2018. The spatial spread of PWD showed a “jumping propagation-multi-point outbreak-point to surface spread” pattern, moving west along the river. Important clusters were concentrated in the Jiangsu-Zhejiang area from 2000 to 2015, forming a cluster including Jiangsu and Zhejiang. Then, from 2015–2018, important clusters were concentrated in Chongqing. According to the spatiotemporal scanning results, PWD showed high aggregation in the four regions of Zhejiang, Chongqing, Hubei, and Jiangxi from 2000 to 2018. In the future, management systems for the prevention and treatment of PWD, including ecological restoration programs, will require more attention.


2021 ◽  
Vol 13 (15) ◽  
pp. 3023
Author(s):  
Jinghua Xiong ◽  
Shenglian Guo ◽  
Jiabo Yin ◽  
Lei Gu ◽  
Feng Xiong

Flooding is one of the most widespread and frequent weather-related hazards that has devastating impacts on the society and ecosystem. Monitoring flooding is a vital issue for water resources management, socioeconomic sustainable development, and maintaining life safety. By integrating multiple precipitation, evapotranspiration, and GRACE-Follow On (GRAFO) terrestrial water storage anomaly (TWSA) datasets, this study uses the water balance principle coupled with the CaMa-Flood hydrodynamic model to access the spatiotemporal discharge variations in the Yangtze River basin during the 2020 catastrophic flood. The results show that: (1) TWSA bias dominates the overall uncertainty in runoff at the basin scale, which is spatially governed by uncertainty in TWSA and precipitation; (2) spatially, a field significance at the 5% level is discovered for the correlations between GRAFO-based runoff and GLDAS results. The GRAFO-derived discharge series has a high correlation coefficient with either in situ observations and hydrological simulations for the Yangtze River basin, at the 0.01 significance level; (3) the GRAFO-derived discharge observes the flood peaks in July and August and the recession process in October 2020. Our developed approach provides an alternative way of monitoring large-scale extreme hydrological events with the latest GRAFO release and CaMa-Flood model.


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