Multi-indicator comparison in characterizing spatiotemporal patterns of water disasters and corresponding agricultural applications in the Middle-and-lower Yangtze River

Cities along rivers are threatened by floods and waterlogging, and the relationship between rainstorms and floods is complex. The temporal and spatial distributions of rainstorms directly affect flood characteristics. The location of the rainstorm center determines the flood peaks, volumes, and processes. In this study, machine learning algorithms were introduced to analyze the rain–flood relationship in Luzhou City, Sichuan Province, China. The spatial and temporal patterns of rainstorms in the region were classified and extracted, and flood characteristics generated by various types of rainstorms were analyzed. In the first type, the center of the rainstorm was in the upper reaches of the Tuojiang River, and the resulting flood caused negligible damage to Luzhou. In the second type, the center of the rainstorm occurred in the Yangtze River Basin. Continuously high water levels in the Yangtze River, combined with local rainfall, supported urban drainage. In the third type, the rainstorm center occurred in the upper reaches of the Yangtze and Tuojiang rivers. During the flooding, rainfall from Yangtze River and Tuojiang River moved towards Luzhou together. The movement of the rainstorm center was consistent with the flood routing direction of the Yangtze and Tuojiang rivers, both of which continued to have high water levels. The flood risk is extremely high in this case, making it the riskiest rainfall process requiring prevention.

Soil erosion by water affects soil organic carbon (SOC) migration and distribution, which are important processes for defining ecosystem carbon sources and sinks. Little has been done to quantify soil carbon erosion in the three major basins in China, the Yangtze River, Yellow River and Pearl River Basins, which contain the most eroded areas. This research attempts to quantify the lateral movement of SOC based on spatial and temporal patterns of water erosion rates derived from an empirical Unit Stream Power Erosion Deposition Model (USPED) model. The water erosion rates simulated by the USPED model agreed reasonably with observations (R2 = 0.43, P < 0.01). We showed that regional water erosion ranged within 23.3–50 Mg ha–1 year–1 during 1992–2013, inducing the lateral redistribution of SOC caused by erosion in the range of 0.027–0.049 Mg C ha–1 year–1, and that caused by deposition of 0.0079–0.015 Mg C ha–1 year–1, in the three basins. The total eroded SOC was 0.006, 0.002 and 0.001 Pg year–1 in the Yangtze River, Yellow River and Pearl River Basins respectively. The net eroded SOC in the three basins was ~0.0075 Pg C year–1. Overall, the annual average redistributed SOC rate caused by erosion was greater than that caused by deposition, and the SOC loss in the Yangtze River Basin was greatest among the three basins. Our study suggests that considering both processes of erosion and deposition – as well as effects of topography, rainfall, land use types and their interactions – on these processes are important to understand SOC redistribution caused by water erosion.

In the summer of 2022, the Yangtze River basin (YRB) experienced the most intense and prolonged extreme high-temperature event since 1961, featured by three successive episodes of 18–29 June (P1), 6–17 July (P2), and 3–26 August (P3). An assessment of two operational subseasonal-to-seasonal models reveals that the spatial pattern of surface air temperature (SAT) anomalies over the YRB can be predicted with lead times of 11–12, 8–9, and 15–20 days for P1, P2, and P3, respectively. However, both models underestimate the intensity of maximum SAT anomalies, especially during P3. In P1 and P2, both models fail to reproduce the propagation of Eurasian transient waves at the lead time of 15 days, hindering the development of high-pressure anomalies over East Asia. In P2, additional biases in reproducing the boreal summer intraseasonal oscillation (BSISO)-like convection anomalies promote the further northward shift of the high-pressure anomaly. These model errors result in poor simulations of local diabatic heating, which is the primary contributor to SAT anomalies over the YRB in P1 and P2. In P3, well-reproduced mid- to high-latitude Eurasian transient waves and BSISO-like convection are favorable for simulating SAT anomalies over YRB. Nonetheless, the underestimation of regional adiabatic heating associated with vertical motion in P3 limits the skill in predicting the intensity of SAT anomalies over the YRB. Thus, the ability of accurately capturing the two predictability sources of Eurasian transient waves and tropical Indo-Pacific convections is the key to improve the subseasonal prediction of this prolonged extreme high-temperature event over the YRB. Significance Statement A record-breaking prolonged extreme high-temperature event occurred over the Yangtze River basin (YRB) in the summer of 2022, featuring three distinct subseasonal episodes. Evaluation of two subseasonal-to-seasonal models from the European Centre for Medium-Range Weather Forecasts and China Meteorological Administration shows that the distribution patterns of surface air temperature anomalies over the YRB can be predicted with lead times of 11–12 days for P1, 8–9 days for P2, and 15–20 days for P3, whereas the intensity of maximum anomalies is consistently underestimated. Mid- to high-latitude Eurasian transient waves and tropical Indo-Pacific convections are identified as key sources of subseasonal predictability for this extreme event. These results offer valuable insights for improving subseasonal prediction skills for future extreme high-temperature events over the YRB.

A novel multi-scale standardized index analyzing monthly to sub-seasonal drought-flood abrupt alternation events in the Yangtze River basin

Modeling the spatial–temporal dynamics of water use efficiency in Yangtze River Basin using IBIS model

Floods caused by extreme precipitation events, in the context of climate warming, are one of the most serious natural disasters in monsoon region societies. The great flood in the Yangtze River Basin in 1849, in Eastern China, was a typical extreme flood event. According to historical archives, local chronicles, diaries, and historical hydrological survey data, this study reconstructed the temporal and spatial patterns of extreme precipitation in 1849, and the flood process of the Yangtze River. We found four major precipitation events at the middle and lower reaches of the Yangtze River, from 18 May to 18 July 1849. The torrential rainfall area showed a dumbbell-like structure along the Yangtze River, with two centers distributed separately in the east and west. For the specific flood process of the Yangtze River, many tributaries of the Yangtze River system entered the flood season consecutively since April, and the mainstream of the Yangtze River experienced tremendous pressure on flood prevention with the arrival of multiple rounds of heavy rainfall. In mid-to-late July, the water level and flow rate of many stations along the mainstream and tributaries had reached their record high. The record-breaking peak flow rate at many stations along the mainstream and tributaries in the middle reaches of the Yangtze River indicated intense precipitation in the area. The heavy rainfall disaster in the Yangtze River Basin could be driven by these reasons. First, the cold air in North China was extraordinary active in 1849, which made it difficult for the subtropical high pressure to move northward. Second, the rain belt stagnated in the Yangtze River Basin for a long time, and the Meiyu period reached 42 days, 62% longer than normal years. Third, the onset of a southwest monsoon was earlier and more active, which provided abundant moisture to the Yangtze River Basin. The great flood disaster was caused by heavy precipitation at the middle reaches, which made it quite different from the other three great floods in the Yangtze River in the 20th century. At present, the large water conservancy projects in the Yangtze River are mainly designed for flood problems caused by rainstorms in the upper reaches of the Yangtze River. The middle reaches of the Yangtze River, however, are facing the weakening of flood diversion capacity, caused by social and economic development. Therefore, future flood prevention measures in the Yangtze River should pay great attention to the threat of this flood pattern.

The Yangtze River Basin (YRB) is the birthplace of Chinese civilization and is rich in traditional village resources. Studying their spatial distribution characteristics and influencing factors can guide the protection, inheritance, and development of traditional villages in YRB. This study takes 5 batches of 3346 traditional villages in YRB since 2012 as the research object. Using the nearest neighbor index, kernel density analysis, standard deviation ellipse, and Geodetector model, we analyzed the spatial distribution characteristics of traditional villages in YRB and detected their influencing factors. The results show that the distribution of traditional villages in YRB exhibited a spatial pattern of cohesive clusters, forming a high-density area and development center in the junction zone between Guizhou and Hunan provinces and southeast of Anhui Province, and secondary-density areas in Northeast Yunnan Province and east Jiangxi Province. The results of the Geodetector show that the formation of the spatial distribution pattern of traditional villages in YRB is affected by the combined effects of natural and socio-economic factors, among which elevation and NDVI were the main factors, and the interaction of multiple factors showed an enhanced trend. The findings of this study can provide scientific decision-making support for the development and protection of traditional villages in YRB.

In this study, a nonstationary standardized precipitation index (NSPI) is calculated by fitting precipitation data to the nonstationary gamma model with climate indices as covariates and compared with stationary standardized precipitation index (SSPI) in fitting observed precipitation and identifying meteorological droughts during 1964–2016 in the Yangtze River basin (YRB). Results show that changing trends of NSPI are roughly consistent with those of SSPI, but the NSPI performs better than SSPI for fitting precipitation. Using the NSPI, spatiotemporal variations and joint return period of drought characteristics are investigated by using modified Mann–Kendall and copula function. It is found that the west YRB experiences mostly severe droughts but shows a mitigating tendency, while in the north-central region, moderate droughts are dominant but have an aggravating tendency. Drought peak shares a spatial distribution pattern similar to intensity, with higher averages in the west and south-central basin and lower averages in the north-central part, but they exhibit a higher occurrence frequency of droughts. The joint return periods of drought characteristics reveal that slight and moderate droughts with duration D of no more than 3 months are more likely to occur in the YRB with return periods of 2–25 years. The severe- and extreme-intensity droughts with more than 3-month duration occur rarely in the YRB, but extreme peak droughts with slight or moderate intensity could hit most of the basin in 100 years. In addition, for most drought scenarios, droughts exhibit longer return periods in the north-central and southeast parts relative to other regions of the YRB. Significance Statement Computation of a widely used standardized precipitation index depends heavily on the assumption of stationarity in precipitation, but this assumption is questionable under a changing climate. This study is the first time that a nonstationary standardized precipitation index is calculated to comprehensively assess drought in the Yangtze River basin (YRB). Results show that the basin is prone to no more than 3-month-duration slight and moderate droughts with return periods of 2–25 years, while extreme-intensity droughts longer than 3 months occur rarely. In addition, for most drought scenarios, the droughts exhibit longer return periods in the north-central and southeast parts relative to other regions of the YRB. These results are important for drought monitoring and early warning in the YRB.

With climate change, the spatial and temporal patterns of precipitation are altered to a certain degree, which potentially affects the grey water footprint (GWF) of total nitrogen (TN) in agriculture, thereby threatening water security in the Yangtze River Basin (YRB), the largest river in China. The current study constructs an assessment framework for climate change impacts on the GWF of agricultural TN by coupling Shared Socioeconomic Pathways (SSPs) with the InVEST model. The framework consists of four components: (i) data collection and processing, (ii) simulating the two critical indicators (LTN and W) in the GWF model based on the InVEST model, (iii) calculating the GWF and GWF index (GI) of TN, and (iv) calculating climate change impact index on GWF of agricultural TN (CI) under two SSPs. It is applied to the YRB, and the results show the following: (i) GWFs are 959.7 and 961.4 billion m3 under the SSP1-2.6 and SSP5-8.5 climate scenarios in 2030, respectively, which are both lower than that in 2020 (1067.1 billion m3). (ii) The GI values for TN in 2030 under SSP1-2.6 and SSP5-8.5 remain at “High” grade, with the values of 0.95 and 1.03, respectively. Regionally, the water pollution level of Taihu Lake is the highest, while that of Wujiang River is the lowest. (iii) The CI values of the YRB in 2030 under SSP1-2.6 and SSP5-8.5 scenarios are 0.507 and 0.527, respectively. And the CI values of the five regions in the YRB are greater than 0, indicating that the negative effects of climate change on GWFs increase. (iv) Compared with 2020, LTN and W in YRB in 2030 under the two SSPs decrease, while the GI of TN in YRB rises from SSP1-2.6 to SSP5-8.5. The assessment framework can provide strategic recommendations for sustainable water resource management in the YRB and other regions globally under climate change.

The quality of shallow groundwater in agricultural areas is being increasingly threatened by nitrogen pollution. However, the complex interactions between natural and anthropogenic sources remain insufficiently studied. In this study, the water chemical characteristics and nitrogen pollution sources in key agricultural areas and counties of the Yangtze River Basin were systematically investigated. Forty-three groundwater samples were analyzed for major ions and nitrides (NH4+, NO2−, NO3−) using hydrogeochemical analysis, spatial interpolation, and positive matrix factorization (PMF) models. The shallow groundwater in the study area is weakly alkaline (pH 7.36) and is dominated by calcium ions (mean 112.67 mg/L) and bicarbonate (mean 361.95 mg/L), which reveals that the hydrogeochemical characteristics are dominated by carbonate. The total hardness has increased, and the nitrogen concentration exhibits significant spatial variability. Nitrates (NO3−) exceed safety thresholds across the entire region and are strongly correlated with Cl−. The PMF analysis identified the following four major pollution factors: Factor 1 represents a combination of anthropogenic pollution and natural processes; Factor 2 is attributed to agricultural fertilizer application and septic tank leakage; Factor 3 is sourced from the weathering of carbonates and the decomposition of organic matter in a reducing environment; and Factor 4 is due to the leakage of domestic sewage or livestock-derived wastewater. Spatial analysis revealed pollution hotspots in the vicinity of urban, agricultural, and livestock areas. This study emphasizes that human activities, such as over-fertilization and inadequate wastewater management, are the main contributors to groundwater nitrogen pollution in the study area. In addition, we compare the groundwater quality of the entire Yangtze River Basin and find that there are distinct regional variations.

Hypophthalmichthys nobilis are widely distributed in the Yangtze River basin and its related lakes. They are an important economic fish species and are a famous cultured species known as the “Four Famous Domestic Fishes” in China. Currently, with the fishing ban in the Yangtze River basin, fishing for H. nobilis in the natural water bodies of the Yangtze River basin has been completely prohibited. In order to identify the sources of H. nobilis appearing in the market, further control and accountability is necessary to trace the sources of H. nobilis in the Yangtze River basin and its related water bodies. Therefore, this study identified and traced different sources of H. nobilis through muscle element fingerprint analysis (EFA). The results show that H. nobilis from different stations have characteristic element compositions. The characteristic element of H. nobilis from Wuhan (WH) is Pb, which is significantly higher than that in other stations; the characteristic element from Anqing (AQ) is Hg, which is significantly higher than that in other stations; and the characteristic element from Taihu (TH) is Al, which is significantly higher than that in other water areas. Multivariate analysis selected different spatial distribution patterns in four discriminative element ratios (Pb/Ca, Cr/Ca, Na/Ca, and Al/Ca) in the muscle of H. nobilis in the Yangtze River basin and its related lakes. This study suggests that the screened discriminative elements can be used to visually distinguish different sources of H. nobilis and to quickly trace and verify the origin of newly emerging samples. Therefore, the use of selected discriminative element fingerprint features to trace the origin of new samples has been proven to be feasible. By further discriminating and verifying the muscle element fingerprints of new samples, the discrimination rate is high. Therefore, a multivariate analysis of muscle element fingerprints can be used for tracing the origins of samples of unknown origin in market supervision.

Studying the shifts of vegetation phenology and the response of vegetation phenology to climate change helps to understand the dynamics of future ecosystems. However, since previous studies mostly focused on temperate ecosystems, much less is known about the biogeographic phenological shifts in sub-tropical regions, which have abundant biodiversity. The Yangtze River Basin (YRB) is located in the subtropical region of China and has abundant natural resources, a large population, and rapid economic development. Studying the variation characteristics of phenology and its responses to recent climate changes in YRB are important for understanding the impact of regional climate on subtropical ecosystems. In this study, we extracted the phenological parameters using Global Inventory Modeling and Mapping Studies (GIMMS) data to investigate the spatial and temporal variations of vegetation phenology across YRB during 1982–2015 and to examine how vegetation phenology responds to climate within different ecological zones. The results revealed that the start of growing season (SOS) was significantly advanced by 0.2 days/year (p < 0.01). However, there has been no significant trend in the end of growing season (EOS) throughout the whole study area for the past 34 years. The spatial pattern of the phenology metrics showed a high spatial heterogeneity: the SOS in the central YRB was earlier than that in other regions; the EOS in the southeast YRB was later than that in any other regions. Meanwhile, the SOS had a higher correlation with temperature than with precipitation. In particular, the spring temperature had a strong impact on the SOS and the effects of winter temperatures cannot be ignored. Although there were no significant correlations between the EOS and precipitation/temperature, it is interesting to note that when examining the interactions between phonological parameters, the EOS was positively correlated with the SOS. Furthermore, the pre-season temperature had a lag effect on the SOS, but no significant lag effect was observed for the EOS in YRB. In all, the present study can enhance our understanding of phenology dynamics and its relationship with climate in YRB and provide a useful reference to put forward a corresponding ecological protection policy.

Aims Terrestrial net primary production (NPP), the balance of gross primary production (GPP) and autotrophic respiration (AR), is a critical measure of carbon sequestration capacity for the Earth’s land surface. The aim of this study was to understand the spatio-temporal variability of NPP associated with GPP and AR in the Yangtze River Basin (YRB), China, from 2000 to 2009 during which the basin warmed significantly. Methods We first derived AR and carbon-use efficiency (CUE) from the improved Moderate Resolution Imaging Spectroradiometer GPP/ NPP products (MOD17) and then conducted spatial analysis to quantify how NPP relates to GPP, AR and their relationship with key observed climate variables (temperature, precipitation and sunshine percentage) in the YRB during 2000–9. Important Findings The spatial pattern of NPP in the YRB was predominantly deter mined by GPP and further modified by AR. Higher GPP and relatively low AR made the southern Jinshajiang sub-basin the most productive area in NPP in the YRB. A large portion of the YRB experienced a warmer and drier climate trend in the growing season during 2000–9. In the upper reaches of the basin, possessing a relatively low temperature base, increases in temperature led to greater increases in GPP than those in AR, resulting in greater increased NPP. However, in the middle and lower reaches of the basin where the base temperature is relatively high, increases in temperature led to greater increases in AR than those in GPP, leading to decreases in NPP. Overall, 86.7% of the vegetated area showed a consistent GPP and NPP trend through time with 71.3% of the vegetated area having a positive trend both in GPP and NPP, and the remaining 13.3% of vegetated areas showed an opposite trend in GPP and NPP, with positive GPP and negative NPP trajectories dominating (10.1% of vegetated area) the trend. Although climate warming generally had positive effects on vegetation growth in most areas of the basin, areas with increased NPP (74.5%) were less extensive than those with increased GPP (81.4%) due to the wider increase in AR (82.2%). During the study period, increases in AR offset 62% of the total increased GPP, leading to a substantial decline of CUE, particularly in the warmer lower altitude regions in the southeast. Our work reveals the diverse responses of NPP associated with GPP and AR as the climate warms and generally suggests that NPP in the middle and lower sub-basins in the YRB is more sensitive to future climate warming. These findings enhance our understanding of terrestrial ecosystem carbon dynamics in response to global warming and provide a scientific basis for managing ecosystem productivity in the YRB, China.

The spatial propagation patterns of meteorological drought events (MDEs) and underlying mechanisms contribute to elucidating and forecasting drought evolution. In this study, gridded MDEs in the Yangtze River Basin (YRB) throughout the entire year, wet season and dry season were extracted from 3-month Standardized Precipitation Evapotranspiration Index (SPEI-3) series. Event synchronization (ES) and complex networks (CN) were employed to construct the MDE synchronization networks and MDE spatial propagation networks for various periods. The former were utilized to identify MDE synchronized subregions where MDEs co-occur and co-evolve in the YRB, while the latter were used to quantify the MDE spatial propagation patterns over both the basin and its subregions. The driving mechanisms behind MDE spatial propagation were further investigated by diagnosing the concomitant drought-inducing climate systems. The findings reveal the presence of four MDE synchronized subregions during the wet season and five subregions during the entire year and dry season. These subregions exhibited distinct spatial propagation patterns of MDEs, aligning with overall findings across the YRB. Notable differences were observed between wet and dry seasons, with various subregions exhibiting distinctive spatial propagation patterns during each season. These patterns are driven by variations in the controlling atmospheric circulation systems, leading to anomalies of wind patterns and moisture distribution, ultimately resulting in deficient moisture supply. The variations of tropical sea surface thermal conditions, influences of the Tibetan Plateau and MDE self-propagation triggered by land–atmosphere feedback are considered as three primary influencing factors for MDE spatial propagation in the YRB.

The Yangtze River is one of the most important rivers in China, and its basin is the most populous urban area in China. The relationship between cities and floods in the Yangtze River Basin is of significance. In our analysis of 4,511 historical county‐level cities and 37,512 historical flood disasters, we used ARCGIS to conduct spatial analyses, including kernel density analysis, coldspot and hotspot analysis, and center of gravity analysis, to reveal the relationship between cities, population, and floods in the Yangtze River Basin in the past 2000 years. The results indicate that three relatively stable, dense urban areas are the Chengdu Plain; the border of the Anhui, Zhejiang, Jiangsu Provinces and surrounding areas; and the central Guizhou Province and southwestern part of Hubei Province. The hotspot areas of floods were the main tributaries and lakes of the Yangtze River, whereas the coldspot areas were the Chengdu Plain and the surrounding areas. More importantly, cities are not far from flood regions, and this will cause serious flooding. Due to location advantages, cities tend to be close to rivers, lakes, and other water systems. This research provides historical details of urban development and ecological environment protection in the Yangtze River Basin in China.