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Droughts resulting from global warming severely hamper the healthy development of terrestrial vegetation ecosystems. This paper defines a terrestrial vegetation ecological drought index, i.e., the Standardized Water Supply–Demand Index (SSDI), based on the water balance method using the same calculation model as the SPEI. The theory of run is used to analyze the spatial and temporal distribution of the drought characteristics in the Yangtze River Basin (YRB). The results show that (1) the drought events monitored by the SSDI were in good agreement with historical drought events, and the correlation coefficient between SSDI and NDVI (0.94) was significantly higher than that between SPEI and NDVI (0.88). (2) About 55.4% of the regions in the YRB experienced more than 13 droughts, and about 41.4% of the regions had an average drought duration of more than 3.1 months. In the northern part of the YRB, droughts tend to develop in a short-term high frequency, while in the southern part of the YRB, there is a long-term low-frequency development trend. Nearly 24.5% of the regions have an average drought intensity of more than 1.4, and most of them are located in the lower reaches of the Yangtze River. (3) Over the last 18 years, about 79.5% of the regions in the YRB showed an increasing trend in SSDI, of which 36.8% showed an increasing trend of more than 0.04/yr. In addition, 40.4% of the regions showed a significant upward trend. Precisely analyzing the spatiotemporal variation of drought characteristics in the YRB is critical for drought risk assessment and sustainable development of water resources and could provide a theoretical basis for effective water resource allocation and drought relief. • A new drought monitoring index, i.e., the Standardized Water Supply–Demand Index (SSDI) was defined. • SSDI can effectively monitor drought events. • SSDI is more suitable for monitoring ecological drought. • Drought of vegetation ecosystem in the Yangtze River Basin was assessed and analyzed with the SSDI. • It provides a theoretical basis for drought management and water allocation in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]

Abstract: This paper examines the spatial variation of sediment yield in the Yangtze basin in China, a large basin with complex geology, climate, land-use history, and extensive sediment monitoring. 287 stations with drainage area less than 10,000km2 were used to study the scale effects of sediment yield. In order to develop scale relations for regional sediment yield, the whole study area was divided into eight sub-basins. Relation between specific sediment yield and drainage basin area was built for each sub-basin. Regional scaling relation was analyzed based on landforms, geology, lithology and land-use of each sub-basin. Three regional trends were identified in relation to the drainage area: (1) a declining trend, due to soil erosion on heavily cultivated steep land and the storage of sediment in floodplains; (2) a flat trend, due to mass movement on the upper reach and heavy agricultural disturbance on the middle and lower reaches; and (3) an increasing trend, due to downstream recruitment of sediment from land downstream where slope farming and deforestation occurred. Using these developed relations, areally adjusted sediment yield maps were created over the entire Yangtze basin. [Copyright &y& Elsevier]

This paper explored the projected changes in precipitation, maximum temperature (T max), and minimum temperature (T min) over the Yangtze River Basin (YRB) based on 23 Global climate models (GCMs) from the Coupled Model Intercomparison Project phase 6 (CMIP6). The Empirical Quantile Mapping (EQM) approach was firstly applied to correct the biases in the GCMs. Next, the future changes were investigated by analyzing the multi-model ensemble (MME) of the bias-corrected dataset during 2025–2044 (near-term), 2045–2064 (mid-term), and 2081–2100 (long-term) periods, with reference to the baseline period 1995–2014, under three integrated scenarios (SSP1-2.6, SSP2-4.5, and SSP5-8.5) of the Shared Socioeconomic Pathways (SSPs) and the Representative Concentration Pathways (RCPs). Results show that: (1) the biases in CMIP6 GCMs can be effectively corrected by EQM, and the MME performs better than individual models for each climatic variable. (2) Precipitation over the YRB from 2025 to 2100 is projected to increase at the rate of 9.66 mm/decade, 13.45 mm/decade, and 21.01 mm/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, the annual precipitation is projected to increase by 10.41%, 10.66% and 15.80%, under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (3) T max (T min) over the YRB is projected to increase by 0.09 (0.07) °C/decade, 0.29 (0.27) °C/decade, and 0.66 (0.64) °C/decade under SSP1‐2.6, SSP2‐4.5, and SSP5‐8.5, respectively. In the long-term, T max (T min) averaged over the YRB is projected to increase by 1.75 (1.50) °C, 2.72 (2.54) °C and 5.04 (4.85) °C under SSP1‐2.6, SSP2‐4.5 and SSP5‐8.5, respectively. (4) Uncertainties in the projected precipitation and temperature over the YRB were reduced based on MME. But further researches, such as selecting the superior models with respect to the regional climate of the YRB from the CMIP6 and using the ensemble methods that assign weight based on the performance of each model, are still needed to provide more reliable climate projections. • Projected changes were explored by 23 CMIP6 GCMs under the three SSP-RCP scenarios. • Biases in the GCMs were corrected by Empirical Quantile Mapping (EQM) method. • Multi-model ensemble (MME) was used to reduce the uncertainties. [ABSTRACT FROM AUTHOR]

This paper developed a GIS-based spatial multi-index model for large basin-scale flood risk assessment. In terms of the risk definition proposed by the IPCC, the flood risk in the Yangtze River Basin (YRB) was classified into indexes of hazard, vulnerability, and exposure. The model systematically accounts for various flood risk indicators related to the economic, social and ecological environment of the YRB. Using the robust data space analysis and processing capabilities of ArcGIS, these flood risk indicators were superimposed and analyzed to generate an integrated flood risk spatial distribution map for the YRB. The modeling results were verified reasonably well using observation data from the YRB floods in 1998, 2008, and 2016. We found that 24.90% of the study area was at very high and high risk in 1998, and the risk in these areas decreased to 15.95% and 17.61% in 2008 and 2016, respectively. We believe that the GIS-based spatial multi-index model can be applied to other areas where basin-scale flood risk assessment is desired and contribute to further scientific research on flood forecasting and mitigation. • Develop a conceptual model for the large-scale flood risk assessment. • Integrating an index system method and a GIS-based approach. • Considering comprehensive economic, social and ecological impacts on the flood risks. • Model verification was conducted using observed floods in the Yangtze River Basin. [ABSTRACT FROM AUTHOR]