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• The counter-demand method effectively simulates water diversion and distribution. • Successfully resolve the simulation of water extraction-conveyance-use in the Karez. • The average annual groundwater overexploitation was 173 million m3 in the ALB. • Excessive extraction of groundwater poses a threat to nature vegetation survival. The long-standing, irrational development and exploitation of water resources in the Aiding Lake Basin (ALB), coupled with excessive groundwater extraction, have led to the gradual depletion of Aiding Lake, the disappearance of Karez wells, the depletion of spring water, and the deterioration of the ecological environment, all of which are serious threats to the economy and survival and welfare of inhabitants. To address the complexities associated with the staggered distribution of natural rivers and artificial canals within the agricultural irrigated region of the ALB, an inverse computation method to gauge canal water requirements was used in building an intelligent simulation of water diversion and conveyance, incorporating different water use methodologies for complex canal systems within the irrigated region. Additionally, this paper characterizes the interaction between the catchment and conveyance section of the Karez wells and the underground aquifer based on the seasonal river module to simulate the entire flow process of the Karez well system, from water extraction and conveyance to groundwater recharge by infiltration. This study presents a coupled simulation model of seasonal river–lake-groundwater interactions in the ALB, where groundwater is simulated under both steady and unsteady flows. The findings indicate that from 2013 to 2022, the annual average groundwater recharge within the ALB was approximately 1.048 billion m3, while the discharge was 1.221 billion m3, with an annual average groundwater overexploitation of 173 million m3. Furthermore, the long-term overexploitation of groundwater has had a direct impact on the ecological environment, resulting in a survival crisis for natural vegetation except in the upper vegetative zone of Aiding Lake, which has good groundwater recharge conditions. [ABSTRACT FROM AUTHOR]

[Display omitted] • The drought pattern in China is closely related to the basin distribution and multiple teleconnection factors. • The intensity and frequency of drought in China exhibited an increasing trend. • The ENSO-AO had important positive effects in the major basins in China. • Multiple wavelet coherence helps identify the processes controlling drought changes. Due to increasing global warming and the frequent occurrence of severe drought risk in recent decades, many studies have investigated drought in China. However, the spatiotemporal heterogeneities of droughts are complicated, and a comprehensive analysis of the driving forces has not been thoroughly explored. In this paper, we studied the temporal and spatial patterns of drought in China from 1960 to 2018 and disclosed its relationship with multiple teleconnection factors on different time scales. The results show that (1) Drought in China has exhibited a fluctuating increasing trend over the past 59 years, with a standardized precipitation–evapotranspiration index (SPEI) rate of change of –0.12/10 a, and the most severe droughts occurred during 2000–2010. (2) There was a significant abrupt change in China's meteorological droughts induced by climate change around 1997. (3) The trend in China was characterized by drought in spring and autumn and humidification in winter, while the trend in the Southwest River Basin was characterized by drought. (4) A combination of factors can best explain the drought variations from basin to basin, and the El Niño-Southern Oscillation (ENSO)-Arctic Oscillation (AO) was most commonly the best predictor. The use of multiple wavelet coherence helps to identify the dominant drought change processes. [ABSTRACT FROM AUTHOR]

• A framework is proposed to analyze compound floods with multiple driving factors. • Local rainfall has a larger impact on the flooding levels of the GBA, China. • Flooding area is about 50 km2 and 1.3 m flooded depth for the worst scenario. • Findings have important implications to GBA's flooding control and management. Low-lying coastal cities are vulnerable to compound floods caused by many factors including river flows, tides and local rainfall. Many previous studies focus on the impacts of rainfall and tidal levels (two driving factors) on estuaries or regions near the main single river, while research about the three influencing factors on the floods for complex urban river networks remain relatively scarce. This paper proposes a framework to simulate the coastal compound flooding process, with a series of scenarios designed to explore the main flooding drivers and their worst possible combination. The approach is used to quantify the induced flooding consequences, in which a two-dimensional model is employed to conduct a case study for a city with complex river networks. The Qianshan River basin in Zhuhai City, located in the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) of China is used as the case study. Application results show that: (i) the occurrence and properties of flooding in this coastal area are jointly affected by upstream river flows, downstream tidal levels and local rainfall intensity with different contribution levels, (ii) compared to tidal levels, local rainfall intensity has a larger impact on the flooding levels of the study region, and (iii) the worst scenario where a 50-year return period upstream river flow co-occurring with high tide and a 100-year return period rainfall can produce a flooding area up to 50 km2 for the study region, with an average of 1.3 m flooded depth. The proposed framework with its findings offers an in-depth understanding and quantification of coastal urban flood characteristics within the GBA of China. [ABSTRACT FROM AUTHOR]