Drought propagation under global warming: Characteristics, approaches, processes, and controlling factors

Evaluating multifaceted effects of watershed properties and human activities on drought propagation in the Wei River Basin with an integrated framework

Understanding the factors driving propagation from meteorological to hydrological drought is crucial for drought mitigation. In this study, an integrated framework based on the Soil and Water Assessment Tool model, standardised drought indices and Geographical Detector were used to investigate how and to what extent watershed properties and human activities affect the spatial heterogeneity of drought propagation in the Wei River Basin, a typical arid and semi-arid region in China. Results indicated that (1) spatially, the propagation times increased from southwest to northeast. Seasonally, the propagation was shorter and stronger in summer and autumn. (2) The aridity index significantly affected the spatial distribution of drought propagation time for the entire basin, especially in summer, while human activities primarily drove spatial distribution in the sub-basins. The explanatory power of any two independent factors was non-linearly enhanced after the interaction. (3) Watershed properties potentially impacted the anthropogenic driving factor of drought propagation. Strong anthropogenic effects on drought propagation often occurred in watersheds with moderate drought levels, steep slopes, low elevations, and small areas, and the key factors varied seasonally. These findings help elucidate the multifaceted effects of watershed properties and human activities on drought propagation. The proposed framework and the results of this study provide valuable guidance for formulating precise drought control strategies in the Wei River Basin and worldwide.

Evolution of drought characteristics and propagation from meteorological to agricultural drought under the influences of climate change and human activities

Understanding the propagation of agricultural droughts (AD) is important to comprehensively assess drought events and develop early warning systems. The present study aims to assess the impacts of climate change and human activities on drought characteristics and propagation from meteorological drought (MD) to AD in the Yellow River Basin (YRB) over the 1950-2021 period using the Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Soil Moisture Index (SSMI). In total, the YRB was classified into three groups of catchments for spring wheat and four groups of catchments for winter wheat based on different human influence degrees (HId). In addition, the entire study period was divided into periods with natural (NP), low (LP), and high (HP) impacts of human activities, corresponding to 1950-1971, 1972-1995, and 1996-2021, respectively. The results demonstrated the significance and credibility of the application of the natural and human-impacted catchment comparison method for drought characteristics and propagation from meteorological to agricultural drought in the YRB. Winter wheat showed a more pronounced drying trend than spring wheat under both MD and AD. The results showed meteorological drought intensity (MDI) and agricultural drought intensity (ADI) intensified for spring and winter wheat in NP, with correspondingly a short propagation time, followed by those in the LP and HP in catchments minimally impacted by human activities. On the other hand, increases in the MDI and ADI, as well as in their times, for both spring and winter wheat were observed from the LP to the HP in all catchments. The MDI, ADI, and their propagation times for winter wheat generally showed greater fluctuations than those for spring wheat. Human activities increasingly prolonged the drought propagation time. In contrast, climate change insignificantly shortened the drought propagation time.

The first global multi-timescale daily SPEI dataset from 1982 to 2021

Global warming accelerates water cycle, causing more droughts globally that challenge monitoring and forecasting. The Standardized Precipitation Evapotranspiration Index (SPEI) is used to assess drought characteristics and response time of natural and economic systems at various timescales. However, existing SPEI datasets have coarse spatial or temporal resolution or limited spatial extent, restricting their ability to accurately identify the start or end dates or the extent of drought at the global scale. To narrow these gaps, we developed a global daily SPEI dataset (SPEI-GD), with a 0.25° spatial resolution from 1982 to 2021 at multiple timescales (5, 30, 90, 180 and 360 days), based on the precipitation from European Center for Medium Weather Forecasting Reanalysis V5 (ERA5) dataset and the potential evapotranspiration from Singer's dataset. Compared to widely used SPEIbase dataset, the SPEI-GD can improve the spatial-temporal resolution and the accuracy of SPEI in areas where meteorological sites are lacking. The SPEI-GD significantly correlates with site-based SPEI and soil moisture. Our dataset solidly supports sub-seasonal and daily-scale global and regional drought research.

Ecology of Saline Watersheds: An Investigation of the Functional Communities and Drivers of Benthic Fauna in Typical Water Bodies of the Irtysh River Basin

In this study, we investigated how changes in salinity affect biodiversity and function in 11 typical water bodies in the Altai region. The salinity of the freshwater bodies ranged from 0 to 5, the brackish water salinities ranged from 5 to 20, and the hypersaline environments had salinities > 20. We identified 11 orders, 34 families, and 55 genera in 3061 benthic samples and classified them into 10 traits and 32 categories. Subsequently, we conducted Mantel tests and canonical correlation analysis (CCA) and calculated biodiversity and functional diversity indices for each sampling site. The results indicated that biodiversity and the proportion of functional traits were greater in freshwater environments than in saline environments and decreased gradually with increasing salinity. Noticeable shifts in species distribution were observed in high-salinity environments and were accompanied by specific functional traits such as swimming ability, smaller body sizes, and air-breathing adaptations. The diversity indices revealed that the species were more evenly distributed in high-diversity environments under the influence of salinity. In contrast, in high-salinity environments, only a few species dominated. The results suggested that increasing salinity accelerated the evolution of benthic communities, leading to reduced species diversity and functional homogenization. We recommend enhancing the monitoring of saline water resources and implementing sustainable water resource management to mitigate the impact of salinity stress on aquatic communities in response to climate-induced soil and water salinization.

Climate Change in the Mediterranean Basin (Part II): A Review of Challenges and Uncertainties in Climate Change Modeling and Impact Analyses

The Mediterranean basin is particularly prone to climate change and vulnerable to its impacts. One of the most relevant consequences of climate change, especially for the southern Mediterranean regions, is certainly water scarcity as result of a reduction of surface runoff and groundwater levels. Despite the progress achieved in recent years in the field of climate change and its impact on water resources, results and outcomes should be treated with due caution since any future climate projection and derived implications are inevitably affected by a certain degree of uncertainty arising from each different stage of the entire modeling chain. This work offers a comprehensive overview of recent works on climate change in the Mediterranean basin, mainly focusing on the last ten years of research. Past and future trends on different components of the hydrological balance are discussed in a companion paper (Noto et al. 2022 ), while the present paper focuses on the problem of water availability and water scarcity. In addition, the work aims to discuss the most relevant sources of uncertainty related to climate change with the aim to gain awareness of climate change impact studies interpretation and reliability.

Evaluation of Drought Propagation Characteristics and Influencing Factors in an Arid Region of Northeast Asia (ARNA)

The characteristics of the drought propagation from meteorological drought (MD) to agricultural drought (AD) differ in various climatic and underlying surface conditions. However, how these factors affect the process of drought propagation is still unclear. In this study, drought propagation and influencing factors were investigated in an arid region of Northeast Asia (ARNA) during 1982–2014. Based on run theory, the drought characteristics were detected using the standardized precipitation index (SPI) and standardized soil moisture index (SMI), respectively. The propagation time from MD to AD was investigated, and the influence factors were identified. Results demonstrated that five clusters (C1–C5) based on land cover distribution were further classified by the K-means cluster algorithm to discuss the spatial and seasonal propagation variation. MD and AD in ARNA became more severe during the study period in all five clusters. The propagation times from MD to AD in all five clusters were shorter (1–3 months) in summer and autumn and longer (5–12 months) in spring and winter. This result suggested that the impact of vegetation on the seasonal drought propagation time was more obvious than that of the spatial drought propagation time. Precipitation and vegetation were the major impactors of AD in spring, summer and autumn (p < 0.05). The impact of precipitation on AD was more noticeable in summer, while vegetation mainly influenced AD in spring and autumn. The research also found that drought propagation time had a negative relationship (p < 0.05) with precipitation, evapotranspiration, soil moisture and NDVI in this region, which indicated that a rapid hydrological cycle and vegetation can shorten the propagation time from MD to AD. This study can help researchers to understand the drought propagation process and the driving factors to enhance the efficiency of drought forecasting.