Effects and contributions of meteorological drought on agricultural drought under different climatic zones and vegetation types in Northwest China

Analysis of propagation thresholds and impact mechanisms from meteorological drought to hydrological drought in the middle and upper reaches of the Han River Basin, China

Drought propagation from meteorological drought (MD) to hydrological drought (HD) involves a temporal delay driven by multiple determinants and complex response dynamics and poses substantial challenges to river basin drought management. This study investigates the MD-HD drought progression in the Upper and Middle Han River Basin (UMHRB). We quantify the duration and intensity of drought propagation and establish the MD propagation thresholds triggering HDs under different drought categories. Furthermore, this study analyzes how meteorological variables and land surface conditions modulate drought progression and employs the coupled water-energy balance equation to reveal the underlying mechanisms influencing drought propagation. HD events generally followed MD episodes, with propagation thresholds for the UMHRB were determined via Bayes' theorem. The results indicate spatially decreasing sensitivity of HD to MD from upstream to downstream in the UMHRB. Temperature emerged as the predominant factor influencing drought progression, whereas precipitation and potential evapotranspiration (PET) showed secondary effects. Additionally, watershed's physical characteristics and anthropogenic activities, which significantly correlated with the parameters ω of the coupled water-energy balance equations, also modulated drought propagation. However, the parameter ω failed to fully represent the influence of human activities in the Huangzhuang section, suggesting a limitation that could be addressed by integrating factors pertinent to drought progression.

Climate change enhances greening while human activities accelerate degradation in northern China's grasslands

Northern China's grasslands play a pivotal role in livestock production, energy utilization, and ecosystem balance, both domestically and globally. However, they exhibit pronounced temporal variability and marked spatial heterogeneity. Since most existing studies rely on single vegetation indices and regional-scale analyses, they may introduce biases in interpreting grassland dynamics and their underlying drivers. To address this gap, we integrated both functional and structural indices - Gross Primary Productivity (GPP), solar-Induced chlorophyll fluorescence (SIF), Normalized Difference Vegetation Index (NDVI), and Leaf Area Index (LAI) - to systematically investigate spatiotemporal trends across various grassland types in northern China. Using partial derivative analysis, we quantified the relative contributions of climate change and human activities to these observed vegetation trends. Results indicated that over 70 % of grassland areas, especially temperate grasslands, showed an overall increase in vegetation indices, while a decline was observed in the southwestern alpine grasslands. Climate change was the primary driver of grassland greening (56.55 %-63.83 %), primarily through increased precipitation in temperate grasslands and rising temperatures in alpine grasslands. Human activities contributed substantially to greening (36.17 %-43.45 %), especially in desertified temperate grasslands (e.g., Mu Us Sandy Land, Gansu, Ningxia, Xinjiang) and Qinghai alpine meadows, mainly through farmland restoration and desertification control. Conversely, human activities also served as the primary driver of grassland degradation (51.70 %-69.64 %) in certain alpine regions, where overgrazing and population growth - compounded by rising temperatures and declining soil moisture - led to significant vegetation losses. Moreover, 72.66 % of temperate grasslands demonstrated strong coupling between vegetation structure and function, whereas 57.59 % of alpine grasslands exhibited increasing GPP alongside declines in both LAI and SIF. Overall, these findings underscore the spatial heterogeneity of grassland responses to climatic and anthropogenic drivers, highlighting the necessity of employing multiple vegetation indices to guide targeted and effective grassland management strategies.

Investigation into the temporal impacts of drought on vegetation dynamics in China during 2000 to 2022

Quantifying vegetation's response to drought and understanding its mechanisms is crucial for mitigating the adverse effects of drought disasters. The asymmetric cumulative and lag effects of drought on vegetation growth are widespread, yet the responses of different vegetation types, climate zones, and elevations in China remain unclear. This study used the Standardized Precipitation Evapotranspiration Index (SPEI) and Normalized Difference Vegetation Index (NDVI) to analyze vegetation status and drought trends from 2000 to 2022, examining the differentiation and mechanisms of cumulative (CED) and lag effect of drought (LED) under various conditions. The main findings are as follows: (1) 85.1% of the study area is becoming greener, with an overall growth rate of 0.026 per decade. Annual drought levels fluctuate, with increasingly severe conditions in parts of southwestern and northwestern China. (2) CED affects 35.94% of vegetated areas, with 77.44% showing a positive correlation between SPEI and NDVI. Grasslands have the longest CED (5.90 months), while forests have the shortest (4.72 months). Temperate and Arid climate zones show higher CED, at 6.91 months and 6.77 months, respectively. The highest CED is found at elevations of 2000-2500 m (6.34 months), and the lowest at 3000-3500 m (4.28 months). (3) LED affects a larger area (39.22%) with an average duration of 6.42 months, greater than the average CED (5.56 months). Grasslands have the longest LED (7.72 months), while forests (6.78 months) and shrublands (6.48 months) are shorter. The Arid climate zone has the highest LED (8.35 months), and the Tropical zone the lowest (4.82 months). LED shows significant elevation differences, being smallest at low elevations (6.48 months). (4) Climate type and potential evapotranspiration explain 0.269 and 0.259 of CED, respectively. For LED, temperature and potential evapotranspiration are dominant (0.173 and 0.167). The combination of factors significantly enhances the explanatory power of temporal effects. (5) NDVI stability is negatively influenced by CED. This study enhances understanding of the vegetation-drought relationship in China and provides theoretical support for addressing drought risks under climate change.

Evaluation of drought events using multiple drought indices under climate change in the Upper Indus Basin

Spatiotemporal variations in drought events were examined through multiple drought indices in the Upper Indus Basin (UIB) during the 1980-2020 period using observed climate data of precipitation, temperature (T max., T min., and T mean), and potential evapotranspiration (PET) from 16 meteorological stations. Software like ClimPACT2 (to quality check data and generate SPI, SPEI, and CDD drought indices), DrinC (to generate AI, eRDI and PD drought indices), CMhyd (to bias correct NASA POWER gridded data), and ArcGIS (to map extreme drought years) were used in this study. It was revealed that precipitation decreased at 30 mm/decade and maximum and minimum temperatures increased at 0.132 °C/decade and 0.23 °C/decade, aridity increased by decreasing aridity index at 0.15/decade, and number of consecutive dry days increased at 2 days/decade. All drought indices reflected decreasing trends, indicating a warming and drying climatic regime. The eRDI drought index analysis revealed that droughts have occurred for 12.6 years in the last four decades, and mild droughts (15%) are more common, followed by moderate droughts (9.4%), severe droughts (4.7%), and extreme droughts (2.4%). The study provides comparisons of drought patterns under changing climate in three distinct climatic and physical regions of UIB, i.e., Jammu, Kashmir, and Ladakh, and reveals that the UIB is not free from droughts.

Dynamic evolution trend and driving mechanisms of water conservation in the Yellow River Basin, China

Water conservation (WC) is a critical ecological service function in the Yellow River Basin (YRB). There is currently a lack of detailed exploration of WC development processes and the impact mechanisms of driving factors at spatiotemporal scales in the YRB. By collecting data on DEM, land use, soil, meteorology, reservoirs, and observed discharge, this study established a large-scale WC model using the soil and water assessment tool (SWAT). The abrupt change test, empirical orthogonal function (EOF), wavelet analysis, hierarchical partitioning analysis (HPA), geodetectors, and aridity index were employed to analyze the multi-spatiotemporal characteristics and driving forces of WC calculated using the water balance method. The results are as follows: (1) The average WC among the YRB was 9.11 mm (74.68 × 108 m3) from 1960 to 2020. Pasture and forests contributed to 48.65% and 22.05% of the average annual WC, respectively. (2) WC exhibited four forms: less/more in the YRB, more in the southeast (northwest), and less in the northwest (southeast). (3) Forests and pastures in land use had higher average WC capacity, while Gansu, Shaanxi, and Qinghai ranked in the top three for average WC among the nine provinces. (4) Precipitation was the major driving force affecting WC variations, with the interaction between precipitation and actual evapotranspiration being the most significant. (5) Drought was a significant cause of negative WC. Protecting and managing crucial WC areas was essential for improving the ecological environment. This research elucidates the driving forces of WC in the YRB, providing scientific support for improving regional WC and promoting sustainable development.

The impact of extreme precipitation on water use efficiency along vertical vegetation belts in Hengduan Mountain during 2001 and 2020

In the context of climate change, extreme precipitation events are continuously increasing and impact the water‑carbon coupling of ecosystems. The vertical vegetation zonation, as a characteristic of mountain ecosystems, reflects the differences in vegetation response to climate change at different elevations. In this study, we used the water use efficiency (WUE) as an indicator to evaluate the water‑carbon relationship. By using MODIS data, we analyzed the spatiotemporal patterns of gross primary productivity (GPP), evapotranspiration (ET), and WUE from 2001 to 2020, as well as the responses of WUE to extreme wetness factor Number of precipitation days (R0.1), extreme dryness factor Consecutive dry days (CDD), and meteorological factors under the vertical vegetation zonation. Our results showed that annual GPP and ET displayed a significant increasing trend between 2001 and 2020, whereas WUE showed a weak decreasing trend. Spatially, GPP and WUE decreased with increasing elevation. Analyzing the WUE of mountainous ecosystems as a unified whole may not precisely capture the reactions of vegetation to severe rainfall occurrences. In fact, across different vegetation belts in mountainous areas, there exists a negative correlation between WUE and R0.1, and a positive correlation with CDD. In terms of meteorological factors, the temporal variation of GPP was primarily associated with vapor pressure deficit (VPD) and temperature (Ta), while those of ET was mainly related to soil water content (SWC). WUE was affected by a combination of meteorological factors and had a certain degree of variation between different altitude intervals. These findings contribute to a better understanding and prediction of the relationship between extreme rainfall climate and water‑carbon coupling in mountainous areas.

Assessing the dynamics and trigger factors of drought propagation in the China-Pakistan economic corridor: A three-dimensional perspective

Effectively managing drought in the China-Pakistan Economic Corridor (CPEC) region requires a precise understanding of the three-dimensional characteristics of meteorological drought (MD) and agricultural drought (AD), as well as the factors that trigger their propagation. This study employed non-stationary drought indices (NSPEI and SSMI) to develop a cutting-edge 3-dimensional drought identification model. This model was used to detect MD and AD patterns from 1981 to 2022 in the CPEC region and was integrated with binomial logistic regression to identify the critical factors that drive drought propagation. This study's key findings include: 1) Between 1981 and 2022, droughts in Xinjiang, China, exhibited a discernible southward migration trend, while in Pakistan, droughts showed a northward migration pattern. Drought frequency and extent have increased over time, with affected regions becoming more widespread in CPEC. Notably, drought events with higher preceding drought contagion indices (DCI) were more likely to evolve into extreme, long-term droughts. 2) Drought area emerged as a significant positive triggering factor for drought propagation in the CPEC region. Conversely, snowmelt in Xinjiang and the leaf area index for low vegetation in Pakistan acted as triggering elements affecting negatively. 3) Various factors played a pivotal role during drought propagation process, including geographical coordinates of drought centroids, DCI, and temperature variations. Additionally, snowmelt and snow evaporation significantly impacted drought propagation in Xinjiang, while vegetation cover in Pakistan played a crucial role during the drought propagation process. By utilizing four regression models and conducting comprehensive attribution analysis, this study sheds light on the characteristics of drought propagation and the factors influencing it. These findings are valuable for enhancing early warning systems and implementing effective drought mitigation strategies in the CPEC region.

Nonlinear effects of agricultural drought on vegetation productivity in the Yellow River Basin, China

Agricultural drought (AD) is the main environmental factor affecting vegetation productivity (VP) in the Yellow River Basin (YRB). In recent years, the nonlinear effects of AD on VP in the YRB have attracted much attention. However, it is still unclear whether fluctuating AD will have complex nonlinear effects on VP in the YRB, and there are scant previous studies at large scale on whether there is a threshold for nonlinear effects of AD on VP in the YRB. Therefore, this study used a newly developed agricultural drought index to explore nonlinear effects on VP revealing the nonlinear effects of AD on VP in the YRB. First, we developed a kernel temperature vegetation drought index (kTVDI) based on kernel normalized difference vegetation index (kNDVI) and land surface temperature data to study the spatiotemporal variation of AD in the YRB. Second, we used GPP data from solar-induced chlorophyll fluorescence inversion as an indicator to explore the spatiotemporal variation of VP in the YRB. Finally, we used several statistical indicators and a distributed lag nonlinear model (DLNM) to analyze the nonlinear effect of AD on VP in the YRB. The results showed that AD decreased significantly during 2000-2020, mainly in the southeast of the Loess Plateau, while GPP increased significantly in 80.93 % of the YRB. Meanwhile, moderate and severe AD stress limited VP growth, with the negative effects gradually decreasing, while mild AD had an increasingly positive promoting effect on VP. AD stress resulted in a VP decrease of 69.78 %, and severe AD stress resulted in a VP decrease of 65.52 %, mainly distributed in the northern Loess and Ordos Plateau. AD had significant nonlinear effects on VP. The effects of moderate and severe AD on the sustained nonlinear lag of vegetation were more obvious, and those of moderate and severe AD on the nonlinear lag of VP were the largest when the lag was approximately 1 month and 7 months. The effect of AD on the nonlinear hysteresis of VP in YRB was significantly different under different vegetation types, and forests were more able to withstand longer and more severe droughts than grasslands and croplands. The results of the study provide a theoretical basis for evaluating AD and analyzing the nonlinear impact of AD on VP. This will provide scientific basis for studying the mechanism of drought effect on vegetation in other regions.

Understanding the effects of flash drought on vegetation photosynthesis and potential drivers over China

Flash droughts characterized by rapid onset and intensification are expected to be a new normal under climate change and potentially affect vegetation photosynthesis and terrestrial carbon sink. However, the effects of flash drought on vegetation photosynthesis and their potential dominant driving factors remain uncertain. Here, we quantify the susceptibility and response magnitude of vegetation photosynthesis to flash drought across different ecosystems (i.e., forest, shrubland, grassland, and cropland) in China based on reanalysis and satellite observations. By employing the extreme gradient boosting model, we also identify the dominant factors that influence these flash drought-photosynthesis relationships. We show that over 51.46 % of ecosystems across China are susceptible to flash drought, and grasslands are substantially suppressed, as reflected in both sensitivity and response magnitude (with median gross primary productivity anomalies of -0.13). We further demonstrate that background climate differences (e.g., mean annual temperature and aridity) predominantly regulate the response variation in forest and shrubland, with hotter/colder or drier ecosystems being more severely suppressed by flash drought. However, in grasslands and croplands, the differential vegetation responses are attributed to the intensity of abnormal hydro-meteorological conditions during flash drought (e.g., vapor pressure deficit (VPD) and temperature anomalies). The effects of flash droughts intensify with increasing VPD and nonmonotonically relate to temperature, with colder or hotter temperatures leading to more severe vegetation loss. Our results identify the vulnerable ecological regions under flash drought and enable a better understanding of vegetation photosynthesis response to climate extremes, which may be useful for developing effective management strategies.

Multifaceted insights into the environmental adaptability of Arnebia guttata under drought stress

Introduction

Global warming has led to increased environmental stresses on plants, notably drought. This affects plant distribution and species adaptability, with some medicinal plants showing enhanced drought tolerance and increased medicinal components. In this pioneering study, we delve into the intricate tapestry of Arnebia guttata, a medicinal plant renowned for its resilience in arid environments. By fusing a rich historical narrative with cutting-edge analytical methodologies, this research endeavors to demystify the plant's intricate response to drought stress, illuminating its profound implications for medicinal valorization.

Methods

The methodology includes a comprehensive textual research and resource investigation of A. guttata, regionalization studies, field sample distribution analysis, transcriptome and metabolome profiling, rhizosphere soil microbiome analysis, and drought stress experiments. Advanced computational tools like ArcGIS, MaxEnt, and various bioinformatics software were utilized for data analysis and modeling.

Results

The study identified significant genetic variations among A. guttata samples from different regions, correlating with environmental factors, particularly precipitation during the warmest quarter (BIO18). Metabolomic analysis revealed marked differences in metabolite profiles, including shikonin content, which is crucial for the plant's medicinal properties. Soil microbial community analysis showed variations that could impact plant metabolism and stress response. Drought stress experiments demonstrated A. guttata's resilience and its ability to modulate metabolic pathways to enhance drought tolerance.

Discussion

The findings underscore the complex interplay between genetic makeup, environmental factors, and microbial communities in shaping A. guttata's adaptability and medicinal value. The study provides insights into how drought stress influences the synthesis of active compounds and suggests that moderate stress could enhance the plant's medicinal properties. Predictive modeling indicates future suitable growth areas for A. guttata, aiding in resource management and conservation efforts. The research contributes to the sustainable development of medicinal resources and offers strategies for improving the cultivation of A. guttata.

Dynamics of solar-induced chlorophyll fluorescence (SIF) and its response to meteorological drought in the Yellow River Basin

Solar-induced chlorophyll fluorescence (SIF) has been used since its discovery to characterize vegetation photosynthesis and is an effective tool for monitoring vegetation dynamics. Its response to meteorological drought enhances our comprehension of the ecological consequences and adaptive mechanisms of plants facing water scarcity, informing more efficient resource management and efforts in mitigating climate change. This study investigates the spatial and temporal patterns of SIF and examines how vegetation SIF in the Yellow River Basin (YRB) responds to meteorological drought. The findings reveal a gradual southeast-to-northwest decline in SIF across the Yellow River Basin, with an overall increase-from 0.1083 W m-2μm-1sr-1 in 2001 to 0.1468 W m-2μm-1sr-1 in 2019. Approximately 96% of the YRB manifests an upward SIF trend, with 75% of these areas reaching statistical significance. The Standardized Precipitation Evapotranspiration Index (SPEI) at a time scale of 4 months (The SPEI-4), based on the Liang-Kleeman information flow method, is identified as the most suitable drought index, adeptly characterizing the causal relationship influencing SIF variations. As drought intensified, the SPEI-4 index markedly deviated from the baseline, resulting in a decrease in SIF values to their lowest value; subsequently, as drought lessened, it gravitated towards the baseline, and SIF values began to gradually increase, eventually recovering to near their annual maximum. The key finding is that the variability of SIF with SPEI is relatively pronounced in the early growing season, with forests demonstrating superior resilience compared to grasslands and croplands. The responsiveness of vegetation SIF to SPEI can facilitate the establishment of effective drought early warning systems and promote the rational planning of water resources, thereby mitigating the impacts of climate change.

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.

Vegetation cover dynamics and its constraint effect on ecosystem services on the Qinghai-Tibet Plateau under ecological restoration projects

Ecological restoration projects (ERPs) are implemented worldwide to restore degraded ecosystems and promote ecosystem sustainability. In recent years, a series of ERPs have been implemented to enhance vegetation cover in the unique alpine ecosystems of the Qinghai-Tibet Plateau (QTP). However, the current assessment of the ecological benefits of ERPs is relatively single, and the scale and extent of future ecological restoration project implementation cannot be determined. We quantified trends in normalized vegetation index (NDVI) since the implementation of ERPs. Changes in four major ecosystem services were assessed before and after ERPs implementation, including wind erosion protection, soil retention, water yield, and net primary productivity (NPP). The relationship between NDVI and ecosystem services was further explored using a constraint line approach to identify NDVI as a threshold reference for ERPs implementation. The results showed that: (1) since the implementation of ERPs, 21.80% of the regional NDVI of the QTP has increased significantly. (2) After the implementation of ERPs, the average total ecosystem services index (TES) increased from 0.269 in 2000 to 0.285 in 2020. The average soil retention and water yield increased but the NPP and sandstorm prevention decreased slightly. (3) NDVI had no significant constraint effect on soil retention and NPP, but there was a significant constraint effect on wind erosion prevention and water yield. (4) The constraint line of NDVI on TES was S-shaped. After the implementation of ERPs, the TES gradually reached a threshold value when NDVI was 0.65-0.75. Our findings identify significant contributions of ERPs and thresholds for the constraining effects of vegetation cover on ecosystem services, which can inform sustainable ERPs for governments.

Spatio-temporal characteristics and driving mechanism of land degradation sensitivity in Northwest China

Northwest China has been experiencing severe land degradation for a long time due to various natural and social elements. Evaluating and analyzing the process of occurrence and driving mechanism of land degradation sensitivity in this area is crucial for enhancing the local ecological environment. In this study, 18 social and environmental elements were used to construct a land degradation sensitivity index (LDSI) evaluation system in the area from vegetation, climate, management, soil, and geomorphology five factors. The spatio-temporal characteristics of LDSI in Northwest China from 2000 to 2020 were evaluated on the basis of analyzing the developmental changes of each factor. Correlation analysis and multiscale geographical weighting regression (MGWR) were used to reveal the driving mechanism of land degradation sensitivity. The results indicated a high level of land degradation sensitivity in Northwest China, with >66 % of the area (190.96 × 104 km2) in the critical sensitive class from 2000 to 2020. But the land degradation sensitivity decreased in 18.52 % of the area (53.58 × 104 km2) from 2000 to 2020, the overall trend was weakening. The spatial distribution mainly showed stronger sensitivity in the northwest and weaker sensitivity in the southeast. By exploring the driving mechanism of land degradation sensitivity, it was found that vegetation and climate showed a strong correlation, with a correlation coefficient >0.8. Drought resistance played a strong role in the dynamic process of land degradation. The basic dynamic elements showed some spatial variability in land degradation in different regions. This study is of significance for land degradation prevention and sustainable development in Northwest China.

Spatiotemporal evolution of agricultural drought and its attribution under different climate zones and vegetation types in the Yellow River Basin of China

Ecological protection and high-quality development of the Yellow River Basin (YRB) are major national strategies in China. Agricultural drought (AD) is one of the most important stress factors of the ecological security of the YRB. Currently, there is a lack of exploration of the spatiotemporal evolution of AD in the YRB under different climatic zones and vegetation types, and the mechanisms by the driving factors influence AD remain unclear. The Temperature Vegetation Dryness Index (TVDI) for the YRB in China during 2000-2020 was calculated using Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). We analyzed the spatiotemporal evolution of AD from the perspective of upstream of the YRB (UYRB), midstream of the YRB (MYRB), and downstream of the YRB (DYRB), as well as different climate zones and vegetation types. The driving factors were selected based on the Pearson correlation analysis, Geographical detector, and Mantel test. Structural equation modeling (SEM) was employed to quantify the direct and indirect effects of the driving factors on AD in the YRB. We found a slowing trend of AD in the YRB, mainly in the Loess Plateau, which is distributed in UYRB and MYRB, but an increasing trend for AD in DYRB. Temperature, which is the most direct influential factor, has exacerbated AD in UYRB and MYRB. However, surface solar radiation (SSR) has the greatest constraining effect on DYRB. AD increased in arid and desert zones, while a decreasing trend is observed for other climatic zones and vegetation types. In arid and semiarid zones, human activities and SSR were the largest indirect factors exacerbating AD. In humid and subhumid zones, the largest indirect factor exacerbating AD was potential evapotranspiration (PET). Temperature is the most direct factor exacerbating AD in cropland and forest, while PET is the largest indirect factor exacerbating AD in grassland. This study elucidates the driving factors and mechanisms of AD in the YRB to provide scientific decision support for mitigating regional drought and promoting regional sustainable development.

Study on the relationship between regional soil desertification and salinization and groundwater based on remote sensing inversion: A case study of the windy beach area in Northern Shaanxi

Soil desertification and salinization are important environmental concerns in arid regions, and their relationship with groundwater change must be further clarified. However, the relationships among soil desertification, salinization, and groundwater are difficult to investigate on a large spatiotemporal scale using traditional ground surveys. In the windy beach area in Northern Shaanxi (WBANS), desertification and salinization problems coexist; therefore, this area was selected as the study area. The feasibility of implementing large-scale remote sensing inversions to identify the degree of desertification and salinization was verified based on measured data, and the degree of influence of groundwater burial depth (GBD) on desertification and salinization was quantified using the geodetector and residual trend analysis methods. The results showed that the GBD in the WBANS presented an increasing trend and the degree of salinization showed a decreasing trend. Moreover, the joint influence of the unique natural environment and anthropogenic activities has led to increases in fractional vegetation cover and considerable improvements in the ecological environment. The intensity of desertification explained by GBD in the WBANS increased significantly (p < 0.01) at a rate of change of 0.0190/year, with high q-values above 0.66 for both Yuyang and Shenmu. The contribution rate of potential evapotranspiration and precipitation to salinization in Yuyang and Shenmu was >97 %, and the contribution rate of GBD to salinization in Dingbian, Jingbian, and Hengshan was 34.78 %, 31.15 %, and 29.41 %, respectively. Overall, the suitable GBD in the WBANS is 2-4 m. The study results provide a reference for research on the inversion, monitoring, and prevention of desertification and salinization dynamics on a large spatiotemporal scale and offer a scientific basis for rationally determining GBD.

Quantifying the drought sensitivity of grassland under different climate zones in Northwest China

Grassland is essential for maintaining the stability and functionality of terrestrial ecosystems. Although previous research has explored how grassland responds to drought, the drought sensitivity of grassland (DSG) across climate zones and aridity gradients remains uncertain. In this study, we conducted a comprehensive investigation spanning 1982 to 2015 in Northwest China. To assess the time-cumulative effect (TCE) and the time-lag effect (TLE) of drought on grassland, we employed Spearman rank correlation analysis, utilizing long-term datasets of the normalized difference vegetation index (NDVI) and the standardized precipitation evapotranspiration index (SPEI). This analysis allowed us to quantify the DSG in the region and further examine its variations across climate zones and aridity gradient. Our results revealed that 81.2 % and 99.7 % of the grassland in Northwest China was influenced by the TCE and TLE of drought, respectively, with 38.2 % and 60.9 % of these effects being statistically significant (p < 0.05). The mean accumulated and lagged timescales of drought on grassland were 7.89 and 9.41 months, respectively. Remarkably, the highest DSG was observed in the semi-arid zone (0.58), followed by the arid (0.54), sub-humid (0.51), and humid (0.44) zones. Furthermore, we identified significant nonlinear variation patterns of DSG along the aridity gradient, characterized by several discernible trend breaks. These findings contribute to our understanding of the impacts of drought on vegetation, particularly in ecologically fragile regions.

Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions

Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.

Effects of extreme drought events on vegetation activity from the perspectives of meteorological and soil droughts in southwestern China

Under climate warming, extreme drought events (EDEs) in southwestern China have become more frequent and severe and have had significant impacts on vegetation growth. Clarifying the influence of soil and meteorological droughts on the vegetation photosynthetic rate (PHR) and respiration rate (RER) can help policymakers to anticipate the impacts of drought on vegetation and take measures to reduce losses. In this study, the frequency and features of EDEs from 1990 to 2021 were analyzed using the standardized precipitation evapotranspiration index, and the longest-lasting and most severe EDE was chosen to assess the effects of drought on vegetation activity. Then, a land surface model was used to simulate the vegetation PHR and RER. Finally, the effects of the EDE on the vegetation PHR and RER were analyzed from the perspectives of soil and meteorological droughts. The results revealed that from 1990 to 2021, a total of 11 EDEs were observed in southwestern China, and the longest-lasting and most severe EDE occurred in 2009-2010 (EDE2009/2010). EDE2009/2010 significantly reduced the monthly mean PHR and RER by 9.82 g C m-2 month-1 and 0.80 g C m-2 month-1, respectively, causing a cumulative reduction of approximately 5.61 × 1013 g C. Soil and meteorological droughts had a driving force of 39 % on the PHR changes and an explanatory force of 42 % on the RER reduction. In particular, the soil drought had an average explanatory force of 25 % on the PHR and made a contribution of 24 % to the RER. The drought affected different types of vegetation differently, and crops were more susceptible than grassland and forests on the monthly time scale. The vegetation exhibited resilience to drought, returning to normal PHR and RER levels 2 months after the end of EDE2009/2010. This research contributes to understanding and predicting the impact of EDEs on vegetation growth in southwestern China.

Drought characteristics and dominant factors across China: Insights from high-resolution daily SPEI dataset between 1979 and 2018

Drought, a complex phenomenon exacerbated by climate change, is influenced by various climate factors. The escalating global temperatures associated with climate change, impact precipitation patterns and water cycle processes, consequently intensifying the occurrence and severity of droughts. To effectively address and adapt to these challenges, it is crucial to identify the dominant climate factors driving drought events. In this study, we utilized the 1979-2018 Chinese meteorological forcing dataset to calculate the daily Standardized Precipitation Evapotranspiration Index (SPEI). The Theil-Sen and Mann-Kendall (M-K) tests were employed to analyze the spatial and temporal trends of drought severity and duration. Additionally, partial correlation analysis was conducted to examine the relationship between climate factors (precipitation and potential evapotranspiration (PET)) and drought characteristic (drought severity and duration). Through this comprehensive analysis, we aimed to identify the primary factors influencing drought severity and duration. The findings revealed the following key results: (1) Over the 40-year period from 1979 to 2018, drought trends in China and its seven climate divisions exhibited an increasing pattern. (2) During drought periods, most regions exhibited a positive correlation between PET and drought severity and duration, while precipitation demonstrated a negative correlation. However, certain areas experiencing severe drought displayed a negative correlation between PET and drought severity and duration, precipitation demonstrated a positive correlation with drought severity and duration. (3) PET emerged as the dominant climatic factor for meteorological drought in the majority of China. These findings contribute valuable insights for policymakers in the development of climate change adaptation and mitigation strategies. By understanding the dominant climate factors driving drought events, policymakers can implement effective measures to mitigate the adverse socioeconomic and environmental impacts associated with climate change.

Vegetation drought risk assessment based on the multi-weight methods in Northwest China

Vegetation makes an outstanding contribution to the stability of ecosystems and to a certain extent reflects the state of the terrestrial ecosystem. Drought conditions greatly affect the growth and development process of vegetation due to its remarkable stochasticity and complexity. Due to the complex coupling mechanism between vegetation and drought, the research on vegetation drought risk is still limited. In this work, we focus on Northwest China and use the improved vegetation health index (VHI) and other multi-source data. We selected indicator factors based on both hazard and vulnerability, and adopt three weight determination methods, namely entropy method, critic method, and coefficient of variation method, to construct the corresponding index model, and also to establish a vegetation drought risk assessment model to quantitatively evaluate the drought risk of vegetation in northwest China. Results show that the percentage of each drought category remarkably changed during the period encompassing 1981-2020, and the vegetation drought shows deterioration in more areas of northwest China. The vegetation drought risks derived from the three weight determination methods were generally consistent, but differed for a particular vegetation type. The overall spatial distribution pattern of vegetation drought risk in Northwest China is higher in the west and lower in the east, and the vegetation in southern Qinghai and northwestern Xinjiang presents higher drought risk. This study may be used as a tool to provide quantitative basis for vegetation protection and vegetation drought management.

Probabilistic assessment of drought stress vulnerability in grasslands of Xinjiang, China

In the process of climate warming, drought has increased the vulnerability of ecosystems. Due to the extreme sensitivity of grasslands to drought, grassland drought stress vulnerability assessment has become a current issue to be addressed. First, correlation analysis was used to determine the characteristics of the normalized precipitation evapotranspiration index (SPEI) response of the grassland normalized difference vegetation index (NDVI) to multiscale drought stress (SPEI-1 ~ SPEI-24) in the study area. Then, the response of grassland vegetation to drought stress at different growth periods was modeled using conjugate function analysis. Conditional probabilities were used to explore the probability of NDVI decline to the lower percentile in grasslands under different levels of drought stress (moderate, severe and extreme drought) and to further analyze the differences in drought vulnerability across climate zones and grassland types. Finally, the main influencing factors of drought stress in grassland at different periods were identified. The results of the study showed that the spatial pattern of drought response time of grassland in Xinjiang had obvious seasonality, with an increasing trend from January to March and November to December in the nongrowing season and a decreasing trend from June to October in the growing season. August was the most vulnerable period for grassland drought stress, with the highest probability of grassland loss. When the grasslands experience a certain degree of loss, they develop strategies to mitigate the effects of drought stress, thereby decreasing the probability of falling into the lower percentile. Among them, the highest probability of drought vulnerability was found in semiarid grasslands, as well as in plains grasslands and alpine subalpine grasslands. In addition, the primary drivers of April and August were temperature, whereas for September, the most significant influencing factor was evapotranspiration. The results of the study will not only deepen our understanding of the dynamics of drought stress in grasslands under climate change but also provide a scientific basis for the management of grassland ecosystems in response to drought and the allocation of water in the future.

Construction and application of Optimized Comprehensive Drought Index based on lag time: A case study in the middle reaches of Yellow River Basin, China

Drought is a complex and dynamic natural phenomenon. A single drought index can hardly reflect the multi-type characteristics of drought, and comprehensive drought indices that incorporate data from multiple sources have been proposed recently. In this study, an Optimized Comprehensive Drought Index (OCDI) was constructed by taking into account the lag time of meteorological drought, agricultural drought and hydrological drought. The Standardized Precipitation Evapotranspiration Index (SPEI), Vegetation Condition Index (VCI), and Water Storage Deficit Index (WSDI) represented the three types of droughts, respectively. Specifically, we used the Solar-induced Chlorophyll Fluorescence (SIF) to characterize the vegetation condition instead of the Normalized Difference Vegetation Index (NDVI). The application results of the proposed drought index in the middle reaches of Yellow River basin (MRYRB) showed that the lag time of different types of drought indices had seasonal differences, with a shorter lag time in summer (0-4 months) and a longer lag time in winter and spring (> 4 months). For typical drought events, the drought intensity and duration identified by OCDI were compatible with the drought evolution characteristics and consistent with the historical records, therefore, OCDI is more suitable for drought monitoring in the study area. Based on the monitoring results of the OCDI, the average number of droughts in the MRYRB was 16 times, with a duration of 2.8 months and an average drought intensity of 0.28 (at moderate drought grade). Drought times and intensity were higher in the northwestern part of the study area, and spring was a high-frequency period for drought occurrences.

How can an ecological compensation threshold be determined? A discriminant model integrating the minimum data approach and the most appropriate land use scenarios

Ecological compensation has become very common worldwide due to the imbalance in the development of modern society, economy, and the environment and the increased pressure on ecosystem carrying capacity. Nonetheless, the various approaches for quantifying ecological compensation standards differ significantly. Thus, the process for determining a reasonable ecological compensation threshold is important to understand. To ensure the maximization of ecosystem service supply and economic benefit incentives for farmers, this paper constructs a discriminant model of an ecological compensation threshold based on the minimum data approach and the most appropriate land use scenario to define the ecological compensation threshold of the Sloping Land Conversion Program in the upper Yangtze River basin. The results show that with an increase in the compensation price, the proportion of farmers participating in returning farmland to forests and grassland increases, and water conservation increases. However, the discriminant curve first increases to a certain threshold point and then decreases, after which the ecoefficiency rate obtained from the compensation decreases. The ecological compensation thresholds for Chongqing, Sichuan, Yunnan, Guizhou, Hubei, Qinghai, Gansu, Tibet and Shaanxi provinces are 17.74 yuan/m³, 13.79 yuan/m³, 19.1 yuan/m³, 17.79 yuan/m³, 15.28 yuan/m³, 45.14 yuan/m³, 17.23 yuan/m³, 25.2 yuan/m³ and 22.36 yuan/m³, respectively. This research examines ecological compensation standards in different watersheds throughout the world and discusses the relationship between ecological compensation and water conservation. The discriminant model of the ecological compensation threshold can provide a new reference for the implementation and management of ecological compensation policies.

Effects of climate changes on net primary productivity variation in the marsh area of the Sanjiang Plain

The Sanjiang Plain includes the largest freshwater marsh in China, playing an important role in regional carbon cycle. As an important indicator of carbon cycle, the net primary productivity (NPP) is a crucial index for estimating the carbon storage of marshy wetlands. Investigating the association between climate factors and NPP variation quantitatively is of great significance for estimating carbon sequestration of marsh. Based on NPP data and climatic data from 1954 to 2014, the spatiotemporal change of NPP in marsh area was analyzed and its association with climate factors was investigated in the Sanjiang Plain in this study. The results indicated that the NPP showed an increase trend in the marsh area of the Sanjiang Plain in the past six decades. Temperate growth made the largest contribution to the NPP increase among the main climate factors in the last six decades, followed by CO2 concentration. Solar Radiation had the largest explanatory power on the spatial distribution of NPP among three climate factors before 1985. After 1985, temperature played an important role in leading the NPP distribution. Results also showed that the explanatory power of interactions between climate factors was stronger than that of single factor. Our results highlight the asymmetric effects of interactions between climate factors on marsh vegetation, which should be adequately considered in estimating carbon sequestration in marsh area in the Sanjiang Plain.

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

Drought is a costly natural hazard with far-reaching impacts on agriculture, ecosystem, water supply, and socio-economy. While propagating through the water cycle, drought evolves into different types and affects the natural system and human society. Despite much progress made in recent decades, a synthesis of the characteristics, approaches, processes, and controlling factors of drought propagation is still lacking. We bridge this gap by reviewing the recent progress of drought propagation and discussing challenges and future directions. We first introduce drought propagation characteristics (e.g., response time scale, lag time), followed by different approaches, including statistical analysis and hydrological modeling. The recent progress in the propagation from meteorological drought to different types of drought (agricultural drought, hydrological drought, and ecological drought) is then synthesized, including the basic process, commonly used indicators, data sources, and main findings of drought propagation characteristics. Different controlling factors of drought propagations, including climate (e.g., aridity, seasonality, and anomalies of meteorological variables), catchment properties (e.g., slope, elevation, land cover, aquifer, baseflow), and human activities (e.g., reservoir operation and water diversion, irrigation, and groundwater abstraction), are then summarized. Challenges in drought propagation include the discrepancy in drought indicators (and approaches) and difficulty in characterizing the full propagation process and isolating influencing factors. Future analysis of drought propagation should shift from single indicators to multiple indicators, from individual drivers to combined drivers, from uni-directional analysis to feedbacks, from hazards to impacts, and from stationary to nonstationary assumptions. This review is expected to be useful for drought prediction and management across different regions under global warming.