Spatiotemporal evolution of global long-term patterns of soil moisture

Evaluating the relative influence of climate and human activities on recent vegetation dynamics in West Bengal, India

Assessing the relative importance of climate change and human activities is important in developing sustainable management policies for regional land use. In this study, multiple remote sensing datasets, i.e. CHIRPS (Climate Hazard Group InfraRed Precipitation with Station Data) precipitation, MODIS Land Surface Temperature (LST), Enhanced Vegetation Index (EVI), Potential Evapotranspiration (PET), Soil Moisture (SM), WorldPop, and nighttime light have been analyzed to investigate the effect that climate change (CC) and regional human activities (HA) have on vegetation dynamics in eastern India for the period 2000 to 2022. The relative influence of climate and anthropogenic factors is evaluated on the basis of non-parametric statistics i.e., Mann-Kendall and Sen's slope estimator. Significant spatial and elevation-dependent variations in precipitation and LST are evident. Areas at higher elevations exhibit increased mean annual temperatures (0.22 °C/year, p < 0.05) and reduced winter precipitation over the last two decades, while the northern and southwest parts of West Bengal witnessed increased mean annual precipitation (17.3 mm/year, p < 0.05) and a slight cooling trend. Temperature and precipitation trends are shown to collectively impact EVI distribution. While there is a negative spatial correlation between LST and EVI, the relationship between precipitation and EVI is positive and stronger (R2 = 0.83, p < 0.05). Associated hydroclimatic parameters are potent drivers of EVI, whereby PET in the southwestern regions leads to markedly lower SM. The relative importance of CC and HA on EVI also varies spatially. Near the major conurbation of Kolkata, and confirmed by nighttime light and population density data, changes in vegetation cover are very clearly dominated by HA (87%). In contrast, CC emerges as the dominant driver of EVI (70-85%) in the higher elevation northern regions of the state but also in the southeast. Our findings inform policy regarding the future sustainability of vulnerable socio-hydroclimatic systems across the entire state.

Extreme rainfall erosivity: Research advances and future perspectives

Extreme rainfall erosivity, the capacity of intense rainfall to induce soil erosion, is vital for anticipating future impacts on soil conservation. Despite extensive research, significant differences persist in terms of understanding influencing mechanisms, potential impacts, estimation models and future trends of extreme rainfall erosivity. Quantitatively describing extreme rainfall erosivity remains a key issue in existing research. In this study, we comprehensively reviewed the literature to assess the relationships between extreme rainfall characteristics and rainfall erosivity, between extreme rainfall erosivity and soil erosion, estimation models and trend prediction. The aim was to summarize previous related research and achievements, providing a better understanding of the generation, impacts and future trends of extreme rainfall erosivity. Future research directions should include identifying the thresholds of extreme rainfall events, increasing research attention on tropical cyclones in terms of rainfall erosivity, considering on the impact of extreme rainfall erosivity on soil erosion, and improving rainfall erosivity estimation and simulation prediction methods. This study could contribute to adapting to global climate change and aiding in formulating soil erosion prevention and environmental protection recommendations.

Influence paradigms of soil moisture on land surface energy partitioning under different climatic conditions

Soil moisture (SM) directly controls the land surface energy partition which plays an important role in the formation of extreme weather events. However, its dependence on specific climatic conditions is not thoroughly understood due to the complexity of soil moisture effects. Here, we examine the relationship between SM and surface energy partitioning under different climate conditions, and identify the influence paradigms of soil moisture on surface energy partition. We find that temperature changes can explicitly determine the impact paradigm of different physical processes, i.e. evapotranspiration, soil freezing and thawing, and such influence paradigms are also affected by atmospheric aridity (VPD). Globally, there are five paradigms that effects on surface energy partitioning, including the warm-wet paradigm (WW), transitional paradigm (TP), warm-dry paradigm (WD), cool-wet paradigm (CW) and cold paradigm (CP). Since 1981, the global area proportion for TP is observed to increase pronouncedly. We also find that the critical SM threshold exhibits regional variations and the global average is 0.45 m3/m3. The identified paradigms and their long-term change trends provide new insights into the global intensification of land-atmosphere interaction, which has important implications for global warming and the formation of heatwaves.

Spatiotemporal links between meteorological and agricultural droughts impacted by tropical cyclones in China

Both droughts and tropical cyclones (TCs) are among the world's most widespread natural disasters. This paper is concentrated on the effects of TCs on the links between meteorological droughts (MDs) and agricultural droughts (ADs). Specifically, changes in characteristics of drought events and variations in propagation features of matched MD and AD event pairs are quantified by using the renowned three-dimensional connected components algorithm; both alleviation and exacerbation effects of TCs are evaluated; and the Spearman's correlation is employed to identify potential contributors to exacerbated droughts after TCs. The results show that TCs exhibit more pronounced and widespread alleviation effects on MD events compared to AD events. >98 % of small-scale drought events are terminated by TCs, leading to 65 % reduction in the total area of MD events smaller than 50,000 km2 and 32 % reduction in AD events of the same scale. In the meantime, TCs can reshape the spatiotemporal links between MDs and ADs by reducing the overall propagation rate from 77 % to 40 % and ameliorating the characteristics of drought event pairs with higher propagation efficiency, by >40 %. After TCs, over 55 % of drought exacerbations in TC-affected regions occur first in the vicinity of the residual large-scale AD events. This occurrence is partially associated with the reduction in moisture exports from these residual droughts downwind to the interior of TC-affected regions, a process potentially facilitated by the TC-induced temperature cooling. The in-depth evaluation of this paper presents useful information for better drought preparation and mitigation under TCs.

Discriminating the impacts of vegetation greening and climate change on the changes in evapotranspiration and transpiration fraction over the Yellow River Basin

Evapotranspiration (ET) is a vital parameter in terrestrial water-energy cycles. The transpiration fraction (TF) is defined as the ratio of transpiration (T) to evapotranspiration (ET), representing the contribution rate of vegetation transpiration to ecosystem ET. Quantifying the relative contributions of vegetation and climate change on the ET and TF dynamic is of great significance to better understand the water budget between the land and atmosphere. Here, we chose Yellow River Basin (YRB) as the study area and analyzed the spatiotemporal changes of ET, T, and TF from 1982 to 2015 using the Priestley-Taylor Jet Propulsion Laboratory (PT-JPL) model. Meanwhile, the relative contributions of vegetation and climate change to ET, T and TF change were quantified. Model evaluation showed that the PT-JPL model performs well in the simulation of ET and T. During 1982-2015, the average annual ET, T, and TF increased at a rate of 3.20 mm/a, 0.77 mm/a and 0.003/a over the YRB during 1982-2015, respectively. The regions with significant increases in ET, T and TF almost covered the whole study area except for the upper reaches of the YRB. Vegetation greening was the main factor for the increase of ET and TF in the YRB and enhanced ET and TF at a rate of 0.72 mm/a and 0.57/a, respectively, which mainly observed in the entire Loess Plateau region (over 50 % of the study area). Precipitation (PRE) was also the dominated factor contributing to the increase in ET and TF, and temperature (TEM) showed a positive correlation with the changes in ET and TF in the most areas of YRB, which jointly dominated ET changes in the upper reaches of the YRB and TF changes in the southern part of the basin. Except for the total effects, leaf area index (LAI) also indirectly promoted ET changes by affecting PRE, TEM and relative humidity (RH). While wind speed (WS) and radiation (RAD) had a relatively weak regulatory effect on the changes in ET and TF. These findings were helpful for regional water resources management and formulating water resources-sustainable vegetation restoration strategies for local government.

Quantifying climate variability and regional anthropogenic influence on vegetation dynamics in northwest India

To explore the spatio-temporal dynamics and mechanisms underlying vegetation cover in Haryana State, India, and implications thereof, we obtained MODIS EVI imagery together with CHIRPS rainfall and MODIS LST at annual, seasonal and monthly scales for the period spanning 2000 to 2022. Additionally, MODIS Potential Evapotranspiration (PET), Ground Water Storage (GWS), Soil Moisture (SM) and nighttime light datasets were compiled to explore their spatial relationships with vegetation and other selected environmental parameters. Non-parametric statistics were applied to estimate the magnitude of trends, along with correlation and residual trend analysis to quantify the relative influence of Climate Change (CC) and Human Activities (HA) on vegetation dynamics using Google Earth Engine algorithms. The study reveals regional contrasts in trends that are evidently related to elevation. An annual increasing trend in rainfall (21.3 mm/decade, p < 0.05), together with augmented vegetation cover and slightly cooler (-0.07 °C/decade) LST is revealed in the high-elevation areas. Meanwhile, LST in the plain regions exhibit a warming trend (0.02 °C/decade) and decreased in vegetation and rainfall, accompanied by substantial reductions in GWS and SM related to increased PET. Linear regression demonstrates a strongly significant relationship between rainfall and EVI (R2 = 0.92), although a negative relationship is apparent between LST and vegetation (R2 = -0.83). Additionally, increased LST in the low-elevation parts of the study area impacted PET (R2 = 0.87), which triggered EVI loss (R2 = 0.93). Moreover, increased HA resulted in losses of 25.5 mm GSW and 1.5 mm SM annually. The relative contributions of CC and HA are shown to vary with elevation. At higher elevations, CC and HA contribute respectively 85% and 15% to the increase in EVI. However, at lower elevations, reduced EVI is largely (79%) due to human activities. This needs to be considered in managing the future of vulnerable socio-ecological systems in the state of Haryana.

Combined influence of soil moisture and atmospheric humidity on land surface temperature under different climatic background

Soil moisture (SM) and atmospheric humidity (AH) are crucial climatic variables that significantly affect the climate system. However, the combined influencing mechanisms of SM and AH on the land surface temperature (LST) under global warming are still unclear. Here, we systematically analyzed the interrelationships among annual mean values of SM, AH, and LST using ERA5-Land reanalysis data and revealed the role of SM and AH on the spatiotemporal variations of LST through mechanism analysis and regression methods. The results showed that net radiation, SM, and AH could well model the long-term variability of LST well and explain 92% of the variability. Moreover, SM played an essential and different role under the different LST backgrounds. The AH always displayed a greenhouse effect on the LST. This study provides essential insights into the global climate change mechanism from the surface hydrothermal processes perspective.

Future transition in climate extremes over Western Ghats of India based on CMIP6 models

The effect of climate change on the tropical river catchments in the Western Ghats of India is studied using the Coupled Model Intercomparison Project-6 data (CMIP-6). Multi-model ensembles of rainfall and temperature are constructed using the Random Forest ensemble technique for bias-corrected GCMs in the near future (2014-2050) and far future (2051-2100) horizons. For the two catchments each in the southern, central, and northern Ghats, the trend in minimum and maximum temperatures, precipitation, and other indices are calculated. By 2100, dry sub-humid and humid catchments will see a higher increase in mean annual temperature than per-humid central catchments. In future decades, the warm days and nights increase by 45-50% and 40-70%, respectively, with twofold warming in the winter season. Under a climate change scenario, annual rainfall increases in Vamanapuram, Ulhas, and Purna, while Chaliyar, Netravati, and Aghanashini catchments experience a decrease in rainfall in the far future with an increase in pre-monsoon rainfall. The southern catchments are anticipated to have contrasting variations in the rainfall extremes; northern catchments face a substantial increase in very wet to extremely wet days and medium to heavy rainfall. In all catchments (excluding Vamanapuram), cumulative wet days increase with a decrease in cumulative dry days. After the mid-twenty-first century, humid to per-humid catchments encompass an increase in cool nights, whereas it disappears in dry sub-humid catchments of the Ghat. Interestingly, warming tendencies begin to slow down after 2050. This investigation can assist in comprehending the regional climate extremes in the Western Ghats to formulate better climate risk planning and adaptation strategies.