Search Results (254)

Leaf phenology is key to ecosystem functioning by regulating carbon, water, and energy fluxes and influencing vegetation productivity. Yet, detecting land surface phenology (LSP) in drylands using remote sensing remains particularly challenging due to sparse and heterogeneous vegetation cover, high spatiotemporal variability, and complex spectral signals. Unlike the Northern Hemisphere, these challenges are further compounded in the Southern Hemisphere (SH), where several regions experience year-round moderate temperatures. When combined with irregular rainfall, this leads to highly variable vegetation activity throughout the year. However, LSP dynamics in the SH remain poorly understood. This study presents a review of remote sensing-based phenology research in drylands, integrating (i) a synthesis of global methodological advances and (ii) a systematic analysis of peer-reviewed studies published from 2015 through April 2025 focused on SH drylands. This review reveals a research landscape still dominated by conventional vegetation indices (e.g., NDVI) and moderate-spatial-resolution sensors (e.g., MODIS), though a gradual shift toward higher-resolution sensors such as PlanetScope and Sentinel-2 has emerged since 2020. Despite the widespread use of start- and end-of-season metrics, their accuracy varies greatly, especially in heterogeneous landscapes. Yet, advanced products such as solar-induced chlorophyll fluorescence or the fraction of absorbed photosynthetically active radiation were rarely employed. Gaps remain in the representation of hyperarid zones, grass- and shrub-dominated landscapes, and large regions of Africa and South America. Our findings highlight the need for multi-sensor approaches and expanded field validation to improve phenological assessments in dryland environments. The accurate differentiation of vegetation responses in LSP is essential not only for refining phenological metrics but also for enabling more realistic assessments of ecosystem functioning in the context of climate change and its impact on vegetation dynamics. Full article

In the African Sahel, fonio (Digitaria sp.) is a cereal crop that alleviates mid-season hunger before other main crops are harvested. As fonio is valued for its ability to grow under low nutrient and drought conditions, it was hypothesized that it may contain endophytic bacteria that can tolerate such extreme stress. White fonio seeds were obtained from a dry environment (Mali) and a moderate rainfall environment (Guinea). Plants were grown indoors on field soil mixed with sand to mimic Sahelian soils, grown at 30 °C, and exposed to drought, optimal water, and low nitrogen stress conditions. In total, 73 cultured bacteria were classified using full-length 16S rRNA sequencing followed by searching three 16S reference databases. Selected strains were tested in vitro for tolerance to relevant abiotic stresses. Including nine isolates from seeds, the candidate root/shoot endophytes spanned 27 genera and 18–39 top-match species. Several well-known nitrogen-fixing bacteria were cultured, including Ensifer. Leaves were dominated by Bacilli (spore-formers known to withstand dry conditions). There were five root isolates of Variovorax. Leifsonia was isolated from the leaves and showed 100% sequence identity with seed isolates, suggestive of transmission from seed to shoot. In vitro experiments showed that seed isolates, including Leifsonia, survived diverse abiotic stresses relevant to the Sahel. Combined, these results suggest that white fonio hosts stress-tolerant microbiota, and points to Leifsonia as a candidate seed-to-plant transmitted endophyte, pending confirmation by future whole genome sequencing. This microbial collection serves as a starting point for long-term experiments to understand stress tolerance in this under-studied crop. Full article

This data descriptor presents a unique high-resolution rainfall dataset derived from 14 pluviograph stations across central Chile’s Mediterranean region, covering variable periods starting from between 1969 and 1992, up to 2009. The dataset provides continuous precipitation records at a 5 min temporal resolution, obtained through the digitization and processing of pluviograph strip charts using specialized software. This high temporal resolution is unprecedented for the region and enables detailed analysis of rainfall intensity, duration, and frequency patterns critical for hydrological research, climate studies, and water resource management in general. Each station’s data was subjected to quality control procedures, including manual validation and correction of digitization errors to ensure data integrity. The dataset reveals the significant temporal variability of rainfall in central Chile, capturing both short-duration high-intensity events and longer precipitation patterns. By making this dataset publicly available, we provide researchers with a valuable resource for studying rainfall behavior in a Mediterranean climate zone subject to significant climate variability and change. The dataset supports various applications, including the development of intensity–duration–frequency curves, analysis of rainfall erosivity, calibration of hydrological models, and investigation of precipitation trends in the context of climate change. Full article

In protected areas of the Brazilian savannas (Cerrado), Land Surface Phenology (LSP) is influenced by both precipitation and fire, but the nature of these relationships remains unexplored. Here, we assessed the impacts of precipitation and fire on LSP metrics derived from the Normalized Difference Vegetation Index (NDVI) at Emas National Park (ENP). Using TIMESAT, along with the 250-m Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and 30-m Harmonized Landsat Sentinel (HLS) products, we investigated these effects in both grassland and woodland areas. To evaluate the effects of precipitation, we identified the driest and wettest seasonal cycles between 2002 and 2023 and analyzed the relationships between accumulated rainfall during the rainy season and each of the 13 TIMESAT metrics. To assess the effects of fire, three major events were examined: 1 September 2005 (affecting 45% of the park’s area), 12 August 2010 (90%), and 10 July 2021 (21%). The burned grassland area and the subsequent vegetation recovery following the 2021 event were analyzed in detail using a non-burned control site and LSP metrics extracted from the HLS product, covering both pre- and post-disturbance cycles. The results indicated that the metrics most positively correlated to precipitation were Amplitude (AMP), End of Season (EOS), Large and Small Seasonal Integrals (LSI and SSI), and Rate of Increase at the Beginning of the Season (RIBS). The highest correlation coefficients were found in woodland areas, which were less affected by fire disturbance than grassland areas. Similar trends were observed in the behavior of AMP, EOS, and SSI in response to both precipitation and fire, with fire exerting a stronger influence. By decoupling the fire effects from rainfall influence using the control site, we identified Base Level (BL), SSI, EOS, AMP, and Values at the End and Start of the Season (VES and VSS), as the metrics most sensitive to fire and subsequent vegetation recovery in burned areas. The effects of fire were evident for most metrics, both during the disturbance cycle and in the post-fire cycle. Our study underscores the importance of combining MODIS and HLS time series to understand vegetation phenology in the Cerrado. Full article

The former Provence coal basin, closed since 2003, has been monitored by a microseismic network since 2008. The objective is to detect the precursor signs of a brittle subsidence that would be caused by the collapse of the old underground mining works. Since the start of monitoring, no subsidence has affected the risk areas, and nearly 4000 events with a local magnitude between −3 < M_L < 3 have been recorded. One sector in particular, called the Fuveau swarm, located outside the risk zones and therefore outside the brittle subsidence hazard zones, has attracted attention since 2012 because it was the subject of several seismic episodes felt in 2010, 2012, 2014, late 2016–early 2017, and August 2017. Since 2017, it has been established that the observed seismicity cannot be explained only by instability phenomena in the old mining works. The most likely hypothesis is that of the remobilization of faults hydraulically connected to the mining works, with seismic activity that is closely linked to variations in the groundwater level, which are themselves influenced by pumping and effective rainfall. This paper shows, through multiplet analysis method of the seismic data recorded by the monitoring network stations, that part of the seismicity in the monitoring areas is also due to the reactivation of tectonic faults. This conclusion is based on the concordance between the location of the multiplets and the orientation of the main faults mapped in the studied areas, as well as on the fact that the strongest events belong to these multiplets. This finding underscores the need to integrate fault reactivation into seismic monitoring strategies, beyond the current focus on mining-induced instabilities. This conclusion leads us to recommend revising the list of post-mining hazards, as post-mining seismic risk is often overlooked in many European regulations. Full article

In an ever-changing driving environment where vehicles are becoming smarter, more autonomous, and more connected, a paradigmatic change in signals for drivers might be required. This need is correlated with road safety (social sustainability). There are several factors affecting road safety, and one of these, especially important on rural roads, is speed. One way to actively influence drivers’ speed is to intervene with regard to speed limit signs by providing credible and effective limits. This goal can be pursued by working on variable speed limits that align with the boundary conditions of the installation site. In this research, an analysis was conducted on the rural road network within the Metropolitan City of Bari (Italy) that involved collecting the speeds on each of the investigated two-way, two-lane rural roads of the network. In addition to the speeds, all the most relevant geometric details of the roads were considered, together with environmental factors like rainfall. A generalized linear model was developed to correlate the operating speed limits and other variables together with information about rainfall, which degrades tire–pavement friction and thus, road safety. After the development of this model, safety performance functions, depending on the amount of rain or number of days of rain, were calculated with the intent of predicting crash frequency, starting with the operative speed and rain conditions. Operative speed, speed limit, percentage of non-compliant drivers, traffic level, and site length were found to be associated with all typologies and locations of crashes investigated. Full article

Changes in climate and land use significantly impact downstream water availability. Quantifying these effects in the Ethiopian Highlands is crucial, as 85% of the transboundary water in Egypt and Sudan originates from these highlands. While the impact of climate change on water availability has been widely studied, few experimental studies have examined how it is affected by eucalyptus reforestation. Therefore, the objective was to investigate how eucalyptus expansion impairs water availability in the Ethiopian Highlands. The study was conducted in the 39 km² Amen watershed, located in the upper reaches of the Blue Nile. Rainfall data were collected from local agencies from 1990 to 2024, while streamflow data were available only for 2002–2009 and 2015–2018. Actual evapotranspiration was obtained using the WaPOR portal, and land use was derived from Landsat 5 TM and Landsat 8 OLI. The satellite images showed that the eucalyptus acreage increased from 238 ha in 2001 to 799 ha in 2024, or 24 ha y⁻¹. The actual evapotranspiration of eucalyptus was up to 30% greater than that of other land uses during the dry monsoon phase (January to March), resulting in decreased water storage in the watershed over a 23-year period. Since runoff is generated by saturation excess runoff, it takes longer for the valley bottoms to become saturated. In the 2002–2009 period, it took an average of around 160 mm of cumulative effective rain for significant runoff to start, and from 2015 to 2018, 274 mm was needed. Additionally, base flow decreased significantly. The annual runoff trended upward when the annual rainfall was more than the additional amount of water evaporated by eucalyptus, but decreased otherwise. Full article

The current changing climate requires the development of water–energy–food (WEF) nexus-oriented systems capable of mainstreaming climate-smart innovations into resource management. This study demonstrates the cross-sectoral impacts of climate change on interlinked sectors of water, energy, and food in Narok County, Kenya, and Vhembe District, South Africa. This study used projected hydroclimatic extremes across past, present, and future scenarios to examine potential effects on the availability and accessibility of these essential resources. The projected temperature and rainfall are based on nine dynamically downscaled Coupled Model Intercomparison Project Phase 5 (CMIP 5) of the Global Climate Models (GCMs). The model outputs were derived from two IPCC “Representative Concentration Pathways (RCPs)’’, the RCP 4.5 “moderate scenario”, and RCP 8.5 “business as usual scenario”, also defined as the addition of 4.5 W/m² and 8.5 W/m² radiative forcing in the atmosphere, respectively, by the year 2100. For the climate change projections, outputs from the historical period (1976–2005) and projected time intervals spanning the near future, defined as the period starting from 2036 to 2065, and the far future, spanning from 2066 to 2095, were considered. An ensemble model to increase the skill, reliability, and consistency of output was formulated from the nine models. The statistical bias correction based on quantile mapping using seven ground-based observation data from the South African Weather Services (SAWS) for Limpopo province and nine ground-based observation data acquired from the Trans-African Hydro-Meteorological Observatory (TAHMO) for Narok were used to correct the systematic biases. Results indicate downscaled climate change scenarios and integrate a modelling framework designed to depict the perceptions of future climate change impacts on communities based on questionnaires and first-hand accounts. Furthermore, the analysis points to concerted efforts of multi-stakeholder engagement, the access and use of technology, understanding the changing business environment, integrated government and private sector partnerships, and the co-development of community resilience options, including climate change adaptation and mitigation in the changing climate. The conceptual climate and WEF resource modelling framework confirmed that future climate change will have noticeable interlinked impacts on WEF resources that will impact the livelihoods of vulnerable communities. Building the resilience of communities can be achieved through transformative WEF nexus solutions that are inclusive, sustainable, equitable, and balance adaptation and mitigation goals to ensure a just and sustainable future for all. Full article

Tartary buckwheat is an important characteristic multigrain crop, mainly planted in Sichuan, Guizhou, Yunnan and Tibet, and other alpine and remote ethnic mountainous areas. In order to clarify the effect of sowing date on the yield and quality of Tartary buckwheat and its relationship with meteorological factors The variety Jinqiao No. 2 was used for a two-year trial at Dingxiang Test Base in Shanxi Province on four sowing dates (15 June, 26 June, 6 July and 17 July 2022 and 19 June, 30 June, 10 July and 21 July 2023) starting from the bud stage. Responses to sowing date were investigated by examining the growth period structure, yield, yield component, quality, and their relationship to climatic factors. The results showed that meteorological factors during the grain grain-filling stage were different when the sowing date was different. Compared with other sowing times, the treatment with the sowing of early and mid-July had less than 13.5~27.9 h of sunshine, less than 28.8~48.5 mm of rainfall, more than 10.5~19 days of ≤15 °C days, but the most serious low-temperature stress (≤15 °C days up to 27 days). The yield of sowing in July was 69.8~77.0% and 69.9~79.1% lower than that of sowing in June in 2022 and 2023 respectively, and the later sowing had a lower yield. Delayed sowing is beneficial to the accumulation of flavonoids and protein in Tartary buckwheat grains, and the average value in 2022 and 2023 is 11.55% and 14.64% higher than that in the first sowing, but the content of fat and starch is significantly reduced. The result of path analysis showed that the low temperature (≤15 °C days up to 27 days) and less solar radiation duration were the key points for attaining high yield and quality, due to the mean daily temperature and ≤15 °C days from flowering to maturity had negative effect on 1000-seed weight, seed setting rate, starch and crude lipid content of Tartary buckwheat, and the direct effect of sunshine duration on the content of protein and flavonoid in Tartary buckwheat was the greatest. The yield of Tartary buckwheat sown in June was higher than that of other treatments, because of avoiding low-temperature stress and long rainy and sunless weather during the grain filling stage, which enabled the blossoming and grain filling normally and finally attained higher yield. Full article

Pre-rain green-up is a distinctive phenological phenomenon observed in arid and semi-arid regions, featuring the sprouting of plants before the onset of the rainy season. This phenomenon indicates the intricate controls of vegetation phenology other than precipitation, yet its global distribution patterns and underlying causes remain unclear. In this study, we used remotely sensed phenology and rainfall data to map the global distribution of pre-rain green-up vegetation for the first time in arid and semi-arid savanna areas. The results revealed that over one-third of pre-rain green-up vegetation is in mountainous regions. Furthermore, to explore the potential effect of groundwater accessibility on pre-rain green-up, we employed high-resolution imagery to quantify phenological parameters and analyzed the relationship between pre-rain green-up and elevation at the watershed scale in a typical mountainous pre-rain green-up region in Africa. We found that within the pre-rain green-up area, 60.64% of sub-watersheds show a significant negative correlation (p < 0.05) between the start of the season (SOS) and elevation, indicating that the SOS occurs earlier at higher elevations despite the complex spatial variability overall. Our study provides a global picture of the pre-rain green-up phenomenon in tropical drylands and suggests that tree internal water regulation mechanisms rather than groundwater accessibility control the pre-rain green-up. Full article

Malaria is a persistent public health problem, particularly in sub-Saharan Africa where its transmission is intricately linked to climatic factors. Climate change threatens malaria elimination efforts in limited resource settings, such as in the Mberengwa district. However, the role of climate change in malaria transmission and management has not been adequately quantified to inform interventions. This protocol employs a multi-method quantitative study design in four steps, starting with a scoping review of the literature, followed by a multi-method quantitative approach using geospatial analysis, a quantitative survey, and the development of a predictive Susceptible-Exposed-Infected-Recovered-Susceptible-Geographic Information System model to explore the link between climate change and malaria transmission in the Mberengwa district. Geospatial overlay, Getis–Ord Gi* spatial autocorrelation, and spatial linear regression will be applied to climate (temperature, rainfall, and humidity), environmental (Land Use–Land Cover, elevations, proximity to water bodies, and Normalised Difference Vegetation Index), and socio-economic (Poverty Levels and Population Density) data to provide a comprehensive understanding of the spatial distribution of malaria in Mberengwa District. The predictive model will utilise historical data from two decades (2003–2023) to simulate near- and mid-century malaria transmission patterns. The findings of this study will be used to inform policies and optimise the management of malaria in the context of climate change. Full article

Malnutrition, particularly its impact on child morbidity and mortality, is one of the top five health effects of climate change. However, quantifying the portion of malnutrition attributed to climate remains challenging due to various confounding factors. This study examines the relationship between climate and acute malnutrition in Niger, a country highly vulnerable to climate change and disasters. Since climate’s effect on malnutrition is indirect, mediated by crop production, we combine rainfall data from TAMSAT satellite estimates with the SARRA-O crop model, which simulates the impact of rainfall variability on crop yields. Our analysis reveals a significant correlation between malnutrition and both rainfall and crop production from the previous year, but not within the same year. The strongest correlation (R = −0.72) was found with the previous year’s crop production. No significant links were found with temperature or intra-seasonal rainfall indices, like the start or duration of the rainy season. Although national correlations between global malnutrition, rainfall, and crop yields were stronger, they were weaker or absent at the regional level and, for Severe Acute Malnutrition crises, are less likely driven by climate variability. However, the one-year lag in the correlation allows for the prediction of future food crises, providing an opportunity to implement early intervention measures. Full article

Quantitative precipitation estimation using polarimetric radar in attenuation-prone frequency (X-band) in tropical regions characterized by convective rain systems with high intensities is a major challenge due to strong attenuations that can lead to total signal extinction over short distances. However, some authors have addressed this issue in Benin since 2006 in the framework of the African Monsoon Multidisciplinary Analysis program. Thus, with an experimental setup consisting of an X-band polarimetric weather radar (Xport) and a network of rain gauges, investigations have started on the subject with the aim of improving rainfall estimates. Based on simulated polarimetric variables and using a Multilayer Perceptron artificial neural network, several bi-variable and tri-variable algorithms were assessed in this study. The data used in this study are of two categories: (i) simulated polarimetric variables (Rayleigh reflectivity $Z$, horizontal attenuation $A_h$, horizontal reflectivity $Z_h$, differential reflectivity $Z_{dr}$, and specific differential phase $K_{dp}$) and rainfall intensity (R) obtained from Rain Drop Size Distribution (DSD) measurements used for algorithm evaluation (training and testing); (ii) polarimetric variables measured by the Xport radar and rainfall intensity measured by rain gauges used for algorithm validation. The simulations are performed using the T-matrix code, which leverages the scattering properties of spheroidal particles. The DSD measurements taken in northwest Benin were used as input for this code. For each spectrum, the T-matrix code simulates multiple variables. The simulated data (first category) were divided into two parts: one for training and one for testing. Subsequently, the best algorithms were validated with the second category of data. The performance of the algorithms during training, testing, and validation was evaluated using metrics. The best selected algorithms are $A1:R(Z,K_{dp})$ and $A12:R(Z_{dr},K_{dp})$ (among the bi-variable); $B2:R(Z_h,Z_{dr},K_{dp})$ and $B3:R(A_h,Z_{dr},K_{dp})$ (among the tri-variable). Tri-variable algorithms outperform bi-variable algorithms. Validation with observation data (Xport measurements and rain gauge network) showed that the algorithm $B3:R(A_h,Z_{dr},K_{dp})$ performs better than $B2:R(Z_h,Z_{dr},K_{dp})$. Full article

Climate-change-induced increases in extreme rainfall events necessitate the enhancement of discharge capacity in aging dam infrastructures. Piano Key Weirs (PKWs), with their compact footprint and efficient discharge performance, present a promising option for improving the discharge efficiency of existing spillways. This study introduces an innovative composite Piano Key Weir (CPKW), which integrates both rectangular and trapezoidal layouts. Numerical simulations were performed to systematically compare the flow field and discharge performance between conventional trapezoidal PKW and composite configurations. Results show that the composite structure significantly improves the discharge capacity of the reference trapezoidal model by up to 16%. This enhancement is primarily attributed to the extended crest length and reduced local submergence, resulting in a more efficient discharge distribution. For the specific composite configurations studied, the optimal key width ratio that effectively balances the inflow efficiency and the adverse effects of nappe interference is found to range between 0.89 and 1.01. Additionally, a relative upstream head of 0.2–0.3 is identified as a critical threshold, beyond which the intense local submergence starts to affect the downstream trapezoidal side-wall section, limiting the contribution of the entire side wall to the total discharge and resulting in decreased overall efficiency. Full article

Open-pit mining often exposes weak rock layers, the strength of which significantly affects the stability of slopes. If these rock layers are also prone to disintegration and expansion, cyclic rainfall can exacerbate instability. Rainfall-induced changes in the seepage field also indirectly threaten the stability of slopes. Therefore, investigating the characteristics of mudstone limestone and the impact of the seepage field on slope instability under different wet–dry cycles is of great significance for the safe mining of open-pit mines. This paper takes the mudstone limestone slope of a certain open-pit mine in the southwest as the starting point and conducts experiments on saturated density, water absorption rate, permeability coefficient, compressive strength, and variable angle shear strength. Combined with scanning electron microscopy and phase analysis of X-ray diffraction analysis, the macroscopic and microscopic characteristics of the samples are comprehensively analyzed. FLAC3D software is used to explore the changes in the seepage field and the mechanism of instability. Our research found that for the preparation of mudstone limestone samples, a particle size of less than 1 mm and a drying temperature of 50 °C are optimal, with specific values for initial natural and saturated density, and natural water content. As the number of wet–dry cycles increases, the saturated density of mudstone limestone increases; the water absorption rate first rises sharply and then rises slowly; the permeability coefficient first rises sharply and then stabilizes, finally dropping sharply; the compressive and shear strength decreases slowly, and the internal friction angle changes little; frequent cycles also lead to mudification and seepage filtration. At the microscopic level, pores become larger and more regular, and the distribution is more concentrated; changes in mineral content weaken the strength. Combined with numerical simulation, the changes in the seepage field at the bottom of the slope exceed those at the slope surface and top, the transient saturated area expands, and the overall and local slope stability coefficients gradually decrease. During the third cycle, the local stability is lower than the overall stability, and the landslide trend shifts. In conclusion, wet–dry cycles change the pores and mineral content, affecting the physical and mechanical properties, leading to the deterioration of the transient saturated area, a decrease in matrix suction, and an increase in surface gravity, eventually causing slope instability. Full article