Influence Of Climate Variability Research Articles

Comparative analysis of mycorrhizal communities associated with Struthiopteris spicant (L.) Weiss across Europe and North America.

Ferns constitute the second largest group of vascular plants. Previous studies have shown that the diversity and composition of fern communities are influenced by resource availability and water stress, among other factors. However, little is known about the influence of these environmental factors on their biotic interactions, especially regarding the relationship between mycorrhizal fungi and ferns. The present study compares the mycorrhizal communities associated with 36 populations of Struthiopteris spicant L. Weiss across Europe and North America. This species exhibits a great tolerance to variations in light, nutrient, and pH conditions, and it can survive with and without mycorrhizae. With the aim of determining which environmental factors impact the composition and abundance of the root-associated fungal communities in this species, we used an ITS-focused metabarcoding approach to identify the mycorrhizal fungi present and analyzed the influence of climatic and edaphic variables at global and regional scales. We encountered striking differences in the relative abundance of arbuscular mycorrhizal fungi (AMF) between S. spicant populations at both spatial levels. We recorded a total of 902 fungal ASVs, but only 2- 4% of the total fungal diversity was observed in each individual, revealing that each fern had a unique fungal community. Light availability and the interactive action of pH and soil nitrogen concentration showed a positive influence on AMF relative abundance, explaining 89% of the variance. However, environmental factors could only explain 4- 8% of the variability in AMF community composition, indicating that it might be determined by stochastic processes. These results support the hypothesis that ferns may be more independent of mycorrhization than other plant groups and interact with fungi in a more opportunistic manner.

Influence of global teleconnections on long-term variability in flood seasonality across peninsular India

Climate change and natural climate variability impact not only the frequency and magnitude of floods but also flood seasonality. However, limited to no study has investigated the seasonality in flood occurrence in peninsular Indian rivers. The Central Water Commission opening its long-term records of river stage and discharge gathered from many monitoring stations offers a unique opportunity to analyse flood seasonality. The primary aims of this study are to identify the time of the year when floods are most likely, investigate whether the occurrence of floods has changed over time due to the influence of climate change and natural climate variability, and determine the most significant large-scale and local climate drivers of flood seasonality. Stage and discharge data from 281 gauging stations across ten peninsular river basins are considered to identify the annual maximum gauge level for a gauging point while retaining the corresponding Julian day (also known as the date of occurrence or DO) for further analysis. Several attributes related to circular statistics are calculated from the DO series to find that 68% of the gauging stations experience floods during August, indicating the dominance of the monsoon system on DO. Preliminary analysis confirms that while most stations experience a non-stationarity in the DO series, a few stations exhibit a non-linear trend. Furthermore, our study develops a machine learning model with DO as predictand and 36 local and large-scale predictors to identify the dominant predictors of DO. The predictor importance metric shows that the Pacific Decadal Oscillation (PDO) and the El Niño and Southern Oscillation (ENSO) explain DO variability better than other drivers. Moreover, since ENSO and PDO are teleconnected with the onset of monsoon and annual maximum rainfall (Pradhan et al 2017 Sci. Rep. 7 14229; Choudhury et al 2021a Q. J. R. Meteorol. Soc. 147 3111–23), flood seasonality demonstrates a connection with both PDO and ENSO.

The Role of the Aleutian Low in the Relationship between Spring Pacific Meridional Mode and Following ENSO

Abstract The spring Pacific meridional mode (PMM) is an important precursor of El Niño–Southern Oscillation (ENSO). However, recent studies reported that only about half of the spring PMM events were followed by ENSO events. This study examines the role of internal climate variability in modulating the impact of PMM on ENSO using 100-member ensemble simulations of the Max Planck Institute Earth System Model (MPI-ESM). The relationship between spring PMM and following winter ENSO shows a large spread among the 100 members. The variation of spring Aleutian low (AL) intensity is identified to be an important factor modulating the PMM–ENSO relation. The spring AL affects the PMM–ENSO relationship by modifying PMM-generated low-level zonal wind anomalies over the tropical western Pacific. The strengthening of the spring AL is accompanied by westerly wind anomalies over the midlatitude northwestern Pacific, leading to sea surface temperature (SST) cooling there via an enhancement of upward surface heat flux. This results in increased meridional SST gradient and leads to northerly wind anomalies over the subtropical northwestern Pacific, which turn to surface westerly wind anomalies after reaching the equatorial western Pacific due to the conservation of potential vorticity. Thus, the low-level westerly (easterly) wind anomalies over the tropical western Pacific associated with the positive (negative) spring PMM were strengthened (weakened), which further contributes to an enhanced (a weakened) PMM–ENSO relation. The mechanism for the modulation of the AL on the spring PMM–ENSO relationship is verified by a set of AGCM simulations. This study suggests that the condition of the spring AL should be considered when predicting ENSO on the basis of the PMM. Significance Statement Spring Pacific meridional mode (PMM) is a predictor of ENSO, but not all spring PMM events are accompanied by the occurrence of ENSO events. This study aims to explore the influence of internal climate variability on the relationship between spring PMM and following ENSO. It is revealed that the Aleutian low exerts a crucial modulation on the spring PMM–ENSO relationship. The underlying physical mechanisms for the impact of the Aleutian low on the relationship between spring PMM and ENSO are further examined. The results of this study have important implications for improving the prediction of ENSO.

Mapping sub-surface distribution of soil organic carbon stocks in South Africa's arid and semi-arid landscapes: Implications for land management and climate change mitigation

Soil organic carbon (SOC) stocks are critical for land management strategies and climate change mitigation. However, understanding SOC distribution in South Africa's arid and semi-arid regions remains a challenge due to data limitations, and the complex spatial and sub-surface variability in SOC stocks driven by desertification and land degradation. Thus, to support soil and land-use management practices as well as advance climate change mitigation efforts, there is an urgent need to provide more precise SOC stock estimates within South Africa's arid and semi-arid regions. Hence, this study adopted remote-sensing approaches to determine the spatial sub-surface distribution of SOC stocks and the influence of environmental co-variates at four soil depths (i.e., 0-30 cm, 30-60 cm, 60-100 cm, and 100-200 cm). Using two regression-based algorithms, i.e., Extreme Gradient Boosting (XGBoost) and Random Forest (RF), the study found the former (RMSE values ranging from 7.12 t/ha to 29.55 t/ha) to be a superior predictor of SOC in comparison to the latter (RMSE values ranging from 7.36 t/ha to 31.10 t/ha). Nonetheless, both models achieved satisfactory accuracy (R2 ≥ 0.52) for regional-scale SOC predictions at the studied soil depths. Thereafter, using a variable importance analysis, the study demonstrated the influence of climatic variables like rainfall and temperature on SOC stocks at different depths. Furthermore, the study revealed significant spatial variability in SOC stocks, and an increase in SOC stocks with soil depth. Overall, these findings enhance the understanding of SOC dynamics in South Africa's arid and semi-arid landscapes and emphasizes the importance of considering site specific topo-climatic characteristics for sustainable land management and climate change mitigation. Furthermore, the study offers valuable insights into sub-surface SOC distribution, crucial for informing carbon sequestration strategies, guiding land management practices, and informing environmental policies within arid and semi-arid environments.

Metaanalysis of Public Wastewater Metagenomes: Revealing the Influence of Climatic Variations on the Abundance of the Bacterial Members

As per the present trend, earth may experience severe hike in temperature by 2040. Therefore, global surveillance is required to combat against the upcoming climatic extremities. Emerging and re-emerging infectious diseases are part of the key pressing issues which can affect millions of people worldwide. Wastewater associated metagenomic data representing the wastewater samples collected from sewer networks in Newcastle (United Kingdom); Zimbabwe (Africa) and West Bengal (India), available in public databases were collected. It was observed that of the top 10 abundant genera, the prevalent genera in samples from United Kingdom, Africa, India were Desulfitobacterium, Prevotella, Sulfurospirillum respectively. By comparing all the three samples under study; it was observed that three microbial genera Bacteroides, Dechloromonas and Faecalibacterium were common throughout the samples. Metagenome-wide association studies were conducted to link microbes in the sample to the host disorders. Our study could predict overexpression of several enriched pathways like Vancomycin resistance, Platinum drug resistance across the samples. These findings prove efficacies of the community genomics approach to serve as a public health monitoring tool through detection of spatial variation as well as degree of commonness in wastewater bacterial profiles and also through the prediction of the pathogenic quantum of wastewater systems.

The influence of multidecadal climate variability and abrupt landscape change on terrestrial ecosystem composition and fire regime in the upper Columbia River basin - A high-resolution Holocene perspective

High-resolution paleoclimatic and paleoecologic datasets from a small lake in eastern Washington (USA) help elucidate Holocene environmental dynamics in the interior Pacific Northwest. Round Lake lies near the ecotone between sagebrush steppe and dry pine forest, making it highly sensitive to changes in precipitation-evaporation (P-E) balance. We present isotopic, sedimentological, and paleoecological data from a single sedimentary sequence analyzed at sufficient resolution to detect sub-decadal climatic variability. During the early Holocene (11,000–8500 cal yr BP), when summer insolation was higher than present, Round Lake experienced persistent aridity that led to reduced forest cover and small, probably frequent surface fires. Sub-centennial hydroclimate fluctuations during this period were muted, as indicated by low multi-decadal variability in δ18Ocarbonate records from the region. Oxygen isotopes indicate increased cool-season moisture during the middle Holocene (8500-5300 BP), but stratigraphic evidence suggests intermediate and variable lake levels. The deposition of the Mazama tephra (ca. 7600 cal yr BP) immediately preceded to a protracted expansion of steppe at the expense of forest. Increased hydroclimate variability and fire activity following ash deposition likely restricted conifer taxa even when elevated cool-season moisture would have facilitated their growth. The late Holocene was marked by persistently high lake levels, as indicated by the lithostratigraphic and pollen records. Comparatively large multidecadal variations in precipitation, which peaked during the last millennium, were also prominent features of late-Holocene hydroclimate, and may have been related to the strengthening of the El Niño Southern Oscillation and Pacific Decadal Oscillation. Pinus and Pseudotsuga show a 60–100 year lag in their response to hydroclimatic variations inferred from the oxygen isotope records. These results highlight how millennial-to-decadal scale hydroclimate conditions, along with abrupt landscape change, influence ecology in a water-stressed region of western North America.

Surface water and geomorphological changes of the Blue Nile dynamics associated with the Grand Ethiopian Renaissance Dam (GERD): a multi-temporal analysis

ABSTRACT The Blue Nile River is an indispensable source of livelihood for over 90 million people in Ethiopia, Sudan, and Egypt. Recently, Ethiopia has constructed the Grand Ethiopian Renaissance Dam (GERD), the largest in Africa, which could potentially alter the geomorphology of the river regime, and impact downstream countries. This study offers the first comprehensive analysis of the geomorphological alterations and water surface coverage changes of the Blue Nile River due to the construction and operation of the GERD. For this, we use multi-temporal Landsat 5 and Sentinel-2 satellite imagery spanning the period from 2009 to 2022, supplemented with Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS) precipitation products to discern the potential influence of climate variability on the observed changes. The findings are examined using the Before-After-Control-Impact (BACI) model, revealing significant fluctuations in the water surface coverage area across different sections of the river, particularly following the filling stages of the GERD. An analysis at every 10 km is performed to assess the extent of GERD’s influence on the Blue Nile, which indicates no notable alterations in surface area or geomorphology within the first 30 km of downstream river flow. The study also determines that changes from 2011 to 2018 are primarily associated with the upgrade activities of the Roseires Dam, while alterations along the Blue Nile from 2018 to 2019 are linked to climate variability. The observed changes between 2020 and 2022 can largely be attributed to the filling stages of the GERD. Notably, these changes are most pronounced in the water retaining areas upstream of the GERD dam. The results also show that Roseires Dam could play a crucial role as a buffer, mitigating potential impacts imposed by the GERD, and serving as a conduit between the GERD and downstream communities.

Hydrogeological trends in an alluvial valley in the Brazilian semiarid: Impacts of observed climate variables change and exploitation on groundwater availability and salinity

Study regionMimoso Alluvial Valley, Semiarid Brazil. Study focusThis study aims to assess the influence of climate variability and exploitation on groundwater accessibility, quantity and quality, based on a spatiotemporal data analysis from long-term monitoring field campaigns, conducted monthly from 2000 to 2019. This study successfully identified representative stable monitoring points, piezometers and wells, for piezometric and salinity levels employing the technique of relative differences, taking into account aquifer hydraulic properties. Trend analysis was then carried out adopting the Mann-Kendall Method, Sen's Slope test, Pettitt test, and the Seasonal Trend decomposition through the Loess (STL) method. Principal Component Multivariate Analysis (PCA) was also employed to validate long-term analysis of annual groundwater levels, rainfall, evapotranspiration, and pumping rates. New hydrological insights for the regionThe spatial-temporal variability of salinity is closely linked to the salt balance in regions with low hydraulic permeability and groundwater use for irrigation. Groundwater salinity presented a strong link between rainfall and groundwater levels. A temporal rise in evapotranspiration alongside declines in rainfall and groundwater levels was observed, potentially exacerbating groundwater scarcity alongside intensified aquifer exploitation. Furthermore, groundwater salinity presented a decreasing trend for the pumping wells and no trends for piezometers. This could potentially disrupt future irrigation plans and cause long-term water shortages in a region already under severe water scarcity. Hence, groundwater pumping constitutes a positive management alternative for controlling groundwater salinity in the domain.

The Influence of Climate Variability and Future Climate Change on Atlantic Hurricane Season Length

AbstractAtlantic hurricane season length is important for emergency management preparation, motivating the need to understand its variability and change. We investigated the influence of ocean variability on Atlantic hurricane season length in observations and a future climate simulated by the Energy Exascale Earth System Model (E3SM). We found that multiple factors influence hurricane season length, through their influence on season start and end. Warm western subtropical Atlantic sea‐surface temperature anomalies (SSTAs) during boreal spring (before the official hurricane season start) drive early starts to the hurricane season, and vice versa for cool SSTAs. Meanwhile, La Niña in autumn (before the official hurricane season end) drives late ends to the hurricane season, and vice versa for El Niño. E3SM projects a 27‐day increase in future Atlantic hurricane season length given La Niña and warm northern tropical Atlantic SSTAs. This research documents sources of predictability for Atlantic hurricane season length.

Influence of climate, physical and chemical variables on the taxonomic and functional responses of macroinvertebrate communities in tropical island rivers

Influence of climate, physical and chemical variables on the taxonomic and functional responses of macroinvertebrate communities in tropical island rivers

Assessing the impact of climate change on landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand, using CMIP6 climate models

Climate variability and climate change may influence the frequency and recurrence interval of landslides. Precipitation, as a main triggering factor of landslides, may be influenced by climate variability and climate change. Changes in precipitation may directly affect landslide frequency and recurrence intervals. Considering the influence of climate variability and climate change, the partial duration series method and critical rainfall threshold are combined with the simulated precipitation of Phase 6 of the Coupled Model Intercomparison Project (CMIP6) general circulation models (GCMs) to predict changes in future landslide recurrence intervals in Nakhon Si Thammarat Province, Thailand. The analytical results predicted changes in the landslide frequency over the next 20 years (2023 to 2042). SSP1–2.6 and SSP2–4.5 are adopted as future socioeconomic development scenarios. According to the predictions, the results showed that the return period of landslide occurrence in the future will be shorter than the return period of landslide occurrence in the historical period; moreover, the landslide recurrence interval will fluctuate greatly. The Nakhon Si Thammarat DWR meteorological station shows the most fluctuation in landslide recurrence intervals for SSP1–2.6. In addition, the Nakhon Si Thammarat meteorological Station experiences a significant decrease of approximately 35% in landslide recurrence intervals under SSP1–2.6. For SSP2–4.5, the Nakhon Si Thammarat meteorological station shows the most fluctuation in landslide return period. In addition, the Nakhon Si Thammarat meteorological station observed a decline in landslide recurrence intervals, with a reduction of approximately 40%. Hence, the frequency of landslides may increase in the future. A comparison between SSP1–2.6 and SSP2–4.5 revealed that SSP2–4.5 yielded lower landslide return periods.

Influence of Climatic Variables on the Stem Growth Rate in Trees of a Tropical Wet Forest

The growth of tropical wet forests has a significant relationship with the climate; aspects such as temperature and precipitation affect the species; however, few studies have characterized the stem growth rate of tropical tree species. This study’s objective was to characterize the effects of climatic variation on the interannual stem growth rate of eight species in tropical wet forest. Six trees per species were selected (n = 48 trees), and a dendrometer was installed to measure diametric growth bi-monthly between 2015 and 2018 (3 years), complemented with environmental measurements, to determine their growth equations from environmental variables and, finally, to define the relationship between the wood density and the stem growth rate. The results showed an average stem growth from 0.45 to 4.35 mm year−1, and 40 to 70% growth occurred in the months with the highest rainfall. Also, species with higher wood densities were found to have lower stem growth rates. Finally, the analysis of stem growth rate showed a significant relationship in all species between the variables of temperature and precipitation (R2 adj 0.88 to 0.96). Our results suggest that species with greater stem growth rates in wet tropical forests are more susceptible to climate changes, which may affect their dynamics in the face of potential drought scenarios and heat waves associated with climate change.

Influence of anthropogenic effects and climate variability on streamflow in a Brazilian tropical watershed

Influence of anthropogenic effects and climate variability on streamflow in a Brazilian tropical watershed

Impacts of climate factors and human activities on NDVI change in China

Vegetation plays a crucial role in terrestrial ecosystems, and there has been a substantial shift in global vegetation cover in recent decades. China is recognized for its substantial impact on global vegetation cover changes, which are influenced by both climate change and human activities. Therefore, this research aims to assess the respective influences of climate modification and human activities on vegetation variations in China. First, the changes in vegetation cover are explored between 1982 and 2020 using satellite-image derived vegetation index, known as the Normalized Difference Vegetation Index (NDVI). Second, a multiple regression model based on time-lag analysis is used to simulate NDVI. In addition to common climatic factors such as temperature, precipitation, solar radiation intensity and relative humidity, the atmospheric CO2 concentration to directly reflect climate change is considered in this model. Finally, the relative influence of climate variation and human activities on the alteration of vegetation cover is determined based on reconstructed NDVI. Results: (1) Precipitation and solar radiation are the most important influences, while carbon dioxide concentration and relative humidity have the least influence. (2) The simulation error before 2000 was 0.875%, which was considerably lower than the error after 2000. (3) After 2000, human activities favorably affected vegetation recovery in most of the study area, with an average degree of influence of >30%.

Quantifying the Influence of Climate Variables on Vegetation Through Remote Sensing and Multi-dimensional Data Analysis

Quantifying the Influence of Climate Variables on Vegetation Through Remote Sensing and Multi-dimensional Data Analysis

Dynamic Changes in Terrestrial Water Balance Using Remote Sensing on the Loess Plateau

In recent decades, the water cycle process in the Loess Plateau has undergone drastic changes under the influence of anthropogenic disturbance and climate variability. The Loess Plateau has been greatly affected by human activities and climate change, and the dynamics of water balance and its key influencing factors remain unknown in this region. To deepen our understanding of water resource status in the Loess Plateau, we analyzed the dynamic changes in the hydrological cycle components and terrestrial water balance via remote sensing during the 2001–2020 period. Moreover, we also discussed the dominant factors affecting the terrestrial water balance. The results indicate that precipitation and ET exhibited increasing trends, with upward rates of 2.56 mm/yr and 5.27 mm/yr, respectively. Spatially, the annual average precipitation and ET showed increasing trends from the north to south. Precipitation in 62.05% of the entire region presented a significant upward trend, with a change rate of 0~2 mm/yr, and the annual change rate of ET in a range of 0~30 mm/year accounted for 89.12%. The runoff exhibited a fluctuating and significantly upward trend during the 2000–2022 period, with a change rate of 3.92 × 108 m3/yr, and was relatively large in the middle reach of the Yellow River. The annual average water consumption in the upper reach of the YRB presented a significant decreasing trend, with a downward rate of −0.06 × 108 m3/yr from 2001 to 2020, and yet it displayed a significant increasing trend in the middle and lower reaches of the YRB with the upward rate of 0.07~0.11 × 108 m3/yr. Based on the principle of water balance, the recharge amount was calculated at less than the discharge amount during the 2001–2020 period, and the difference between recharge and discharge is gradually expanding, with a change rate of −3.72 × 108 m3/yr. The spatial distributions of TWSC revealed that the eastern region was in an imbalanced state, while the western region was in a relatively balanced state. Terrestrial water balance changes were mainly affected by climate factors and human disturbance, and land use/cover change was the dominant factor. The results will be of great significance for optimizing water resource management and formulating various water-saving strategies in the Loess Plateau.

Modern pollen-plant diversity relationship in open landscapes of Tibetan Plateau

Past plant diversity dynamics can provide a historical perspective on biodiversity change and ecosystem dynamics as a guide to conservation management in the future. Pollen analysis is one of the most widely used approaches to reconstruct plant diversity change through time, but the representativeness of pollen diversity to plant diversity is not yet fully understood and especially in open landscapes. In this paper, we compare pollen assemblages from topsoil in the open landscapes of the Tibetan Plateau with the surrounding vegetation to investigate their compositional similarity and the correlations between their diversity (richness and evenness), and to evaluate the influence of climate variables, landscape characteristics, and human disturbance on the pollen diversity. The results show that pollen assemblages vary obviously in different vegetation types and they can represent their surrounding plant communities at low taxonomic levels. Pollen richness boarders a better match with plant richness than pollen evenness with plant evenness across the whole study area, but the correlation is weak (radj2 < 0.2, p < 0.001). Transforming plants into their pollen equivalents has little improvement for the correlations between pollen and plant richness/evenness. Pollen richness and evenness can capture well the trend in plant richness and evenness along the vegetation gradient, suggesting that they can be used as gamma (landscape scale) rather than alpha (local scale) diversity metrics in the study area. Mean annual precipitation (MAP), mean annual temperature (MAT), and patch richness (PatchS) are positively associated with pollen richness. MAP, PatchS, and human disturbance (HD) are significantly predictors for pollen evenness. These confirm that pollen richness and evenness can provide insights into past plant diversity dynamics and help evaluating the effects of climate and habitat changes and human disturbance on long timescales.

Influence of climatic variation on microbial communities during organic Pinot noir wine production.

To assess the possible impact of climatic variation on microbial community composition in organic winemaking, we employed a metabarcoding approach to scrutinize the microbiome in a commercial, organic, Pinot noir wine production system that utilizes autochthonous fermentation. We assessed microbial composition across two vintages (2018 and 2021) using biological replicates co-located at the same winery. Microbial dynamics were monitored over four important fermentation time points and correlated with contemporaneous climate data. Bacterial (RANOSIM = 0.4743, p = 0.0001) and fungal (RANOSIM = 0.4738, p = 0.0001) compositions were different in both vintages. For bacteria, Lactococcus dominated the diversity associated with the 2018 vintage, while Tatumella dominated the 2021 vintage. For fungal populations, while Saccharomyces were abundant in both vintages, key differences included Starmerella, copious in the 2018 vintage; and Metschnikowia, substantive in the 2021 vintage. Ordination plots correlated the climatic variables with microbial population differences, indicating temperature as a particularly important influence; humidity values also differed significantly between these vintages. Our data illustrates how climatic conditions may influence microbial diversity during winemaking, and further highlights the effect climate change could have on wine production.

Lake Tanganyika basin water storage variations from 2003–2021 for water balance and flood monitoring

Lake Tanganyika in East Africa contains 17% of the free freshwater on the Earth's surface and provides important ecosystem services to ∼13 million people in the region. It is one of the great lakes in East Africa for which a significant rise in water level between 2019 and 2020 led to flooding, with major environmental consequences and social impacts. This study focused on the Lake Tanganyika basin water balance between 2003 and 2021 to assess the influence of recent climate variability on lake water level variations (due in particular to the floods of 2020 and 2021) and to explore early warnings of flooding in the lake's surrounding lowlands. This process is performed using remote sensing data. For the computation of the basin's water balance, we compared variations in the watershed total water storage (TWS) with the basin water flux calculated using rainfall, evaporation (E), evapotranspiration (ET) and discharges data. The space–time variations in rainfall, E and ET were analyzed by decomposing their time series into trend and seasonal signals and applying (only for rainfall) multivariate statistical analysis to the decomposed signals. For flood mapping, we calculated the MNDWI spectral water index from Sentinel–2 images acquired between 2017 and 2022. Our study showed that the basin water balance is closed when rainfall from Era5 is combined with E and ET from GLEV and MOD16A2, respectively. During the 2003–2021 period, over the entire watershed, water losses of ∼70 km³ due to lake E were offset by an increase in water inflows of ∼100 km³ in the rest of the watershed. During the period from 2003 to 2021, the E rate from the lake was stable overall, while the ET and rainfall mainly in the Malagarasi basin increased significantly. The surface water storage (SWS), which represents the variation in lake water volume derived from altimetry measurements, corresponds to 41.8% of the TWS, groundwater storage corresponds to 57.7% of the TWS, and the soil moisture is less than 0.5%. The TWS strongly correlated with the SWS (∼91%), with a one-month lag in the SWS variations in response to the TWS fluctuations. Therefore, the SWS in May, when the flood risk is the highest, was estimated using TWS in February, March and April with accuracies of 85%, 94% and 95%, respectively. This valuable information could be integrated into flood management tools, particularly for areas such as Gatumba city and the Ruzizi Delta Nature Reserve, which were heavily affected by the May 2021 floods.

The influence of climatic and environmental variables on sunflower planting season suitability in Tanzania

Crop survival and growth requires identification of correlations between appropriate suitable planting season and relevant climatic and environmental characteristics. Climatic and environmental conditions may cause water and heat stress at critical stages of crop development and thus affecting planting suitability. Consequently, this may affect crop yield and productivity. This study assesses the influence of climate and environmental variables on rain-fed sunflower planting season suitability in Tanzania. Data on rainfall, temperature, slope, elevation, soil and land use/or cover were accessed from publicly available sources using Google Earth Engine. This is a cloud-based geospatial computing platform for remote sensed datasets. Tanzania sunflower production calendar of 2022 was adopted to mark the start and end limits of planting across the country. The default climate and environmental parameters from FAO database were used. In addition, Pearson correlation was used to evaluate the relationship between rainfall, temperature over Normalized Difference Vegetation Index (NDVI) from 2000 to 2020 at five-year interval for January-April and June–September, for high and poor suitability season. The results showed that planting suitability of sunflower in Tanzania is driven more by rainfall than temperature. It was revealed that intra-annual planting suitability increases gradually from short to long- rain season and diminishes towards dry season of the year. January-April planting season window showing highest suitability (41.65%), whereas June–September indicating lowest suitability (0.05%). Though, not statistically significant, rainfall and NDVI were positively correlated with r = 0.65 and 0.75 whereas negative correlation existed between temperature and NDVI with r = -− 0.6 and − 0.77. We recommend sunflower subsector interventions that consider appropriate intra-regional and seasonal diversity as an important adaptive mechanism to ensure high sunflower yields.