Drought Occurrence Research Articles

Sustainable soil management under drought stress through biochar application: Immobilizing arsenic, ameliorating soil quality, and augmenting plant growth

Rise in climate change-induced drought occurrences have amplified pollution of metal(loid)s, deteriorated soil quality, and deterred growth of crops. Rice straw-derived biochars (RSB) and cow manure-enriched biochars (CEB) were used in the investigation (at doses of 0%, 2.5%, 5%, and 7.5%) to ameliorate the negative impacts of drought, improve soil fertility, minimize arsenic pollution, replace agro-chemical application, and maximize crop yields. Even in soils exposed to severe droughts, 3 months of RSB and CEB amendment (at 7.5% dose) revealed decreased bulk density (13.7% and 8.9%), and increased cation exchange capacity (6.0% and 6.3%), anion exchange capacity (56.3% and 28.0%), porosity (12.3% and 7.9%), water holding capacity (37.5% and 12.5%), soil respiration (17.8% and 21.8%), and nutrient contents (especially N and P). Additionally, RSB and CEB decreased mobile (30.3% and 35.7%), bio-available (54.7% and 45.3%), and leachable (55.0% and 56.5%) fractions of arsenic. Further, pot experiments with Bengal gram and coriander plants showed enhanced growth (62–188% biomass and 90–277% length) and reduced arsenic accumulation (49–54%) in above ground parts of the plants. Therefore, biochar application was found to improve physico-chemical properties of soil, minimize arsenic contamination, and augment crop growth even in drought-stressed soils. The investigation suggests utilisation of cow manure for eco-friendly fabrication of nutrient-rich CEB, which could eventually promote sustainable agriculture and circular economy. With the increasing need for sustainable agricultural practices, the use of biochar could provide a long-term solution to enhance soil quality, mitigate the effects of climate change, and ensure food security for future generations. Future research should focus on optimizing biochar application across various soil types and climatic conditions, as well as assessing its long-term effectiveness.

Tracking the Evolution of Snow Drought in the U.S. Pacific Northwest at Variable Scales

AbstractLong‐term and year‐to‐year changes in climate can cause anomalously warm and/or dry conditions, leading to periods with snowfall deficits known as snow droughts. How the occurrence of distinct types of snow drought has evolved at different spatial and temporal scales is not well understood. Here, we investigate how snow droughts and associated seasonal snow conditions vary subseasonally in the US Pacific Northwest. We specifically consider differences with spatial unit (point vs. river basin), data set and intra‐annual timing of snow drought. Data sets included in the research come from in situ observations, gridded model outputs and optical remote sensing. We found that overall, snow drought occurrences have increased 10%–15% over the last 30 years based on decadal counts, but the change was non‐uniform across snow drought types and winter periods. Our research showed a decrease in dry snow droughts but an increase in warm/dry snow droughts according to in situ observations and only a modest increase in the model record. We also found that dry snow droughts were more prevalent in the eastern portion of our study region while warm/dry snow droughts were generally more common in the western part of the study area. With optical remote sensing data, it was possible to identify warm/dry snow drought conditions in the mid to late winter (January–May), but not possible to distinguish other types of snow drought in the early winter. This research points to the importance of data set choice, spatial resolution and spatial/temporal aggregation when selecting parameters for snow drought research.

Role of Pacific Ocean climate in regulating runoff in the source areas of water transfer projects on the Pacific Rim

Over the past two decades, more frequent and intense climate events have seriously threatened the operation of water transfer projects in the Pacific Rim region. However, the role of climatic change in driving runoff variations in the water source areas of these projects is unclear. We used tree-ring data to reconstruct changes in the runoff of the Hanjiang River since 1580 CE representing an important water source area for China’s south-north water transfer project. Comparisons with hydroclimatic reconstructions for the southwestern United States and central Chile indicated that the Pacific Rim region has experienced multiple coinciding droughts related to ENSO activity. Climate simulations indicate an increased likelihood of drought occurrence in the Pacific Rim region in the coming decades. The combination of warming-induced drought stresses with dynamic El Niño (warming ENSO) patterns is a thread to urban agglomerations and agricultural regions that rely on water transfer projects along the Pacific Rim.

Оценка частоты возникновения засухи в Файзабадском районе (Таджикистан) в зависимости от метеорологических условий

The results of the analysis of the manifestation of drought in the Faizabad region based on calculations of the standardized precipitation and evapotranspiration index (SPEI) are presented. It has been established that there is no definite pattern in the occurrence of drought, even for a long period. By comparing the number and duration of droughts in the Fayzabad district with the climatic characteristics of the Fayzabad district, a close dependence of drought on the average annual temperature and precipitation has been established.

Investigate the Spatiotemporal Evolution of Drought and Its Interaction with Atmospheric Circulation in the Yellow River Middle Basin

Global warming contributes to an increased frequency and severity of droughts. Drought emerges as a highly prevalent natural calamity, distinguished by its formidable disruptive impact and the capacity to trigger considerable economic setbacks. Understanding the spatiotemporal characteristics of droughts and clarifying the driving role of atmospheric circulation on droughts is vital for agricultural, hydrological, ecological, and socio-economic systems. Leveraging meteorological data from 36 stations in the middle reaches of the Yellow River Basin from 1961 to 2020, we employed the Standardized Precipitation Evapotranspiration Index (SPEI) to calculate drought occurrence. Concurrently, we explored the influence of atmospheric circulation on the SPEI. The findings of our study underscore a concerning trend of worsening drought conditions within the study area. We discovered a significant correlation between the duration and severity of drought (R = 0.83, p < 0.001); longer durations often corresponded to higher levels of severity. Turning our attention to atmospheric dynamics, the Nino Eastern Pacific index (NE) emerged as a critical driver of SPEI dynamics (the contribution of NE to SPEI was 0.22), significantly impacting drought patterns. In conclusion, the study significantly contributes to our comprehension of the evolving drought patterns under the influence of global warming. The findings can provide valuable information for water resource management and drought disaster control.

Nexus between the deficit in moisture transport and drought occurrence in regions with projected drought trends

In this article, we focus on studying the nexus between moisture transport deficit and drought occurrence in nine key regions across the world where the magnitude of meteorological drought is projected to increase from 1850 to 2100 under a high anthropogenic emission scenario. These regions are central America, southwestern South America, northern Brazil, the Amazon, northeastern Brazil, the western Mediterranean, southern Africa, the eastern Mediterranean, and southwestern Australia. Using the Lagrangian particle dispersion model FLEXPART, we identify the specific moisture sources of the regions (the own region, the nearby continental source and the oceanic sources) and obtain their contributions to the precipitation in the regions for the period 1980–2018. For each region and specific moisture source, the conditional probability of meteorological drought occurrence given an equivalent contribution deficit from the source is estimated using copula models, a statistical methodology that allows us to capture complex relationships between variables. We identify the dominant moisture source in each region, which is the source for which the contribution deficit maximises drought probability. A variety of cases are found: in three regions, the dominant source is the region itself, in one region, it is the nearby terrestrial source, and in five regions, it is an oceanic source. In general, contribution deficits from specific moisture sources are associated with only slightly greater drought probabilities than those from major global moisture sources. We also reveal that the source that contributes the most to precipitation in a given region is not necessarily the dominant source of drought in the region. These results highlight the importance of understanding the role of dominant moisture sources and moisture transport deficits on meteorological drought occurrence at a regional scale.

Modeling drought mortality and resilience of savannas and forests in tropical Asia

The projected increase of drought occurrence in many tropical and sub-tropical regions globally under future climates will affect terrestrial ecosystems, particularly by increasing drought-induced plant mortality. The capacity to simulate drought mortality in vegetation models is therefore essential to understand future ecosystem dynamics. Using the trait-based vegetation model aDGVM2, we assessed drought mortality and resilience in tropical Asia under climate change. We conducted model simulations for ten sites in tropical Asia, representing a biogeographic gradient. Responses of vegetation attributes and mortality rates were simulated until 2099 for hypothetical drought scenarios and recovery times were calculated. Model simulations showed biomass dieback during drought due to increased plant mortality, primarily among tall and old trees. Drought responses were related to hydraulic traits and associated ecological strategies. Despite severe drought impacts, recovery was possible, but recovery times differed between ecosystem attributes. We conclude that the aDGVM2 enhances our ability to understand drought impacts in tropical ecosystems. The model can simulate increased mortality during drought in a trait- and individual-based modeling framework. It indicated drought resilience of forests and adaptation to drought by changes in community trait composition and the demographic structure. Yet, further model improvements are required to better represent drought impact and recovery.

Frequency, duration, severity of energy drought and its propagation in hydro-wind-photovoltaic complementary systems

Analyzing low-renewable-output events, termed “energy droughts” is crucial for renewable energy systems. However, due to the challenges in hydropower regulation and complex spatiotemporal correlations among resources, the assessment and contributions of various resources to energy droughts in hydro-wind-photovoltaic (PV) energy systems (HWPSs) remain unexplored. To address these issues, this study evaluated energy droughts and compound resource droughts rather than single-resource in HWPSs, exploring the propagation. Assessments of frequency, duration, and severity relied on weather-to-resource conversion models and total power obtained through complementary operation. Estimating propagation probability from resource to energy droughts was achieved via the C-vine copula, quantifying resource contributions to drought propagation. Results of a case study in the Yalong River Basin indicated that (1) short-lived compound resource droughts have been increasingly frequent recently, peaking during winter or summer. After incorporating hydro energy resources, the severity and annual average occurrence of compound droughts decreased (from 18.56 to 5.24 events/year). (2) Complementary operation effectively reduced the probability of drought propagation. (3) Hydro and PV energy resources were pivotal contributors to drought propagation, contributing 49.1 % and 40.1 % when representing 53.4 % and 22.5 % of the total system capacity, respectively. Therefore, the study offers valuable insights into energy drought warnings and risk mitigation.

An optimized network for drought prediction using satellite images

The change in climate and the hot temperature environment increased the risk of drought around the workplace. Predicting and forecasting the drought occurrence is essential for managing water resources and agricultural plans. Therefore, in this study, a novel Chimp-based Wide ResNet Prediction Framework (CWRPF) is designed to predict the drought. The key motive of the presented research is to predict the drought and no drought conditions derived from the satellite images. The satellite images are collected from the Bhuvan site. Initially, the satellite images are noise-filtered. The filtered images are then injected into the feature analysis phase to compute the drought indices of a specific area by the fitness function activated in the framework. After estimating the drought indices, the drought condition was categorized. Finally, the designed system is tested in the MATLAB platform and has gained more significant results by providing a 97.68% accuracy rate, R2 as 0.998, and lower RMSE and MAE values of 0.223 and 0.193. The accumulated results are compared with existing techniques to validate the improvement score. The accuracy of the CWRPF is more remarkable than that of other prediction models. Therefore, the system is efficient for drought prediction in satellite images.

Exploring short- and long-term meteorological drought parameters in the Vaippar Basin of Southern India

Evaluating drought parameters at the basin level is one of the fundamental processes for planning sustainable crop production. This study aimed to evaluate both short-term and long-term meteorological drought parameters within the Vaippar Basin, located in southern India, by employing the standardized precipitation index (SPI). Gridded rainfall values developed from 13 rain gauge stations were employed to calculate the SPI values. Drought parameters, encompassing occurrence, intensity, duration, frequency, and trends, were assessed for both short-term and long-term droughts. The study findings indicated that the occurrence of short-term drought was 51.7%, while that of long-term drought was 49.82%. Notably, the basin experienced extreme short-term droughts in 1980, 1998 and 2016 and long-term droughts in 1981, 2013, and 2017. Utilizing an innovative trend identification method for SPI values, a significant monotonic upwards trend was identified in October and December for short-term drought and in December for long-term drought. This study defined the minimum threshold rainfall, which represents the critical amount required to prevent short-term drought (set at 390 mm) and long-term drought (set at 635 mm). The drought severity recurrence curves developed in this study indicate that when the SPI values fall below − 1.0, short-term drought affects 25% of the basin area, while long-term drought impacts 50% of the basin area at a 20-year recurrence interval. Additionally, the drought hazard index (DHI), which combines drought intensity and severity, demonstrated higher values in the northwestern regions for short-term drought and in the southern areas for long-term drought. The study's findings, highlighting areas of drought vulnerability, severity, and recurrence patterns in the basin, direct the attention for timely intervention when drought initiates.

Evaluation of the sensitivity of meteorological drought in the Mediterranean region to different data record lengths.

The division and evaluation of data series used in monitoring drought into different time intervals is a practical approach to detecting the spatial and temporal extent of drought spread. This study aimed to determine meteorological drought's spatial and temporal distribution using overlapping and consecutive periods and cycles of the standardized precipitation index (SPI) time series in the Mediterranean region, Turkey. In the scope of the research, SPI values for the SPI12, SPI6 (1), and SPI6 (2) seasons were calculated for consecutive and overlapping hydrological years (1978-1998/21years, 1978-2008/31years, and 1978-2018/41years) at 28 meteorological stations. Autocorrelation, Mann-Kendall, and Sen slope trend tests were applied at a 5% significance level for each season (SPI12, SPI6 (1), and SPI6 (2)) and different time scales (21, 31, and 41years). For each season and period, maps of the SPI drought class, average formation of drought class, Mann-Kendall (MK) trend, and Sen's slope (SS) trend test statistics for the Mediterranean region were obtained, and the spatial distribution rate of trends was determined by drawing hypsometric curves. Changes in drought occurrence at different time scales were thoroughly evaluated with the changing length of data recording.Consequently, it was determined that the mild wet (MIW) and mild drought (MID) classes dominate the study area in the Mediterranean region. Significant and nonstationary changes detected in extreme wet and drought occurrences (extreme wet, EW; severe wet, SW; extreme drought, ED; severe drought, SD) were found to pose a risk in the study area. It was observed that there were spatially and temporally insignificant decreasing drought trends in the Mediterranean basin, considering that the time scales of these trends slowed down. Despite a nonsignificant trend from the MID drought class to the MIW drought class, it is predicted that the MIW and MID classes will maintain their dominance in the Mediterranean region. The central part of the study area (central Mediterranean basin) is the region with the highest drought risk.

A Comparison of the Frequency and Intensity of Standardized Precipitation Index (SPI) and the Rainfall Anomaly Index (RAI) during the Meteorological Drought across Harohar-Punpun Basin (India)

The term "drought" applies to a prolonged period when there is a water shortage because of insufficient precipitation, an excessive rate of evaporation, and excessive use of water from reservoirs and other storage, including ground water. It is a slow-onset phenomenon that can have significant social, economic, and environmental impacts. Both the frequency and severity of droughts are increasing globally due to manmade and natural factors. This study looked at how well SPIs (3, 6, 12-month time scales) and RAI (Rainfall Anomaly Index) performed at identifying drought occurrences over a period of 70 years (1951 to 2021) in India's Agro-Ecological Zones. The RAI and SPI values were computed using rainfall data from 9 meteorological stations located throughout the Harohar- Punpun Basin. According to the results, the RAI is more capable than SPIs in detecting historical records of actual occurrences. Additionally, RAI is more effective than SPIs for determining both short- and long-term droughts. Since RAI can better capture the true nature of the drought situation in the Harohar-Punpun Basin, it appears to be more responsive to drought circumstances. The primary causes of drought, according to the study, include minor variations in precipitation, willful ground water removal, changing cropping patterns, and substantial changes in land use. Regional planners and administrators will surely find use for this scientific study and integrated watershed management methods for sustainable water resource management, particularly for this region.

Identification of sinkhole‐prone zones by successive coincidence deficit index analysis

AbstractHydrological data‐driven models require the time series of several hydrological events with different time resolutions. The interpretation of any time series event is generally difficult without some sort of filtering or converting it to a single index value. The simultaneous analysis of two or more hydrological events over a definite time span may be more informative about the region of interest. For this purpose, a new index, referred to as the successive coincidence deficit index (SCDI), was introduced to identify sinkhole‐prone regions using the persistent water deficit concept. In this study, monthly integrated multi‐satellite retrievals for GPM based precipitation (P) and gravity recovery and climate experiment‐based groundwater storage (GWS) datasets over Konya Closed Basin (KCB) in Türkiye were used to analyse the sinkhole occurrence. The main finding of this study is that SCDI distribution with high index values, concentrated on the southwestern part of KCB, is in line with the sinkholes occurred mainly after 2010. The proposed SCDI could also serve as a kind of drought index, which enables practitioners to quantify the relationship between drought and sinkhole occurrence. Moreover, the event coincidence analysis was utilized to detect deficiency in GWS over the KCB, which was associated with a rate of 0.8 for P deficiency, and this rate reaches up to 0.9 in the sinkhole region analysed in this study. As a conclusion, the proposed methodology can detect sinkhole‐prone regions to construct risk maps for stakeholders, policymakers, and end users.

Spatiotemporal dynamics of meteorological and agricultural drought, part of Manbhum-Singhbhum Plateau (India): Four decades study using NASA POWER and MODIS data

Drought is an extremely hazardous situation that predominantly affects ecosystems, hydrological systems, and agricultural mechanisms in different pockets of the world. Management of water resources in dry and semi-arid environments has become a critical challenge in the last few decades. The principal objectives of this study are (i) to categorize the severity and frequency of drought events using the Reconnaissance Drought Index and Rainfall Deviation Index and ii) to evaluate the spatial extension of drought in particular drought times of severe and extreme droughts through Remote Sensing Drought Indices (RSDIs). This drought monitoring index is commonly used index for its high degree of resilience and sensitivity to droughts. The result shows that severe to extreme drought occurred in Bero, Tulin, Sirkabad, Manbazar and Bundwan which are 22, 28, 23, 14 and 25 months correspondingly based on RDI3 whereas RDI12 values indicated 26, 47, 42, 22 and 38 months in the study period (1981 to 2021). Bundwan area faced the most extreme drought occurrence in May month of 1996 with −3.58 values followed by Sirkabad, Bero, Manbazar and Tulin. Manbazar is going through severe to extreme drought months (for short time) whereas ‘extreme drought’ frequency (1.67 % to 1.05 %) is higher in the western part mainly in Jhalda I, Jhalda II, Bagmundi, and Arsha blocks of Purulia district (part of Manbhum Singhbhum Plateau). Additionally, the recurrence of ‘moderate drought’ is much greater in Balarampur along with some portions of Purulia I block. The whole study can be summarized as the northeastern portion being challenged with moderate or severe drought conditions while mild or severe drought is a considerable recurrence in the northern section. The outcome of this study will be helpful for local planners and management officials during implementation strategies related to water resource management.

Enhanced Modulation of Streamflow Flash Droughts by Reservoir Operations in India

AbstractStreamflow flash droughts (SFDs) occur due to a rapid decline in streamflow and cause major challenges associated with water availability for downstream ecosystems, hydropower generation, and irrigation water demand. Human interventions such as reservoir operations and reservoir storage can considerably influence streamflow variability. However, the crucial role of dams/reservoirs on the occurrence of SFDs in India remains unexamined. Using a combination of hydrological and hydrodynamical models, we examined the role of reservoirs on SFDs in India during 1971–2020. Reservoirs play a considerable role in the occurrence of SFDs during the summer monsoon season (June‐September) in India. The frequency and severity of SFDs in the presence of reservoirs are substantially lesser than in the absence of them. In addition, high and low antecedent reservoir storage conditions before meteorological flash droughts (MFDs) do not support the rapid decline of streamflow (i.e., SFDs) downstream of reservoirs, while the medium reservoir storage conditions prior to MFDs favor the development of SFDs. Similar to conventional (or long‐term) streamflow droughts (SDs), SFDs are more frequent in the El Nino phase than in the La Nina phase. Unlike the long‐term streamflow droughts, the implementation of dams considerably reduces the frequency of SFDs during both the negative and positive phases of El Nino Southern Oscillation. Overall, our findings demonstrate the considerable role of human interventions in flash drought occurrence, as SFDs are triggered by MFDs but modulated by reservoir storage and operations.

Regional and farm level droughts characteristics for southwestern Uganda during 1981–2017

An increase in drought events associated with rising temperatures indicates that Uganda is facing a growing challenge from climate variability. Despite these challenges, there is a lack of comprehensive information on how climate variability affects soils, particularly drought characteristics. In an effort to address this limitation, this study utilised high-quality, in-situ climate data and soil Available Water Capacity (AWC) specific to south-western Uganda. The study employed the Palmer Drought Severity Index (PDSI) and the Standardised Precipitation-Evapotranspiration Index (SPEI) to assess drought occurrences over the period 1981–2017. Notably, the results from the 3-month SPEI indicated higher frequencies across all drought categories. Meanwhile, the 12-month SPEI exhibited more stabilised negative and positive truncations for drought and wet events, respectively. Analysing the temporal evolution of monthly PDSI values for five major soil mapping units revealed distinct patterns. Moderate droughts were observed over Lixic Ferralsols between 1981 and 1992 and between 1998 and 2008. Extreme drought events occurred during the first 5–7 months of 2017. Luvisols exhibited prolonged negative truncation levels, indicating a water deficit during several periods: 1982–1984, 1990–1994, 1998–2000, 2010, and 2012–2014. Histosols experienced drought conditions from 1982 to 1986, interspersed with wet events in 1988, 1997, 1999–2002, and 2005. The study emphasises the differential response of soil units to drought and wet conditions. As a result, the research recommends implementing water management practices such as irrigation, mulching, conservation tillage, zero tillage, and drainage for all soils to enhance resilience and sustainable agricultural practices in the region.

Compound and consecutive drought-flood events at a global scale

Flooding during or after droughts poses significant challenges to disaster risk management. However, interactions between droughts and floods are often overlooked as studies typically analyse these events in isolation. Here we explore historical occurrences of compound and consecutive drought-flood events and drought effects on flood severity and timing by analysing global datasets of hydrometeorological and biophysical variables for 8255 catchments worldwide. These data show that 24% of floods globally (anomalies above the 85th percentile) are preceded by, or happen during, drought conditions. Flood events occurring during drought conditions are typically of lower magnitude, especially in arid regions, while floods following drought events have a severity distribution comparable to single flood events. For most drought-flood events, flood timing appears relatively unaffected by drought conditions, but almost a quarter of the drought-flood events had flood timings occurring two to three months later than expected. These shifts in flood timing suggest droughts potentially affect flood-generating processes. As both drought and flood occurrences are projected to increase in a warming climate, interactions between them may become more common and need to be accounted for in flood risk assessment and management.

Drought Monitoring and Prediction in Agriculture: Employing Earth Observation Data, Climate Scenarios and Data Driven Methods; a Case Study: Mango Orchard in Tamale, Ghana

The study focused on the prediction of the Temperature Vegetation Dryness Index (TVDI), an agricultural drought index, for a Mango orchard in Tamale, Ghana. It investigated the temporal relationship between the meteorological drought index, Standardized Precipitation Index (SPI), and TVDI. The SPI was calculated based on utilizing precipitation data from the World Meteorological Organization (WMO) database (2010–2022) and CMIP6 projected precipitation data (2023–2050) from 35 climate models representing various Shared Socioeconomic Pathway (SSP) climate change scenarios. Concurrently, TVDI was derived from Landsat 8/9 satellite imagery, validated using thermal data obtained from unmanned aerial vehicle (UAV) surveys. A comprehensive cross-correlation analysis between TVDI and SPI was conducted to identify lag times between these indices. Building on this temporal relationship, the TVDI was modeled as a function of SPI, with varying lag times as inputs to the Wavelet-Adaptive Neuro-Fuzzy Inference System (Wavelet-ANFIS). This innovative approach facilitated robust predictions of TVDI as an agricultural drought index, specifically relying on SPI as a predictor of meteorological drought occurrences for the years 2023–2050. The research outcome provides practical insights into the dynamic nature of drought conditions in the Tamale mango orchard region. The results indicate significant water stress projected for different time frames: 186 months for SSP126, 183 months for SSP245, and 179 months for both SSP370 and SSP585. This corresponds to a range of 55–57% of the projected months. These insights are crucial for formulating proactive and sustainable strategies for agricultural practices. For instance, implementing supplemental irrigation systems or crop adaptations can be effective measures. The anticipated outcomes contribute to a nuanced understanding of drought impacts, facilitating informed decision-making for agricultural planning and resource allocation.

Modeling the dynamics of anti-microbial resistant cholera infection with reinfection

Cholera continues to pose a significant global public health challenge. The occurrence of severe weather events, including floods, droughts, and cyclones, has led to a surge in new cholera outbreaks and exacerbated both epidemic and endemic conditions in numerous countries. We propose a ten-state ordinary differential system of equations to model antimicrobial resistant cholera infections, considering both direct and indirect transmission pathways. Antimicrobial resistant cholera infection is considered to occur in some infected individuals receiving antibiotic treatment. The model integrates key interventions such as vaccination, screening, and treatment to curb cholera spread. Loss of infection-acquired immunity for the recovered individuals is also considered in the model. A threshold quantity referred to as the model reproduction number Rc is computed and stability analysis of equilibrium points for the full model and submodels is performed. Sensitivity analysis is performed and specific measures to reduce parameters associated with cholera transmission and enhance parameters related to control measures are suggested. Numerical simulations are carried out to support theoretical findings. The results obtained places a significant emphasis on antimicrobial resistance and its impact on cholera control. The importance of minimizing antimicrobial resistance through targeted interventions is highlighted. Therefore, there is an urgent need to implement policies aimed at mitigating the spread of antimicrobial resistance.

An Approach to Assess the Impact of High Biaxial Photovoltaic Trackers on Crop Growth and Yield

The growing need for producing renewable energy such as photovoltaic electricity, and the mitigation of the increasing occurrences of heatwaves and drought affecting annual crops, could be addressed by the installation of agrivoltaic systems. Depending on pedoclimatic context, cultivated crop, solar panels technology and implementation configuration, solar panels shading can improve or reduce crop growth and yields. Among photovoltaic installations, solar trackers might have a high development potential. These photovoltaic panels are mounted on a vertical axis at a 7m height. Thanks to their height, their biaxial moving capacity, their small anchoring surface and their punctual structure making plants design easily adaptable to agricultural constraints, they can fit with all types of agricultural systems. The aim of this study was to evaluate the impact of such trackers on crop growth and yields. For this purpose, a set of 6 different fields crop located in western France were studied. Crop phenology, height and yield were investigated. Results showed a delay in crop development near the trackers that was overcome late in the crop cycle, near harvest. For crop height and crop yield, the results showed important spatial variability but without clear trend related to the tracker shadow. The results are discussed in the light of new perspectives, including the consideration of microclimatic and pedological data to better explore the effects of trackers on plant growth and development, the measurement of morphological and physiological traits of plants, the accounting of a multi-trackers effect implemented on the same site, the temporal dynamics of the effect of a tracker.