基于24Model-D-ISM的地铁站火灾疏散影响因素研究

为预防地铁站火灾事故,深入了解地铁站火灾人员疏散影响因素间的内在联系与层次结构,基于第6版“2-4”模型(24Model)分析63起地铁站火灾疏散事故,充分考虑各个因素之间的交互作用,提取19个影响地铁站人员疏散的关键因素,建立地铁站火灾人员疏散影响因素指标体系;采用算子客观赋权法(C-OWA)改进决策试验与评价实验法(DEMATEL),确定地铁站火灾人员疏散的重要影响因素;在此基础上,采用解释结构模型(ISM)分析各个因素间的层次结构及相互作用路径,构建地铁站火灾人员疏散影响因素的多级递阶结构模型。研究结果表明:疏散引导、恐慌从众行为、人员拥挤为地铁站火灾人员疏散的关键影响因素;地铁站火灾人员疏散受表层因素、中间层因素、深层因素共同作用的影响,其中,疏散教育与培训、设施维护与检查、疏散预案等因素是根源影响因素,重视根源影响因素的改善有利于从本质上预防和控制事故的发生。

24Model与LCM原因因素定义对比研究

为探究损失致因模型(LCM)原因因素定义与事故致因“2-4”模型(24Model)存在的异同和优缺点,梳理2个模型各层面原因和结果的定义,对比定义内容及其对事故原因分析等安全实务的指导作用,并以一起瓦斯爆炸事故为例加以实证分析,获得二者分析结果之间的差异。研究结果表明:LCM是首个将管理因素纳入事故致因分析的一维事件序列模型,可明确各层面原因因素的定义和因素间的逻辑关系,但部分定义存在交叉重复的问题,并没有揭示安全工作指导思想等深层次事故致因因素;24Model作为系统性事故致因模型,对各类因素的定义均以组织为主体,描述事件、事故、安全的概念内涵,划分个体安全动作、安全能力和组织安全管理体系的类别并给出含义解析,探究组织安全文化层面的问题并以32个元素体现;2个模型的事故原因分析方法均建立在对各层级原因因素定义的基础上,并适用于模型理论体系本身。

Immunobiology of COVID-19: Mechanistic and therapeutic insights from animal models

The distribution of the immune system throughout the body complicates in vitro assessments of coronavirus disease 2019(COVID-19)immunobiology,often resulting in a lack of reproducibility when extrapolated to the whole organism.Consequently,developing animal models is imperative for a comprehensive understanding of the pathology and immunology of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)infection.This review summarizes current progress related to COVID-19 animal models,including non-human primates(NHPs),mice,and hamsters,with a focus on their roles in exploring the mechanisms of immunopathology,immune protection,and long-term effects of SARS-CoV-2 infection,as well as their application in immunoprevention and immunotherapy of SARS-CoV-2 infection.Differences among these animal models and their specific applications are also highlighted,as no single model can fully encapsulate all aspects of COVID-19.To effectively address the challenges posed by COVID-19,it is essential to select appropriate animal models that can accurately replicate both fatal and non-fatal infections with varying courses and severities.Optimizing animal model libraries and associated research tools is key to resolving the global COVID-19 pandemic,serving as a robust resource for future emerging infectious diseases.

A thermochemical model description of CaO_(2)-SiO2-Al_(2)O_(3) silicate system

A thermochemical model based on the ion and molecule coexistence theory(IMCT)was developed to calculate thermodynamic data in the CaO-SiO_(2)-Al_(2)O_(3) slag system,considering the influential role of oxide activities on the thermodynamic properties of slags.Using this model,iso-activity contours were obtained for oxide components CaO,SiO_(2) and Al2O3 in this system at temperatures of 1,873 K and 1,773 K.When compared with the IMCT model,it is found that the predicted activities of oxide components in the CaO-SiO_(2)-Al_(2)O_(3) system using the model developed in this study better matches experimental data from literature in terms of both trend and numerical value.Therefore,the model developed in this study can serve as a robust modeling tool for metallurgical processes,and the thermodynamic data predicted by this new model can be used to improve the metallurgical technology.

Spatial Inhomogeneity of Atmospheric CO_(2) Concentration and Its Uncertainty in CMIP6 Earth System Models

This paper provides a systematic evaluation of the ability of 12 Earth System Models(ESMs)participating in the Coupled Model Intercomparison Project Phase 6(CMIP6)to simulate the spatial inhomogeneity of the atmospheric carbon dioxide(CO_(2))concentration.The multi-model ensemble mean(MME)can reasonably simulate the increasing trend of CO_(2) concentration from 1850 to 2014,compared with the observation data from the Scripps CO_(2) Program and CMIP6 prescribed data,and improves upon the CMIP5 MME CO_(2) concentration(which is overestimated after 1950).The growth rate of CO_(2) concentration in the northern hemisphere(NH)is higher than that in the southern hemisphere(SH),with the highest growth rate in the mid-latitudes of the NH.The MME can also reasonably simulate the seasonal amplitude of CO_(2) concentration,which is larger in the NH than in the SH and grows in amplitude after the 1950s(especially in the NH).Although the results of the MME are reasonable,there is a large spread among ESMs,and the difference between the ESMs increases with time.The MME results show that regions with relatively large CO_(2) concentrations(such as northern Russia,eastern China,Southeast Asia,the eastern United States,northern South America,and southern Africa)have greater seasonal variability and also exhibit a larger inter-model spread.Compared with CMIP5,the CMIP6 MME simulates an average spatial distribution of CO_(2) concentration that is much closer to the site observations,but the CMIP6-inter-model spread is larger.The inter-model differences of the annual means and seasonal cycles of atmospheric CO_(2) concentration are both attributed to the differences in natural sources and sinks of CO_(2) between the simulations.

A Numerical Simulation of Air Flow in the Human Respiratory System Based on Lung Model

The lung is an important organ that takes part in the gas exchange process. In the study of gas transport and exchange in the human respiratory system, the complicated process of advection and diffusion (AD) in airways of human lungs is considered. The basis of a lumped parameter model or a transport equation is modeled during the inspiration process, when oxygen enters into the human lung channel. The quantitative measurements of oxygen are detached and the model equation is solved numerically by explicit finite difference schemes. Numerical simulations were made for natural breathing conditions or normal breathing conditions. The respiratory flow results for the resting conditions are found strongly dependent on the AD effect with some contribution of the unsteadiness effect. The contour of the flow rate region is labeled and AD effects are compared with the variation of small intervals of time for a constant velocity when breathing is interrupted for a negligible moment.

Phosphorus limitation on CO_(2)fertilization effect in tropical forests informed by a coupled biogeochemical model

Tropical forests store more than half of the world's terrestrial carbon(C)pool and account for one-third of global net primary productivity(NPP).Many terrestrial biosphere models(TBMs)estimate increased productivity in tropical forests throughout the 21st century due to CO_(2)fertilization.However,phosphorus(P)liaitations on vegetation photosynthesis and productivity could significantly reduce the CO_(2)fertilization effect.Here,we used a carbon-nitrogen-phosphorus coupled model(Dynamic Land Ecosystem Model;DLEM-CNP)with heterogeneous maximum carboxylation rates to examine how P limitation has affected C fluxes in tropical forests during1860-2018.Our model results showed that the inclusion of the P processes enhanced model performance in simulating ecosystem productivity.We further compared the simulations from DLEM-CNP,DLEM-CN,and DLEMC and the results showed that the inclusion of P processes reduced the CO_(2)fertilization effect on gross primary production(GPP)by 25%and 45%,and net ecosystem production(NEP)by 28%and 41%,respectively,relative to CN-only and C-on ly models.From the 1860s to the 2010s,the DLEM-CNP estimated that in tropical forests GPP increased by 17%,plant respiration(Ra)increased by 18%,ecosystem respiration(Rh)increased by 13%,NEP increased by 121%per unit area,respectively.Additionally,factorial experiments with DLEM-CNP showed that the enhanced NPP benefiting from the CO_(2) fertilization effect had been offset by 135%due to deforestation from the 1860s to the 2010s.Our study highlights the importance of P limitation on the C cycle and the weakened CO_(2)fertilization effect resulting from P limitation in tropical forests.

Comparison of immune responses and intestinal flora in epicutaneously sensitized BALB/c or C57BL/6 mouse models of food allergy

Cutaneous exposure to food allergens through a disrupted skin barrier is recognized as an important cause of food allergy,and the cutaneous sensitized mouse model has been established to investigate relevant allergic disorders.However,the role of different genetic backgrounds of mice on immune responses to food allergens upon epicutaneous sensitization is largely unknown.In this study,two strains of mice,i.e.,the BALB/c and C57BL/6 mice,were epicutaneously sensitized with ovalbumin on atopic dermatitis(AD)-like skin lesions,followed by intragastric challenge to induce IgE-mediated food allergy.Allergic outcomes were measured as clinical signs,specific antibodies and cytokines,and immune cell subpopulations,as well as changes in intestinal barrier function and gut microbiota.Results showed that both strains of mice exhibited typical food-allergic symptoms with a Th2-skewed response.The C57BL/6 mice,rather than the BALB/c mice,were fitter for establishing an epicutaneously sensitized model of food allergy since a stronger Th2-biased response and severer disruptions in the intestinal barrier and gut homeostasis were observed.This study provides knowledge for selecting an appropriate mouse model to study food-allergic responses associated with AD-like skin lesions and highlights the role of genetic variations in the immune mechanism underlying pathogenesis of food allergy.

Performance validation of High Mountain Asia 8-meter Digital Elevation Model using ICESat-2 geolocated photons

High Mountain Asia(HMA),recognized as a third pole,needs regular and intense studies as it is susceptible to climate change.An accurate and high-resolution Digital Elevation Model(DEM)for this region enables us to analyze it in a 3D environment and understand its intricate role as the Water Tower of Asia.The science teams of NASA realized an 8-m DEM using satellite stereo imagery for HMA,termed HMA 8-m DEM.In this research,we assessed the vertical accuracy of HMA 8-m DEM using reference elevations from ICESat-2 geolocated photons at three test sites of varied topography and land covers.Inferences were made from statistical quantifiers and elevation profiles.For the world’s highest mountain,Mount Everest,and its surroundings,Root Mean Squared Error(RMSE)and Mean Absolute Error(MAE)resulted in 1.94 m and 1.66 m,respectively;however,a uniform positive bias observed in the elevation profiles indicates the seasonal snow cover change will dent the accurate estimation of the elevation in this sort of test sites.The second test site containing gentle slopes with forest patches has exhibited the Digital Surface Model(DSM)features with RMSE and MAE of 0.58 m and 0.52 m,respectively.The third test site,situated in the Zanda County of the Qinghai-Tibet,is a relatively flat terrain bed,mostly bare earth with sudden river cuts,and has minimal errors with RMSE and MAE of 0.32 m and 0.29 m,respectively,and with a negligible bias.Additionally,in one more test site,the feasibility of detecting the glacial lakes was tested,which resulted in exhibiting a flat surface over the surface of the lakes,indicating the potential of HMA 8-m DEM for deriving the hydrological parameters.The results accrued in this investigation confirm that the HMA 8-m DEM has the best vertical accuracy and should be of high use for analyzing natural hazards and monitoring glacier surfaces.

A multi-mechanism numerical simulation model for CO_(2)-EOR and storage in fractured shale oil reservoirs

Under the policy background and advocacy of carbon capture,utilization,and storage(CCUS),CO_(2)-EOR has become a promising direction in the shale oil reservoir industry.The multi-scale pore structure distribution and fracture structure lead to complex multiphase flow,comprehensively considering multiple mechanisms is crucial for development and CO_(2) storage in fractured shale reservoirs.In this paper,a multi-mechanism coupled model is developed by MATLAB.Compared to the traditional Eclipse300 and MATLAB Reservoir Simulation Toolbox(MRST),this model considers the impact of pore structure on fluid phase behavior by the modified Peng—Robinson equation of state(PR-EOS),and the effect simultaneously radiate to Maxwell—Stefan(M—S)diffusion,stress sensitivity,the nano-confinement(NC)effect.Moreover,a modified embedded discrete fracture model(EDFM)is used to model the complex fractures,which optimizes connection types and half-transmissibility calculation approaches between non-neighboring connections(NNCs).The full implicit equation adopts the finite volume method(FVM)and Newton—Raphson iteration for discretization and solution.The model verification with the Eclipse300 and MRST is satisfactory.The results show that the interaction between the mechanisms significantly affects the production performance and storage characteristics.The effect of molecular diffusion may be overestimated in oil-dominated(liquid-dominated)shale reservoirs.The well spacing and injection gas rate are the most crucial factors affecting the production by sensitivity analysis.Moreover,the potential gas invasion risk is mentioned.This model provides a reliable theoretical basis for CO_(2)-EOR and sequestration in shale oil reservoirs.

3D seismic forward modeling from the multiphysical inversion at the Ketzin CO_(2) storage site

From June 2008 to August 2013,approximately 67 kt of CO_(2) was injected into a deep saline formation at the Ketzin pilot CO_(2) storage site.During injection,3D seismic surveys have been performed to monitor the migration of sequestered CO_(2).Seismic monitoring results are limited by the acquisition and signal-to-noise ratio of the acquired data.The multiphysical reservoir simulation provides information regarding the CO_(2) fluid behavior,and the approximated model should be calibrated with the monitoring results.In this work,property models are delivered from the multiphysical model during 3D repeated seismic surveys.The simulated seismic data based on the models are compared with the real data,and the results validate the effectiveness of the multiphysical inversion method.Time-lapse analysis shows the trend of CO_(2) migration during and after injection.

The Cloud Model for Climate Change

In 1995, the Intergovernmental Panel on Climate Change (IPCC) released a thermodynamic model based on the Greenhouse Effect, aiming to forecast global temperatures. This study delves into the intricacies of that model. Some interesting observations are revealed. The IPCC model equated average temperatures with average energy fluxes, which can cause significant errors. The model assumed that all energy fluxes remained constant, and the Earth emitted infrared radiation as if it were a blackbody. Neither of those conditions exists. The IPCC’s definition of Climate Change only includes events caused by human actions, excluding most causes. Satellite data aimed at the tops of clouds may have inferred a high Greenhouse Gas absorption flux. The model showed more energy coming from the atmosphere than absorbed from the sun, which may have caused a violation of the First and Second Laws of Thermodynamics. There were unexpectedly large gaps in the satellite data that aligned with various absorption bands of Greenhouse Gases, possibly caused by photon scattering associated with re-emissions. Based on science, we developed a cloud-based climate model that complied with the Radiation Laws and the First and Second Laws of Thermodynamics. The Cloud Model showed that 81.3% of the outgoing reflected and infrared radiation was applicable to the clouds and water vapor. In comparison, the involvement of CO2 was only 0.04%, making it too minuscule to measure reliably.

Depositional model of the Member Deng-2 marginal microbial mound-bank complex of the Dengying Formation in the southwestern Sichuan Basin, SW China: Implications for the Ediacaran microbial mound construction and hydrocarbon exploration

Recent advances in hydrocarbon exploration have been made in the Member Deng-2 marginal microbial mound-bank complex reservoirs of the Dengying Formation in the western Sichuan Basin, SW China,where the depositional process is regarded confusing. The microfacies, construction types, and depositional model of the Member Deng-2 marginal microbial mound-bank complex have been investigated using unmanned aerial vehicle photography, outcrop section investigation, thin section identification,and seismic reflections in the southwestern Sichuan Basin. The microbialite lithologic textures in this region include thrombolite, dendrolite, stromatolite, fenestral stromatolite, spongiostromata stone,oncolite, aggregated grainstone, and botryoidal grapestone. Based on the comprehensive analysis of“depositional fabrics-lithology-microfacies”, an association between a fore mound, mound framework,and back mound subfacies has been proposed based on water depth, current direction, energy level and lithologic assemblages. The microfacies of the mound base, mound core, mound flank, mound cap, and mound flat could be recognized among the mound framework subfacies. Two construction types of marginal microbial mound-bank complex have been determined based on deposition location, mound scale, migration direction, and sedimentary facies association. Type Jinkouhe microbial mound constructions(TJMMCs) develop along the windward margin owing to their proximity to the seaward subfacies fore mound, with a northeastwardly migrated microbial mound on top of the mud mound,exhibiting the characteristics of large-sized mounds and small-sized banks in the surrounding area. Type E'bian microbial mound constructions(TEMMCs) primarily occur on the leeward margin, resulting from the presence of onshore back mound subfacies, with the smaller southwestward migrated microbial mounds existing on a thicker microbial flat. The platform margin microbial mound depositional model can be correlated with certain lateral comparison profile and seismic reflection structures in the 2D seismic section, which can provide references for future worldwide exploration. Microbial mounds with larger buildups and thicker vertical reservoirs are typically targeted on the windward margin, while small-sized microbial mounds and flats with better lateral connections are typically focused on the leeward margin.

Numerical modeling of blast-induced rock fragmentation in deep mining with 3D and 2D FEM method approaches

To optimize the excavation of rock using underground blasting techniques,a reliable and simplified approach for modeling rock fragmentation is desired.This paper presents a multistep experimentalnumerical methodology for simplifying the three-dimensional(3D)to two-dimensional(2D)quasiplane-strain problem and reducing computational costs by more than 100-fold.First,in situ tests were conducted involving single-hole and free-face blasting of a dolomite rock mass in a 1050-m-deep mine.The results were validated by laser scanning.The craters were then compared with four analytical models to calculate the radius of the crushing zone.Next,a full 3D model for single-hole blasting was prepared and validated by simulating the crack length and the radius of the crushing zone.Based on the stable crack propagation zones observed in the 3D model and experiments,a 2D model was prepared.The properties of the high explosive(HE)were slightly reduced to match the shape and number of radial cracks and crushing zone radius between the 3D and 2D models.The final methodology was used to reproduce various cut-hole blasting scenarios and observe the effects of residual cracks in the rock mass on further fragmentation.The presence of preexisting cracks was found to be crucial for fragmentation,particularly when the borehole was situated near a free rock face.Finally,an optimization study was performed to determine the possibility of losing rock continuity at different positions within the well in relation to the free rock face.

Metal-N_(4) model single‐atom catalyst with electroneutral quadri‐pyridine macrocyclic ligand for CO_(2) electroreduction

Metal–N–C single‐atom catalysts,mostly prepared from pyrolysis of metalorganic precursors,are widely used in heterogeneous electrocatalysis.Since metal sites with diverse local structures coexist in this type of material and it is challenging to characterize the local structure,a reliable structure–property relationship is difficult to establish.Conjugated macrocyclic complexes adsorbed on carbon support are well‐defined models to mimic the singleatom catalysts.Metal–N_(4) site with four electroneutral pyridine‐type ligands embedded in a graphene layer is the most commonly proposed structure of the active site of single‐atom catalysts,but its molecular counterpart has not been reported.In this work,we synthesized the conjugated macrocyclic complexes with a metal center(Co,Fe,or Ni)coordinated with four electroneutral pyridinic ligands as model catalysts for CO_(2) electroreduction.For comparison,the complexes with anionic quadri‐pyridine macrocyclic ligand were also prepared.The Co complex with the electroneutral ligand expressed a turnover frequency of CO formation more than an order of magnitude higher than that of the Co complex with the anionic ligand.Constrained ab initio molecular dynamics simulations based on the well‐defined structures of the model catalysts indicate that the Co complex with the electroneutral ligand possesses a stronger ability to mediate electron transfer from carbon to CO_(2).

Delayed treatment of diabetic foot ulcer in patients with type 2 diabetes and its prediction model

BACKGROUND Diabetic foot(DF)is a serious complication of type 2 diabetes.This study aimed to investigate the factors associated with DF occurrence and the role of delayed medical care in a cohort of patients with type 2 diabetes.AIM To reveal the impact of delayed medical treatment on the development of DF in patients with type 2 diabetes and to establish a predictive model for DF.METHODS In this retrospective cohort study,292 patients with type 2 diabetes who underwent examination at our hospital from January 2023 to December 2023 were selected and divided into the DF group(n=82,DF)and nondiabetic foot group(n=210,NDF).Differential and correlation analyses of demographic indicators,laboratory parameters,and delayed medical treatment were conducted for the two groups.Logistic regression was applied to determine influencing factors.Receiver operating characteristic(ROC)analysis was performed,and indicators with good predictive value were selected to establish a combined predictive model.RESULTS The DF group had significantly higher body mass index(BMI)(P<0.001),disease duration(P=0.012),plasma glucose levels(P<0.001),and HbA1c(P<0.001)than the NDF group.The NDF group had significantly higher Acute Thrombosis and Myocardial Infarction Health Service System(ATMHSS)scores(P<0.001)and a significantly lower delayed medical treatment rate(72.38%vs 13.41%,P<0.001).BMI,duration of diabetes,plasma glucose levels,HbA1c,diabetic peripheral neuropathy,and nephropathy were all positively correlated with DF occurrence.ATMHSS scores were negatively correlated with delayed time to seek medical treatment.The logistic regression model revealed that BMI,duration of diabetes,plasma glucose levels,HbA1c,presence of diabetic peripheral neuropathy and nephropathy,ATMHSS scores,and delayed time to seek medical treatment were influencing factors for DF.ROC analysis indicated that plasma glucose levels,HbA1c,and delayed medical treatment had good predictive value with an area under the curve of 0.933 for the combined predictive model.CONCLUSION Delayed medical treatment significantly affects the probability of DF occurrence in patients with diabetes.Plasma glucose levels,HbA1c levels,and the combined predictive model of delayed medical treatment demonstrate good predictive value.

Prediction of(n,2n)reaction cross-sections of long-lived fission products based on tensor model

Interest has recently emerged in potential applications of(n,2n)reactions of unstable nuclei.Challenges have arisen because of the scarcity of experimental cross-sectional data.This study aims to predict the(n,2n)reaction cross-section of long-lived fission products based on a tensor model.This tensor model is an extension of the collaborative filtering algorithm used for nuclear data.It is based on tensor decomposition and completion to predict(n,2n)reaction cross-sections;the corresponding EXFOR data are applied as training data.The reliability of the proposed tensor model was validated by comparing the calculations with data from EXFOR and different databases.Predictions were made for long-lived fission products such as^(60)Co,^(79)Se,^(93)Zr,^(107)P,^(126)Sn,and^(137)Cs,which provide a predicted energy range to effectively transmute long-lived fission products into shorter-lived or less radioactive isotopes.This method could be a powerful tool for completing(n,2n)reaction cross-sectional data and shows the possibility of selective transmutation of nuclear waste.

Tidal modeling based on satellite altimetry observations of TOPEX/ Poseidon, Jason1, Jason2, and Jason3 with high prediction capability: A case study of the Baltic Sea

This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.

24 Model在道路运输事故成因中的应用

为预防道路运输事故,基于事故致因“2-4”(24 Model)模型,对2015—2021年发生的215起道路运输事故的行为原因进行研究。从个人层面和组织层面分析导致事故发生的直接原因、间接原因、根本原因及其根源原因。结果表明:发生频次最多的不安全动作是驾驶员超速行驶(占10.67%);22.33%的道路运输事故存在管理者违章安排无资质员工上岗作业;管理者和领导者对57.67%的道路运输事故的发生有重要影响;由人为因素产生的不安全物态占比达71.53%;驾驶员、车辆安全生产管理制度欠缺或执行不到位在根本原因中尤为突出(占20.92%)。基于此,提出道路运输事故预防对策并构建出道路运输系统各因素关系图。

Hydrological Modelling of the Casamance River in Its Upstream Section (Basin at Kolda Level) to Predict Its Future States as a Function of Different Stresses

Flow records for stations in the Casamance basin are incomplete. Several gaps were noted over the 1980-2021 study period, making this study tedious. The aim of this study is to assess the potential impact of climate change on the flow of the Casamance watershed at Kolda. To this end, hydrological series are simulated and then extended using the GR2M rainfall-runoff model, with a monthly time step. Projected climate data are derived from a multi-model ensemble under scenarios SSP2-4.5 (scenario with additional radiative forcing of 4.5 W/m2 by 2099) and SSP5-8.5 (scenario with additional radiative forcing of 8.5 W/m2 by 2099). An analysis of the homogeneity of the rainfall data series from the Kolda station was carried out using KhronoStat software. The Casamance watershed was then delimited using ArcGIS to determine the morphometric parameters of the basin, which will be decisive for the rest of the work. Next, monthly evapotranspiration was calculated using the formula proposed by Oudin et al. This, together with rainfall and runoff, forms the input data for the model. The GR2M model was then calibrated and cross-validated using various simulations to assess its performance and robustness in the Casamance watershed. The version of the model with the calibrated parameters will make it possible to extend Casamance river flows to 2099. This simulation of future flows with GR2M shows a decrease in the flow of the Casamance at Kolda with the two scenarios SSP2-4.5 and SSP5-8.5 during the rainy period, and almost zero flows during the dry season from the period 2040-2059.