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Abstract Route choice modelling is a critical aspect of analysing urban rail transit (URT) networks and provides a foundation for URT planning and operation. Unlike in a free-flow road network, the consideration set for route choice decisions in a URT network does not depend purely on the physical connectivity of the network and decision makers’characteristics. Instead, it is also contingent on the train schedules. This paper delves into the evolution of research on route choices in URT networks, encompassing both probabilistic route choice modelling derived from utility maximisation theory and logit curve with physical connectivity, and retrospective route choice modelling based on travel time chaining along with comprehensive transport data. The former is noted for its conciseness, simplicity, and interpretability in real-world applications, even though the methodologies may not be cutting-edge. The latter incorporates dynamic temporal information to understand activities of passengers in URT networks. Enhancements of each genres are also examined. However, these improvements might not fully address the inherent limitations of models relating to a dependency on the quality of parameters, experience of experts, and calculation efficiency. In addition, novel research adopting contemporary data mining techniques instead of classical models are introduced. The historical development of research on URT network route choices underscores the importance of amalgamating independent information networks such as surveillance networks and social networks to establish a comprehensive multi-dimensional network. Such an approach integrates passenger attributes across networks, offering a multi-dimensional understanding of passengers’ route choice behaviours. Our review work aims to present not only a systematic conceptual framework for route choices in URT networks but also a novel path for transport researchers and practitioners to decipher the travel behaviours of passengers.

Near-Infrared (NIR) spectrometry has emerged as a promising tool for the non-destructive and rapid analysis of temperate fruit quality, maturity, and other parameters. The technique provides a wealth of information, including details of chemical composition, without damaging the fruit, making it a highly viable alternative to traditional methods. This paper reviews the recent research and applications of NIR spectrometry for fruit evaluation, highlighting its strengths and potential limitations. The analysis shows a significant potential for NIR spectrometry, especially when combined with machine learning and artificial intelligence to handle complex data and improve predictive models. The development of portable NIR spectrometers allows for in-situ quality assessment, expanding its applicability to various fields including on-site quality control. Despite the benefits, this review identifies key challenges including spectral complexity, fruit variability, and the influence of the external environment. Recommendations for future research include focusing on improving calibration and validation of models, increasing predictive accuracy, and developing user-friendly instruments. In addition, standardization of measurement procedures and analytical methods is needed to ensure comparability and reproducibility of results. Further research is needed to fully realize the full potential of NIR spectrometry in fruit quality control.

Using simulation models is a key strategy in agricultural water management and an effective way to predict the impact of irrigation management and water quality on crop yield. This study aimed to evaluate the performance of the SWAP and AquaCrop models in simulating the growth and biomass production of three maize varieties under the conditions of using saline water for irrigation with a drip irrigation system at the research farm of Tehran University of Agriculture and Natural Resources Campus. In order to calibrate and validate the models, field data obtained from a factorial experiment with two factors of maize variety (SC704, 400, and 260) and irrigation water salinity (0.7, 3, and 5 dS/m) were used. In the validation stage of the AquaCrop model, the R², RMSE, and NRMSE statistics for the canopy cover (CC) showed a high level of agreement between the measured and simulated data, with values of 0.953, 5.69, and 8% respectively. For the SWAP model, the calculated statistics for the leaf area index (LAI) were 0.477, 1.610, and 54.2%, respectively. Despite the poor performance of the SWAP model in estimating LAI, both the SWAP and AquaCrop models effectively simulated the biomass of maize cultivars under different treatments. In the calibration and validation stage, RMSE and NRMSE of both models were less than 0.5 ton/ha, with 3% (calibration) and 1 ton/ha, 7% (validation), respectively. In general, both models can be used in various studies for different maize cultivars under irrigation water and soil salinity conditions. [ABSTRACT FROM AUTHOR]

Route choice modelling is a critical aspect of analysing urban rail transit (URT) networks and provides a foundation for URT planning and operation. Unlike in a free-flow road network, the consideration set for route choice decisions in a URT network does not depend purely on the physical connectivity of the network and decision makers’characteristics. Instead, it is also contingent on the train schedules. This paper delves into the evolution of research on route choices in URT networks, encompassing both probabilistic route choice modelling derived from utility maximisation theory and logit curve with physical connectivity, and retrospective route choice modelling based on travel time chaining along with comprehensive transport data. The former is noted for its conciseness, simplicity, and interpretability in real-world applications, even though the methodologies may not be cutting-edge. The latter incorporates dynamic temporal information to understand activities of passengers in URT networks. Enhancements of each genres are also examined. However, these improvements might not fully address the inherent limitations of models relating to a dependency on the quality of parameters, experience of experts, and calculation efficiency. In addition, novel research adopting contemporary data mining techniques instead of classical models are introduced. The historical development of research on URT network route choices underscores the importance of amalgamating independent information networks such as surveillance networks and social networks to establish a comprehensive multi-dimensional network. Such an approach integrates passenger attributes across networks, offering a multi-dimensional understanding of passengers’ route choice behaviours. Our review work aims to present not only a systematic conceptual framework for route choices in URT networks but also a novel path for transport researchers and practitioners to decipher the travel behaviours of passengers. [ABSTRACT FROM AUTHOR]

This study examines the possible effects of climate change on sorghum in the western zone (WZ) comprising Coimbatore, Tirupur, and Erode districts of Tamil Nadu. The DSSAT crop simulation model was used to simulate sorghum yields with considering various planting dates and amounts of fertilizer application. The downscaled CCSM4 climate model data was utilized for the historical baseline period spanning from 1991 to 2020, as well as for future pridicted data from 2021 to 2099, under the RCP 4.5 scenarios. The key findings indicate that there is a projected yield decline range of -1.3% to -12.5% for the near century (2021-2040), -6.2% to -23.7% for the mid-century (2041-2070), and -12.6% to -30.5% for the end century (2071-2099). The sorghum yield experiences a high decrease at the end of the century (276.83 kg ha-1), mid-century (178.16 kg ha-1), and lastly in the near century (89.4 kg ha-1). The study revealed that a enhanced fertilizer application can have a minor positive effect on sorghum productivity. The study underscores the significant threat that climate change poses to food security in Tamil Nadu and emphasizes the need for adaptation strategies to protect agricultural productivity. [ABSTRACT FROM AUTHOR]

Abstract The DSSAT CANEGRO model was calibrated and verified using field experimental data from five Tamil Nadu Agroclimatic Zones (1981–2022). The genetic coefficients of the sugarcane cultivar (CO-86032) were calculated. R2 obtained between measured and simulated stalk fresh mass was 0.9 with the nRMSE (0.01) and RMSE (1.6) and R2 between measured and simulated sucrose mass was 0.9 with the nRMSE (0.16) and RMSE (1.2). For yield R2 obtained between measured and simulated was 0.9 with the nRMSE (0.01) and RMSE (1.6). As a result, the CANEGRO model may be used to mimic the phenology and yield features of the sugarcane cultivar in Tamil Nadu's Agro Climatic Zones. Temperature increases in Agro Climatic Zones resulted in varying yield reductions, with 2 °C increases causing a 3% loss, 3 °C increases 5%, and 4 °C increases 9%. The Water Requirement rose throughout all of the ACZ due to the high temperature, but to differing degrees. A 2 °C increase often results in an average 4% increase in the WR. 3 °C rise in temperature increased WR to 9% and WR rose by 13% when the temperature was raised by 4 °C.

In order to accomplish the calibration and validation (Cal/Val) of altimeters, the Wanshan calibration site (WSCS) has been used as a calibration site for satellite altimeters since its completion in August 2019. In this paper, we introduced the WSCS and the dedicated equipment including permanent GNSS reference stations (PGSs), acoustic tide gauges (ATGs), and dedicated GNSS buoys (DGB), etc. placed on Zhi'wan, Wai'ling'ding, Dan'gan, and Miao'Wan islands of the WSCS. The PGSs data of Zhi'wan and Wai'ling'ding islands were processed and analyzed using the GAMIT/GLOBK (Version 10.7) and Hector (Version 1.9) software to define the datum for Cal/Val of altimeters in WSCS. The DGB was used to transfer the datum from the PGSs to the ATGs of Zhi'wan, Wai'ling'ding, and Dan'gan islands. Separately, the tidal and mean sea surface (MSS) corrections are needed in the Cal/Val of altimeters. We evaluated the global/regional tide models of FES2014, HAMTIDE12, DTU16, NAO99jb, GOT4.10, and EOT20 using the three in situ tide gauge data of WSCS and Hong Kong tide gauge data (No. B329) derived from the Global Sea Level Observing System. The HAMTIDE12 tide model was chosen to be the most accurate one to maintain the tidal difference between the locations of the ATGs and the altimeter footprints. To establish the sea surface connections between the ATGs and the altimeter footprints, a GPS towing body and a highly accurate ship-based SSH measurement system (HASMS) were used to measure the sea surface of this area in 2018 and 2022, respectively. The global/regional mean sea surface (MSS) models of DTU 2021, EGM 2008 (mean dynamic topography minus by CLS_MDT_2018), and CLS2015 were accurately evaluated using the in situ measured data and HY-2A altimeter, and the CLS2015 MSS model was used for Cal/Val of altimeters in WSCS. The data collected by the equipment of WSCS, related auxiliary models mentioned above, and the sea level data of the hydrological station placed on Dan'gan island were used to accomplish the Cal/Val of HY-2B, HY-2C, Jason-3, and Sentinel-3A (S3A) altimeters. The bias of HY-2B (Pass No. 375) was −16.7 ± 45.2 mm, with a drift of 0.5 mm/year. The HY-2C biases were −18.9 ± 48.0 mm with drifts of 0.0 mm/year and −5.6 ± 49.3 mm with −0.3 mm/year drifts for Pass No. 170 and 185, respectively. The Jason-3 bias was −4.1 ± 78.7 mm for Pass No. 153 and −25.8 ± 85.5 mm for Pass No. 012 after it has changed its orbits since April 2022, respectively. The biases of S3A were determined to be −16.5 ± 46.3 mm with a drift of −0.6 mm/year and −9.8 ± 30.1 mm with a drift of 0.5 mm/year for Pass No. 260 and 309, respectively. The calibration results show that the WSCS can commercialize the satellite altimeter calibration. We also discussed the calibration potential for a wide swath satellite altimeter of WSCS. [ABSTRACT FROM AUTHOR]

In this work, we propose 2LevelCalibration, a multi-stage approach for the calibration of unknown parameters of agent-based models. First, we detail the aspects of agent-based models that make this task so cumbersome. Then, we conduct extensive research on common methods applied for this purpose in other domains, highlighting the strong points of each approach that could be explored to efficiently calibrate the parameters of agent-based models. Finally, we present a multi-stage method for this task, 2LevelCalibration, which benefits from the simplicity of equation-based models, used to faster explore a large set of possible combinations of parameters and to quickly select the more promising ones. These values are then analysed more carefully in the second step of our method, which performs the calibration of the agent-based model parameters' near the region of the search space that potentially contains the best set of parameters, previously identified in our method. This strategy outperformed traditional techniques when tested to calibrate the parameters of an agent-based model to replicate real-world observations of the housing market. With this testbed, we show that our method has highly desirable characteristics such as lightweight implementation and consistency, which are ideal for agent-based models' development process. [ABSTRACT FROM AUTHOR]

Taking advantage of vehicle-to-vehicle (V2V) communications, driving behavior will be impacted by information on preceding vehicles in communication range. In this work, a cooperative adaptive cruise control (CACC) model is proposed based on the traditional carfollowing model by introducing the speed and acceleration signals received from multiple preceding vehicles with less delay through V2V communication. With two-vehicle and platoon car-following sections from a trajectory data set, the parameters of the car-following model are calibrated, respectively. The stability analysis of the CACC model is conducted to explore the impact of preceding vehicles’ information. Then, the optimal parameter values of the CACC model and the CACC maximum platoon size are explored by the multiobjective influence analysis framework. The experiments and analysis indicate that (1) V2V communication and the increase in the number of connected vehicles help the traffic to be more stable; (2) the framework of the optimal value of model parameters can be obtained by considering the traffic safety, efficiency, and environmental impact; and (3) the optimized maximum platoon size can be determined by the trade-off among multiple objectives. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) are expected to have a significant impact on highways, but their planning horizon impacts have not been fully studied in the literature. This study seeks to address this gap by investigating the impact of AVs/CAVs at different stages of adoption on long-range transportation planning horizons in the United States. Planners use travel demand forecasts to make important and expensive transportation supply investment decisions, and this study uses oversaturated traffic data from the NGSIM database to estimate the parameters of the Wiedemann car-following model for a basic freeway. Using data from the European-funded Coexist Project, we construct AV/CAV scenarios that incorporate various mixes of AV/CAV technologies, including cautious driving behavior (AV-Cautious) and more aggressive driving behavior (AV All-Knowing), and span multiple planning horizon planning years. Our findings suggest that the capacity impact of AVs will change based on their penetration in the vehicle fleet. For medium-term planning horizons, AVs will reduce capacities, whereas for long-term planning horizons and the buildout, capacities will be positively impacted. However, the impact of AVs/CAVs on highway capacity is subject to two main limitations, including the assumptions made in this study about the behavior of AVs/CAVs and the lack of consideration for AVs/CAVs in oversaturated traffic in previous literature. Future studies could explore these limitations in more detail and consider other factors, such as the impact of AVs/CAVs on travel demand and the potential for AVs/CAVs to affect mode share. Overall, this research provides valuable information for transportation planners and decision-makers to consider as they develop medium and long-term transportation plans and make informed decisions about the impact of AVs/CAVs.

In order to accomplish the calibration and validation (Cal/Val) of altimeters, the Wanshan calibration site (WSCS) has been used as a calibration site for satellite altimeters since its completion in August 2019. In this paper, we introduced the WSCS and the dedicated equipment including permanent GNSS reference stations (PGSs), acoustic tide gauges (ATGs), and dedicated GNSS buoys (DGB), etc. placed on Zhi’wan, Wai’ling’ding, Dan’gan, and Miao’Wan islands of the WSCS. The PGSs data of Zhi’wan and Wai’ling’ding islands were processed and analyzed using the GAMIT/GLOBK (Version 10.7) and Hector (Version 1.9) software to define the datum for Cal/Val of altimeters in WSCS. The DGB was used to transfer the datum from the PGSs to the ATGs of Zhi’wan, Wai’ling’ding, and Dan’gan islands. Separately, the tidal and mean sea surface (MSS) corrections are needed in the Cal/Val of altimeters. We evaluated the global/regional tide models of FES2014, HAMTIDE12, DTU16, NAO99jb, GOT4.10, and EOT20 using the three in situ tide gauge data of WSCS and Hong Kong tide gauge data (No. B329) derived from the Global Sea Level Observing System. The HAMTIDE12 tide model was chosen to be the most accurate one to maintain the tidal difference between the locations of the ATGs and the altimeter footprints. To establish the sea surface connections between the ATGs and the altimeter footprints, a GPS towing body and a highly accurate ship-based SSH measurement system (HASMS) were used to measure the sea surface of this area in 2018 and 2022, respectively. The global/regional mean sea surface (MSS) models of DTU 2021, EGM 2008 (mean dynamic topography minus by CLS_MDT_2018), and CLS2015 were accurately evaluated using the in situ measured data and HY-2A altimeter, and the CLS2015 MSS model was used for Cal/Val of altimeters in WSCS. The data collected by the equipment of WSCS, related auxiliary models mentioned above, and the sea level data of the hydrological station placed on Dan’gan island were used to accomplish the Cal/Val of HY-2B, HY-2C, Jason-3, and Sentinel-3A (S3A) altimeters. The bias of HY-2B (Pass No. 375) was −16.7 ± 45.2 mm, with a drift of 0.5 mm/year. The HY-2C biases were −18.9 ± 48.0 mm with drifts of 0.0 mm/year and −5.6 ± 49.3 mm with −0.3 mm/year drifts for Pass No. 170 and 185, respectively. The Jason-3 bias was −4.1 ± 78.7 mm for Pass No. 153 and −25.8 ± 85.5 mm for Pass No. 012 after it has changed its orbits since April 2022, respectively. The biases of S3A were determined to be −16.5 ± 46.3 mm with a drift of −0.6 mm/year and −9.8 ± 30.1 mm with a drift of 0.5 mm/year for Pass No. 260 and 309, respectively. The calibration results show that the WSCS can commercialize the satellite altimeter calibration. We also discussed the calibration potential for a wide swath satellite altimeter of WSCS.

In this paper, we investigated the vertical distribution characteristics of surface soil moisture based on ISMN (International Soil Moisture Network) multilayer in situ data (5, 10, and 20 cm; 2, 4, and 8 in) and performed comparisons between the in situ data and four microwave satellite remote sensing products (SMOS L2, SMOS-IC, SMAP L2, and SMAP L4). The results showed that the mean soil moisture difference between layers can be −0.042~−0.024 (for the centimeter group)/−0.067~−0.044 (for the inch group) m3/m3 in negative terms and 0.020~0.028 (for the centimeter group)/0.036~0.040 (for the inch group) m3/m3 in positive terms. The surface soil moisture was found to have very significant stratification characteristics, and the interlayer difference was close to or beyond the SMOS and SMAP 0.04 m3/m3 nominal retrieval accuracy. Comparisons revealed that the satellite retrievals had a higher correlation with the field measurements of 5 cm/2 in, and SMAP L4 had the smallest difference with the in situ data. The mean difference caused by using 10 cm/4 in and 20 cm/8 in in situ data instead of the 5 cm/2 in data could be about −0.019~−0.018/−0.18~−0.015 m3/m3 and −0.026~−0.023/−0.043~−0.039 m3/m3, respectively, meaning that there would be a potential depth mismatch in the data validation. [ABSTRACT FROM AUTHOR]

Autonomous vehicles (AVs) and connected autonomous vehicles (CAVs) are expected to have a significant impact on highways, but their planning horizon impacts have not been fully studied in the literature. This study seeks to address this gap by investigating the impact of AVs/CAVs at different stages of adoption on long-range transportation planning horizons in the United States. Planners use travel demand forecasts to make important and expensive transportation supply investment decisions, and this study uses oversaturated traffic data from the NGSIM database to estimate the parameters of the Wiedemann car-following model for a basic freeway. Using data from the European-funded Coexist Project, we construct AV/CAV scenarios that incorporate various mixes of AV/CAV technologies, including cautious driving behavior (AV-Cautious) and more aggressive driving behavior (AV All-Knowing), and span multiple planning horizon planning years. Our findings suggest that the capacity impact of AVs will change based on their penetration in the vehicle fleet. For medium-term planning horizons, AVs will reduce capacities, whereas for long-term planning horizons and the buildout, capacities will be positively impacted. However, the impact of AVs/CAVs on highway capacity is subject to two main limitations, including the assumptions made in this study about the behavior of AVs/CAVs and the lack of consideration for AVs/CAVs in oversaturated traffic in previous literature. Future studies could explore these limitations in more detail and consider other factors, such as the impact of AVs/CAVs on travel demand and the potential for AVs/CAVs to affect mode share. Overall, this research provides valuable information for transportation planners and decision-makers to consider as they develop medium and long-term transportation plans and make informed decisions about the impact of AVs/CAVs. [ABSTRACT FROM AUTHOR]

An original mathematical model describing the photo fermentation process is proposed. The model represents the first attempt to describe the photo fermentative hydrogen production and polyhydroxybutyrate accumulation, simultaneously. The mathematical model is derived from mass balance principles and consists of a system of ordinary differential equations describing the biomass growth, the nitrogen and the substrate degradation, the hydrogen and other catabolites production, and the polyhydroxybutyrate accumulation in photo fermentation systems. Moreover, the model takes into account important inhibiting phenomena, such as the self-shading and the substrate inhibition, which can occur during the evolution of the process. The calibration was performed using a real experimental data set and it was supported by the results of a sensitivity analysis study. The results showed that the most sensitive parameters for both hydrogen and PHB production were the hydrogen yield on substrate, the catabolites yield on substrate, and the biomass yield. Successively, a different experimental data set was used to validate the model. Performance indicators showed that the model could efficiently be used to simulate the photo fermentative hydrogen and polyhydroxybutyrate production by Rhodopseudomonas palustris. For instance, the index of agreement of 0.95 was observed for the validated hydrogen production trend. Moreover, the model well predicted the maximum PHB accumulation in bacterial cells. Indeed, the predicted and observed accumulated PHB were 4.5 and 4.8%, respectively. Further numerical simulations demonstrated the model consistency in describing process inhibiting phenomena. Numerical simulations showed that the acetate and nitrogen inhibition phenomena take place when concentrations are higher than 12.44 g L-1 and lower than 4.76 mg L-1, respectively. Finally, the potential long term hydrogen production from accumulated polyhydroxybutyrate in bacterial cells was studied via a fast-slow analysis technique.

This study calibrated a refined split-window algorithm for land surface temperature (LST) retrieval based on Fengyun-2D (FY-2D) meteorological satellite. First, FY-2D land surface emissivity (LSE) was predicted from Moderate-resolution Imaging Spectroradiometer (MODIS) LSE based on sensors spectral similarities. The retrieved FY-2D LST data were validated in an arid region where the traditional split-window algorithm generally performed unsatisfactorily. Validation results show R2 (coefficient of determination) and RMSE (root mean square error) values range 0.53–0.67 and 2.86–6.21 K, respectively, against ground observed LST. Better LST retrievals were observed over vegetated regions with an RMSE value of ~2.8 K. Spatially, the FY-2D LST was highly correlated (R2 = 0.83) with and showed marginal differences (±2 K) from MODIS LST for ~40% of the whole area.

Abstract Introduction: Rainfall-runoff modeling is considered one of the important methods in the study of hydrology and environmental management, especially in urban areas, in which sudden floods lead to significant financial and human losses. Thereupon, various models have been developed for urban flood simulation, among which selecting the best, is of significant consideration in the literature. Methods: Runoff peak flow and hydroghs measured in three nodes of an urban drainage network were applied for both spatial and temporal evaluation of the SWMM hydrological model in EPA SWMM, ASSA and Bently SewerGEMS V8i softwares. Other rainfall-runoff models also evaluated were SCS TR-55, SCS TR-20, Rational, Dekalb Rational, Santabarbara UH models (in ASSA software) and SCS UH model (in SewerGEMS V8i software). The models were calibrated considering the measurements during three precipitation events, and then validated by the measured data of three other events. The Nash-Sutcliffe coefficient along with the BIAS coefficient, the Coefficient of Determination and the Root Mean Square Error were used as the efficiency indicators. Findings: The measured runoff peak flow and hydrograph were most compatible with those simulated by SWMM models of EPA SWMM, SewerGEMS V8i and ASSA softwares, respectively. Regarding the results of the partial parameter and the Spearman correlation coefficient methods, model outputs were most sensitive to the percentage of impervious areas, equivalent width, roughness coefficient of impervious areas, the depth of depression of impervious and pervious areas, the percentage of impervious areas without surface storage and the curve number, respectively. The model was not sensitive to the roughness of the permeable areas. The results suggest EPA SWMM as the software with more reliable simulation results for runoff management projects in the study area and urban basins alike.

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Car-following models serve an important role in gaining a thorough understanding of traffic flow and driving behavior characteristics. By analyzing these characteristics, the models are critical to microscopic traffc simulation, and consequently, to traffic safety. However, lack of reliable traffic data in China has, until recently, limited the use of car-following models. As the Shanghai Naturalistic Driving Study (SH-NDS) has now made such data accessible, car-following models have been built for freeways and urban expressways, but none have yet been developed for urban streets. To compare car following for the three road types and to determine the best model for urban streets, five commonly used car-following models were calibrated and validated with 5,500 urban street-level carfollowing events extracted from the 161,055 km of data collected in the SH-NDS. The models were evaluated based on their parameter estimates and root mean square percentage errors (RMSPE). Results show that (1) the intelligent driver model (IDM), with a calibration error of 24% and a validation error of 28%, performed best in modeling drivers' car-following behavior on urban Shanghai streets; and (2) in comparison to previous car-following research on Chinese freeways and urban expressways, drivers on urban streets tend to assume a relatively lower car-following speed, and maintain slightly larger time headway and maximum acceleration. Because the IDM demonstrated great performance on expressways, freeways, and urban streets in China, it is reasonable to assume the model may show similar performance when used to analyze car following in other countries. [ABSTRACT FROM AUTHOR]

Externally bonded (EB) and near-surface mounted (NSM) bonding are two widely adopted and researched strengthening methods for reinforced-concrete structures. EB composite substrates are easy to reach and repair using appropriate surface treatments, whereas NSM techniques can be easily applied to the soffit and concrete member sides. The EB bonded fiber-reinforced polymer (FRP) technique has a significant drawback: combustibility, which calls for external protective agents, and textile reinforced mortar (TRM), a class of EB composites that is non-combustible and provides a similar functionality to any EB FRP-strengthened substrate. This study employs a finite element analysis technique to investigate the failing failure of carbon textile reinforced mortar (CTRM)-strengthened reinforced concrete beams. The principal objective of this numerical study was to develop a finite element model and validate a set of experimental data in existing literature. A set of seven beams was modelled and calibrated to obtain concrete damage plasticity (CDP) parameters. The predicted results, which were in the form of load versus deflection, load versus rebar strain, tensile damage, and compressive damage patterns, were in good agreement with the experimental data. Moreover, a parametric study was conducted to verify the applicability of the numerical model and study various influencing factors such as the concrete strength, internal reinforcement, textile roving spacing, and externally-applied load span. The ultimate load and deflection of the predicted finite element results had a coefficient of variation (COV) of 6.02% and 5.7%, respectively. A strain-based numerical comparison with known methods was then conducted to investigate the debonding mechanism. The developed finite element model can be applied and tailored further to explore similar TRM-strengthened beams undergoing debonding, and the preventive measures can be sought to avoid premature debonding. [ABSTRACT FROM AUTHOR]

The combination of multiple imaging modalities in a single microscopy system can enable new insights into biological processes. In this work, we describe the construction and rigorous characterization of a custom microscope with multimodal imaging in a single, cost-effective system. Our design utilizes advances in LED technology, robotics, and open-source software, along with existing optical components and precision optomechanical parts to offer a modular and versatile design. This microscope is operated using software written in Arduino and Python and has the ability to run multi-day automated imaging experiments when placed inside of a cell culture incubator. Additionally, we provide and demonstrate methods to validate images taken in brightfield and darkfield, along with validation and optimization for differential phase contrast (DPC) quantitative phase imaging.

Free piston engine generator is an effective alternative to conventional range extender, which is able to facilitate the transportation sector decarbonization attributed to its high thermal efficiency and ultimate fuel flexibility. However, due to the lack of crankshaft mechanism, stable and robust operation of free piston engine generator is difficult to achieve since various disturbances may exist during its operation. In this paper, a combustion stability control based on active disturbance rejection control algorithm was proposed for a single piston free piston engine generator. To develop this control, a thermodynamic model of the free piston engine generator system was calibrated and validated through experimental data. Afterward, a 2nd order active disturbance rejection control based speed control was developed by leveraging the developed free piston engine generator model. The proposed active disturbance rejection control was employed into multiple abnormal combustion scenarios through a simulation, including various fuel heat released, ignition positions and burn durations, aimed to verify the control ability of rejecting disturbances and enhancing the robustness of the free piston engine generator operation. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of two hydrological models in the Storm Water Management Model (SWMM) software, namely, the non-linear reservoir (N-LR) and the unit hydrograph (UH), on the urban catchment of Cascina Scala, Pavia in Italy. The two models were applied for the simulation of the rainfall-runoff transformation in the 42 sub-catchments in Cascina Scala, while flow routing in the underground channels was simulated by means of the De Saint-Venant equations. A dataset of rainfall and runoff for 14 events from 2000 to 2003 was adopted for the calibration and validation of the models. The calibration was performed on 7 out of the 14 events by maximizing the fit of modeled-to-measured hydrographs in the final channel of the system. Prediction performance was assessed through different indices. Results from both models fit measured data well in terms of the total hydrograph. Whereas the time to peak was reliably predicted by both models, the N-LR was found to slightly outperform the UH in terms of total volume and peak flow prediction, though it requires a more detailed knowledge of the system for its implementation. Accordingly, the UH must be preferred in the case of a scarcity of data. [ABSTRACT FROM AUTHOR]

In arid and semi-arid areas, assessing the potential impact of climate change on water availability is of critical importance for achieving better management of future water resources. Iraq as one example of those areas is expected to experience more stress on water due to the climatological characteristics and to the rapid population growth in addition to the policy of the riparian upstream countries. Therefore, the present study aims to quantify the impacts of climate change on the Khabour River catchment north of Iraq, which is one of the riparian catchments between Iraq and Turkey. The HEC-HMS model was firstly calibrated and validated against daily streamflow data measured for the period 01Jan2004-30Jun2009 near the catchment outlet at Zakho station. Thereafter, the future climate changes data from the HadGEM2_ES model was fed into the calibrated HEC-HMS model to quantify the future water resources availability. The impacts of climate change on the water under four possible scenarios of RCPs (RCP2.6, RCP4.5, RCP6, and RCP8.5) of atmospheric greenhouse gas (GHG) concentrations for three future slice periods (2021-2030), (2041-2050), and (2061-2070); was assessed in attribution to that from the period (2000-2009). Results show that the implemented HEC-HMS model was superior in modeling the streamflow data. NSE, R² and RMSE value was 0.871, 0.89 and 26.7, respectively, for calibration and 0.936, 0.9364 and 18.0, respectively for validation. The results also suggest that annual river runoff will likely decrease under all scenarios of RCPs and time stages of the future period.

• The applicability of InVEST urban cooling model in coastal areas was assessed. • Model calibration and validation were performed considering seawater effects. • Various methods were suggested to improve the model accuracy in the coastal city. • The sensitivities of the heat mitigation index in the region are important factors. Measures are needed to alleviate the urban heat island (UHI) problem, which has become increasingly severe due to recent climate change. The InVEST urban cooling model (UCM) estimates the heat mitigation capacity of cities based on land use, weather, and biophysical data. This study evaluated the applicability of InVEST UCM to coastal areas, which was mainly applied to inland areas. Sensitivity analysis, model calibration, and reclassification of land use and land cover maps were also conducted to increase the model's accuracy. Using linear regression analysis between the heat mitigation index and surface temperature, the results showed that sensitivity analysis and model calibration could improve the accuracy. The model validation results demonstrated that the InVEST UCM could be used reliably in coastal areas. The verified model, whose reliability has been secured through the calibration and validation processes, can help select regions where heat mitigation methods should be introduced. The results showed that heat mitigation measures such as nature-based solutions should be introduced preferentially in areas with high Heat Mitigation Index (HMI) sensitivity to crop coefficient (K c) and low average HMI values or high HMI sensitivity and large K c to HMI ratios. These areas include mixed, seaport, commercial & business, and industrial. [ABSTRACT FROM AUTHOR]

Study region: China Study focus: This study focuses on the continental-scale spatiotemporal calibration of the Blaney–Criddle equation (BC) for different climate zones in China. Daily meteorological data from 82 weather stations in China were collected for the periods of 1970–2004 and 2005–2014, respectively, to calibrate and validate the BC model. The coefficients of the BC model were spatially and temporally calibrated in different climate types via a linear regression method. New hydrological insights for the region: (1) Performance of the quarterly calibrated BC model was the most satisfactory. Statistical indices were in the range of 0.449–0.797 mm d−1 for the mean absolute error, 0.567–0.969 mm d−1 for the root mean square error and 0.82–0.953 for the index of agreement. The accuracy ranges increased from 42.95–96.56 % to 87.18–98.74 %; (2) Correction coefficient b and a for every quarter was mapped. Value of b showed a bell-shaped consist with temperature, while a showed an opposite trend. The quarterly calibrated BC model provided satisfactory results in the temperate monsoon and temperate continental climate zones; and (3) results indicated maximum temperature was the most influential factor for reference evapotranspiration (ET0), followed by minimum temperature. This study provides a more accurate BC model to calculate ET0 for different climate types in China and a reference for agricultural decision-makers in irrigation areas that lack sufficient meteorological data.

The capacity analysis under mixed traffic flow conditions considers a dynamic problem. Traffic microsimulation models have been a very effective tool for such problem. Calibration and validation of microsimulation models are essential steps to ensure the reliability of the models. This paper suggests the use of measurable variables for calibrating micro-simulation models. Therefore, the objective of this paper is to estimate the roadway capacity through micro-simulation models calibrated using spot speed distributions. The micro-simulation software VISSIM was used to model and analyze the two-lane and multi-lane roads. The models were calibrated and validated using the data collected in Menoufia Governorate, Egypt. The K-S test was performed to ensure that simulated speed distributions matched the observed distributions. It was found that the models were successfully calibrated and validated. Finally, roadway capacity was estimated based on field data and micro-simulation models through the flow rate-density relationship. The results showed a good match between the field and simulated capacity. [ABSTRACT FROM AUTHOR]

In order to estimate the adaptability of Agricultural Production Systems Simulator (APSIM)-Maize model under the special climate environment in tropic, 10 field experiments were conducted at different seasons in three sites (Longchuan, Mangshi and Ruili) of tropic in Yunnan Province, China. The parameters of APSIM model were calibrated and its adaptability was validated. The results showed that the days from sowing to flowering and sowing to maturity were predicted accurately for all sites with mean errors of 2.0 ± 0.4, and 3.2 ± 0.7 d respectively. The normalized root mean square errors (NRMSE) of the model for yield prediction were 2%, 3% and 5% for each of three sites, respectively, which indicated that the APSIM model had good accuracy and sensitivity in predicting phenological phases and yield of maize (Zea mays L.) grown in different seasons, and the model had good adaptability in the tropic of Southwest China. This study provided the basis and technical support for evaluating maize production potential based on the model. [ABSTRACT FROM AUTHOR]

The China Seismo-Electromagnetic Satellite (CSES-01) provides in situ electron density (Ne) observations through Langmuir probes (LPs) in the topside ionosphere since February 2018. CSES-01 is a sun-synchronous satellite probing the ionosphere around two fixed local times (LTs), 14 LT in the daytime sector and 02 LT in the night-time sector, at an altitude of about 500 km. Previous studies evidenced that CSES-01 seems to underestimate Ne measurements with respect to those acquired by similar satellites or obtained from different instruments. To overcome this issue, we calibrated CSES-01 LP Ne observations through Swarm B satellite data, which flies approximately at CSES-01 altitude. As a first step, Swarm B LP Ne observations were calibrated through Faceplate (FP) Ne observations from the same satellite. Such calibration allowed solving the Ne overestimation made by Swarm LP during nighttime for low solar activity. Then, the calibrated Swarm B LP Ne observations were used to calibrate CSES-01 Ne observations on a statistical basis. Finally, the goodness of the proposed calibration procedure was statistically assessed through a comparison with Ne observations by incoherent scatter radars (ISRs) located at Jicamarca, Arecibo, and Millstone Hill. The proposed calibration procedure allowed solving the CSES-01 Ne underestimation issue for both daytime and nighttime sectors and brought CSES-01 Ne observations in agreement with corresponding ones measured by Swarm B, ISRs, and with those modelled by the International Reference Ionosphere (IRI). This is a first fundamental step towards a possible future inclusion of CSES-01 Ne observations in the dataset underlying IRI for the purpose of improving the description of the topside ionosphere made by IRI. [ABSTRACT FROM AUTHOR]

In this paper, we investigated the vertical distribution characteristics of surface soil moisture based on ISMN (International Soil Moisture Network) multilayer in situ data (5, 10, and 20 cm; 2, 4, and 8 in) and performed comparisons between the in situ data and four microwave satellite remote sensing products (SMOS L2, SMOS-IC, SMAP L2, and SMAP L4). The results showed that the mean soil moisture difference between layers can be −0.042~−0.024 (for the centimeter group)/−0.067~−0.044 (for the inch group) m3/m3 in negative terms and 0.020~0.028 (for the centimeter group)/0.036~0.040 (for the inch group) m3/m3 in positive terms. The surface soil moisture was found to have very significant stratification characteristics, and the interlayer difference was close to or beyond the SMOS and SMAP 0.04 m3/m3 nominal retrieval accuracy. Comparisons revealed that the satellite retrievals had a higher correlation with the field measurements of 5 cm/2 in, and SMAP L4 had the smallest difference with the in situ data. The mean difference caused by using 10 cm/4 in and 20 cm/8 in in situ data instead of the 5 cm/2 in data could be about −0.019~−0.018/−0.18~−0.015 m3/m3 and −0.026~−0.023/−0.043~−0.039 m3/m3, respectively, meaning that there would be a potential depth mismatch in the data validation.

Climate change, as well as increasing urbanization, lead to an increase in urban flooding events around the world. Accurate urban flood models are an established tool to predict flooding areas in urban as well as peri-urban catchments, to derive suitable measures to increase resilience against urban flooding. The high computational cost and complex processes of urban flooding with numerous subprocesses are the reason why many studies ignore the discussion of model uncertainties as well as model calibration and validation. In addition, the influence of steep surface (hillside) conditions on calibration parameters such as surface roughness are frequently left out of consideration. This study applies a variance-based approach to analyze the impact of three uncertainty sources on the two variables—flow and water depth—in a steep peri-urban catchment: (i) impact of DEM validation; (ii) calibration of the model parameter; (iii) differences between 1D/2D and 2D models. The results demonstrate the importance of optimizing sensitive model parameters, especially surface roughness, in steep catchments. Additional findings of this work indicate that the sewer system cannot be disregarded in the context of urban flood modeling. Further research with real heavy storm events is to be pursued to confirm the main results of this study. [ABSTRACT FROM AUTHOR]

Iraq is one of the Middle East countries that suffer from water scarcity. In addition to the water policy of the upstream riparian countries; rapid population increase, economic growth, and climate changes are the major stressors of water resources available for domestic and agricultural sectors in this country. Therefore, it is of importance to determine the optimal water management methodology. This study aims to identify the optimal water allocation among the domestic, agricultural, and industrial sectors of Baghdad city under present and potential future scenarios. As such, the WEAP model was used to assess and analyze the current and projected balance of water resource management. The model was firstly calibrated and validated using the monthly streamflow data at Sarai station on the Tigris River. Subsequently, the calibrated model was fed with different future scenarios over the period 2020-2040. The employed future scenarios included normal growth population rate (I), high growth population rate (II), halved river discharges (III), combined scenario of the high population with halved water flow (ΙV) and the simulated future water year type scenario (V). Results proved that the WEAP model satisfactorily modeled the water supply/demand in Baghdad with R2 and Pbias of 0.73 and 2.43%, respectively during the validation period. Also, it was found that the water demand and supply were unmet under all proposed future scenarios which implies that there is a swift need for sustainable water management in Iraq and in Baghdad.

Calibrating microscopic traffic simulation models is a prerequisite for simulation applications. This study proposes three novel methods to improve the accuracy and interpretability of the calibration model. The proposed approach involves selecting the calibration parameter, refining the model parameter system, and optimizing the calibration results. The first method expands the single-point mean into a multi-point distribution. The cumulative distribution curve of delay was selected as the calibration parameter. The second method divides the parameter system into global and local parameters. Global parameters were calibrated using NGSIM measured data, and local parameters were calibrated through intelligent algorithms. The third method proposes a methodology of parameter clustering recursion based on the genetic algorithm results, with information entropy selected as the analysis index. To evaluate the effectiveness of the proposed optimization methods, this study used NGSIM trajectory data as a case study. Eight simulation schemes based on the three optimization methods were designed, and simulation experiments were conducted using the VISSIM platform. The results show that the accuracy of the multi-point distribution calibration and parameter value optimization method is significantly higher than the default method. Additionally, the optimization method with calibration of both global and local parameters was more consistent with actual driving characteristics. This study provides a theoretical foundation for improving the practical application of traffic simulation technology, which has significant implications for transportation planning and management. [ABSTRACT FROM AUTHOR]

The geodetic Corsica site was set up in 1998 in order to perform altimeter calibration of the TOPEX/Poseidon (T/P) mission and subsequently, Jason-1, OSTM/Jason-2, Jason-3 and more recently Sentinel-6 Michael Freilich (launched on November, 21 2020). The aim of the present study held in June 2015 is to validate a recently developed GNSS-based sea level instrument (called CalNaGeo) that is designed with the intention to map Sea Surface Heights (SSH) over large areas. This has been undertaken using the well-defined geodetic infrastructure deployed at Senetosa Cape, and involved the estimation of the stability of the waterline (and thus the instantaneous separation of a GNSS antenna from water level) as a function of the velocity at which the instrument is towed. The results show a largely linear relationship which is approximately 1 mm/(m/s) up to a maximum practical towing speed of ∼10 knots (∼5 m/s). By comparing to the existing "geoid" map, it is also demonstrated that CalNaGeo can measure a sea surface slope with a precision better than 1 mm/km (∼2.5% of the physical slope). Different processing techniques are used and compared including GNSS Precise Point Positioning (PPP, where the goal is to extend SSH mapping far from coastal GNSS reference stations) showing an agreement at the 1-2 cm level. [ABSTRACT FROM AUTHOR]

Particulate volume scattering function (VSF), especially at angles larger than 170°, is of particular importance for interpreting ocean optical remote sensing signals and underwater imagery. In this study, a laboratory-based VSF instrument (VSFlab) adopting the periscopic optical system was developed to obtain VSF measurements from 1°–178.5°. In the VSFlab, a new prism design that simply combines a single prism and a neutral density filter was proposed to more efficiently reduce the stray light in the backward direction, while a detailed calibration procedure was given. A full validation based on standard beads of various sizes and a comparison with the results from LISST-VSF and POLVSM indicated that the VSFlab can provide reliable results from 1° to 178.5°. VSFlab measurements in the East China Sea (ECS) exhibited a moderate increase (not more than 5 times) in VSF from 170° to 178.5° rather than a sharp increase of more than one order of magnitude presented in other instrument results measured in other coastal regions. The estimates of the particulate backscattering coefficient using single angle scattering measurements near 120° or 140° and suitable χp were justified. Two types of the VSFs with different size distribution and shape parameters in the ECS can be distinguished based on the variability of χp after 155°. The measured VSF could provide a basis for the parameterization of VSF in the radiative transfer model and the variability of χp in the backward direction had the potential to be used to characterize the particles in the coastal region of the ECS. [ABSTRACT FROM AUTHOR]

Altimetry is widely used in the research of oceanic phenomena. Particularly, wide-swath interferometric altimetry (WIA) can be used to measure sea surface height (SSH) with sufficiently high resolution. Although it has provided that the steric height can be used to validate the SSH by the theoretical and the observation data, validating sea-level variability in the two dimensions of WIA remains a difficult task. Site selection and influencing factor analysis are important in the validation process. In this paper, we analyze the validation process at three sites (Panyu site, DJxxxx site, and Wanshan site) in the South China Sea and discuss the effects of different sites on the validation of SSH variability. On this basis, we analyze the influencing factors, which include significant wave heights, wind, and currents, at three sites. Based on the results, we discuss how site selection for the validation process of WIA can be improved. At DJxxxx site, greater water depth and more equipment layout schemes have emerged with better performance in wavenumber. At the same time, the performance under the tidal, wave, wind and current is different for the other two sites. However, further analysis is necessary for the site selection. [ABSTRACT FROM AUTHOR]

This paper presents a comparative analysis of two hydrological models in the Storm Water Management Model (SWMM) software, namely, the non-linear reservoir (N-LR) and the unit hydrograph (UH), on the urban catchment of Cascina Scala, Pavia in Italy. The two models were applied for the simulation of the rainfall-runoff transformation in the 42 sub-catchments in Cascina Scala, while flow routing in the underground channels was simulated by means of the De Saint-Venant equations. A dataset of rainfall and runoff for 14 events from 2000 to 2003 was adopted for the calibration and validation of the models. The calibration was performed on 7 out of the 14 events by maximizing the fit of modeled-to-measured hydrographs in the final channel of the system. Prediction performance was assessed through different indices. Results from both models fit measured data well in terms of the total hydrograph. Whereas the time to peak was reliably predicted by both models, the N-LR was found to slightly outperform the UH in terms of total volume and peak flow prediction, though it requires a more detailed knowledge of the system for its implementation. Accordingly, the UH must be preferred in the case of a scarcity of data.

Ion temperature is one of the key parameters that provides insight into the thermal balance of the coupled ionosphere‐thermosphere system. Together with the temperatures of neutral and electron gases, it affects physical and chemical processes and parameters in the upper atmosphere. These include the ion‐neutral collision frequencies, chemical reaction rates and plasma scale height, all of which influence the variation and distribution of ionospheric plasma. The European Space Agency's three, nearly polar‐orbiting Swarm satellites at about 500 km altitude measure ionospheric electron temperature, density, and ion drifts using electric field instrument (EFI) Langmuir probes and Thermal Ion Imagers. Measurements of the ion temperature, though initially planned, are not available due to technical problems with the ion imagers. This paper describes a model that estimates the ion temperature along the orbits of Swarm satellites and evaluates the validity of the corresponding data. This data‐driven, physics‐based model combines an ion heat balance equation of the upper ionosphere, the Swarm EFI measurements, and empirical models for neutral composition, winds, and electric field. The validity of this approach was investigated using a physics‐based ionosphere model (SAMI3) for different geophysical conditions. We have studied the effects of various assumptions and input data limitations to the model accuracy, and have validated the estimated ion temperature against independent measurements from low, middle, and high‐latitude incoherent scatter radars (ISRs). When compared with the ISR data, the obtained Swarm‐based ion temperature shows small systematic errors (1%–2%), high correlations (Swarm A/C 0.8, Swarm B 0.6), and random errors of 10%–20%. Key Points: A physics‐based, data‐driven model of the ionospheric ion temperature is developedThe model estimates ion temperature along the orbits of Swarm satellites in the upper ionosphere at around 500 kmThe estimated ion temperature agrees well with independent observations made by incoherent scatter radars [ABSTRACT FROM AUTHOR]

The Upper Indus Basin has a large concentration of glaciers and mainly fed by snow and glacier melt. These melt runoffs are the primary driver of discharge and significantly contribute to Indus flows. Therefore, the present study was undertaken in the Upper Indus Basin (UIB) up to the Besham Quila site. This study focuses on quantifying runoff's contribution from different sources, including snow and glacier melt, and evaluates model performance in the glacierized Himalayan basin. The model was calibrated (1981–2000) and validated (2001–2007) daily and monthly using 27 years of measured discharge data at the Besham Quila station. A statistical indicator shows a "good" relationship between simulated and observed discharge on a daily and "very good" on a monthly timestamp. In this study, the annual contribution from snow/ice melt in the basin was quantified and found to be 51% of the total runoff. Apart from this, around 30% of water comes from direct runoff generated through liquid precipitation and 3.8% from groundwater. The remaining (~15%) is contributed by interflows sourced from the rainfall and snow/ice melt. The basin receives 61% contribution from snow and glacier melt during monsoon (July–Sept) and 38% during summer (April–June) seasons, while negligible in other seasons. A decreasing trend is observed in modelled total runoff and melt runoff of about 1.11 × 109 m3 a−1 and 0.73 × 109 m3 a−1, respectively. [ABSTRACT FROM AUTHOR]

This paper presents an integrated approach to simulate flooding and inundation for small- and medium-sized coastal river basins where measured data are not available or scarce. By coupling the rainfall–runoff model, the one-dimensional and two-dimensional models, and the integration of these with global tide model, satellite precipitation products, and synthetic aperture radar imageries, a comprehensive flood modeling system for Tra Bong river basin selected as a case study was set up and operated. Particularly, in this study, the lumped conceptual model was transformed into the semi-distributed model to increase the parameter sets of donor basins for applying the physical similarity approach. The temporal downscaling technique was applied to disaggregate daily rainfall data using satellite-based precipitation products. To select an appropriate satellite-derived rainfall product, two high temporal-spatial resolution products (0.1 × 0.1 degrees and 1 h) including GSMaP_GNRT6 and CMORPH_CRT were examined at 1-day and 1-h resolutions by comparing with ground-measured rainfall. The CMORPH_CRT product showed better performance in terms of statistical errors such as Correlation Coefficient, Probability of Detection, False Alarm Ratio, and Critical Success Index. Land cover/land use, flood extent, and flood depths derived from Sentinel-1A imageries and a digital elevation model were employed to determine the surface roughness and validate the flood modeling. The results obtained from the modeling system were found to be in good agreement with collected data in terms of NSE (0.3–0.8), RMSE (0.19–0.94), RPE (− 213 to 0.7%), F1 (0.55), and F2 (0.37). Subsequently, various scenarios of flood frequency with 10-, 20-, 50-, and 100-year return periods under the probability analysis of extreme values were developed to create the flood hazard maps for the study area. The flood hazards were then investigated based on the flood intensity classification of depth, duration, and velocity. These hazard maps are significantly important for flood hazard assessments or flood risk assessments. This study demonstrated that applying advanced hydrodynamic models on computing flood inundation and flood hazard analysis in data-scarce and ungauged coastal river basins is completely feasible. This study provides an approach that can be used also for other ungauged river basins to better understand flooding and inundation through flood hazard mapping. [ABSTRACT FROM AUTHOR]

Assessing the impact of climate change on streamflow is crucial for depicting the vulnerability of water resources and for identifying proper adaptation measures. This study used the Soil and Water Assessment Tool (SWAT) to simulate the impact of climate change on the streamflow of El Kalb river, a major perennial river in Lebanon. The model performance was tested for monthly flow at two stations under a nine-year calibration period (2003--2011) and a four-year validation period (2012--2015). The model results indicated satisfactory precision in fitting observed and simulated flow using various acceptable statistical indices. Future projections of climate change were obtained for three Representative Concentration Pathways (RCPs) (2.6, 4.5, and 8.5). The model indicated that the average annual discharge of El Kalb River in the near future (2021--2040) will decrease by around 28--29% under the three RCP scenarios. End-of-century projections (2081--2100) indicated that the flow will decrease by 23%, 28%, and 45% under RCP 2.6, RCP 4.5, and RCP 8.5, respectively. [ABSTRACT FROM AUTHOR]