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Groundwater is an important source of water supply in arid and semi-arid areas. The purpose of this study is to predict the impact of climate change on groundwater recharge in an arid environment in Ilam Province, west of Iran.

A three-dimensional transient groundwater flow model (modular finite difference groundwater FLOW model: MODFLOW) was used to simulate the impacts of three climate scenarios (i.e. an average of a long-term rainfall, predicted rainfall in 2015-2030 and three years moving average rainfall) on groundwater recharge and groundwater levels. Various climate scenarios in Long Ashton Research Station Weather Generator were applied to predict weather data.

HadCM3 climatic model and A2 emission scenario were selected as the best methods for weather data generation. Based on the results of these models, annual precipitation will decrease by 3 per cent during 2015-2030. For three emission scenarios, i.e. an average of a long-term rainfall, predicted rainfall in 2015-2030 and three years moving average rainfall, precipitation in 2030 is estimated to be 265, 257 and 247 mm, respectively. For the studied aquifer, predicted recharge will decrease compared to recharge calculated based on the average of long-term rainfall.

The decline of groundwater level in the study area was 11.45 m during the past 24 years or 0.48 m/year. Annual groundwater depletion should increase to 0.75 m in the coming 16 years via climate change. Climate change adaptation policies in the basin should include changing the crop type, as well as water productivity and irrigation efficiency enhancement at the farm and regional scales.

Due to technological improvement and development of the vehicle-to-home (V2H) concept, electric vehicle (EV) can be considered as an active component of net-zero energy buildings (NZEBs). However, to achieve more dependable results, proper energy analysis is needed to take into consideration the stochastic behavior of renewable energy, energy consumption in the building and vehicle use pattern. This study aims to stochastically model a building integrating photovoltaic panels as a microgeneration technology and EVs to meet NZEB requirements.

First, a multiobjective nondominated sorting genetic algorithm (NSGA-II) was developed to optimize the building energy performance considering panels installed on the façade. Next, a dynamic solution is implemented in MATLAB to stochastically model electricity generation using solar panels as well as building and EV energy consumption. Besides, the Monte Carlo simulation method is used for quantifying the uncertainty of NZEB performance. To investigate the impact of weather on both energy consumption and generation, the model is tested in five different climatic zones in Iran.

The results show that the stochastic simulation provides building designers with a variety of convenient options to select the best design based on level of confidence and desired budget. Furthermore, economic evaluation signifies that investing in all studied cities is profitable.

Considering the uncertainty in building energy demand and PV power generation as well as EV mobility and the charging–discharging power profile for evaluating building energy performance is the main contribution of this study.

Prediction of sediment yield for a particular river is essential to study the river morphology, agricultural land management and the lake/reservoir sedimentation investigation. The purpose of this research was to predict sediment yield by simulating and optimizing using model analysis from Bilate River.

Continuous daily sediment produced was estimated using sediment rating curve analysis. Sediment yield was simulated with soil and water assessment tool (SWAT) and the parameters were optimized by using Sequential Uncertainty Fitting algorithm. A total of 15 years of monthly flow and sediment yield data was calibrated and validated during the course of time.

Results evaluated through SWAT showed that the model performance was very good. From the model output prediction, the total measured and simulated sediment yield were 5.425 million ton/year and 5.538 million ton/year, respectively. The result indicates that there were high amount of soil loss resulting into sediment yield produced from the watershed per year which needs appropriate soil and water conservation techniques. Thus, the finding of this research work can provide an effective watershed/river basin management and environmental restoration.

This paper is an original research work and all the referred sources are cited properly wherever deemed fit.

The purpose of this study is to examine the biophysical and socioeconomic impacts of climate change on maize production and food security in sub-Saharan Africa (SSA) using adapted improved maize varieties and well-calibrated and validated bioeconomic models.

Using the past climate (1950-2000) as a baseline, the study estimated the biophysical impacts of climate change in 2050 (2040-2069) and 2080 (2070-2099) under the A1B emission scenario and three nitrogen levels, and the socioeconomic impacts in 2050.

Climate change will affect maize yields across SSA in 2050 and 2080, and the extent of the impact at a given period will vary considerably between input levels, regions and maize mega environments (MMEs). Greater relative yield reductions may occur under medium and high-input intensification than under low intensification, in Western and Southern Africa than in Eastern and Central Africa and in lowland and dry mid-altitude than in highland and wet mid-altitude MMEs. Climate change may worsen food insecurity in SSA in 2050 through its negative impact on maize consumption and reduction in daily calorie intake. However, international trade has the potential to offset some of the negative impacts.

The study calibrated and applied bioeconomic models to estimate the biophysical and socioeconomic impact of climate change on maize production at fine resolution. The results could be used as a baseline to evaluate measures that will be applied to adapt maize to the future climate in SSA.

The work set out to design and develop an overheating risk tool using the UKCP09 climate projections that is compatible with building performance simulation software. The aim of the tool is to exploit the Weather Generator and give a reasonably accurate assessment of a building's performance in future climates, without adding significant time, cost or complexity to the design team's work.

Because simulating every possible future climate is impracticable, the approach adopted was to use principal component analysis to give a statistically rigorous simplification of the climate projections. The perceptions and requirements of potential users were assessed through surveys, interviews and focus groups.

It is possible to convert a single dynamic simulation output into many hundreds of simulation results at hourly resolution for equally probable climates, giving a population of outcomes for the performance of a specific building in a future climate, thus helping the user choose adaptations that might reduce the risk of overheating. The tool outputs can be delivered as a probabilistic overheating curve and feed into a risk management matrix. Professionals recognized the need to quantify overheating risk, particularly for non‐domestic buildings, and were concerned about the ease of incorporating the UKCP09 projections into this process. The new tool has the potential to meet these concerns.

The paper is the first attempt to link UKCP09 climate projections and building performance simulation software in this way and the work offers the potential for design practitioners to use the tool to quickly assess the risk of overheating in their designs and adapt them accordingly.

To critically compare three future weather year (FWY) downscaling approaches, based on the 2009 UK Climate Projections, used for climate change impact and adaptation analysis in building simulation software.

The validity of these FWYs is assessed through dynamic building simulation modelling to project future overheating risk in typical English homes in 2050s and 2080s.

The modelling results show that the variation in overheating projections is far too significant to consider the tested FWY data sets equally suitable for the task.

It is recommended that future research should consider harmonisation of the downscaling approaches so as to generate a unified data set of FWYs to be used for a given location and climate projection. If FWY are to be used in practice, live projects will need viable and reliable FWY on which to base their adaptation decisions. The difference between the data sets tested could potentially lead to different adaptation priorities specifically with regard to time series and adaptation phasing through the life of a building.

The paper investigates the different results derived from FWY application to building simulation. The outcome and implications are important considerations for research and practice involved in FWY data use in building simulation intended for climate change adaptation modelling.

Mobile travel apps (MTA) smart features were identified based on recent travel application (app) trends and a literature review of MTA smart features. Subsequently, the MTA features that could be prioritised to increase user interest in MTA were determined. The MTA smart feature development challenges that should be mitigated were also identified.

The app identification and selection were based on the one-stop solution characteristics containing the common function of travel apps and eight MTA smart features. A total of 193 Apple apps and 250 Google apps were identified, where 36 apps that met the inclusion and exclusion criteria based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart were selected for evaluation.

The high user ratings for apps from both app stores revealed the acceptance of smart technology in the tourism industry. Geolocation tracking services, travel itinerary generators, and real-time personalisation and recommendation were the three major features available in the included MTA. The challenges of MTA with smart features were highlighted from the tourism organisation, app developer and user perspectives.

The findings can guide tourism organisations and app developers on the smart features that MTA should offer for user engagement. Technological organisations could optimise their technology stack by considering the identified smart features. The findings are valuable for scholars in terms of MTA aesthetics and usability to gain acceptability. The development challenges included significant investment in technology, location accuracy and privacy concerns when implementing MTA smart features.

The previous literature mainly focused on evaluating app quality, assessing app functionality, and user ratings using the Mobile Application Rating Scale, and scoping reviews of MTA articles. Contrastingly, this study is among the first in which MTA smart features were examined from a developer-centric perspective. Moreover, it is suggested that MTA includes integrated smart features for better tourism services and market penetration in the tourism industry.

The Middle Eastern terrain is expected to encounter unprecedented climatic conditions before the turn of the next century (circa. 80 years), emanating from extreme heat waves that exceed the critical threshold of habitable conditions. This threatens to cause a significant challenge that is exacerbated by a gap between the supply and demand of affordable energy. Therefore, the purpose of this study is to investigate the potential of utilising nearly zero-energy buildings (nZEB) to improve the performance of residential buildings in Iraq and the Middle East.

This study uses Iraq as a case-study because of the breadth of climatic conditions experienced across its wide-reaching territory and also because of the recent critical infrastructural challenges following the geo-political crisis. Three virtual buildings were simulated for Baghdad, Mosul and Basra cities to narrow the confines of the region to achieve nZEB under current and future climatic weather scenarios.

The findings showed that in all three cases studies, the buildings located within the three climatic regions in Iraq could achieve both significant annual energy reductions as well as nZEB standards which could range from 41 per cent to 87 per cent for current climatic conditions and 40 per cent to 84 per cent by 2080. An analysis has also been carried out for the three case-study cities which revealed significant operational-cost savings achievable through nZEB buildings.

There are currently limited studies that investigate such positive potential for nZEB strategies under the current and predicted future climatic scenarios in the Middle East.

This study aims to present the climate change effect on potential evapotranspiration (ETP) in future periods.

Daily minimum and maximum temperature, solar radiation and precipitation weather parameters have been downscaled by global circulation model (GCM) and Lars-WG outputs. Weather data have been estimated according to the Had-CM3 GCM and by A1B, A2 and B1 scenarios in three periods: 2011-2030, 2045-2046 and 2080-2099. To select the more suitable method for ETP estimation, the Hargreaves-Samani (H-S) method and the Priestly–Taylor (P-T) method have been compared with the Penman-Monteith (P-M) method. Regarding the fact that the H-S method has been in better accordance with the P-M method, ETP in future periods has been estimated by this method for different scenarios.

In all five stations, in all three scenarios and in all three periods, ETP will increase. The highest ETP increase will occur in the A1B scenario and then in the A1 scenario. The lowest increase will occur in the B1 scenario. In the 2020 decade, the highest ETP increase in three scenarios will occur in Khorramabad and then Hamedan. Kermanshah, Sanandaj and Ilam stations come at third to fifth place, respectively, with a close increase in amount. In the 2050 decade, ETP increase percentages in all scenarios are close to each other in all the five stations. In the 2080 decade, ETP increase percentages in all scenarios will be close to each other in four stations, namely, Kermanshah, Sanandaj, Khorramabad and Hamedan, and Ilam station will have a higher increase compared with the other four stations.

Meanwhile, the highest ETP increase will occur in hot months of the year, which are significant with regard to irrigation and water resources.

The purpose of this study is to simulate the climate change impacts on winter wheat production and evaluate the possibilities of using various varieties and shifting planting date as two climate change adaptation strategies in Kerman Province, Iran.

Two types of global circulation model and three scenarios for three periods were used. Daily climatic parameters were generated by LARS-WG (Long Ashton Research Station-Weather Generator). The CERES-wheat model was used to simulate future winter wheat growth, development and production.

The results showed that CO₂ had no effect on the phenology of winter wheat, and the negative impact of temperature on the grain yield was higher than the positive effect of CO₂ enrichment. The length of the reproductive growth period of the winter wheat was significantly shortened as affected by the negative impacts of rise in temperature. The simulated results indicated that the grain yield of common (medium maturing) variety of winter wheat will decline, ranging from −0.27 to −18.71 per cent according to future climate changes. Adaptation strategies showed that the early maturing variety had a higher and more stable grain yield under climate change conditions than medium and delayed maturing varieties. Earlier planting date (20 October) increased wheat grain yield under future climatic conditions than common (November 5) planting date. In reverse, later planting (November 20) would accelerate harmful effects of climate change on wheat grain yield.

The results highlighted the potential of early maturing variety and early planting date as the appropriate agronomical approaches for mitigating harmful impacts of climate change on winter wheat production in arid regions.