Reservoir operation using system dynamics under climate change impacts: a case study of Yamchi reservoir,Iran

This paper proposes a decision support system for Yamchi reservoir operation in semi-arid region of Iran. The paper consists of the following steps: Firstly, the potential impacts of climate change on the streamflow are predicted. The study then presents the projections of future changes in temperature and precipitation under A2 scenario using the LARS-WG downscaling model and under RCP2.6, RCP4.5, and RCP8.5 using the statistical downscaling model (SDSM) in the northwestern of Iran. To do so, a general circulation model of HadCM3 is downscaled by using the LARS-WG model. As a result, the average temperature, for the horizon 2030 (2011–2030), will increase by 0.77 °C and precipitation will decrease by 11 mm. Secondly, the downscaled variables are used as input to the artificial neural network to investigate the possible impact of climate change on the runoffs. Thirdly, the system dynamics model is employed to model different scenarios for reservoir operation using the Vensim software. System dynamics is an effective approach for understanding the behavior of complex systems. Simulation results demonstrate that the water shortage in different sectors (including agriculture, domestic, industry, and environmental users) will be enormously increased in the case of business-as-usual strategy. In this research, by providing innovative management strategies, including deficit irrigation, the vulnerability of reservoir operation is reduced. The methodology is evaluated by using different modeling tests which then motivates using the methodology for other arid/semi-arid regions.     

Climate change impact projections at the catchment scale in Tunisia using the multi-model ensemble mean approach

In this work, we developed a mean projection for climate change and assessed its impact on some hydro-meteorological indicators relevant to climatic condition, precipitation extremes magnitude and frequency for the Siliana catchment in Tunisia based on an ensemble of seven combinations of global circulation models (GCMs) and regional climate models (RCMs) derived from the EU-FP6 ENSEMBLES project. We performed quantile-based mapping (QM) bias correction technique of climate model projection using local observations. Because there is no warranty that the best climate model based on its performances in reproducing historic climate will be superior to other models in simulating future climate, we used the multi-model ensemble (MME) mean approach to derive a mean projection as the best guess for climate change projection for the Siliana catchment. We also quantified the uncertainty of the MME in the projected change in the selected indicators by comparing their values in the reference period (1981–2010) to these in the future period (2041–2070). Results reveal that the Siliana catchment will be prone to drier and warmer climate in the future with less rainy days for each month. The uncertainty associated with the MME projection suggests that no clear general tendency for extreme rainy days in the future is expected. These findings highlight the need to consider an ensemble of multi-climate models with an uncertainty framework if reliable climate change impact study is sought at the catchment scale.     

Shallow landslide susceptibility assessment under future climate and land cover changes: A case study from southwest China

There is no doubt that land cover and climate changes have consequences on landslide activity, but it is still an open issue to assess and quantify their impacts. Wanzhou County in southwest China was selected as the test area to study rainfall-induced shallow landslide susceptibility under the future changes of land use and land cover (LULC) and climate. We used a high-resolution meteorological precipitation dataset and frequency distribution model to analyse the present extreme and antecedent rainfall conditions related to landslide activity. The future climate change factors were obtained from a 4-member multi-model ensemble that was derived from statistically downscaled regional climate simulations. The future LULC maps were simulated by the land change modeller (LCM) integrated into IDRISI Selva software. A total of six scenarios were defined by considering the rainfall (antecedent conditions and extreme events) and LULC changes towards two time periods (mid and late XXI century). A physically-based model was used to assess landslide susceptibility under these different scenarios. The results showed that the magnitude of both antecedent effective recharge and event rainfall in the region will evidently increase in the future. Under the scenario with a return period of 100 years, the antecedent rainfall in summer will increase by up to 63% whereas the event rainfall will increase by up to 54% for the late 21st century. The most considerable changes of LULC will be the increase of forest cover and the decrease of farming land. The magnitude of this change can reach + 22.1% (forest) and –9.2% (farmland) from 2010 until 2100, respectively. We found that the negative impact of climate change on landslide susceptibility is greater than the stabilizing effect of LULC change, leading to an over decrease in stability over the study area. This is one of the first studies across Asia to assess and quantify changes of regional landslide susceptibility under scenarios driven by LULC and climate change. Our results aim to guide land use planning and climate change mitigation considerations to reduce landslide risk.     

Potential impacts of climate change on groundwater levels on the Kerdi-Shirazi plain,Iran

It is important to predict how groundwater levels in an aquifer will respond to various climate change scenarios to effectively plan for how groundwater resources will be used in the future. Due to the overuse of groundwater resources and the multi-year drought in the Kerdi-Shirazi plain in Iran, some land subsidence and a drop in groundwater levels has taken place, and without active management, further degradation of the groundwater resource is possible under predicted future climate change scenarios in the country. To determine the potential impacts of climate change on groundwater levels in the region, the groundwater model GMS was coupled with the atmospheric circulation model HADCM3 using scenarios A1B, A2 and B1 for the period 2016–2030. The results of the climate modelling suggest that the Kerdi-Shirazi plain will experience an increase in minimum temperature and maximum temperature of, respectively, between 0.03 and 0.47, and 0.32–0.45 °C for this time period. The results of the groundwater modelling suggest that water levels on the Kerdi-Shirazi plain will continue to decline over the forecast period with decreases of 34.51, 36.57 and 33.58 m being predicted, respectively, for climate scenarios A1B, A2 and B1. Consequently, groundwater resources in the Kerdi-Shirazi plain will urgently need active management to minimize the effects of ongoing water level decline and to prevent saltwater intrusion and desertification in the region.     

Land use change assessment in coastal mangrove forests of Iran utilizing satellite imagery and CA–Markov algorithms to monitor and predict future change

Mangrove forest stores large organic carbon stocks in a setting that is highly vulnerable to climate change and direct anthropogenic influences. As such there is a need to elucidate the causes and consequences of land use change on these ecosystems that have high value in terms of ecosystem services. We examine the areal pattern of land types in a coastal region located in southern Iran over a period of 14 years to predict future loss and gain in land types to the year 2025. We applied a CA–Markov model to simulate and predict mangrove forest change. Landsat satellite images from 2000 to 2014 were used to analyze the land cover changes between soil, open water and mangroves. Major changes during this period were observed in soil and water which could be attributed to rising sea level. Furthermore, the mangrove area in the more seaward position was converted to open water due to sea-level rise. A cellular automata model was then used to predict the land cover changes that would occur by the year 2025. Results demonstrated that approximately 21 ha of mangrove area will be converted to open water, while mangroves are projected to expand by approximately 28 ha in landward direction. These changes need to be delineated to better inform precise mitigation and adaptation measures.     

Simulation of global warming effect on outdoor thermal comfort conditions

In the coming decades, global warming and increase in temperature, in different regions of the world, may change indoor and outdoor thermal comfort conditions and human health. The aim of this research was to study the effects of global warming on thermal comfort conditions in indoor ambiences in Iran. To study the increase in temperature, model for assessment of greenhouse-gas induced climate change scenario generator compound model has been used together with four scenarios and to estimate thermal comfort conditions, adaptive model of the American Society of Heating, Refrigerating and Air-conditioning Engineers has been used. In this study, Iran was divided into 30 zones, outdoor conditions were obtained using meteorological data of 80 climatological stations and changes in neutral comfort conditions in 2025, 2050, 2075 and 2100 were predicted. In accordance with each scenario, findings from this study showed that temperature in the 30 zones will increase by 2100 to between 3.4 °C and 5.6 °C. In the coming decades and in the 30 studied zones, neutral comfort temperature will increase and be higher and more intense in the central and desert zones of Iran. The low increase in this temperature will be connected to the coastal areas of the Caspian and Oman Sea in southeast Iran. This increase in temperature will be followed by a change in thermal comfort and indoor energy consumption from 8.6 % to 13.1 % in air conditioning systems. As a result, passive methods as thermal inertia are proposed as a possible solution.     

Spatio-temporal distributions of climate disasters and the response of wheat yields in China from 1983 to 2008

Climate disasters are now on the rise and more likely to increase in frequency and/or severity under climate change in the future. To clearly illustrate spatial–temporal distributions of climate disasters and the response of wheat yields to disasters over the past three decades, several disaster indices including the impact of climate disasters, the sensitivity to climate disasters and the response index of wheat yield losses to climate disasters were defined and calculated. The impact and sensitivity indices were examined by the agricultural production losses due to climate disasters, and the response of wheat yields to climate disasters was assessed by wheat yield loss compared with the 5-year moving average. The results showed that the indices of climate disaster impacts and sensitivities as well as response index of wheat yields to climate disasters could represent the spatial–temporal distributions of climate disasters well in the whole China. Droughts in northern China had higher impacts and sensitivities than those in southern China during the period 1983–2008, but the impacts of floods were opposite. In northern China, although impacted area by drought was larger than that by flood, the flood sensitivities were larger than drought sensitivities when flood happened. Although drought significantly affected wheat yields in most of the regions with drier conditions during 1983–2008 in major wheat-producing regions, better management practices like irrigation and drought-tolerant cultivars applied in the Huang-Huai-Hai Plain can adapt to climate disasters especially droughts. To ensure the stability of agricultural production, future food security will need to be achieved through quantifying the relative effects of climate disasters and effective adaptation to increasingly frequent extreme climate events.     

60年来我国主要粮食作物适宜生长区的时空分布

模拟作物适宜生长区的时空分布是分析气候变化对作物生长影响、提高作物生长适应能力的重要内容。选择影响主要粮食作物(小麦、玉米和水稻)生长的气候要素,结合地表土壤和地面高程要素与农业观测站数据,模拟和分析1953—2012年主要粮食作物适宜生长区的变动,评估气候变化下作物的适应能力。研究发现:(1)60年来3种粮食作物适宜生长区对气候变化响应程度从大到小依次是小麦、水稻和玉米。(2)同一时空尺度上,主要粮食作物适宜生长类型区在南方农区较北方农区多样化,在山地较盆地多样化,在高原较平原多样化。(3)小麦生长适应气候变化的能力在多数农区略有上升。玉米生长的适应能力在北方和南方农区分别略微提高和下降。水稻生长的适应能力在长江中下游区、西南区和华南区相对稳定,在黄淮海区和东北区分别下降和提高。(4)60年来,主要粮食作物综合生长适应气候变化的能力在黄淮海区和长江中下游区下降,在其余农区升高。(5)玉米和水稻适宜生长区分别与播种面积和作物产量显著相关,这为模拟未来不同气候情景下二者适宜生长区的分布提供了可行性。小麦适宜生长区与播种面积和产量均不显著相关,未来需要考虑更多因素精准识别小麦适宜生长区,以便更为有效地提高小麦生长对气候变化的适应能力。     

Predicting twenty-first century recession of architectural limestone in European cities

Cities of the twenty-first century will expose buildings to environments that are quite different from those experienced over preceding periods. The recent reduction in sulfur dioxide in cities and continued pressure to lower the emissions of combustion generated pollutants creates a potential for climate induced deterioration, by contrast, to be more important. Given that climate will likely change over the next hundred years, recession rates of calcareous stones have been predicted for Oviedo (Spain), Paris and Prague over the period 1981–2099. This can give guidance as to the likely change in balance of future threat. The Lipfert, ICP, and MULTI-ASSESS functions were used to calculate recession from estimates of climate and air quality. It is likely that under a continued decline or stable levels of pollution, recession rates having reached low values will remain largely unchanged over the coming century, despite likely changes in climate. Although the functions adopted disagree in a quantitative sense, there is evidence that they were reasonably concordant in the last decades of the twentieth century. In a cleaner future their different underlying assumptions lead to poorer agreement.     

Lake Neor reveals how mountain vegetation responded to 7000 years of hydroclimate variability in northwestern Iran

Palynological and geochemical analyses provide valuable information about modern and past climatic regimes and vegetation. The impact of climate and humans on past vegetation in the semi-arid areas of northwestern Iran has received increased interest in the wake of warming temperatures in the Middle East. Palynological and down-core XRF elemental abundances from a peat core from Lake Neor enabled a reconstruction of vegetational changes of the past 7000 years over the highlands of northwestern Iran. Periods of increased arboreal pollen (AP) types and high (Artemisia + Poaceae)/Chenopodiaceae ratios along with low titanium abundances, high percentages of total organic carbon, more negative δD values, and higher carbon accumulation rates suggest a relatively wet climate. These conditions have persisted during the periods 6700–6200, 5200–4450 and 3200–2200 cal a bp. The overall low AP values, substantial rise of Chenopodiaceae, high Ti abundances and low values of palaeo-redox proxies, are all evidences of a drier climate, as has been reconstructed for the periods 6200–5200 and 4030–3150 cal a bp and the last 2200 years. An important feature of the last centuries is the increase of anthropogenic and pastoral indicator pollen types. Our results may provide basic data to predict future trends in vegetation dynamics under future climate change in western Asia.     

Impacts of climate change on stream flow and water quality in a drinking water source area,Northern China

Understanding the impacts of climate change on water quality and stream flow is important for management of water resources and environment. Miyun Reservoir is the only surface drinking water source in Beijing, which is currently experiencing a serious water shortage. Therefore, it is vital to identify the impacts of climate change on water quality and quantity of the Miyun Reservoir watershed. Based on long-time-series data of meteorological observation, future climate change scenarios for this study area were predicted using global climate models (GCMs), the statistical downscaling model (SDSM), and the National Climate Centre/Gothenburg University—Weather Generator (NWG). Future trends of nonpoint source pollution load were estimated and the response of nonpoint pollution to climate change was determined using the Soil and Water Assessment Tool (SWAT) model. Results showed that the simulation results of SWAT model were reasonable in this study area. The comparative analysis of precipitation and air temperature simulated using the SDSM and NWG separately showed that both tools have similar results, but the former had a larger variability of simulation results than the latter. With respect to simulation variance, the NWG has certain advantages in the numerical simulation of precipitation, but the SDSM is superior in simulating precipitation and air temperature changes. The changes in future precipitation and air temperature under different climate scenarios occur basically in the same way, that is, an overall increase is estimated. Particularly, future precipitation will increase significantly as predicted. Due to the influence of climate change, discharge, total nitrogen (TN) and total phosphorus (TP) loads from the study area will increase over the next 30 years by model evaluation. Compared to average value of 1961?~?1990, discharge will experience the highest increase (15%), whereas TN and TP loads will experience a smaller increase with a greater range of annual fluctuations of 2021 ~ 2050.     

Climate Change and Extreme Weather: A Basis for Action

The economic and social costs of extreme weather-related events have been increasing around the globe. There is some debate over how much of this past increase has been due to social factors and how much due to changes in frequency or characteristics of extreme events. The Intergovernmental Panel on Climate Change (2001a) has affirmed that humans are having a role in changing the climate and will have a larger role in the future. Although the changes in extreme events are by their nature both difficult to detect and difficult to model, the consensus is that there will be changes in the future. Through a risk-based decision-making analysis, it is concluded that society should make the additional investments to reduce vulnerability to this increased risk.     

Acknowledgement of Reviewers

Variations in frequency and intensity of extreme events have substantial impact on water resources and environment, which in turn are reflected on agriculture, society, and economy. We assessed spatiotemporal changes in pattern of daily precipitation to identify drought- and flood-prone areas of Iran. To do this, we generated gridded daily precipitation for the period of 1962–2013 over Iran using measured daily precipitation and the Kriging approach. We applied 11 precipitation indices that were stated by the Expert Team on Climate Change Detection and Indices (ETCCDI) to identify significant changes in frequency and intensity of extreme precipitation events. According to significant changes of these 11 precipitation indices, drought- and flood-prone areas of Iran were, then, detected. We observed significant changes in pattern of daily precipitation over more than half of the country. 40% of the country, which were located in the elevated regions of Iran, particularly along Zagros Mountain, was identified as flood-prone areas. As a result, in these regions, there is a need for flood risk management based on changes in stormwater events such as runoff generated from rain on snow and snowmelt events. In addition, we detected drought-prone areas in large portion of the northwest of Iran and in the low elevated regions of the country that have semiarid or arid climate. This suggests that it is necessary to prepare a long-term drought plan to mitigate impacts of severe drought events.     

Impacts of climate change on groundwater in Australia: a sensitivity analysis of recharge

Groundwater recharge is a complex process reflecting many interactions between climate, vegetation and soils. Climate change will impact upon groundwater recharge but it is not clear which climate variables have the greatest influence over recharge. This study used a sensitivity analysis of climate variables using a modified version of WAVES, a soil-vegetation-atmosphere-transfer model (unsaturated zone), to determine the importance of each climate variable in the change in groundwater recharge for three points in Australia. This study found that change in recharge is most sensitive to change in rainfall. Increases in temperature and changes in rainfall intensity also led to significant changes in recharge. Although not as significant as other climate variables, some changes in recharge were observed due to changes in solar radiation and carbon dioxide concentration. When these variables were altered simultaneously, changes in recharge appeared to be closely related to changes in rainfall; however, in nearly all cases, recharge was greater than would have been predicted if only rainfall had been considered. These findings have implications for how recharge is projected to change due to climate change.     

Surface Air Temperature Projection Under 1.5 ℃ Warming Threshold Based on Corrected Pattern Scaling Technique

The global mean temperature during the recent decade (2007-2016) has increased above 1 ℃ relative to the pre-industrial period (1861-1890). The climate change and impact under 1.5 ℃ warming in the future have become a great concern in global society. Temperature projections, especially in regional scale, show great uncertainty depending on used climate models. Taking advantage of pattern scaling technique and observed temperature changes during 1951-2005, we tried to project the temperature changes globally under 1.5 ℃ threshold relative to current climate state, i.e. about 1 ℃ warming around 2007-2016. The projections of 21 climate models from the Coupled Model Intercomparison Project - Phase 5 under four Representative Concentration Pathways (RCP2.6, RC4.5, RCP6.0 and RCP8.5) were used to correct the assumptions in pattern scaling. Results showed that the geographical distribution and warming amplitude of surface air temperature changes under 1.5 ℃ threshold are similar in the four scenarios. Warming over most of the land would be above 0.6 ℃, 0.3 ℃ warmer than ocean. The Northern Hemisphere would be 0.2 ℃ warmer than the Southern Hemisphere. The temperature over China region will increase by 0.7 ℃. The warming in the Northern and Central China under RCP2.6 was obviously higher than that in the other scenarios. Ignoring the impact of correction method, uncertainty in temperature projection based on pattern scaling was much smaller than that in climate models, both in global and regional scales.     

Estimations of climate change impacts on crop production in the Republic of Moldova

Statistical methods for assessing crop sensitivity and vulnerability to climate change in Moldova were demonstrated and the following procedures were discussed: (1) projections of likely agroclimatic change; (2) assessments of crop sensitivity to climate change; and (3) assessments of the impact of climate change on crops. In order to predict the future agroclimate, key meteorological variables were transformed statistically to correspond to changes in plants' heat and water supply characteristics. Sensitivity of crop production was examined for corn and winter wheat. By combining the agroclimatic changes with crop response, possible impacts have been estimated and form a basis for possible adaptation strategies. It was shown that regional climate change can result in elevated aridity of Moldova's territory, especially during periods of crop growth. Cultivation of cereal crops in new agroclimatic conditions without adaptation measures will negatively affect yields, especially of winter wheat, whose yield decrease may be 18–39% by 2020s and 22–50% by 2050s. Corn yields may increase by 0–3% and 1–6%, respectively. As an example of adaptation, it is shown that the use of an increased number of late hybrids results in a 25–35% increase in corn yields. This revised version was published online in July 2006 with corrections to the Cover Date.     

气候变化对澜湄流域气象水文干旱时空特性的影响

受全球气候变化影响,澜沧江-湄公河流域气象水文干旱发生了较大变化,预测未来流域干旱的时空变化与传播特征是应对气候变化、开展澜湄水资源合作的基础。利用SWAT模型通过气陆耦合方式模拟了澜沧江-湄公河流域历史（1960—2005年）和未来时期（2022—2050年,2051—2080年）的水文过程,采用标准化降水指数和标准化径流指数预估并分析了流域未来气象水文干旱时空变化趋势。结果表明:①澜沧江-湄公河流域未来降水呈增长趋势,气象干旱将有所缓解,但降水年内分配不均与流域蒸发的增加,将导致水文干旱更为严峻,干旱从气象到水文的传播过程加剧;②水文干旱具有明显的空间异质性,允景洪和清盛站的水文干旱最为严重,琅勃拉邦、穆达汉和巴色站次之,万象站最弱;③未来流域水文干旱事件发生频次略有减少,但其中重旱、特旱事件占比增加,极端干旱将趋多趋强,且空间变化更加显著。     

Greenhouse warming over Indian sub-continent

A hierarchy of climate models have been developed and applied to the problem of doubling the CO₂ concentration in the atmosphere. Currently available general circulation models include the most complete treatment of the global wanning and are capable of providing changes in several of the meteorological parameters in time scales of half a century or even more. Much skill is gradually being achieved now for future climate simulations. In this paper, we have attempted to describe the response of the National Center for Atmospheric Research Climate Community Model (NCAR CCM), whose performance for northern hemispheric climate simulations was reported to be very satisfactory to Indian region. The seasonal (winter and summer) changes in surface temperature, rainfall and soil moisture expected over the Indian sub-continent due to doubling of CO₂ in the atmosphere as inferred from model output statistics are discussed. A probable scenario for sea level rise along the Indian coastline by the year 2030 AD as a result of ocean water’s expansion due to global warming is outlined. These projections should not be treated as predictions of what is going to happen over the Indian sub-continent. Rather, they merely illustrate to what extent we might be affected by the future climate change.     

Climate change impacts on water demand and availability using CMIP5 models in the Jaguaribe basin,semi-arid Brazil

The objective of this study was to analyze climate change impacts on irrigation water demand and availability in the Jaguaribe River basin, Brazil. For northeastern Brazil, five global circulation models were selected using a rainfall seasonal evaluation screening technique from the Intergovernmental Panel on Climate Change named Coupled Model Intercomparison Project Phase 5. The climate variables were generated for the base period of 1971–2000, as were projections for the 2025–2055 future time slice. Removal of maximum and minimum temperature and rainfall output bias was used to estimate reference evapotranspiration, irrigation water needs, and river flow using the rainfall—river flow hydrological model Soil Moisture Accounting Procedure for the baseline and future climate (Representative Concentration Pathways 4.5 and 8.5 scenarios). In addition, by applying improved irrigation efficiency, a scenario was evaluated in comparison with field observed performance. The water-deficit index was used as a water availability performance indicator. Future climate projections by all five models resulted in increases in future reference evapotranspiration (2.3–6.3%) and irrigation water needs (2.8–16.7%) for all scenarios. Regarding rainfall projections, both positive (4.8–12.5%) and negative (??2.3 to ??15.2%) signals were observed. Most models and scenarios project that annual river flow will decrease. Lower future water availability was detected by the less positive water-deficit index. Improved irrigation efficiency is a key measure for the adaptation to higher future levels of water demand, as climate change impacts could be compensated by gains in irrigation efficiency (water demand changes varying from ??1.7 to ??35.2%).     

Impacts of future climate and land cover changes on landslide susceptibility: regional scale modelling in the Val d’Aran region (Pyrenees,Spain)

It is widely accepted that future environmental changes will affect rainfall-induced shallow slides in high-mountain areas. In this study, the Val d’Aran region located in the Central Pyrenees was selected to analyze and quantify the impacts of land use and land cover (LULC) and climate changes on regional landslides susceptibility. We analyzed 26 climate models of the EURO-CORDEX database focussing on the future rainfall conditions. The IDRISI TerrSet software suite was used to create the future LULC maps. These two inputs were analyzed individually and in a combined way defining 20 different scenarios. All these scenarios were incorporated in a physically based stability model to compute landslides susceptibility maps. The results showed that both environmental conditions will considerably change in the future. The daily rainfall will increase between 14 and 26% assuming a return period of 100 years. This intensification of precipitation will produce an overall decrease of the stability condition in the study area. Regarding the LULC prediction, the forest area will significantly increase, while in particular grassland, but also shrubs decrease. As a consequence, the overall stability condition improves, because the root strength is higher in forest than in grassland and shrubs. When we analyzed the combined impacts, the results showed that the positive effect of LULC changes is larger than the negative influence of rainfall changes. Hence, when combining the two aspects in the future scenarios, the stability condition in the study area will improve.