Far-future Periods Research Articles

Flooding Conditions at Aveiro Port (Portugal) within the Framework of Projected Climate Change

Ports constitute a significant influence in the economic activity in coastal areas through operations and infrastructures to facilitate land and maritime transport of cargo. Ports are located in a multi-dimensional environment facing ocean and river hazards. Higher warming scenarios indicate Europe’s ports will be exposed to higher risk due to the increase in extreme sea levels (ESL), a combination of the mean sea level, tide, and storm surge. Located on the west Iberia Peninsula, the Aveiro Port is located in a coastal lagoon exposed to ocean and river flows, contributing to higher flood risk. This study aims to assess the flood extent for Aveiro Port for historical (1979–2005), near future (2026–2045), and far future (2081–2099) periods scenarios considering different return periods (10, 25, and 100-year) for the flood drivers, through numerical simulations of the ESL, wave regime, and riverine flows simultaneously. Spatial maps considering the flood extent and calculated area show that most of the port infrastructures’ resilience to flooding is found under the historical period, with some marginal floods. Under climate change impacts, the port flood extent gradually increases for higher return periods, where most of the terminals are at high risk of being flooded for the far-future period, whose contribution is primarily due to mean sea-level rise and storm surges.

Modelling the impact of climate change on the flow of the Eerste River in South Africa

This research investigated the impact of climate change on the Eerste River, which is the primary source of water for the Stellenbosch Municipality and the agricultural sector in the surrounding areas of Stellenbosch Town, South Africa. Climate data projected by 11 Global Circulation Models (GCMs) of the Coupled Model Intercomparison Project - Phase 5 enforced by Representative Concentration Pathways 4.5 and 8.5, was statistically downscaled to reflect the “near” (2022–2057) and “far” (2058–2093) future periods, respectively. The ensemble mean of these GCMs outputs for the near and far future periods was compared to that of the present-day period which was accepted as the period between 1983 and 2018. This was done to determine the climate change signal, which was then transferred onto the observed precipitation and evaporation data of the present-day period. The climate change induced data, as well as land use and water demand analysed data, were then used as input to the Pitman Model, which is the conceptual semi-distributed hydrological model, for the simulation of the impact of climate change on the flow of the Eerste River. The results showed that climate change is expected to increase evaporation between 6% and 15% and, at the same time, causing rainfall to decrease between 2% and 8% in the future periods. This future climate is anticipated to cause a reduction in available water of between 8% and 18%, potentially triggering an increase in irrigation demand of between 12% and 29% in the future periods with a possible failure to meet the municipal water abstractions expected in the far-future period. Therefore, this research suggests increasing the capacity of existing farm dams and the promotion of water demand management practices to curb the potential impact of climate change on the available flow of the Eerste River.

Assessing the impact of climate change on urban water demand and related uncertainties: a case study of Neyshabur, Iran

This study represents a new strategy for assessing how climate change has impacted urban water demand per capita in Neyshabur, Iran. Future rainfall depths and temperature variations are projected using several general circulation models (GCMs) for two representative concentration pathway (RCP) (i.e., RCP45 and RCP85) scenarios using LARS-WG software. A simulator model is developed using the genetic programming (GP) model to predict future water demand based on projected climate variables of rainfall depth and maximum temperature. The period of 1996–2016 is selected as the base period. Three future periods, namely the near-future (2021–2040), middle future (2041–2060), and far future (2061–2080), are also employed to assess climate change impact on water demand. Results indicate significant increases in annual projected rainfall depth (14~53%), maximum temperature (0.04~4.21 °C), and minimum temperature (1.01~4.71 °C). The projected monthly patterns of rainfall depth and temperature are predicted to cause a 1-month shift in the water demand peak (i.e., it will occur in April instead of May) for all future periods. Furthermore, the annual water demand per capita is projected to increase by 0.5~1.2%, 1.5~3.2%, and (2.2~7.1%), during the near-, middle-, and far-future periods, respectively. The uncertainty associated with water demand is also projected to increase over time for RCP45. The mathematical expression of urban water demand based on climatic variables is vital to managing the water resources of Neyshabur. The methodology proposed in the present study represents a robust approach to assessing how climate change might affect urban water demand in cities other than Neyshabur and provides crucial information for decision-makers.

The Impact of Climate Change on Wheat, Barley, and Maize Growth Indices in Near-Future and Far-Future Periods in Qazvin Plain, Iran

The current noticeable climate change that has a significant impact on the environment and agricultural systems has become a serious concern for human society. Followed by the industrial activities of the global community and increased concentrations of greenhouse gases in the atmosphere, these changes are still considered as a threat to food safety and the environment. Changes in minimum and maximum temperature, rainfall amounts, and precipitation pattern, changes in CO2 concentrations, and complex interactions between these factors and different crops are studied in the form of different probabilistic scenarios to get a glimpse of the future cultivation situation. Agriculture in Qazvin Plain is based on the water transferred from Taleqan Dam and groundwater. Since today these resources are facing issues like restriction on transfer and draw off, which is because of growth of interest in city dwelling, inappropriate water consumption patterns and over-exploitation, agriculture is sensitive to probable changes in water requirements and it is necessary to predict these changes for better management in the future. This study was carried out to investigate the effect of climate change on growth indices for three crops including wheat, barley, and maize in Qazvin Plain with different possible climate change scenarios, in the form of five large-scale climate models and three greenhouse gas emissions scenarios in 30 years’ time from 2021 to 2050 as well as from 2051 to 2080. Results showed that biomass production, grain yield, and water use efficiency in three crops of wheat, barley, and maize have increased up to 20–40% in future periods in Qazvin region climate. Growing degree-days (GDD) of these three crops have increased by 20%. Transpiration has risen by 10% in wheat and maize; however, it was stable on average in the first period and slightly decreased in the second period in barley. The transpiration coefficient has reduced by 5% for wheat and barley and has increased by 15% for maize. Results are valid as long as the initial growing conditions of these three plants are done as before, and the irrigation scheduling is performed according to the present period in spite of climate change.

Impact assessment of climate change on hydro-climatic conditions of arid and semi-arid watersheds (case study: Zoshk-Abardeh watershed, Iran)

Abstract The hydrologic cycle in the river basins of semi-arid regions is severely influenced by climate change. The aim of this study is to assess the impact of climate change on the hydro-climatic condition in Zoshk-Abardeh watershed in eastern Iran. The Soil and Water Assessment Tool (SWAT) was calibrated using the Sequential Uncertainty Fitting – Version 2 (SUFI-2) algorithm to improve the simulation results of the runoff. The Model for Interdisciplinary Research on Climate-Earth System Models (MIROC-ESM) was used to investigate the effects of climate change on hydro-climatic components under the representative concentration pathway scenarios (RCPs: 2.6, 4.5, 6.0, and 8.5) and in near- (2014–2042), mid- (2042–2071), and far- (2072–2100) futures. The temperature component under the RCP4.5 and RCP6.0 during the near- and mid-future intervals and the far-future period (for RCP6.0) indicated a significant rising trend. The rainfall parameter in all RCPs and future intervals showed an insignificant descending trend. Runoff alterations under the RCP4.5 amid the mid- to far-future intervals and under the RCP8.5 throughout the far-future period trailed a significant descending trend. The results determined that the temperature will track an upward tendency, while precipitation and runoff will follow a descending trend in this watershed by the end of the 21st century.

Increase in probable maximum precipitation in a changing climate over India

Probable Maximum Precipitation (PMP) is considered as an important design criteria and it is expected to change over time owing to the impacts of climate change and intensification of global hydrological cycle. Thus, reconstruction of PMP map and investigation about its temporal change are very essential in the context of climate change. This study develops 1-day PMP map of India for five consecutive time periods (two in historical, i.e., 1901-70, 1971-2010; and three in future, i.e., 2010-39, 2040-69 and 2070-2100) to study its temporal change. Observed gridded daily precipitation data from India Meteorological Department (IMD) and outputs from three climate models following two Representative Concentration Pathways (RCPs) are used to develop historical and future PMP maps, respectively. The modified Hershfield method is used for estimation of PMP with an updated method for enveloping technique. The results show a clear increasing trend in PMP for most part of India. Specifically, 84% area of Indian mainland exhibits an increasing trend in PMP with an average of around 35% increase in post-1970 (1971–2010) period as compared to pre-1970 (1901–1970) period. Similarly, in the far-future period (2071–2100), around 70–80% area is showing an increase with an approximate average increase of 20%-35% in PMP across different models with respect to recent past (1971–2010) following RCP 8.5 scenario. These observations evidently indicate how significantly PMP is increasing due to climate change and it should be considered in the revised planning and design in water resources engineering.

Performance Evaluation of Bias Correction Methods for Climate Change Monthly Precipitation Projections over Costa Rica

Six bias correction (BC) methods; delta-method (DT), linear scaling (LS), power transformation of precipitation (PTR), empirical quantile mapping (EQM), gamma quantile mapping (GQM) and gamma-pareto quantile mapping (GPQM) were applied to adjust the biases of historical monthly precipitation outputs from five General Circulation Models (GCMs) dynamically downscaled by two Regional Climate Models (RCMs) for a total of seven different GCM-RCM pairs over Costa Rica. High-resolution gridded precipitation observations were used for the control period 1951–1980 and validated over the period 1981–1995. Results show that considerable biases exist between uncorrected GCM-RCM outputs and observations, which largely depend on GCM-RCM pair, seasonality, climatic region and spatial resolution. After the application of bias correction, substantial biases reductions and comparable performances among most BC methods were observed for most GCM-RCM pairs; with EQM and DT marginally outperforming the remaining methods. Consequently, EQM and DT were selectively applied to correct the biases of precipitation projections from each individual GCM-RCM pair for a near-future (2011–2040), mid-future (2041–2070) and far-future (2071–2100) period under Representative Concentration Pathways (RCPs) 2.6, 4.5 and 8.5 using the control period 1961–1990. Results from the bias-corrected future ensemble-mean anticipate a marked decreasing trend in precipitation from near to far-future periods during the dry season (December, January, February (DJF) and March, April, May (MAM)) for RCP4.5 and 8.5; with pronounced drier conditions for those climatic regions draining towards the Pacific Ocean. In contrast, mostly wetter conditions are expected during the dry season under RCP2.6, particularly for the Caribbean region. In most of the country, the greatest decrease in precipitation is projected at the beginning of the rainy season (June, July, August (JJA)) for the far-future period under RCP8.5, except for the Caribbean region where mostly wetter conditions are anticipated. Regardless of future period, slight increases in precipitation with higher radiative forcing are expected for SON excluding the Caribbean region, where precipitation is likely to increase with increasing radiative forcing and future period. This study demonstrates that bias correction should be considered before direct application of GCM-RCM precipitation projections over complex territories such as Costa Rica.

Evaluation of Statistical-Downscaling/Bias-Correction Methods to Predict Hydrologic Responses to Climate Change in the Zarrine River Basin, Iran

Modeling the hydrologic responses to future changes of climate is important for improving adaptive water management. In the present application to the Zarrine River Basin (ZRB), with the major reach being the main inflow source of Lake Urmia (LU), firstly future daily temperatures and precipitation are predicted using two statistical downscaling methods: the classical statistical downscaling model (SDSM), augmented by a trend-preserving bias correction, and a two-step updated quantile mapping (QM) method. The general circulation models (GCM) input to SDSM are climate predictors of the Canadian Earth System Model (CanESM2) GCM under the representative concentration pathway (RCP) emission scenarios, RCP45 and RCP85, whereas that to the QM is provided by the most suitable of several Climate Model Intercomparison Project Phase 5 (CMIP5) GCMs under RCP60, in addition. The performances of the two downscaling methods are compared to each other for a past “future” period (2006–2016) and the QM is found to be better and so is selected in the subsequent ZR streamflow simulations by means of the Soil and Water Assessment Tool (SWAT) hydrological model, calibrated and validated for the reference period (1991–2012). The impacts of climate change on the hydrologic response of the river basin, specifically the inflow to the Boukan Reservoir, the reservoir-dependable water release (DWR), are then compared for the three RCPs in the near- (2020–2038), middle- (2050–2068) and far- (2080–2098) future periods assuming (1) the “current” consumptive demand to be continued in the future, and (2) a more conservative “recommended” demand. A systematic future shortage of the available water is obtained for case (1) which can be mitigated somewhat for (2). Finally, the SWAT-predicted ZRB outflow is compared with the Montana-based estimated environmental flow of the ZR. The latter can successfully be sustained at good and fair levels for the near- and middle-future periods, but not so for the summer months of the far-future period, particularly, for RCP85.

GCM 및 상세화 기법 선정을 고려한 충주댐 유입량 기후변화 영향 평가

In this study, we evaluated the uncertainty in the process of selecting GCM and downscaling method for assessing the impact of climate change, and influence of user-centered climate change information on reproducibility of Chungju Dam inflow was analyzed. First, we selected the top 16 GCMs through the evaluation of spatio-temporal reproducibility of 29 raw GCMs using 30-year average of 10-day precipitation without any bias-correction. The climate extreme indices including annual total precipitation and annual maximum 1-day precipitation were selected as the relevant indices to the dam inflow. The Simple Quantile Mapping (SQM) downscaling method was selected through the evaluation of reproducibility of selected indices and spatial correlation among weather stations. SWAT simulation results for the past 30 years period by considering limitations in weather input showed the satisfactory results with monthly model efficiency of 0.92. The error in average dam inflow according to selection of GCMs and downscaling method showed the bests result when 16 GCMs selected raw GCM analysi were used. It was found that selection of downscaling method rather than selection of GCM is more is important in overall uncertainties. The average inflow for the future period increased in all RCP scenarios as time goes on from near-future to far-future periods. Also, it was predicted that the inflow volume will be higher in the RCP 8.5 scenario than in the RCP 4.5 scenario in all future periods. Maximum daily inflow, which is important for flood control, showed a high changing rate more than twice as much as the average inflow amount. It is also important to understand the seasonal fluctuation of the inflow for the dam management purpose. Both average inflow and maximum inflow showed a tendency to increase mainly in July and August during near-future period while average and maximum inflows increased through the whole period of months in both mid-future and far-future periods.

Downscaled climate change projections for the Hindu Kush Himalayan region using CORDEX South Asia regional climate models

This study assessed the regional climate models (RCMs) employed in the Coordinated Regional climate Downscaling Experiment (CORDEX) South Asia framework to investigate the qualitative aspects of future change in seasonal mean near surface air temperature and precipitation over the Hindu Kush Himalayan (HKH) region. These RCMs downscaled a subset of atmosphere ocean coupled global climate models (AOGCMs) in the Coupled Model Intercomparison Project phase 5 (CMIP5) to higher 50 km spatial resolution over a large domain covering South Asia for two representation concentration pathways (RCP4.5 and RCP8.5) future scenarios. The analysis specifically examined and evaluated multi-model and multi-scenario climate change projections over the hilly sub-regions within HKH for the near-future (2036–2065) and far-future (2066–2095) periods. The downscaled multi-RCMs provide relatively better confidence than their driving AOGCMs in projecting the magnitude of seasonal warming for the hilly sub-region within the Karakoram and northwestern Himalaya, with higher projected change of 5.4 °C during winter than of 4.9 °C during summer monsoon season by the end of 21st century under the high-end emissions (RCP8.5) scenario. There is less agreement among these RCMs on the magnitude of the projected warming over the other sub-regions within HKH for both seasons, particularly associated with higher RCM uncertainty for the hilly sub-region within the central Himalaya. The downscaled multi-RCMs show good consensus and low RCM uncertainty in projecting that the summer monsoon precipitation will intensify by about 22% in the hilly sub-region within the southeastern Himalaya and Tibetan Plateau for the far-future period under the RCP8.5 scenario. There is low confidence in the projected changes in the summer monsoon and winter season precipitation over the central Himalaya and in the Karakoram and northwestern Himalaya due to poor consensus and moderate to high RCM uncertainty among the downscaled multi-RCMs. Finally, the RCM related uncertainty is found to be large for the projected changes in seasonal temperature and precipitation over the hilly sub-regions within HKH by the end of this century, suggesting that improving the regional processes and feedbacks in RCMs are essential for narrowing the uncertainty, and for providing more reliable regional climate change projections suitable for impact assessments in HKH region.

Climate projections in the Hornsund area, Southern Spitsbergen

Abstract The aim of this study was to provide an estimation of climate variability in the Hornsund area in Southern Spitsbergen in the period 1976-2100. The climatic variables were obtained from the Polar-CORDEX initiative in the form of time series of daily air temperature and precipitation derived from four global circulation models (GCMs) following representative concentration pathways (RCP) RCP 4.5 and RCP 8.5 emission scenarios. In the first stage of the analysis, simulations for the reference period from 1979 to 2005 were compared with observations at the Polish Polar Station Hornsund from the same period of time. In the second step, climatic projections were derived and monthly and annual means/sums were analysed as climatic indices. Following the standard methods of trend analysis, the changes of these indices over three time periods - the reference period 1976-2005, the near-future period 2021-2050, and far-future period 2071-2100 - were examined. The projections of air temperature were consistent. All analysed climate models simulated an increase of air temperature with time. Analyses of changes at a monthly scale indicated that the largest increases were estimated for winter months (more than 11°C for the far future using the RCP 8.5 scenario). The analyses of monthly and annual sums of precipitation also indicated increasing tendencies for changes with time, with the differences between mean monthly sums of precipitation for the near future and the reference period similar for each months. In the case of changes between far future and reference periods, the highest increases were projected for the winter months.

Hydro-Meteorological Drought Projections into the 21-st Century for Selected Polish Catchments

The nature of drought conditions is estimated using a range of indices describing different aspects of drought events. Three drought indices are evaluated, namely the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Runoff Index (SRI), using observed hydroclimatic data and applying them to hydro-meteorological projections into the 21st century. The first two indices are evaluated using only meteorological variables and from this point of view, are better suited to meteorological drought projections than the third index, SRI, which is based on catchment discharge and represents hydrological drought. We assess information contained in those indices and their suitability to catchment scale climate projection drought assessment in ten selected Polish catchments, representing different hydro-climatic conditions, which are used as a case study. Projections of climatic variables (precipitation and temperature) are obtained from the EURO-CORDEX initiative derived from seven climate models at a grid resolution of 12.5 km for the time period 1971–2100. Future runoff projections for the catchments are obtained using a conceptual rainfall-runoff model (HBV). The results of analyses of indices based on observations in the reference period show consistent estimates for most of the catchments. Hydro-meteorological climate model projections for three periods, including the reference period 1971–2000, and two 30-year periods, near-future 2021–2050 and far-future 2071–2100, are used to estimate changes of future drought conditions in the catchments studied. The results show a substantial variation of temporal drought patterns over the catchments and their dependence on projected precipitation and temperature variables and the type of indices applied. Of the three indices studied, only SPEI projections indicate drier conditions in the catchments in the far-future period. The other two indices, SPI and SRI, indicate wetter climates in the future.

Impact of climate change on the streamflow in the glacierized Chu River Basin, Central Asia

Catchments dominated by meltwater runoff are sensitive to climate change as changes in precipitation and temperature inevitably affect the characteristics of glaciermelt/snowmelt, hydrologic circle and water resources. This study simulated the impact of climate change on the runoff generation and streamflow of Chu River Basin (CRB), a glacierized basin in Central Asia using the enhanced Soil and Water Assessment Tool (SWAT). The model was calibrated and validated using the measured monthly streamflow data from three discharge gauge stations in CRB for the period 1961–1985 and was subsequently driven by downscaled future climate projections of five Global Circulation Models (GCMs) in Coupled Model Inter-comparison Project Phase 5 (CMIP5) under three radiative forcing scenarios (RCP2.6, RCP4.5 and RCP8.5). In this study, the period 1966–1995 was used as the baseline period, while 2016–2045 and 2066–2095 as the near-future and far-future period, respectively. As projected, the climate would become warmer and drier under all scenarios in the future, and the future climate would be characterized by larger seasonal and annual variations under higher RCP. A general decreasing trend was identified in the average annual runoff in glacier (−26.6% to −1.0%), snow (−21.4% to +1.1%) and streamflow (−27.7% to −6.6%) for most of the future scenario periods. The projected maximum streamflow in each of the two future scenarios occurred one month earlier than that in the baseline period because of the reduced streamflow in summer months. Results of this study are expected to arouse the serious concern about water resource availability in the headwater region of CRB under the continuously warming climate. Changes in simulated hydrologic outputs underscored the significance of lowering the uncertainties in temperature and precipitation projection.

Future hydropower production in the Lower Zambezi under possible climate change influence

Hydropower is the most important energy source in Mozambique and many other countries in southern Africa. Substantial hydropower development is planned for the Lower Zambezi for the next decades, with regional importance due to integration into the Southern African Power Pool. For such a long-term development, the possible impact of climate change on the future production is of essential interest. The objective of the presented study is to assess hydropower generation in the 21st century for a future hydropower development scenario under two climate scenarios. The two climate scenarios represent a future wetting climate and a future drying climate, both with considerable warming, and are based on bias-corrected data of two recent Global Climate Models. All hydro-meteorological input data are publicly available from an online decision support system, the Zambezi DSS. The future hydropower scenario considers the extension of the existing Cahora Bassa plant and three planned facilities downstream, Mphanda Nkuwa, Boroma and Lupata. Hydropower modelling for this cascade of reservoirs and hydropower plants is carried out with the HEC-ResSim model. Modelling results show a strong impact of precipitation projections on simulated future hydropower generation. With a wetting climate scenario, a marked increase of hydropower production of +11% for a near-future period (2021–2050) and +9% for a far-future period (2071-2100) are projected, as compared with simulation results for a historic reference scenario. In a drying climate, hydropower generation decreases by -6% (near future) and -13% (far future). The climate change impact is stronger for the large extended Cahora Bassa plant than for the smaller downstream facilities. The results show the importance of considering climate risk in technical design and financial assessment of hydropower projects in the region.Keywords: Zambezi River, hydropower development, climate change, hydropower modelling, water resources

Hydrological Flood Simulation Using a Design Hyetograph Created from Extreme Weather Data of a High-Resolution Atmospheric General Circulation Model

To understand the characteristics of severe floods under global climate change, we created a design hyetograph for a 100-year return period. This incorporates a modified ranking method using the top 10 extreme rainfall events for present, near-future, and far-future periods. The rainfall data sets were projected with a general circulation model with high spatial and temporal resolution and used with a flood model to simulate the higher discharge peaks for the top 10 events of each term in a local watershed. The conventional-like ranking method, in which only a dimensionless shape is considered for the creation of a design hyetograph for a temporal distribution of rainfall, likely results in overestimates of discharge peaks because, even with a lower peak of rainfall intensity and a smaller amount of cumulative rainfall, the distribution shape is the only the factor for the design hyetograph. However, the modified ranking method, which considers amounts of cumulative rainfalls, provides a discharge peak from the design hyetograph less affected by a smaller cumulative rainfall depth for extreme rainfall. Furthermore, the effects of global climate change indicate that future discharge peaks will increase by up to three times of those of Present-term peaks, which may result in difficult flood control for the downstream river reaches.

Climate Projections for South America: RegCM3 Driven by HadCM3 and ECHAM5

This study shows climate projections of air temperature and precipitation over South America (SA) from the Regional Climate Model version 3 (RegCM3) nested in ECHAM5 and HadCM3 global models. The projections consider the A1B scenario from Intergovernmental Panel on Climate Change (IPCC) and three time-slices: present (1960–1990), near- (2010–2040), and far-future (2070–2100) climates. In the future, RegCM3 projections indicate general warming throughout all SA and seasons, which is more pronounced in the far-future period. In this late period the RegCM3 projections indicate that the negative trend of precipitation over northern SA is also higher. In addition, a precipitation increase over southeastern SA is projected, mainly during summer and spring. The lifecycle of the South American monsoon (SAM) was also investigated in the present and future climates. In the near-future, the projections show a slight delay (one pentad) of the beginning of the rainy season, resulting in a small reduction of the SAM length. In the far-future, there is no agreement between projections related to the SAM features.

Climate change’s impact on irrigation system and farmers’ response: a case study of the Plaichumpol Irrigation Project, Phitsanulok Province, Thailand

The Plaichumpol Irrigation Project, in Nan Basin of Thailand, is selected as a case study of impact study, where farmers depended on both surface and groundwater sources (especially in the dry year), to assess the impact on irrigation systems. The study used the MRI-GCM data to project the future climate condition and assess the impact on irrigation systems focusing on water shortage and groundwater pumping aspects in the selected consecutive dry years. The responses from farmers on the impact and adaptation were also gathered via site interviews and analyzed. Based on the bias-corrected MRI-GCM data, the annual rainfall in Nan Basin will decrease in the near future (2015–2039), compared with the past average data (1979–2006), while the rainfall will increase in the far future (2075–2099) compared with past. Water supply from dam will decrease in wet season and dry season, while water demand in both of near future and far future will increase in wet season and dry season. Less water shortage and groundwater pumping in both near-future and far-future periods are expected in the future consecutive dry years compared with the past, though the groundwater is still an important supplementary irrigation water source in the dry year. From the field interview, the farmers are ready to adapt to the changing situations and join in the water use meeting to follow up with irrigation officers about the adjustment of plant calendar and water allocation due to the climate change and to prepare adaptation measures as necessary.

A new methodology for weighting high-resolution model simulations to project future rainfall in the Middle East

A divergence metric was used to combine 4 high-resolution climate models to gen- erate more reliable simulations of future rainfall. The approach is based on the assumption that the use of multiple models (an ensemble) is superior to the use of a single model, even if one of the models is shown to better capture past trends. Such an approach is especially useful in areas with steep climatic gradients, where large-scale climate models are not effective in capturing oro- graphic and local effects. We applied the methodology to the Middle East, and specifically to Israel, where climate shifts from arid to humid temperate occur over a distance of around 400 km. Model weights were determined by calculating the similarity between the probability distribu- tions of the models and those of the historical data using the Jenson-Shannon divergence metric. These weights were then applied to future model projections. Annual amounts of rainfall, num- bers of wet days and numbers of 3 d wet spells were analyzed. Compared with observed data, the weighted ensemble outperformed the equal weights ensemble, which outperformed the best model. For the northern and central stations, average annual amounts of rainfall decreased in both near- and far-future periods, with most of the change occurring at the peak and in the left-hand tail and less change in the right-hand tail of the probability distribution. This, combined with the change in the right-hand tail of the distribution in numbers of wet spells in the near future, sug- gests that the decline in overall rainfall will be higher than the corresponding decline in extreme events; or in other words even though there will be less rainfall, the extreme events will remain, and even possibly increase. In the south, a mixed trend of slightly increasing median amounts of rainfall and slightly decreasing extreme events is projected.