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1.
Nonlinear dynamics and recurrence analysis of extreme precipitation for observed and general circulation model generated climates 
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下载免费PDF全文 A statistical framework based on nonlinear dynamics theory and recurrence quantification analysis of dynamical systems is proposed to quantitatively identify the temporal characteristics of extreme (maximum) daily precipitation series. The methodology focuses on both observed and general circulation model (GCM) generated climates for present (1961–2000) and future (2061–2100) periods which correspond to 1xCO2 and 2xCO2 simulations. The daily precipitation has been modelled as a stochastic process coupled with atmospheric circulation. An automated and objective classification of daily circulation patterns (CPs) based on optimized fuzzy rules was used to classify both observed CPs and ECHAM4 GCM‐generated CPs for 1xCO2 and 2xCO2 climate simulations (scenarios). The coupled model ‘CP‐precipitation’ was suitable for precipitation downscaling. The overall methodology was applied to the medium‐sized mountainous Mesochora catchment in Central‐Western Greece. Results reveal substantial differences between the observed maximum daily precipitation statistical patterns and those produced by the two climate scenarios. A variable nonlinear deterministic behaviour characterizes all climate scenarios examined. Transitions’ patterns differ in terms of duration and intensity. The 2xCO2 scenario contains the strongest transitions highlighting an unusual shift between floods and droughts. The implications of the results to the predictability of the phenomenon are also discussed. Copyright © 2013 John Wiley & Sons, Ltd. 相似文献
2.
Abstract A methodology has been developed and applied to an eastern Nebraska, USA, case study to estimate the space-time distribution of daily precipitation under climate change. The approach is based on the analysis both of the type and of the Markov properties of atmospheric circulation patterns (CPs), and a stochastic linkage between daily (here 500 hPa) CP types and daily precipitation events. Historical data and General Circulation Model (GCM) output of daily CPs corresponding to 1 × CO2 and 2 × CO2 are considered. Time series of both local and regional precipitation corresponding to each of those cases were simulated and their statistical properties were compared. Under the dry continental climate of eastern Nebraska, a highly variable spatial response to climate change was obtained. Most of the local and the regional average precipitation values reflect, under 2 × CO2, a somewhat wetter and a more variable precipitation regime in eastern Nebraska. The sensitivity of the results to the GCM utilized should be considered. 相似文献
3.
A comparison of three methods for downscaling daily precipitation in the Punjab region 总被引：1，自引：0，他引：1
Many downscaling techniques have been developed in the past few years for projection of station‐scale hydrological variables from large‐scale atmospheric variables simulated by general circulation models (GCMs) to assess the hydrological impacts of climate change. This article compares the performances of three downscaling methods, viz. conditional random field (CRF), K‐nearest neighbour (KNN) and support vector machine (SVM) methods in downscaling precipitation in the Punjab region of India, belonging to the monsoon regime. The CRF model is a recently developed method for downscaling hydrological variables in a probabilistic framework, while the SVM model is a popular machine learning tool useful in terms of its ability to generalize and capture nonlinear relationships between predictors and predictand. The KNN model is an analogue‐type method that queries days similar to a given feature vector from the training data and classifies future days by random sampling from a weighted set of K closest training examples. The models are applied for downscaling monsoon (June to September) daily precipitation at six locations in Punjab. Model performances with respect to reproduction of various statistics such as dry and wet spell length distributions, daily rainfall distribution, and intersite correlations are examined. It is found that the CRF and KNN models perform slightly better than the SVM model in reproducing most daily rainfall statistics. These models are then used to project future precipitation at the six locations. Output from the Canadian global climate model (CGCM3) GCM for three scenarios, viz. A1B, A2, and B1 is used for projection of future precipitation. The projections show a change in probability density functions of daily rainfall amount and changes in the wet and dry spell distributions of daily precipitation. Copyright © 2011 John Wiley & Sons, Ltd. 相似文献
4.
Downscaling of precipitation for climate change scenarios: A support vector machine approach 总被引：7，自引：0，他引：7
The Climate impact studies in hydrology often rely on climate change information at fine spatial resolution. However, general circulation models (GCMs), which are among the most advanced tools for estimating future climate change scenarios, operate on a coarse scale. Therefore the output from a GCM has to be downscaled to obtain the information relevant to hydrologic studies. In this paper, a support vector machine (SVM) approach is proposed for statistical downscaling of precipitation at monthly time scale. The effectiveness of this approach is illustrated through its application to meteorological sub-divisions (MSDs) in India. First, climate variables affecting spatio-temporal variation of precipitation at each MSD in India are identified. Following this, the data pertaining to the identified climate variables (predictors) at each MSD are classified using cluster analysis to form two groups, representing wet and dry seasons. For each MSD, SVM- based downscaling model (DM) is developed for season(s) with significant rainfall using principal components extracted from the predictors as input and the contemporaneous precipitation observed at the MSD as an output. The proposed DM is shown to be superior to conventional downscaling using multi-layer back-propagation artificial neural networks. Subsequently, the SVM-based DM is applied to future climate predictions from the second generation Coupled Global Climate Model (CGCM2) to obtain future projections of precipitation for the MSDs. The results are then analyzed to assess the impact of climate change on precipitation over India. It is shown that SVMs provide a promising alternative to conventional artificial neural networks for statistical downscaling, and are suitable for conducting climate impact studies. 相似文献
5.
Abstract The regional hydroclimatological effect of global climate change has been estimated and compared using a semi-empirical downscaling method with two versions (T21 and T42) of the general circulation model (GCM) developed at the Max Planck Institute for Meteorology, Germany. The comparisons were performed with daily mean temperature and daily precipitation amounts for the continental climate of the state of Nebraska, USA. Both the T21 and the T42 versions resulted in an increase of daily mean temperature under a 2 x C02 climatess. The magnitude of warming was substantially greater for T21 than for T42, except for February and June and at some stations in July where the T42 model suggested greater warming. Both GCMs resulted in a slight decrease in precipitation frequency and an increase in the amount of precipitation on wet days. Here, the T42 model again led to smaller changes. Different locations within Nebraska exhibited somewhat different temperature and precipitation responses with both GCM versions. 相似文献
6.
Sujeewa Malwila Herath Priyantha Ranjan Sarukkalige Van Thanh Van Nguyen 《水文科学杂志》2013,58(11):2061-2070
ABSTRACTDownscaling of climate projections is the most adapted method to assess the impacts of climate change at regional and local scales. This study utilized both spatial and temporal downscaling approaches to develop intensity–duration–frequency (IDF) relations for sub-daily rainfall extremes in the Perth airport area. A multiple regression-based statistical downscaling model tool was used for spatial downscaling of daily rainfall using general circulation models (GCMs) (Hadley Centre’s GCM and Canadian Global Climate Model) climate variables. A simple scaling regime was identified for 30 minutes to 24 hours duration of observed annual maximum (AM) rainfall. Then, statistical properties of sub-daily AM rainfall were estimated by scaling an invariant model based on the generalized extreme value distribution. RMSE, Nash-Sutcliffe efficiency coefficient and percentage bias values were estimated to check the accuracy of downscaled sub-daily rainfall. This proved the capability of the proposed approach in developing a linkage between large-scale GCM daily variables and extreme sub-daily rainfall events at a given location. Finally IDF curves were developed for future periods, which show similar extreme rainfall decreasing trends for the 2020s, 2050s and 2080s for both GCMs.
Editor M.C. Acreman; Associate editor S. Kanae 相似文献
7.
Large scale climate and rainfall seasonality in a Mediterranean Area: Insights from a non‐homogeneous Markov model applied to the Agro‐Pontino plain 下载免费PDF全文
下载免费PDF全文 Francesco Cioffi Federico Conticello Upmanu Lall Lucia Marotta Vito Telesca 《水文研究》2017,31(3):668-686
In the context of climate change and variability, there is considerable interest in how large scale climate indicators influence regional precipitation occurrence and its seasonality. Seasonal and longer climate projections from coupled ocean–atmosphere models need to be downscaled to regional levels for hydrologic applications, and the identification of appropriate state variables from such models that can best inform this process is also of direct interest. Here, a Non‐Homogeneous Hidden Markov Model (NHMM) for downscaling daily rainfall is developed for the Agro‐Pontino Plain, a coastal reclamation region very vulnerable to changes of hydrological cycle. The NHMM, through a set of atmospheric predictors, provides the link between large scale meteorological features and local rainfall patterns. Atmospheric data from the NCEP/NCAR archive and 56‐years record (1951–2004) of daily rainfall measurements from 7 stations in Agro‐Pontino Plain are analyzed. A number of validation tests are carried out, in order to: 1) identify the best set of atmospheric predictors to model local rainfall; 2) evaluate the model performance to capture realistically relevant rainfall attributes as the inter‐annual and seasonal variability, as well as average and extreme rainfall patterns. Validation tests show that the best set of atmospheric predictors are the following: mean sea level pressure, temperature at 1000 hPa, meridional and zonal wind at 850 hPa and precipitable water, from 20°N to 80°N of latitude and from 80°W to 60°E of longitude. Furthermore, the validation tests show that the rainfall attributes are simulated realistically and accurately. The capability of the NHMM to be used as a forecasting tool to quantify changes of rainfall patterns forced by alteration of atmospheric circulation under climate change and variability scenarios is discussed. 相似文献
8.
近几年来,国家气候中心己经建立了中国主要四大流域气候对水资源影响评估的模式框架.本文拟进一步证明其中之一的两参数分布式月水量平衡水文模式对长江之上汉江和赣江两子流域径流的模拟能力,结果表明该水文模式对目前气候条件下径流模拟效果较好,运行稳定,可用于实时业务运行.在此基础上,利用ECHAM4和HadCM2两GCM(General Circulation Model)未来气候情景模拟结果及目前实测气候情况,对汉江和赣江两子流域的径流对未来气候变化的敏感性进行评估.经检验,两GCM对未来气候,特别是降水情景模拟存在一定差异,因此,造成径流对气候变化的响应不同,这充分反映了全球模式模拟结果不确定性在气候变化影响研究中的重要性. 相似文献
9.
Suryun Ham Song-You Hong Young-Hwa Byun Jhoon Kim 《Journal of Atmospheric and Solar》2009,71(17-18):1924-1934
The purpose of this study is to investigate the effects of precipitation physics in a general circulation model (GCM) on a simulated climate. Experiments are performed under the single column model (SCM) framework to examine basic features and under the general circulation model framework to investigate the impact on seasonal simulation. The SCM simulation shows that convection processes in the model have a considerable influence on the change in vertical thermodynamic structure, resulting in a change in precipitation, whereas in the GCM framework stratiform precipitation physics play a distinct role in changing the atmospheric structure. The GCM experiments also show that the overall reduction of precipitation in simulations with prognostic stratiform precipitation physics is highly related to changes in cloudiness and corresponding changes in radiative flux, which in turn leads to the reduction of convective activities. 相似文献
10.
Potential hydrological impacts of climate change on long‐term water balances were analysed for Harp Lake and its catchment. Harp Lake is located in the boreal ecozone of Ontario, Canada. Two climate change scenarios were used. One was based on extrapolation of long‐term trends of monthly temperature and precipitation from a 129‐year data record, and another was based on a Canadian general circulation model (GCM) predictions. A monthly water balance model was calibrated using 26 years of hydrological and meteorological data, and the model was used to calculate hydrological impact under two climate change scenarios. The first scenario with a warmer and wetter climate predicted a smaller magnitude of change than the second scenario. The first scenario showed an increase in evaporation each month, an increase in catchment runoff in summer, fall and winter, but a decrease in spring, resulting in a slight increase in lake level. Annual runoff and lake level would increase because the precipitation change overrides evaporation change. The second scenario with a warmer, drier climate predicted a greater change, and indicated that evaporation would increase each month, runoff would increase in many months, but would decrease in spring, causing the lake level to decrease slightly. Annual runoff and lake level would decrease because evaporation change overrides precipitation change. In both scenarios, the water balance changes in winter and spring are pronounced. Copyright © 2009 John Wiley & Sons, Ltd. 相似文献
11.
AbstractAdequate water resources management at the basin level needs quality downscaling of climate change scenarios for application to impact assessment and adaptation work. This study evaluates the ability of a regional climate model (RegCM3) to simulate the present-day climate and regional water balance over the Niger River Basin (NRB). RegCM3 gives a good simulation of the NRB hydroclimatic features. The mean bias error for monthly temperature is 1.5°C, 0.3 mm d-1 for rainfall, and 0.4 mm d-1 for runoff. Moderate to high correlations (0.66–0.95) were found between the modelled and the observed variables. RegCM3-based water cycling indices were not statistically different from the observation. Seasonal moistening efficiency (m) ranges between 19% and 37%; 66% of the available atmospheric moisture over NRB precipitates between June and September, of which 21% originates from local evaporation. The result suggests that the moisture sink period is July to October with very high precipitation efficiency over the basin. The model reproduces the hydroclimatology of the NRB and hence is a suitable tool for further studies relating to the assessment of climate change impacts on river basin water systems.
Editor Z. W. Kundzewicz; Associate editor D. Hughes 相似文献
12.
L. J. TISON 《水文科学杂志》2013,58(1):5-8
Abstract A simple method is used to study the response of runoff in the Sahel to climate change. The statistical characteristics of rainfall are calculated over the western part of the Sahel for the period 1961–1990, using the BADOPLU network. Daily rainfall is simulated using a Markov process with Weibull distribution for rainfall depths. Runoff is modelled using a conceptual SCS model and the curve numbers are calculated for West Africa. Climate change is provided by simulations using the Arpège GCM (Scenario A1B), and a perturbation method is used on the parameters which describe the rainfall. Changes in rainfall are assumed to occur through increases in frequency, not intensity. Using Arpège, runoff is mainly found to increase, in depth and in number of events, by the end of the 21st century. Changes in evaporation and land use are not included in the analysis. The impact of this 21st century potential climate change (rainfall) on the runoff is found to be of the same magnitude as the impact of changes in land use. 相似文献
13.
Climate and land use changes greatly modify hydrologic regimes. In this paper, we modelled the impacts of biofuel cultivation in the US Great Plains on a 1061‐km2 watershed using the Soil and Water Assessment Tool (SWAT) hydrologic model. The model was calibrated to monthly discharges spanning 2002–2010 and for the winter, spring, and summer seasons. SWAT was then run for a climate‐change‐only scenario using downscaled precipitation and a projected temperature for 16 general circulation model (GCM) runs associated with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios A2 scenario spanning 2040–2050. SWAT was also run on a climate change plus land use change scenario in which Alamo switchgrass (Panicum virgatum L.) replaced native range grasses, winter wheat, and rye (89% of the basin). For the climate‐change‐only scenario, the GCMs agreed on a monthly temperature increase of 1–2 °C by the 2042–2050 period, but they disagreed on the direction of change in precipitation. For this scenario, decreases in surface runoff during all three seasons and increases in spring and summer evapotranspiration (eT) were driven predominantly by precipitation. Increased summer temperatures also significantly contributed to changes in eT. With the addition of switchgrass, changes in surface runoff are amplified during the winter and summer, and changes in eT are amplified during all three seasons. Depending on the GCM utilized, either climate change or land use change (switchgrass cultivation) was the dominant driver of change in surface runoff while switchgrass cultivation was the major driver of changes in eT. Copyright © 2014 John Wiley & Sons, Ltd. 相似文献
14.
Impact of climate change on 24‐h design rainfall depth estimation in Qiantang River Basin,East China
The frequency and magnitude of extreme meteorological or hydrological events such as floods and droughts in China have been influenced by global climate change. The water problem due to increasing frequency and magnitude of extreme events in the humid areas has gained great attention in recent years. However, the main challenge in the evaluation of climate change impact on extreme events is that large uncertainty could exist. Therefore, this paper first aims to model possible impacts of climate change on regional extreme precipitation (indicated by 24‐h design rainfall depth) at seven rainfall gauge stations in the Qiantang River Basin, East China. The Long Ashton Research Station‐Weather Generator is adopted to downscale the global projections obtained from general circulation models (GCMs) to regional climate data at site scale. The weather generator is also checked for its performance through three approaches, namely Kolmogorov–Smirnov test, comparison of L‐moment statistics and 24‐h design rainfall depths. Future 24‐h design rainfall depths at seven stations are estimated using Pearson Type III distribution and L‐moment approach. Second, uncertainty caused by three GCMs under various greenhouse gas emission scenarios for the future periods 2020s (2011–2030), 2055s (2046–2065) and 2090s (2080–2099) is investigated. The final results show that 24‐h design rainfall depth increases in most stations under the three GCMs and emission scenarios. However, there are large uncertainties involved in the estimations of 24‐h design rainfall depths at seven stations because of GCM, emission scenario and other uncertainty sources. At Hangzhou Station, a relative change of ?16% to 113% can be observed in 100y design rainfall depths. Copyright © 2012 John Wiley & Sons, Ltd. 相似文献
15.
ABSTRACT Rainfall events largely control hydrological processes occurring on and in the ground, but the performance of climate models in reproducing rainfall events has not been investigated enough to guide selection among the models when making hydrological projections. We proposed to compare the durations, intensities, and pause periods, as well as depths of rainfall events when assessing the accuracy of general circulation models (GCMs) in reproducing the hydrological characteristics of observed rainfall. We also compared the sizes of design storm events and the frequency and severity of drought to demonstrate the consequences of GCM selection. The results show that rainfall and extreme hydrological event projections could significantly vary depending on climate model selection and weather stations, suggesting the need for a careful and comprehensive evaluation of GCM in the hydrological analysis of climate change. The proposed methods are expected to help to improve the accuracy of future hydrological projections for water resources planning. 相似文献
16.
This research investigates the potential impacts of climate change on stormwater quantity and quality generated by urban residential areas on an event basis in the rainy season. An urban residential stormwater drainage area in southeast Calgary, Alberta, Canada is the focus of future climate projections from general circulation models (GCMs). A regression‐based statistical downscaling tool was employed to conduct spatial downscaling of daily precipitation and daily mean temperature using projection outputs from the coupled GCM. Projected changes in precipitation and temperature were applied to current climate scenarios to generate future climate scenarios. Artificial neural networks (ANNs) developed for modelling stormwater runoff quantity and quality used projected climate scenarios as network inputs. The hydrological response to climate change was investigated through stormwater runoff volume and peak flow, while the water quality responses were investigated through the event mean value (EMV) of five parameters: turbidity, conductivity, water temperature, dissolved oxygen (DO) and pH. First flush (FF) effects were also noted. Under future climate scenarios, the EMVs of turbidity increased in all storms except for three events of short duration. The EMVs of conductivity were found to decline in small and frequent storms (return period < 5 years); but conductivity EMVs were observed to increase in intensive events (return period ≥ 5 years). In general, an increasing EMV was observed for water temperature, whereas a decreasing trend was found for DO EMV. No clear trend was found in the EMV of pH. In addition, projected future climate scenarios do not produce a stronger FF effect on dissolved solids and suspended solids compared to that produced by the current climate scenario. Copyright © 2010 John Wiley & Sons, Ltd. 相似文献
17.
K. Y. Raneesh 《水文科学杂志》2013,58(6):946-965
Abstract Climate change is recognized to be one of the most serious challenges facing mankind today. Driven by anthropogenic activities, it is known to be a direct threat to our food and water supplies and an indirect threat to world security. Increase in the concentration of carbon dioxide and other greenhouse gases in the atmosphere will certainly affect hydrological regimes. The consequent global warming is expected to have major implications on water resources management. The objective of this research is to present a general approach for evaluating the impacts of potential climate change on streamflow in a river basin in the humid tropical zone of India. Large-scale global climate models (GCMs) are the best available tools to provide estimates of the effect of rising greenhouse gases on rainfall and temperature. However the spatial resolution of these models (250 km?×?250 km) is not compatible with that of watershed hydrological models. Hence the outputs from GCMs have to be downscaled using regional climate models (RCMs), so as to project the output of a GCM to a finer resolution (50 km?×?50 km). In the present work, the projections of a GCM for two scenarios, A2 and B2 are downscaled by a RCM to project future climate in a watershed. Projections for two important climate variables, viz. rainfall and temperature are made. These are then used as inputs for a physically-based hydrological model, SWAT, in order to evaluate the effect of climate change on streamflow and vegetative growth in a humid tropical watershed. Citation Raneesh, K. Y. & Santosh, G. T. (2011) A study on the impact of climate change on streamflow at the watershed scale in the humid tropics. Hydrol. Sci. J. 56(6), 946–965. 相似文献
18.
《水文科学杂志》2013,58(4):727-738
Abstract Projected warming in equatorial Africa, accompanied by greater evaporation and more frequent heavy precipitation events, may have substantial but uncertain impacts on terrestrial hydrology. Quantitative analyses of climate change impacts on catchment hydrology require high-resolution (<50 km) climate data provided by regional climate models (RCMs). We apply validated precipitation and temperature data from the RCM PRECIS (Providing Regional Climates for Impact Studies) to a semi-distributed soil moisture balance model (SMBM) in order to quantify the impacts of climate change on groundwater recharge and runoff in a medium-sized catchment (2098 km2) in the humid tropics of southwestern Uganda. The SMBM explicitly accounts for changes in soil moisture, and partitions effective precipitation into groundwater recharge and runoff. Under the A2 emissions scenario (2070–2100), climate projections from PRECIS feature not only rises in catchment precipitation and modelled potential evapotranspiration by 14% and 53%, respectively, but also increases in rainfall intensity. We show that the common application of the historical rainfall distribution using delta factors to the SMBM grossly underestimates groundwater recharge (i.e. 55% decrease relative to the baseline period of 1961–1990). By transforming the rainfall distribution to account for changes in rainfall intensity, we project increases in recharge and runoff of 53% and 137%, respectively, relative to the baseline period. 相似文献
19.
Nationwide changes in spatially well‐resolved patterns of British runoff were investigated under two climate change scenarios derived from general circulation model (GCM) output. A physical process‐based hydrological model (HYSIM) was used to simulate effective runoff across a 10 km×10 km British grid under baseline and future climate conditions. A gridded baseline climatology for precipitation and the Penman variables was used to validate HYSIM across Britain using grid cell‐specific parameters derived from land use and soil type. The climate change scenarios were constructed from the Hadley Centre's high resolution equilibrium GCM (UKHI) for 2050 and transient GCM (UKTR) for 2065. Future effective runoff was simulated under both scenarios by applying changes in precipitation and the Penman variables to the baseline climatology. Annual effective runoff is shown to increase throughout most of Britain under the UKHI scenario for 2050, whilst it decreases over much of England and Wales under the UKTR scenario for 2065. Both scenarios show an increasing gradient in runoff between a wetter northern Britain and a drier south‐eastern Britain. This gradient is more pronounced under the UKTR scenario. Changes in effective runoff for winter and summer show an increase in seasonality under both scenarios. Winter runoff is shown to increase most in northern Britain under both scenarios, whilst summer runoff is shown to experience major reductions over much of England and Wales under the UKTR scenario. If these simulations are realized, Britain may expect an accentuated north to south‐east imbalance in available water resources. If this is combined with a temporal imbalance suggested by the increased seasonality, there could be problems for the future management of British water resources. Copyright © 1999 John Wiley & Sons, Ltd. 相似文献
20.
Groundwater systems in arid regions will be particularly sensitive to climate change owing to the strong dependence of rates of evapotranspiration on temperature, and shifts in the precipitation regimes. Irrigation use in these arid regions is typically a large component of the water budget, and may increase due to changes in soil moisture resulting from higher temperatures and changes in the timing of precipitation events. In this study, future predicted climate change scenarios from three global climate models (CGCM1 GHG+A1, CGCM3.1 A2, and HadCM3 A2) are used to determine the sensitivity of recharge to different climate models in an irrigated agricultural region. The arid Oliver region (annual precipitation 300 mm) in the Okanagan Basin, British Columbia, is used to demonstrate the approach. Irrigation return flow, as a contribution to total diffuse recharge, is simulated by calculating the daily applied irrigation based on estimates of seasonal crop water demand and the forecasted precipitation and evaporation data. The relative contribution of irrigation return flow to groundwater recharge under current and future climate conditions is modelled. Temperature data were downscaled using Statistical Downscaling Model (SDSM), while precipitation and solar radiation changes were estimated directly from the GCM data. Shifts in climate, from present to future predicted, were applied to a stochastic weather generator, and used to force a one-dimensional hydrologic model, HELP 3.80D. Results were applied spatially, according to different soil profiles, slope and vegetation, over a 22.5 km by 8.6 km region. Changes to recharge in future time periods for each GCM result in modest increases of recharge with the peak recharge shifting from March to February. Lower recharge rates and higher potential evapotranspiration rates are similarly predicted by all three models for the summer months. All scenarios show that the potential growing season will expand between 3 and 4 weeks due to increases in temperature. However, the magnitude of the change varies considerably between models. CGCM3.1 has the largest increases of recharge rates, CGCM1 has very minor increases, and HadCM3 is relatively stable (as indicated by the near-zero changes between climate states). The significant differences between these three models indicate that prediction of future recharge is highly dependent on the model selected. The minor increase of annual recharge in future predicted climate states is due the shift of peak recharge from increased temperature. Irrigation rates dominate total recharge during the summer months in this arid area. Recharge in irrigated areas is significantly higher than natural recharge, with irrigation return flow between 25% and 58%. A comparison of recharge results for the least efficient and the most efficient irrigation systems indicates that the latter are more sensitive to choice of GCM. 相似文献