Mapping of climatic parameters under climate change impacts in Iran

ABSTRACT

This research aims to provide a comprehensive evaluation of climate change effects on temperature, precipitation and potential evapotranspiration over the country of Iran for the time periods 2010–2039, 2040–2069 and 2070–2099, and under scenarios A2 and B2. After preparation of measured temperature and precipitation data and calculation of potential evapotranspiration for the base time period of 1960–1990 for 46 meteorological stations (with a nationwide distribution), initial zoning of these three parameters over the country was attempted. Maximum and minimum temperatures and values of precipitation were obtained from the HadCM3 model under scenarios A2 and B2 for the three time periods, and these data were downscaled. Corresponding maps were prepared for the three parameters in the three time periods, and spatial and temporal variations of these climatic parameters under scenarios A2 and B2 were extracted and interpreted. Results showed that the highest increase in temperature would occur in western parts of the country, but the highest increase of potential evapotranspiration would occur in the central region of Iran. However, precipitation would vary temporally and spatially in different parts of the country depending on the scenario used and the time period selected.

Editor Z. W. Kundzewicz; Associate editor not assigned     

Modelling regional impacts of climate change on water resources: the Júcar basin,Spain

Abstract

In this paper we analyse all currently available simulated climate scenarios, proposed by the Spanish Agency of Meteorology (AEMET), for the period 2010–2040 on the geographical area covered by the Júcar River basin, located in eastern Spain. This is done through the validation of these scenarios using historical records, and by assessing the impact on water resources for the next 30 years by means of a hydrological model. By taking the period 1960–1990 as the control period, a careful comparison of its historical records against AEMET scenarios is performed. Although temperature records are modelled properly, precipitation data are widely underestimated in a range from 8% to 29%. This wide variability observed in the control period is also found in the precipitation scenarios for the period 2010–2040. The impact on water resources shows a great degree of dispersion, ranging from –13.45% to 18.1% with a mean value of –2.13%.

Editor Z.W. Kundzewicz; Associate editor F. Hattermann     

Climate change impacts on surface water resources in the Rheraya catchment (High Atlas,Morocco)

This study aimed to quantify possible climate change impacts on runoff for the Rheraya catchment (225 km²) located in the High Atlas Mountains of Morocco, south of Marrakech city. Two monthly water balance models, including a snow module, were considered to reproduce the monthly surface runoff for the period 1989?2009. Additionally, an ensemble of five regional climate models from the Med-CORDEX initiative was considered to evaluate future changes in precipitation and temperature, according to the two emissions scenarios RCP4.5 and RCP8.5. The future projections for the period 2049?2065 under the two scenarios indicate higher temperatures (+1.4°C to +2.6°C) and a decrease in total precipitation (?22% to ?31%). The hydrological projections under these climate scenarios indicate a significant decrease in surface runoff (?19% to ?63%, depending on the scenario and hydrological model) mainly caused by a significant decline in snow amounts, related to reduced precipitation and increased temperature. Changes in potential evapotranspiration were not considered here, since its estimation over long periods remains a challenge in such data-sparse mountainous catchments. Further work is required to compare the results obtained with different downscaling methods and different hydrological model structures, to better reproduce the hydro-climatic behaviour of the catchment.

EDITOR M.C. Acreman

ASSOCIATE EDITOR R. Hirsch     

Regional precipitation and temperature scenarios for climate change

Abstract

To investigate the consequences of climate change on the water budget in small catchments, it is necessary to know the change of local precipitation and temperature. General Circulation Models (GCM) cannot provide regional climate parameters yet, because of their coarse resolution and imprecise modelling of precipitation. Therefore downscaling of precipitation and temperature has to be carried out from the GCM grids to a small scale of a few square kilometres. Daily rainfall and temperature are modelled as processes conditioned on atmospheric circulation. Rainfall is linked to the circulation patterns (CPs) using conditional probabilities and conditional rainfall amount distribution. Both temperature and precipitation are downscaled to several locations simultaneously taking into account the CP dependent spatial correlation. Temperature is modelled using a simple autoregressive approach, conditioned on atmospheric circulation and local areal precipitation. The model uses the classification scheme of the German Weather Service and a fuzzy rule-based classification. It was applied in the Aller catchment for validation using observed rainfall and temperature, and observed classified geopotential pressure heights. GCM scenarios of the ECHAM model were used to make climate change predictions (using classified GCM geopotential heights); simulated values agree fairly well with historical data. Results for different GCM scenarios are shown.     

Water balance of Lake Victoria: update to 2000 and climate change modelling to 2100 / Bilan hydrologique du Lac Victoria: mise à jour jusqu’en 2000 et modélisation des impacts du changement climatique jusqu’en 2100

Abstract

Abstract An annual water balance model of Lake Victoria is derived for the period 1925–2000. Regression techniques are used to derive annual inputs to the water balance, based on lake rainfall data, measured and derived inflows and estimated evaporation during the historical period. This approach acknowledges that runoff is a nonlinear function of lake rainfall. A longer inflow series is produced here which is representative of the whole inflow to the lake, rather than just from individual tributaries. The results show a good simulation of annual lake levels and outflows and capture the high lake level in 1997–1998. Climate change scenarios, from a recent global climate model experiment, are applied to the lake rainfall inflow series and evaporation data to estimate future water balances of the lake. The scenarios produce a potential fall in lake levels by the 2030s horizon, and a rise by the 2080s horizon. A discussion of the application of climate change data to this complex hydrological system is presented.     

Simulating precipitation in the Northeast United States using a climate-informed K-nearest neighbour algorithm

Decadal prediction using climate models faces long-standing challenges. While global climate models may reproduce long-term shifts in climate due to external forcing, in the near term, they often fail to accurately simulate interannual climate variability, as well as seasonal variability, wet and dry spells, and persistence, which are essential for water resources management. We developed a new climate-informed K-nearest neighbour (K-NN)-based stochastic modelling approach to capture the long-term trend and variability while replicating intra-annual statistics. The climate-informed K-NN stochastic model utilizes historical data along with climate state information to provide improved simulations of weather for near-term regional projections. Daily precipitation and temperature simulations are based on analogue weather days that belong to years similar to the current year's climate state. The climate-informed K-NN stochastic model is tested using 53 weather stations in the Northeast United States with an evident monotonic trend in annual precipitation. The model is also compared to the original K-NN weather generator and ISIMIP-2b GFDL general circulation model bias-corrected output in a cross-validation mode. Results indicate that the climate-informed K-NN model provides improved simulations for dry and wet regimes, and better uncertainty bounds for annual average precipitation. The model also replicates the within-year rainfall statistics. For the 1961–1970 dry regime, the model captures annual average precipitation and the intra-annual coefficient of variation. For the 2005–2014 wet regime, the model replicates the monotonic trend and daily persistence in precipitation. These improved modelled precipitation time series can be used for accurately simulating near-term streamflow, which in turn can be used for short-term water resources planning and management.     

Projections of future deterioration in UK river quality are hampered by climatic uncertainty under extreme conditions

ABSTRACT

A modelling study was undertaken to quantify effects that the climate likely to prevail in the 2050s might have on water quality in two contrasting UK rivers. In so doing, it pinpointed the extent to which time series of climate model output, for some variables derived following bias correction, are fit for purpose when used as a basis for projecting future water quality. Working at daily time step, the method involved linking regional climate model (HadRM3-PPE) projections, Future Flows Hydrology (rainfall–runoff modelling) and the QUESTOR river network water quality model. In the River Thames, the number of days when temperature, dissolved oxygen, biochemical oxygen demand and phytoplankton exceeded undesirable values (>25°C, <6 mg L^?1, >4 mg L^?1 and >0.03 mg L^?1, respectively) was estimated to increase by 4.1–26.7 days per year. The changes do not reflect impacts of any possible change in land use or land management. In the River Ure, smaller increases in occurrence of undesirable water quality are likely to occur in the future (by 1.0–11.5 days per year) and some scenarios suggested no change. Results from 11 scenarios of the hydroclimatic inputs revealed considerable uncertainty around the levels of change, which prompted analysis of the sensitivity of the QUESTOR model to simulations of current climate and hydrology. Hydrological model errors were deemed of less significance than those associated with the derivation and downscaling of driving climatic variables (rainfall, air temperature and solar radiation). Errors associated with incomplete understanding of river water quality interactions with the aquatic ecosystem were found likely to be more substantial than those associated with hydrology, but less than those related to climate model inputs. These errors are largely a manifestation of uncertainty concerning the extent to which phytoplankton biomass is controlled by invertebrate grazers, particularly in mid-summer; and the degree to which this varies from year to year. The quality of data from climate models for generating flows and defining driving variables at the extremes of their distributions has been highlighted as the major source of uncertainty in water quality model outputs.

EDITOR A. Castellarin; ASSOCIATE EDITOR X. Fang     

European precipitation connections with large-scale mean sea-level pressure (MSLP) fields

Abstract

To advance understanding of hydroclimatological processes, this paper links spatiotemporal variability in gridded European precipitation and large-scale mean sea-level pressure (MSLP) time series (1957–2002) using monthly concurrent correlation. Strong negative (positive) correlation near Iceland and (the Azores) is apparent for precipitation in northwest Europe, confirming a positive North Atlantic Oscillation (NAO) association. An opposing pattern is found for southwest Europe, and the Mediterranean in winter. In the lee of mountains, MSLP correlation is lower reflecting reduced influence of westerlies on precipitation generation. Importantly, European precipitation is shown to be controlled by physically interpretable climate patterns that change in extent and position from month to month. In spring, MSLP–precipitation correlation patterns move and shrink, reaching a minimum in summer, before expanding in the autumn, and forming an NAO-like dipole in winter. These space–time shifts in correlation regions explain why fixed-point NAO indices have limited ability to resolve precipitation for some European locations and seasons.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Lavers, D., Prudhomme, C., and Hannah, D.M., 2013. European precipitation connections with large-scale mean sea-level pressure (MSLP) fields. Hydrological Sciences Journal, 58 (2), 310–327.     

Projection of surface water resources in the context of climate change in typical regions of China

Climate change and its impact on hydrological processes are overarching issues that have brought challenges for sustainable water resources management. In this study, surface water resources in typical regions of China are projected in the context of climate change. A water balance model based on the Fu rational function equation is established to quantify future natural runoff. The model is calibrated using data from 13 hydrological stations in 10 first-class water resources zones of China. The future precipitation and temperature series come from the ISI-MIP (Inter-Sectoral Impact Model Intercomparison Project) climate dataset. Taking natural runoff for 1961–1990 as a baseline, the impacts of climate change on natural runoff are studied under three emissions scenarios: RCP2.6, RCP4.5 and RCP8.5. Simulated results indicate that the arid and semi-arid region in the northern part of China is more sensitive to climate change compared to the humid and semi-humid region in the south. In the near future (2011–2050), surface water resources will decrease in most parts of China (except for the Liaozhong and Daojieba catchments), especially in the Haihe River Basin and the middle reaches of the Yangtze River Basin. The decrement of surface water resources in the northern part of China is more than that in the southern part. For the periods 2011–2030 and 2031–2050, surface water resources are expected to decrease by 12–13% in the northern part of China, while those in the southern part will decrease by 7–10%.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR R. Hirsch     

Announcements

ABSTRACT

Global climate variations are expected to cause serious challenges to water resources planning and management, including an increase in sea level, abrupt changes in rainfall patterns and changes in ecosystems. This study evaluates impacts of mid-century climate variability as projected by climate models in the Haw River watershed, which contributes significantly to Jordan Lake, a major source of drinking water supply in central North Carolina, USA. The watershed-based hydrological model, Soil and Water Assessment Tool (SWAT), was successfully calibrated with very good to excellent performance. Projected precipitation and temperature information for 2040–2069 from four dynamically downscaled regional climate models (RCMs) was used to force the SWAT modeling set-up of the watershed. On a long-term basis, a 38% decrease in the precipitation in early fall is expected while spring months are expected to receive 30% higher precipitation compared to the baseline condition (1980–2009). Water yield was found to increase in spring months, with a maximum of 74% increase on average. Summer months are expected to have on average 8% higher evapotranspiration (ET) than the baseline. Analysis of the change in average monthly streamflow at the watershed outlet (which leads to Lake Jordan) shows that there might be, on average, an 80% increase in streamflow in spring months (February, March, April and May), with the greatest increase (107%) in May. In general, simulation results indicated that the hydrological response of the watershed is very sensitive to the potential variation in climate (precipitation and temperature), with precipitation being one of the decisive factors in water yield increase.

Editor Z.W. Kundzewicz Associate editor N. Verhoest     

Standard normal homogeneity test as a tool to detect change points in climate-related river discharge variation: case study of the Kupa River Basin

ABSTRACT

The study addresses homogeneity testing of annual discharge time series for eight hydrological stations and five annual climate time series for one weather station in the Kupa River Basin, between Slovenia and Croatia, and global annual average surface temperature time series for the period 1961–2010. The standard normal homogeneity test (SNHT) was used to detect both abrupt and gradual linear trend homogeneity breaks. The results reveal natural change points at the beginning of the 1980s. Absolute homogeneity testing of average annual weather station-level air pressure, annual precipitation, differences between precipitation totals and potential evapotranspiration and surface runoff from the independent observation time series confirmed an abrupt shift, also at the beginning of the 1980s. The trend of local air temperature for 1985–2000, which partly coincides with global surface temperature trend for 1974–2005, strengthened the river discharge regime shift since the beginning of the 1980s. These results could improve climate variation monitoring and estimation of the impact of climate variation on the environment in the area. Generally, an indication of climate regime change points and an assessment of their duration could provide significant benefits for the society.     

Hydrological sciences—society's needs

Abstract

The hydrological regime of a mountainous catchment, in this instance the Mesochora catchment in Central Greece, was simulated for altered climates resulting when using the Goddard Institute for Space Studies (GISS) model for carbon dioxide doubling. The catchment snow water equivalent was predicted on the basis of the snow accumulation and ablation model of the US National Weather Service River Forecast System (NWSRFS), while the catchment runoff, as well as actual evapotranspiration and soil moisture storages, were simulated through application of the soil moisture accounting model of NWSRFS. Two scenarios of monthly climate change were drawn from the GISS model, one associated with temperature and precipitation changes, while the other referred to temperature changes alone. A third hypothetical scenario with temperature and precipitation changes similar to those corresponding to the mean monthly GISS scenarios was used to test the sensitivity of the monthly climate change of the hypothetical case on catchment hydrology. All three scenarios projected decreases in average snow accumulations and in spring and summer runoff and soil moisture, as well as increases in winter runoff and soil moisture storage and spring evapotranspiration.     

Climate impacts on global irrigation requirements under 19 GCMs,simulated with a vegetation and hydrology model

Abstract

This study quantifies global changes in irrigation requirements for areas presently equipped for irrigation of major crop types, using climate projections from 19 GCMs up to the 2080s. Analysis is based on results from the global eco-hydrological model LPJmL that simulates the complex and dynamic interplay of direct and indirect climate change effects upon irrigation requirements. We find a decrease in global irrigation demand by ～17% in the ensemble median, due to a combination of beneficial CO₂ effects on plants, shorter growing periods and regional precipitation increases. In contrast, increases of >20% are projected with a high likelihood (i.e. in more than two thirds of the climate change scenarios) for some regions, including southern Europe, and, with a lower likelihood, for parts of Asia and North America as well. If CO₂ effects were not accounted for, however, global irrigation demand would hardly change, and increases would prevail in most regions except for southern Asia (where higher precipitation is projected). We stress that the CO₂ effects may not be realized everywhere, that irrigation requirements will probably increase further due to growing global food demand (not considered here), and that a significant amount of water to meet future irrigation requirements will have to be taken from fossil groundwater, environmental flow reserves or diverted rivers.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Konzmann, M., Gerten, D., and Heinke, J., 2013. Climate impacts on global irrigation requirements under 19 GCMs, simulated with a vegetation and hydrology model. Hydrological Sciences Journal, 58 (1), 1–18.     

Climate change impacts on extreme precipitation of water supply area in Istanbul: use of ensemble climate modelling and geo-statistical downscaling

ABSTRACT

Numerous statistical downscaling models have been applied to impact studies, but none clearly recommended the most appropriate one for a particular application. This study uses the geographically weighted regression (GWR) method, based on local implications from physical geographical variables, to downscale climate change impacts to a small-scale catchment. The ensembles of daily precipitation time series from 15 different regional climate models (RCMs) driven by five different general circulation models (GCMs), obtained through the European Union (EU)-ENSEMBLES project for reference (1960–1990) and future (2071–2100) scenarios are generated for the Omerli catchment, in the east of Istanbul city, Turkey, under scenario A1B climate change projections. Special focus is given to changes in extreme precipitation, since such information is needed to assess the changes in the frequency and intensity of flooding for future climate. The mean daily precipitation from all RCMs is under-represented in the summer, autumn and early winter, but it is overestimated in late winter and spring. The results point to an increase in extreme precipitation in winter, spring and summer, and a decrease in autumn in the future, compared to the current period. The GWR method provides significant modifications (up to 35%) to these changes and agrees on the direction of change from RCMs. The GWR method improves the representation of mean and extreme precipitation compared to RCM outputs and this is more significant, particularly for extreme cases of each season. The return period of extreme events decreases in the future, resulting in higher precipitation depths for a given return period from most of the RCMs. This feature is more significant with downscaling. According to the analysis presented, a new adaption for regulating excessive water under climate change in the Omerli basin may be recommended.     

A water balance model to estimate climate change impact on groundwater recharge in Yucatan Peninsula,Mexico

ABSTRACT

The aim of this paper is to estimate the effect that climate change will have on groundwater recharge at the Yucatan Peninsula, Mexico. The groundwater recharge is calculated from a monthly water balance model considering eight methods of potential and actual evapotranspiration. Historical data from 1961–2000 and climate model outputs from five downscaled general circulation models in the near horizon (2015–2039), with representative concentration pathway (RCP) 4.5 and 8.5 are used. The results estimate a recharge of 118 ± 33 mm·year^–1 (around 10% of precipitation) in the historical period. Considering the uncertainty from GCMs under different RCP and evapotranspiration scenarios, our monthly water balance model estimates a groundwater recharge of 92 ± 40 mm·year^–1 (RCP4.5) and 94 ± 38 mm·year^–1 (RCP8.5) which represent a reduction of 23% and 20%, respectively, a result that threatens the socio-ecological balance of the region.     

Assessing climate change impacts on the ecohydrology of the Jinghe River basin in the Loess Plateau,China

Abstract

Quantifying the impacts of climate change on the hydrology and ecosystem is important in the study of the Loess Plateau, China, which is well known for its high erosion rates and ecosystem sensitivity to global change. A distributed ecohydrological model was developed and applied in the Jinghe River basin of the Loess Plateau. This model couples the vegetation model, BIOME BioGeochemicalCycles (BIOME-BGC) and the distributed hydrological model, Water and Energy transfer Process in Large river basins (WEP-L). The WEP-L model provided hydro-meteorological data to BIOME-BGC, and the vegetation parameters of WEP-L were updated at a daily time step by BIOME-BGC. The model validation results show good agreement with field observation data and literature values of leaf area index (LAI), net primary productivity (NPP) and river discharge. Average climate projections of 23 global climate models (GCMs), based on three emissions scenarios, were used in simulations to assess future ecohydrological responses in the Jinghe River basin. The results show that global warming impacts would decrease annual discharge and flood season discharge, increase annual NPP and decrease annual net ecosystem productivity (NEP). Increasing evapotranspiration (ET) due to air temperature increase, as well as increases in precipitation and LAI, are the main reasons for the decreasing discharge. The increase in annual NPP is caused by a greater increase in gross primary productivity (GPP) than in plant respiration, whilst the decrease in NEP is caused by a larger increase in heterotrophic respiration than in NPP. Both the air temperature increase and the precipitation increase may affect the changes in NPP and NEP. These results present a serious challenge for water and land management in the basin, where mitigation/adaption measures for climate change are desired.

Editor Z.W. Kundzewicz; Associate editor D. Yang

Citation Peng, H., Jia, Y.W., Qiu, Y.Q., and Niu, C.W., 2013. Assessing climate change impacts on the ecohydrology of the Jinghe River basin in the Loess Plateau, China. Hydrological Sciences Journal, 58 (3), 651–670.     

Assessing groundwater sustainability under changing climate using isotopic tracers and climate modelling,southwest Ohio,USA

Groundwater, an essential resource, is likely to change with global warming because of changes in the CO₂ levels, temperature and precipitation. Here, we combine water isotope geochemistry with climate modelling to examine future groundwater recharge in southwest Ohio, USA. We first establish the stable isotope profiles of oxygen and deuterium in precipitation and groundwater. We then use an isotope mass balance model to determine seasonal groundwater recharge from precipitation. Climate model output is used to project future changes in precipitation and its seasonal distribution under medium and high climate change scenarios. Finally, these results are combined to examine future changes in groundwater recharge. We find that 76% of the groundwater recharge occurs in the cool season. Climate models project precipitation increase in the cool season and decrease in the warm season. The total groundwater recharge is expected to increase by 3.2% (8.8%) under the medium (high) climate change scenarios.     

Changes to flow regime on the Niger River at Koulikoro under a changing climate

Abstract

A significant decrease in mean river flow as well as shifts in flood regimes have been reported at several locations along the River Niger. These changes are the combined effect of persistent droughts, damming and increased consumption of water. Moreover, it is believed that climate change will impact on the hydrological regime of the river in the next decades and exacerbate existing problems. While decision makers and stakeholders are aware of these issues, it is hard for them to figure out what actions should be taken without a quantitative estimate of future changes. In this paper, a Soil and Water Assessment Tool (SWAT) model of the Niger River watershed at Koulikoro was successfully calibrated, then forced with the climate time series of variable length generated by nine regional climate models (RCMs) from the AMMA-ENSEMBLES experiment. The RCMs were run under the SRES A1B emissions scenario. A combination of quantile-quantile transformation and nearest-neighbour search was used to correct biases in the distributions of RCM outputs. Streamflow time series were generated for the 2026–2050 period (all nine RCMs), and for the 2051–2075 and 2076–2100 periods (three out of nine RCMs) based on the availability of RCM simulations. It was found that the quantile-quantile transformation improved the simulation of both precipitation extremes and ratio of monthly dry days/wet days. All RCMs predicted an increase in temperature and solar radiation, and a decrease in average annual relative humidity in all three future periods relative to the 1981–1989 period, but there was no consensus among them about the direction of change of annual average wind speed, precipitation and streamflow. When all model projections were averaged, mean annual precipitation was projected to decrease, while the total precipitation in the flood season (August, September, October) increased, driving the mean annual flow up by 6.9% (2026–2050), 0.9% (2051–2075) and 5.6% (2076–2100). A t-test showed that changes in multi-model annual mean flow and annual maximum monthly flow between all four periods were not statistically significant at the 95% confidence level.     

Simulation of spatiotemporal dynamics of water fluxes in Germany under climate change

In most of Europe, an increase in average annual surface temperature of 0·8 °C is observed, and a further increase is projected. Precipitation tends to increase in northern Europe and decrease in southern Europe, with variable trends in central Europe. The climate scenarios for Germany suggest an increase in precipitation in western Germany and a decrease in eastern Germany, and a shift of precipitation from summer to winter. When investigating the effects of climate change, impacts on water resources are among the main concerns. In this study, the first German‐wide impact assessment of water fluxes dynamics under climate change is presented in a spatially and temporally distributed manner using the state‐of‐the‐art regional climate model, Statistical Regional (STAR) model and the semi‐distributed process‐based eco‐hydrological model, soil and water integrated model (SWIM). All large river basins in Germany (lower Rhine, upper Danube, Elbe, Weser and Ems) are included. A special focus of the study was on data availability, homogeneity of data sets, related uncertainty propagation in the model results and scenario‐related uncertainty. After the model calibration and validation (efficiency from 0·6 to 0·9 in 80% of cases) the water flow components were simulated at the hydrotope level, and the spatial distributions were compared with those in the Hydrological Atlas of Germany. The actual evapotransipration is likely to increase in most parts of Germany, while total runoff generation may decrease in south and east regions. The results for the second scenario period 2051–2060 show that water discharge in all six rivers would be 8–30% lower in summer and autumn compared with the reference period, and the strongest decline is expected for the Saale, Danube and Neckar. Higher winter flow is expected in all of these rivers, and the increase is most significant for the Ems (about 18%). However, the uncertainty of impacts, especially in winter and for high water flows, remains high. Copyright © 2010 John Wiley & Sons, Ltd.     

Non-stationary frequency analysis of heavy rainfall events in southern France

Abstract

Heavy rainfall events often occur in southern French Mediterranean regions during the autumn, leading to catastrophic flood events. A non-stationary peaks-over-threshold (POT) model with climatic covariates for these heavy rainfall events is developed herein. A regional sample of events exceeding the threshold of 100 mm/d is built using daily precipitation data recorded at 44 stations over the period 1958–2008. The POT model combines a Poisson distribution for the occurrence and a generalized Pareto distribution for the magnitude of the heavy rainfall events. The selected covariates are the seasonal occurrence of southern circulation patterns for the Poisson distribution parameter, and monthly air temperature for the generalized Pareto distribution scale parameter. According to the deviance test, the non-stationary model provides a better fit to the data than a classical stationary model. Such a model incorporating climatic covariates instead of time allows one to re-evaluate the risk of extreme precipitation on a monthly and seasonal basis, and can also be used with climate model outputs to produce future scenarios. Existing scenarios of the future changes projected for the covariates included in the model are tested to evaluate the possible future changes on extreme precipitation quantiles in the study area.

Editor Z.W. Kundzewicz; Associate editor K. Hamed

Citation Tramblay, Y., Neppel, L., Carreau, J., and Najib, K., 2013. Non-stationary frequency analysis of heavy rainfall events in southern France. Hydrological Sciences Journal, 58 (2), 280–294.