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Highlights • Innovative trend analysis (ITA) and Mann-Kendall (MK) determine average trend. • Double-ITA, Triple-ITA, and partial MK are proposed for stability test of trends. • ITA should be used together D-ITA or T-ITA for better trend analysis. • MK should be used together partial MK for better trend analysis. • Comparisons of ITA, D-ITA, T-ITA, classical MK, and partial MK are presented. Abstract The climate change is an important event that affects hydrological, agricultural and water resources planning variables, and therefore, the hydrologists and meteorologists frequently try to identify trend possibilities especially in rainfall, runoff and temperature time series. For this purpose, the classical Mann-Kendall (MK), Spearman's rho (SR), Sen's slope, and linear regression approaches are applied frequently in the literature. Recently, innovative trend analysis (ITA) provides visual inspection and identification of categorical trends, which is one of the main concerns in this paper. On the basis of ITA methodology, several improvements namely double-ITA (D-ITA) and triple-ITA (T-ITA) procedures are suggested using with simple ITA together. These methods are attractive for the trend stability assessment by comparing partial trend components during different sub-periods of a given record series. Furthermore, partial MK test approach is proposed in this paper for the same purpose. These procedures and approach are applied to a set of annual rainfall records at many stations in different regions of Turkey. As a result, the comparison of the suggested methods based on partial sub-series of the same time series helps to improve trend detection with stability identification. [ABSTRACT FROM AUTHOR]

• Nationwide streamflow projections for Australia informed by CMIP5 and CMIP6. • Vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. • Lower winter rainfall translates to a significant reduction in annual runoff. • Modelled median projection of runoff shows a 50% reduction in far southwest Australia. • Modelled median projection of runoff shows a 20% reduction in far southeast Australia. Projections of streamflow under future climate are essential for developing adaptation strategies in the water and related sectors. This paper presents nationwide streamflow projections for Australia informed by climate change signals in CMIP6 GCMs and compares the projections with those from CMIP5 GCMs. The modelled future runoff projections driven by CMIP5 and CMIP6 GCMs are relatively similar for far southern Australia. The median projection is a 50% reduction in mean annual runoff in far southwest Australia and 20% reduction in far southeast Australia by 2046–2075 relative to 1976–2015 under the high SSP5-8.5/RCP8.5 global warming scenario. The vast majority of CMIP5 and CMIP6 GCMs project less winter rainfall across Australia. As most of the runoff in far southern Australia occurs in winter and spring, the lower winter rainfall translates to a significant reduction in annual runoff. It is therefore prudent to plan and manage for a reduction in future water resources, particularly in the densely populated and important agricultural regions in southeast Australia. There is less agreement between GCMs in the summer rainfall projection, with the CMIP6 GCMs generally projecting a wetter future (or smaller decrease in rainfall) than the CMIP5 GCMs. The modelled median projection for mean annual runoff is a 10% reduction in the south-east coast, 5% reduction in the north-east coast and little change in northern Australia. More GCMs project an increase rather than a decrease in the interannual variability of rainfall, and this would further amplify multi-year hydrological droughts. [ABSTRACT FROM AUTHOR]

• We propose a new method to quantify Climate Change Effects at hydrological scales. • The method allows to assimilate climatic projections in CDFs at rain gauge scale. • The initial (i.e., before any change scenario begins) skewness plays a crucial role. • A strong increase of outliers frequency is expected for series EV1 alike skewed. Quantifying the potential effects of Climate Change (CC) on hydrological scales is a topic with a more and more increasing interest for the scientific community, given the CC impact on agriculture, industry, economy, human health, ecosystems, among the others. In this context, the paper focuses on the sub-daily Annual Maxima (AM) of rainfall height time series, and specifically on the crucial role played by initial skewness, i.e. the skewness of the observed rainfall series used to evaluate potential parametric trends. Here a quick and user-friendly methodology is proposed, that is aimed at quantifying plausible future changes in terms of probability distributions assumed at rain gauge scale, from projections of any climatic model. In detail, the Generalized Extreme Value (GEV) and the Two-Component Extreme Value (TCEV) distributions are adopted as probability functions suitable for modelling observed rainfall AM series, which could increase their frequency and magnitude into future horizons under CC. EURO-CORDEX projections for Europe are considered, under the hypothesis that the values of the change factor, i.e. the ratio between the values of a specific quantile at two specific time horizons, are invariant when moving from an areally-averaged scale (typical for any climate model) to a point rain gauge scale, which induces that future changes are provided (in terms of frequency and magnitude of extreme events) without the need of any spatial downscaling from the assumed projections. The proposed methodology can contribute to hazard quantification associated to potential climate changes, and thus it can play a crucial role in the assessment of hydraulic structures resilience; the obtained results, specific for the study area of Italy, but easily extendable on a global scale, showed that larger increases in frequency of future heavy events are expected for time series with "EV1 alike" values of initial skewness. [ABSTRACT FROM AUTHOR]

• Exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. • Source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. • The analysis of source areas contribution further illustrates the reason why the study area would undergo inundation damage when the precipitation exceeds 100 mm. • The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. Extreme stormwater and high-impervious area, caused by climate change and high-urbanization, are widely considered as the essential factors for causing urban flood. Understanding the response law of urban inundation to characteristics of rainstorms is helpful to implement integrated flood mitigation measures. Therefore, this paper is focused on exploring the urban inundation response law based on designed rainstorms by coupled hydrodynamic and rainfall-tracking model. Pilot area of Guyuan sponge city, which is divided into 5 source areas, is adopted to conduct 36 types of rainfall scenario simulations with the combination of different rainfall amounts and durations as well as peak coefficients. Inundation analysis methods is used to obtain the relationship between maximum inundation maps and characteristics of rainstorms, and source tracking analysis method is novelty proposed to excavate the response law of the connectivity among source areas to characteristics of rainstorms. First, Results of inundation analysis reveal that rainfall amount, duration and peak value are the first, second and third critical rainstorm characteristics that determine the severity of disasters, the variation of inundation volume are 140 %, 30 % and 4.2 % when precipitation and duration as well as peak value double. Second, the inundation area that water depth more than 0.5 m increases quickly is the major reason that inundation volume varies with 2 times as the increasing of precipitation; the transferring runoff volume between source areas and land use reaches 0–6 % and 0–10 % of inundation volume. Third, SA 1 and 2 are the critical sub-areas to manage the runoff, when precipitation equals to 200 mm, SA 1 contributes 19.5–33.7 % of inundation volume in SA 2, and SA 2 contributes 28–30 % of inundation volume in SA 3. The study is helpful to further understand the response law of inundation and relationship among source areas to characteristics of rainstorms, provide novel insights for constructing integrated flooding intervention practices. [ABSTRACT FROM AUTHOR]

Summary The aim of this paper is to analyse the potential relationship between flash flood events and convective precipitation in Catalonia, as well as any related trends. The paper starts with an overview of flash floods and their trends in the Mediterranean region, along with their associated factors, followed by the definition of, identification of, and trends in convective precipitation. After this introduction the paper focuses on the north-eastern Iberian Peninsula, for which there is a long-term precipitation series (since 1928) of 1-min precipitation from the Fabra Observatory, as well as a shorter (1996–2011) but more extensive precipitation series (43 rain gauges) of 5-min precipitation. Both series have been used to characterise the degree of convective contribution to rainfall, introducing the β parameter as the ratio between convective precipitation versus total precipitation in any period. Information about flood events was obtained from the INUNGAMA database (a flood database created by the GAMA team), with the aim of finding any potential links to convective precipitation. These flood data were gathered using information on damage where flood is treated as a multifactorial risk, and where any trend or anomaly might have been caused by one or more factors affecting hazard, vulnerability or exposure. Trend analysis has shown an increase in flash flood events. The fact that no trends were detected in terms of extreme values of precipitation on a daily scale, nor on the associated ETCCDI (Expert Team on Climate Change Detection and Indices) extreme index, could point to an increase in vulnerability, an increase in exposure, or changes in land use. However, the summer increase in convective precipitation was concentrated in less torrential events, which could partially explain this positive trend in flash flood events. The β parameter has been also used to characterise the type of flood event according to the features of the precipitation. The highest values correspond to short and local events, usually with daily β values above 0.5, while the minimum threshold of daily β for catastrophic flash floods is 0.31. [ABSTRACT FROM AUTHOR]

• Developed a hybrid statistical-numerical model which predicts that without intervention the compound flood risk will increase in Haikou City under the influence of future climate change. • Under the influence of climate change, both rainfall and sea water level will increase. • Climate change will increase the probability and the failure probability of compound flood, and will intensify inundation (increase flood depths, extend the flood extent and longer flood durations). • The combined impact of future changes in rainfall and water level on the magnitude of flooding is greater than the sum of their individual impacts. Compound flooding caused by a combination of rainfall and water level may occur in coastal cities. Under the influence of climate change, compound flooding is likely to be intensified. In this paper, using the main urban area of Haikou City as an example, we developed an event-based statistical-numerical hybrid framework to investigate the effects of sea level rise (SLR) and future rainfall changes on compound flood risk. Future rainfall was predicted by using five global climate models (GCMs) in CMIP5. A combination of GCMs and IPCC AR5 was used to predict the future SLR. The copula was then used to calculate the probabilistic risk of compound flooding (OR joint probability and failure probability) for historical and future scenarios, and the numerical model was utilized to evaluate the risk of inundation under historical and future scenarios. The probabilistic risk results show that both the probability and the failure probability of compound flooding will increase in the future. Output from GCMs indicate that when the OR event of the 5-year event (the compound flooding when at least one of the 5-year rainfall and the 5-year water level happens) occurs, the joint probability of future compound flooding will likely increase to 37.5%. The numerical model results indicate that the flood extent, flood depth and flood duration will increase under the influence of future rainfall and SLR. Under the impact of climate change, the flood depth in the FS 5 case will increase by 22.85% and the flood extent in the FS 5 case will increase by 41.42% compared to HS 5. By controlling for variables, we also find that the combined impact of future changes in rainfall and water level on the magnitude of flooding is greater than the sum of their individual impacts. Finally, we find that water storage facilities and tide gates could be set up to mitigate compound flooding under climate change. [ABSTRACT FROM AUTHOR]

Summary: Catchment hydrological models are widely used in climate change impact studies. The considered climate scenarios often involve increases in rainfall intensities. These increases might go beyond the range of historical events used in model calibration and validation. The hydrological impact results of climate change consequently are under these circumstances highly uncertain. This paper presents a method to test the validity of hydrological models for that type of impact analysis. The method is based on the evaluation of peak flow increases due to different levels of rainfall increases. The method is demonstrated, based upon the results of three conceptual rainfall–runoff models (NAM, PDM, VHM) for three catchments in Belgium. It is shown how the performance of the model in predicting impacts of rainfall increases can be integrated in the calibration process and how this method can increase the reliability of climate change impact results on peak flows. The paper addresses the importance of the relation between the soil moisture content and the overland flow coefficient, as it controls the generation of peak flows in the considered rainfall–runoff models. [ABSTRACT FROM AUTHOR]

Highlights • Main controlling factors for groundwater recharge among 88 metrics were identified. • Same annual rainfall with a seasonal shift could result in a decline of recharge. • Lower groundwater depth could lead to a positive feedback of declining recharge. • Spatially the most significant factors for recharge were soil and land attributes. • Findings could serves as a reference for climate change impacts on groundwater. Abstract This paper demonstrated the benefits of statistical methods when investigating the climatic and non-climatic drivers responsible for variations in groundwater recharge with a series of up to 43 years of annual recharge for 426 bores in South-East South Australia. We identified the factors influencing groundwater recharge based on 71 climatic metrics and 17 non-climatic metrics (including groundwater abstraction). The results showed: (1) Rainfall during April to October was the most important variable influencing recharge temporal variation, with its decline identified as the most significant factor related to recharge reduction; (2) In contrast, a negative correlation between rainfall during December to February (DJF) and annual groundwater recharge was found. This suggests that a seasonal shift in rainfall (such as decreasing rainfall during April to October and an increase during DJF) can result in a decline in recharge even when the annual rainfall remains unchanged; (3) The length of wet spells (consecutive rain days) and increasing potential evapotranspiration (PET) were additional significant predictors for recharge temporal variation. It demonstrated that a simple empirical relationship (such as recharge as a fixed percentage of rainfall) is not a reliable estimation of renewable groundwater resources under changing climatic conditions; (4) There is a statistically significant correlation between mean groundwater depth and recharge, which implies that if groundwater level fall due to rainfall declines then a positive feedback loop can lead to further recharge declines; (5) Spatially the most statistically significant factors influencing groundwater recharge were soil types and land attributes. The findings of this study can identify which stressors should be included when investigating the impact of climate change on groundwater recharge. [ABSTRACT FROM AUTHOR]

Highlights • High resolution catchment scale rainfall predictions were generated from 8 GCMs. • Multiple GCMs is preferable over a best model to account for the future variability. • Simulated climate change has limited impact on pollutant treatment performance. • Larger WSUD systems are recommended to account for the future variability. • Bigger rainwater tank is suggested for same harvesting reliability in the future. Abstract Water Sensitive Urban Design (WSUD) stormwater systems, also known as Low Impact Development (LID) systems or Nature Based Solutions (NBS), are currently implemented based on the underlying assumption of statistical stationarity of rainfall, which threatens to become outdated under climatic uncertainty. This paper applies a new downscaling method to examine the implications of climate change on future rainfall and evaluate the reliability of WSUD stormwater infrastructure in pollution reduction, flow frequency mitigation and reliability as an alternative water supply. A variety of future atmospheric scenarios are considered as part of this comprehensive assessment by analysing an ensemble of eight different downscaled General Circulation Models (GCMs). High resolution catchment-scale rainfall projections for Melbourne, Australia were generated using a scheme called High-resolution Downscaling of Rainfall Using STEPS (HiDRUS) at a fine 1 km and 6-min scale for more precise analysis with uncertainty estimates. Statistical analyses show that, in general, the climate models predict a drier future with fewer rainfall events and longer dry periods when comparing the simulated near future (2040–2049) periods against the base-line period (1995–2004). The difference simulated between historical and future rainfall projections show minimum difference of WSUD performance in pollution removal and flow frequency reduction, with slightly lower harvesting reliability (<3%) observed under future climate; high variabilities, however, were observed across GCM simulations, indicating big uncertainties of system reliability under various conditions, e.g. design wetland sizes may vary from 2.5% to 4.0% of the impervious catchment area according to different future projects across GCMs. Larger WSUD systems are recommended to ensure reliable performance of pollution removal, as well as harvesting reliability under simulated future conditions. The significance of considering an ensemble of different GCMs as opposed to many scenarios generated by a single 'best' climate model was also demonstrated for the robust estimation of uncertainty in future WSUD reliability. This work highlights important considerations for the future design, management and quantitative evaluation of WSUD reliability. [ABSTRACT FROM AUTHOR]

Abstract: The first part of this two-part paper demonstrated the feasibility of the direct use of data from a high resolution (25km) Regional Climate Model (RCM) to provide inputs for a rainfall-runoff model, in order to obtain estimates of flood frequency. This paper uses data from a climate change experiment with the same RCM (HadRM3H) to provide estimates of change in flood frequency between the 1970s and 2080s, for 15 catchments across Great Britain. This experiment is a rerun, at twice the horizontal resolution, of one of those used by the UK Climate Impacts Programme (UKCIP) in the construction of its UKCIP02 climate change scenarios for the UK. It thus allows an exploration of the implication of these scenarios using a resolution more suited to the detailed hydrological application addressed in this paper. Despite decreases in annual average rainfall in all but one catchment, eight show an increase in flood frequency at most return periods whereas two show substantial decreases. As part I of this paper showed a distinct positive correlation between errors in annual rainfall and errors in flood frequency, the fact that flood frequency can increase despite an overall decrease in rainfall implies a marked change in the distribution of rainfall, either in terms of the probability of rainfall events and/or its seasonal cycle. Decreases in flood peaks are shown for a number of the catchments in the south and east of England, despite an increase in winter mean and extreme rainfall. Increased summer and autumn soil moisture deficits are thought to be the reason for this. Other catchments, further north or west, show an increase in flood peaks, in some cases of over 50% at the 50-year return period. Care needs to be taken when interpreting these results, as they are based on a single RCM experiment (using driving data from one GCM under a single emissions scenario). Other RCM experiments may give quite different results, and ensemble runs would ideally be required to limit sample error. [Copyright &y& Elsevier]

• Drought propagation time increased with decreasing precipitation. • Climate change is the main driver of agricultural drought. • Precipitation was the main driver of human activities. • Prolonged drought propagation time reduced winter wheat NPP. • The sensitivity of winter wheat NPP to agricultural drought is higher in humid area. Drought is a major natural disaster worldwide. Understanding the correlation between meteorological drought (MD) and agricultural drought (AD) is essential for relevant policymaking. In this paper, standardized precipitation evapotranspiration index and standardized soil moisture index were used to estimate the MD and AD in the North China Plain (NCP) to identify the correlation between MD and AD during the growth period of winter wheat. In addition, we investigated the contributions of climate change (CC) and human activity (HA) to AD and the factors influencing the loss of winter wheat net primary production (NPP). Drought propagation time (PT) increased spatially from the southern to northern NCP (from 3 to 11 months). PT first increased and then decreased during the phenological period of winter wheat, and the decreasing trend was delayed with an increasing latitude. In general, the relative contribution of CC to AD was higher than that of HA; the correlation between MD and AD exhibited a weakening trend, particularly during the middle and late phenological stages of winter wheat. Precipitation was the main driver of the effects of HA on AD; the effects were stronger in areas with less precipitation. However, because of the improved irrigation conditions and scarce rainfall during the growth period of winter wheat in the study area, the effects of precipitation on AD were nonsignificant. Instead, temperature, wind, and total solar radiation, which are highly correlated with evapotranspiration, were identified as the primary drivers of AD; spatiotemporal variations were noted in these correlations. Prolonged drought PT reduced NPP; the sensitivity of winter wheat NPP to AD was higher in humid areas than in semiarid or semihumid areas. NPP loss occurred primarily due to HA. Our findings revealed a correlation between MD and AD in agroecosystems and may facilitate policymaking related to drought mitigation and food security. [ABSTRACT FROM AUTHOR]

The spatial variability of the hydrological response is controlled by the interaction of two spatial variabilities: climatic forcing and physiographic characteristics. This paper investigates their impact on streamflow modelling throughout a large catchment. They are assessed by successively refining the spatial information of climatic inputs and model parameters, going from the lumped to the sub-catchment or mesh scale. The analysis is conducted according to a spatial split-sample test. For each resolution, the distributed model first calibrated on calibration station(s) is then evaluated in light of this(these) station(s) in addition to validation stations previously treated as ungauged. For that purpose, simulated and observed streamflows are compared focusing on four hydrological signatures: daily runoff, daily regime, flood and low flow. The above framework is applied at the daily time step over a French basin, the Loire catchment at Gien covering 35,707 km 2 , whose streamflow data are available at the catchment outlet and 105 interior points. The results show that spatially distributed climatic forcing greatly enhances the four signatures as the resolution increases, until the right rainfall volume is provided for each simulation point. By taking advantage of the interior calibration stations to spatialise the parameters, the model’s performance progresses again but to a lesser extent. Finally, the catchment’s hydrological behaviour is mainly driven by the spatial variability of the climatic inputs (around 90% over the validation stations), while that of the parameters seems to be of second order. [ABSTRACT FROM AUTHOR]

Recently developed methodologies such as climate reanalysis make it possible to create a historical record of climate systems. This paper proposes a methodology called Hydrological Retrospective (HR), which essentially simulates large rainfall datasets, using this as input into hydrological models to develop a record of past hydrology, making it possible to analyze past floods and droughts. We developed a methodology for the Amazon basin, where studies have shown an increase in the intensity and frequency of hydrological extreme events in recent decades. We used eight large precipitation datasets (more than 30 years) as input for a large scale hydrological and hydrodynamic model (MGB-IPH). HR products were then validated against several in situ discharge gauges controlling the main Amazon sub-basins, focusing on maximum and minimum events. For the most accurate HR, based on performance metrics, we performed a forecast skill of HR to detect floods and droughts, comparing the results with in-situ observations. A statistical temporal series trend was performed for intensity of seasonal floods and droughts in the entire Amazon basin. Results indicate that HR could represent most past extreme events well, compared with in-situ observed data, and was consistent with many events reported in literature. Because of their flow duration, some minor regional events were not reported in literature but were captured by HR. To represent past regional hydrology and seasonal hydrological extreme events, we believe it is feasible to use some large precipitation datasets such as i) climate reanalysis, which is mainly based on a land surface component, and ii) datasets based on merged products. A significant upward trend in intensity was seen in maximum annual discharge (related to floods) in western and northwestern regions and for minimum annual discharge (related to droughts) in south and central-south regions of the Amazon basin. Because of the global coverage of rainfall datasets, this methodology can be transferred to other regions for better estimation of future hydrological behavior and its impact on society. [ABSTRACT FROM AUTHOR]

[Display omitted] • Improve the accuracy of LID parameters through physical experiments. • Offer a new perspective on studying the urban hydrological effects in LID regions. • Even a tiny percentage of LID practices can be effective in runoff control. • LID removal or density reduction leads to an increased possibility of flood risk. Global climate change and rapid urbanization led to frequent extreme rainstorms and waterlogging. Low impact development (LID) as an essential measure of urban stormwater control, it is necessary to explore the urban hydrological response under low impact development combined with physical experiment and numerical simulation. This paper takes the Beiyangyuan campus of Tianjin University, where numerous LID practices have been implemented, as the study area. The prototype permeable pavement in the campus was scaled down to a laboratory-scale for infiltration experiments. The results show that the Horton infiltration model could describe the infiltration process of permeable concrete and grass-planting brick. The initial infiltration rate of the permeable concrete is large but decays faster. In contrast, the infiltration process of the grass-planting brick decays slower, and the stable infiltration rate and infiltration capacity are higher than that of the permeable concrete. The mean infiltration rates measured for the permeable concrete and the grass-planting brick were 95 mm/hr and 190 mm/hr, respectively. A SWMM-MIKE21 coupled model was constructed based on the LID experimental results to explore the effects of the removal or density reduction of the LID practices on surface hydrological processes. The results show that permeable pavement performs best in the reduction of runoff volume, inundation area, and inundation depth, while the bio-retention cell takes the second place, and the sunken greenbelt has limited effect. Frequent light rainfall is sensitive to the density of LID practices, and the implementation of even a tiny percentage (4% of the catchment area) of LID practices can be effective in controlling runoff. The removal or density reduction of LID practices has little effect on the inundation region but leads to an increased possibility of flood risk due to increasing inundation depth. [ABSTRACT FROM AUTHOR]

• Future rainfall and sea level rise are predicted. • Impact of sea level rise and future rainfall change on compound flooding is assessed. • Changes in depth, extent, and duration of floods under climate change are analyzed. Flood disasters in coastal cities are generally caused by the combined effect of typhoon rainfall, storm surge and other factors. Coastal cities will face more severe compound flooding under climate change. Although some studies have analyzed compound flooding under climate change, there is a lack of research considering the combined effect of sea level rise (SLR) and future rainfall changes, especially lack of the jacking effect of SLR on the volume and duration of compound flooding. This paper investigates the impact of future rainfall changes and SLR on compound flood risk, via a case study of a coastal city, Haikou, China. Future rainfall in Haikou is obtained by bias correction of rainfall from five global climate models (GCMs) in CMIP5. The SLR in 2050 and 2090 is predicted according to IPCC. Then, a 1D/2D hydrological-hydrodynamic model for dynamic simulation of surface runoff is applied to simulate compound flooding. Results show that both future rainfall changes and SLR will lead to the increase of flood extent, flood depth and flood duration. But future rainfall changes will have a greater impact on flood, and the combined effect of future rainfall changes and SLR on flood is greater than the sum of their individual effects. The individual effects of SLR and future rainfall changes would increase flood depth in 10.6 % and 32.1 % of the study area, respectively, while their combined effect would increase this proportion to 34.9 %. Also, the jacking effect of SLR on compound flooding will lead to an increase in flood volume, but it presents a nonlinear relationship that gradually slows down with the increase of SLR. A SLR of 0.3 m and 0.63 m will lead to a 2.34 % and 3.22 % increase in flood volume, respectively. And the jacking effect of SLR is more obvious when future rainfall changes are considered, which will lead to a sharp increase in the duration of compound flooding. Moreover, water storage facilities and tidal gates are effective ways to reduce the impact of climate change on compound flooding. [ABSTRACT FROM AUTHOR]

• Adverse impacts of sea-level rises are not limited to a landward shift in shoreline. • Shallow groundwater can impact inland infrastructure kilometers from the coastline. • About 2/3 of the stormdrain length is subject to seawater & groundwater intrusion. • Coastal stressors can increase flood magnitude, frequency, and duration. • Compound flooding volume increases up to 6 times by a 2 m sea-level rise. Low-lying coastal areas are susceptible to multiple types of flooding from marine, subsurface, and surface sources. The co-occurrence of a rainfall event with high sea level, which raises coastal groundwater tables conjointly, may result in a compound flooding event, which could be much more widespread and dangerous than that of an individual flooding source. Focusing on Imperial Beach as a low-elevation coastal community in California, this paper provides a generalized methodology to determine the vulnerability of coastal stormdrain systems to compound seawater, groundwater, and stormwater flooding under a changing climate. Although marine inundation by itself is expected to flood only 7% of the study area by 2100 under the most pessimistic scenario (i.e. 2 m rise), our results show that more than 20% of the study area's subterranean stormdrain system is already at the risk of subsurface flooding at current sea levels. While marine inundation is a concern near the coastline as sea level rises, the results show that seawater intrusion into the stormdrain system can impact areas kilometers away from the coastline. The consequences of sea-level rise (SLR) can be exacerbated by an under-resourced stormdrain system, caused by groundwater infiltration through system defects. As such, by a 2 m rise in current sea-level, the flooding volume may double in an ideal system (i.e., no defects) while this ratio can increase six fold in a slightly defective stormdrain system (with 0.25 % porosity systemwide). The continuous simulations of the stormdrain system performance indicate that flood events will be more destructive and frequent under these circumstances. [ABSTRACT FROM AUTHOR]

• The novel target flow control (TFC) approach for the real-time control (RTC) of stormwater storages is proposed. • The TFC approach does not require calibration. • The approach achieves target flows for a wide range of rainfall events with minor errors. • The approach is practical as it only requires real-time storage level information. Stormwater systems will likely require major upgrades due to increases in peak flows caused by the combined effects of urbanization, densification (urban infill) and climate change. Recently, the real-time control (RTC) of storages has been considered as a means to reduce peak flows and potentially avoid major infrastructure upgrades. This paper introduces a RTC approach, the Target Flow Control (TFC) approach, which is able to maintain system outflows at or below specified target flows (e.g., existing system capacity). The key features of the approach are that it does not require calibration to catchment specific data, as is the case for existing approaches and is only based on storage level information measured in real-time during rainfall events. This makes the approach generally applicable to different catchments and able to respond to future changes in rainfall due to land use and/or climate change. The TFC approach is tested on a simple two-storage system for 750 design rainfall events from a range of climates, event durations, rainfall intensities and temporal patterns using a practically achievable control time step of 30 s. Results show that the TFC approach can achieve the desired target flows effectively, with 95% of the experiments having less than 10% errors in target flows. This is an exciting achievement, given the TFC approach does not require calibration and only requires measurable storage level information. The outcomes highlight the potential of the TFC approach as a practical RTC approach that can maximize the effectiveness of existing stormwater conveyance systems by maintaining stormwater system outflows at desired target flows, thereby potentially avoiding stormwater infrastructure upgrades due to land use and climate change. [ABSTRACT FROM AUTHOR]

• The novel target flow control (TFC) approach for the real-time control (RTC) of stormwater storages is proposed. • The TFC approach does not require calibration. • The approach achieves target flows for a wide range of rainfall events with minor errors. • The approach is practical as it only requires real-time storage level information. Stormwater systems will likely require major upgrades due to increases in peak flows caused by the combined effects of urbanization, densification (urban infill) and climate change. Recently, the real-time control (RTC) of storages has been considered as a means to reduce peak flows and potentially avoid major infrastructure upgrades. This paper introduces a RTC approach, the Target Flow Control (TFC) approach, which is able to maintain system outflows at or below specified target flows (e.g., existing system capacity). The key features of the approach are that it does not require calibration to catchment specific data, as is the case for existing approaches and is only based on storage level information measured in real-time during rainfall events. This makes the approach generally applicable to different catchments and able to respond to future changes in rainfall due to land use and/or climate change. The TFC approach is tested on a simple two-storage system for 750 design rainfall events from a range of climates, event durations, rainfall intensities and temporal patterns using a practically achievable control time step of 30 s. Results show that the TFC approach can achieve the desired target flows effectively, with 95% of the experiments having less than 10% errors in target flows. This is an exciting achievement, given the TFC approach does not require calibration and only requires measurable storage level information. The outcomes highlight the potential of the TFC approach as a practical RTC approach that can maximize the effectiveness of existing stormwater conveyance systems by maintaining stormwater system outflows at desired target flows, thereby potentially avoiding stormwater infrastructure upgrades due to land use and climate change. [ABSTRACT FROM AUTHOR]

The estimation of intensity-duration-frequency (IDF) curves for rainfall data comprises a classical task in hydrology studies to support a variety of water resources projects, including urban drainage and the design of flood control structures. In a changing climate, however, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to poor estimates of rainfall intensity quantiles. Climate change scenarios built on General Circulation Models offer a way to access and estimate future changes in spatial and temporal rainfall patterns at the daily scale at the utmost, which is not as fine temporal resolution as required (e.g. hours) to directly estimate IDF curves. In this paper we propose a novel methodology based on a four-parameter beta distribution to estimate IDF curves conditioned on the observed (or simulated) daily rainfall, which becomes the time-varying upper bound of the updated nonstationary beta distribution. The inference is conducted in a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters when building the IDF curves. The proposed model is tested using rainfall data from four stations located in South Korea and projected climate change Representative Concentration Pathways (RCPs) scenarios 6 and 8.5 from the Met Office Hadley Centre HadGEM3-RA model. The results show that the developed model fits the historical data as good as the traditional Generalized Extreme Value (GEV) distribution but is able to produce future IDF curves that significantly differ from the historically based IDF curves. The proposed model predicts for the stations and RCPs scenarios analysed in this work an increase in the intensity of extreme rainfalls of short duration with long return periods. [ABSTRACT FROM AUTHOR]

A water supply system can be impacted by rainfall reduction due to climate change, thereby reducing its supply potential. This highlights the need to understand the system resilience, which refers to the ability to maintain service under various pressures (or disruptions). Currently, the concept of resilience has not yet been widely applied in managing water supply systems. This paper proposed three technical resilience indictors to assess the resilience of a water supply system. A case study analysis was undertaken of the Water Grid system of Queensland State, Australia, to showcase how the proposed indicators can be applied to assess resilience. The research outcomes confirmed that the use of resilience indicators is capable of identifying critical conditions in relation to the water supply system operation, such as the maximum allowable rainfall reduction for the system to maintain its operation without failure. Additionally, resilience indicators also provided useful insight regarding the sensitivity of the water supply system to a changing rainfall pattern in the context of climate change, which represents the system’s stability when experiencing pressure. The study outcomes will help in the quantitative assessment of resilience and provide improved guidance to system operators to enhance the efficiency and reliability of a water supply system. [ABSTRACT FROM AUTHOR]

Summary Bias correction is considered as a critical post-processing step to remove systematic errors and improve the quality of General Circulation Model (GCM) simulations before their use in climate change impact assessment applications. A majority of the bias correction approaches correct for biases either at a single time scale or at multiple pre-specified time scales. An inappropriate or insufficient selection of time scales may lead to improper or sub-optimal bias corrected outputs, especially when persistence attributes across a range of scales are of interest. In this paper, we present a new bias correction approach that works in the frequency space and is independent of specific time scales. The approach is named as frequency-based bias correction (FBC). The usefulness of the approach is demonstrated by applying it to the monthly rainfall simulations of MIROC5 GCM over Australia and comparing the results with two other approaches, namely, empirical quantile mapping and recursive nesting bias correction, in cross validation. The comparison is based on the reproduction of various observed distribution and persistence attributes. Cross-validation results indicate that the proposed approach shows similar performance in terms of reproducing the first- and second-order moments of observed precipitation time series, however, outperforms with regard to persistence attributes. The approach shows high potential for use in downscaling and other climate change impact assessment studies, especially for the planning and design of hydrologic systems that are sensitive to the characterisation of persistence in the hydrologic time series. [ABSTRACT FROM AUTHOR]

Summary Areal reduction factors (ARFs) are commonly used to transform point design rainfall to represent the average design rainfall for a catchment area. While there has been considerable attention paid in the research and engineering communities to the likely changes in rainfall intensity in future climates, the issue of changes to design areal rainfall has been largely ignored. This paper investigates the impact of climate change on ARFs. A new methodology for estimating changes in ARFs is presented. This method is used to assess changes in ARFs in the greater Sydney region using a high-resolution regional climate model (RCM). ARFs under present (1990–2009) and future (2040–2059) climate conditions were derived and compared for annual exceedance probabilities (AEPs) from 50% to 5% for durations ranging from 1 h to 120 h. The analysis shows two main trends in the future changes in ARFs. For the shortest duration events (1-h) the ARFs are found to increase which implies that these events will tend to have a larger spatial structure in the future than the current climate. In contrast, storms with durations between 6 and 72 h are likely to have decreased ARFs in the future, suggesting a more restricted spatial coverage of storms under a warming climate. The extent of the decrease varies with event frequency and catchment size. The largest decreases are found for large catchments and rare events. Although the results here are based on a single RCM and need to be confirmed in future work with multiple models, the framework that is proposed will be useful for future studies considering changes in the areal extent of rainfall extremes. [ABSTRACT FROM AUTHOR]

Summary This paper assesses the implications of climate and anthropic pressures on short to long-term changes in water resources in a Mediterranean karst using wavelet analysis. This approach was tested on 38-year (1974–2011) hydrogeological time series recorded at the Lez spring (South France), which is exploited for water supply. Firstly, we investigated inter-relationships in the frequency domain by cross-correlation across multiresolution levels. Our results showed that rainfall and spring discharge are highly correlated in the high frequency domain which reflects the hydrogeological response during flood events of typical highly karstified systems. Pumping and groundwater level are correlated in a lower frequency domain, illustrating seasonal to multi-year relationships. Secondly, continuous wavelet transform was applied to characterize the temporal variability of the inter-relationships involved. On the contrary to examples of “non-managed” karst aquifers in the literature, our results showed that the 10-year rainfall component was attenuate in the discharge signal. We assume that the reason is that the storage variations are strongly affected by pumping. This interesting result shows that possible long-term impacts of rainfall variability due to climate change may be masked by a high pumping rate. We showed also that despite an increase of the pumping rate from the 1980s, the stress on the groundwater resource does not increase from year to year. The present pumping strategy does not affect the drawdown in the long term, avoiding an over-exploitation of the aquifer. Finally, this study highlights the effectiveness of wavelet analysis in characterizing the response variability of karst systems where the hydrogeological regime is modified by pumping. [ABSTRACT FROM AUTHOR]

Summary Flash floods and debris flows develop at space and time scales that conventional observation systems for rainfall, streamflow and sediment discharge are not able to monitor. Consequently, the atmospheric, hydrological and geomorphic controls on these hydrogeomorphic processes are poorly understood, leading to highly uncertain warning and risk management. On the other hand, remote sensing of precipitation and numerical weather predictions have become the basis of several flood forecasting systems, enabling increasingly accurate detection of hazardous events. The objective of this paper is to provide a review on current European and international research on early warning systems for flash floods and debris flows. We expand upon these themes by identifying: (a) the state of the art; (b) knowledge gaps; and (c) suggested research directions to advance warning capabilities for extreme hydrogeomorphic processes. We also suggest three areas in which advancements in science will have immediate and important practical consequence, namely development of rainfall estimation and nowcasting schemes suited to the specific space–time scales, consolidating physical, engineering and social datasets of flash floods and debris-flows, integration of methods for multiple hydrogeomorphic hazard warning. [ABSTRACT FROM AUTHOR]

Summary: This paper presents the results of computer simulations of runoff from 13 major fresh and brackish river basins in south-western Australia (SWA) under climate projections obtained from 15 GCMs with three future global warming scenarios equivalent to global temperature rises of 0.7°C, 1.0°C and 1.3°C by 2030. The objective was to apply an efficient methodology, consistent across a large region, to examine the implications of the best available projections in climate trends for future surface water resources. An ensemble of rainfall-runoff models was calibrated on stream flow data from 1975 to 2007 from 106 gauged catchments distributed throughout the basins of the study area. The sensitivity of runoff to projected changes in mean annual rainfall is examined using the climate ‘elasticity’ concept. Averaged across the study area, all 15 GCMs project declines in rainfall under all global warming scenarios with a median decline of 8% resulting in a median decline in runoff of 25%. Such uniformity in projections from GCMs is unusual. Over SWA the average annual runoff under the 5th wettest and 5th driest of the 45 projections of the 2030 climate declines by 10 and 42%, respectively. Under the 5th driest projection the runoff decline ranges from 53% in the northern region to 40% in the southern region. Strong regional variations in climate sensitivity are found with the proportional decline in runoff greatest in the northern region and the greatest volumetric declines in the wetter basins in the south. Since the mid 1970s stream flows into the major water supply reservoirs in SWA have declined by more than 50% following a 16% rainfall reduction. This has already had major implications for water resources planning and for the preservation of aquatic and riparian ecosystems in the region. Our results indicate that this reduction in runoff is likely to continue if future climate projections eventuate. [Copyright &y& Elsevier]

Summary: The effect of future climate scenarios on surface water and groundwater resources has been shown to have a consequent impact on water-dependent ecosystems. A regional-scale analysis of changes in water resources as a result of changing climate was undertaken in south-western Australia; a region with a large number of nationally and internationally recognised water-dependent ecosystems. The paper examines the potential environmental impacts of a substantial reduction in rainfall and an increase in temperature as projected by global climate models (GCMs) on river and groundwater-dependent terrestrial vegetation by 2030. Climate change effects on environmentally significant flow regimes were evaluated by applying the climate projections from 15 GCMs under three global warming ‘scenarios to rainfall–runoff and groundwater models. It was estimated that under a dry future climate scenario, the frequency of river flow rates important for ecological communities is likely to be reduced by up to 2months per year, which is likely to cause a significant level of stress to ecological communities. Additionally, the duration of no-flow periods may increase by more than 120days in some streams. Under a dry future climate scenario, groundwater-dependent vegetation is projected to be at a high risk in over 19% of its current habitat area. Water-dependent ecosystems are also projected to be affected by an increase in groundwater abstraction. The results indicate that the projected impacts of future climate conditions are not likely to be uniform across the region but overall they could cause a continuing threat to water-dependent ecosystems. The implementation of water management plans should place particular emphasis on the ecological water requirements in 6 of the 13 river catchments in south-western Australia and in areas where groundwater abstraction is high. The climate projections and ecological impacts are a continuation of the trends that have taken place in the past three decades. [Copyright &y& Elsevier]

Summary: A Gibbs sampling technique was recently proposed to model nonstationary trend and periodic components in monthly climatic series (). This paper describes the development of new techniques for simulating trends and periodicities estimated by the Gibbs procedure from observed rainfall data. The objective is to provide possible future climatic scenarios for planning, design and operation of water resource systems. In particular, trend is considered as an important indicator of climate change. Historical series of rainfall observations from Italy and Switzerland are used in this study. Support is found for the approach from the results of Mann–Kendall and associated tests for trend which do not provide evidence of long-term trends. Analysis of amplitudes and periodicities of waves in trend curves from Gibbs sampling highlights the diversity of the procedure. [ABSTRACT FROM AUTHOR]

Summary: This paper presents results from a modelling study carried out to investigate whether the calibrated parameter values for rainfall–runoff models based on historical observed data can be used to reliably predict runoff responses to changes in future climate inputs. The modelling experiments are carried out for four rainfall–runoff models using long records of historical daily climate and streamflow data from 61 catchments in southeast Australia. The results indicate that the models, when calibrated using more than 20years of data, can generally be used for climate impact studies where the future mean annual rainfall is not more than 15% drier or 20% wetter than the mean annual rainfall in the model calibration period. It is generally more difficult for a model calibrated over a wet period to predict runoff over a dry period compared to a model calibrated over a dry period to predict runoff over a wet period. For southeast Australia, there is a good reason to use the recent records to calibrate rainfall–runoff models to represent the current prolonged drought over the region and for climate change impact studies where the large majority of climate models predict a drier future across this region. [ABSTRACT FROM AUTHOR]

Summary: This paper: (i) assesses the rainfall downscaled from three global climate models (GCMs) using five downscaling models, (ii) assesses the runoff modelled by the SIMHYD rainfall–runoff model using the downscaled daily rainfall, and (iii) compares the modelled changes in future rainfall and runoff characteristics. The modelling study is carried out using rainfall and streamflow data from eight unimpaired catchments near the headwaters of the Murray River in south-east Australia. The downscaling models used, in increasing order of complexity, are a daily scaling model, an analogue statistical downscaling model, GLIMCLIM and NHMM parametric statistical downscaling models, and CCAM dynamic downscaling model. All the downscaling models can generally reproduce the observed historical rainfall characteristics. The rainfall–runoff modelling using downscaled rainfall also generally reproduces the observed historical runoff characteristics. The future simulations are most similar between the daily scaling, analogue and NHMM models, all of them simulating a drier future. The GLIMCLIM and CCAM models simulate a smaller decrease in future rainfall. The differences between the modelled future runoff using the different downscaled rainfall can be significant, and this needs to be further investigated in the context of projections from a large range of GCMs and different hydrological models and applications. The simpler to apply daily scaling and analogue models (they also directly provide gridded rainfall inputs) can be relatively easily used for impact assessments over very large regions. The parametric downscaling models offer potential improvements as they capture a fuller range of daily rainfall characteristics. [Copyright &y& Elsevier]

Summary: The future rainfall series used to drive hydrological models in many climate change impact on runoff studies are informed by rainfall simulated by global climate models (GCMs). This paper assesses how the choice of GCMs based on their abilities to reproduce the observed historical rainfall can affect runoff impact assessment. The 23 GCMs used in IPCC 4AR are considered together with 1961–2000 observed rainfall data over southeast Australia. The results indicate that most of the GCMs can reproduce the observed spatial mean annual rainfall pattern, but the errors in the mean seasonal and annual rainfall amounts can be significant. The future mean annual rainfall projections averaged across southeast Australia range from −10% to +3% change per degree global warming, which is amplified as −23% to +4% change in the future mean annual runoff. There is no clear difference in the future rainfall projections between the better and poorer GCMs based on their abilities to reproduce the observed historical rainfall, therefore using only the better GCMs or weights to favour the better GCMs give similar runoff impact assessment results as the use of all the 23 GCMs. The range of future runoff in impact assessment studies is probably best determined using future rainfall projections from the majority of available archived GCM simulations. [Copyright &y& Elsevier]

Summary: The Gourma site in Mali is one of the three instrumented meso-scale sites deployed in West-Africa as part of the African Monsoon Multi-disciplinary Analysis (AMMA) project. Located both in the Sahelian zone sensu stricto, and in the Saharo–Sahelian transition zone, the Gourma meso-scale window is the northernmost site of the AMMA-CATCH observatory reached by the West African Monsoon. The experimental strategy includes deployment of a variety of instruments, from local to meso-scale, dedicated to monitoring and documentation of the major variables characterizing the climate forcing, and the spatio-temporal variability of surface processes and state variables such as vegetation mass, leaf area index (LAI), soil moisture and surface fluxes. This paper describes the Gourma site, its associated instrumental network and the research activities that have been carried out since 1984. In the AMMA project, emphasis is put on the relations between climate, vegetation and surface fluxes. However, the Gourma site is also important for development and validation of satellite products, mainly due to the existence of large and relatively homogeneous surfaces. The social dimension of the water resource uses and governance is also briefly analyzed, relying on field enquiry and interviews. The climate of the Gourma region is semi-arid, daytime air temperatures are always high and annual rainfall amounts exhibit strong inter-annual and seasonal variations. Measurements sites organized along a north–south transect reveal sharp gradients in surface albedo, net radiation, vegetation production, and distribution of plant functional types. However, at any point along the gradient, surface energy budget, soil moisture and vegetation growth contrast between two main types of soil surfaces and hydrologic systems. On the one hand, sandy soils with high water infiltration rates and limited run-off support almost continuous herbaceous vegetation with scattered woody plants. On the other hand, water infiltration is poor on shallow soils, and vegetation is sparse and discontinuous, with more concentrated run-off that ends in pools or low lands within structured endorheic watersheds. Land surface in the Gourma is characterized by rapid response to climate variability, strong intra-seasonal, seasonal and inter-annual variations in vegetation growth, soil moisture and energy balance. Despite the multi-decadal drought, which still persists, ponds and lakes have increased, the grass cover has largely recovered, and there are signs of increased tree cover at least in the low lands. [Copyright &y& Elsevier]

Summary: This paper presents a systematic examination of the process controls on inter-annual variability of annual water balance. A simple, linear rainfall–runoff model is used for this purpose, in combination with idealised patterns of within-year variability of rainfall. The effects of these intra-annual patterns of variability of climate (e.g., storminess, seasonality) on annual water balance are examined through the simulation of annual runoff in three semi-arid catchments located in Queensland, South Australia and Western Australia, and one temperate catchment in New Zealand. A simple lumped model, that includes saturation excess overland flow and subsurface stormflow, is used, via sensitivity analyses with respect to different aspects of the intra-annual variability (i.e., seasonality and storminess). In the Queensland catchment storminess is found to be the dominant factor, whereas in Western Australia and South Australia seasonality is found to be the dominant climate control. In wetter catchments (e.g., New Zealand), the water balance is relatively insensitive to soil properties, whereas in dry places (e.g., Western Australia and South Australia) the water balance is highly sensitive to soil properties, such as the soil depth, confirming the results of previous modelling studies. The insights gained from this study can assist in the deciphering of the vast complexity of observed inter-annual variability of catchment responses in terms of their underlying process controls, which can be valuable towards the development of parsimonious water balance models. [Copyright &y& Elsevier]

Summary: Recent news on the occurrence of off-seasonal natural disasters, such as pre-monsoon drought and post-monsoon flooding in India and particularly in the peninsular region, highlight the urgent need to look at the patterns of change in seasonal extremes at the local level. Kerala, the south-western state of the Indian peninsula, comprising of a total of six gridded areas, was chosen for this study focusing on the variability and changes in rainfall extremes in the different seasons. Since other studies by the authors have focused on the monsoon season, this paper considers the winter, spring and autumn seasons only. A set of indices derived from the daily rainfall time series is defined and used to examine the changes in extreme rainfall through assessing long-term trends by non-parametric Mann–Kendall technique. The trends are determined over the period of 1954–2003, which are also tested for significance. The results show that there are large intra-regional differences in the trends in different seasons. Local changes were found different from the large spatial scale averages in Kerala. Winter and autumn extreme rainfall were found having an increasing tendency with statistically significant changes in some regions indicating more occurrences of winter and autumn floods. On the other hand the spring seasonal extreme rainfall showed decreasing trends, which together with increasing frequency of the dry days is mainly affecting the total seasonal precipitation, which mainly point towards the vulnerability of Kerala to increasing probability of water scarcity in the pre-monsoon time and a delaying monsoon onset. Overall, the results of this study are good indicators of local climate changes over the five decades that will assist in seasonal forecasting and risk management. [Copyright &y& Elsevier]

Summary: With the current concern over climate change, descriptions of how rainfall patterns are changing over time can be useful. Observations of daily rainfall data over the last few decades provide information on these trends. Generalized linear models are typically used to model patterns in the occurrence and intensity of rainfall. These models describe rainfall patterns for an average year but are more limited when describing long-term trends, particularly when these are potentially non-linear. Generalized additive models (GAMs) provide a framework for modelling non-linear relationships by fitting smooth functions to the data. This paper describes how GAMs can extend the flexibility of models to describe seasonal patterns and long-term trends in the occurrence and intensity of daily rainfall using data from Mauritius from 1962 to 2001. Smoothed estimates from the models provide useful graphical descriptions of changing rainfall patterns over the last 40 years at this location. GAMs are particularly helpful when exploring non-linear relationships in the data. Care is needed to ensure the choice of smooth functions is appropriate for the data and modelling objectives. [Copyright &y& Elsevier]

Abstract: Under enhanced greenhouse conditions, climate models suggest an increase in rainfall intensities in the northern Hemisphere. Major flood events in the UK during autumn 2000 and central Europe in August 2002, have focussed attention on the dramatic impacts these changes may have on many sectors of society. In the companion paper [Fowler et al., J. Hydrol. (2004) this issue], we suggested that the HadRM3H model may be used with some confidence to estimate extreme rainfall distributions, showing good predictive skill in estimating statistical properties of extreme rainfall during the baseline period, 1961–1990. In this study, we use results from the future integration of HadRM3H (following the IPCC SRES scenario A2 for 2070–2100) to assess possible changes in extreme rainfall across the UK using two methods: regional frequency analysis and individual grid box analysis. Results indicate that for short duration events (1–2 days), event magnitude at a given return period will increase by 10% across the UK. For longer duration events (5–10 days), event magnitudes at given return periods show large increases in Scotland (up to +30%), with greater relative change at higher return periods (25–50 years). In the rest of the UK, there are small increases in the magnitude of more frequent events (up to +10%) but reductions at higher return periods (up to -20%). These results provide information to alter design storm depths to examine climate change impacts on various structures. The uncertainty bounds of the estimated changes and a ‘scaling’ methodology are additionally detailed. This allows the estimation of changes for the 2020s, 2050s and 2080s, and gives some confidence in the use of these estimates in impact studies. [Copyright &y& Elsevier]

• Landscape evolution response to future climate change was analyzed. • CAESAR-Lisflood combined with NEX-GDDP was used to simulate mass movement in an earthquake area. • 27 years (~2035) are needed before the Wenchuan earthquake-stricken area stabilizes. The Wenchuan earthquake caused rapid and gradual changes to the local geomorphology in the earthquake-stricken area. Extreme rainfall events can have strong impacts on local geomorphic evolution and alter the risks of subsequent geohazards and flooding. However, there is still lack of understanding of long-term geomorphic and fluvial evolution in face of changing future climate. In this paper, we first perform the future extreme rainfall projection and then analyze the landscape evolution variation under future climate change with the CAESAR-Lisflood model. A new approach to applying the 'NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP)' dataset at the local scale is presented, and a future landscape evolution analysis is conducted. We used spatial (tailoring process) and statistical temporal downscaling methods with NEX-GDDP data to project future extreme rainfall in combination with the CAESAR-Lisflood model to simulate the landscape evolution in response to climate change. The results showed that the future rainfall projection model can provide the most robust and effective representative of future climate change scenarios at the local scale, the geological and geomorphological environment of the basin continues to change dynamically after the earthquake, and nearly 27 years (~2035) are needed before the geomorphology of the basin stabilizes, and then, the yearly yield remains at an average rate of 1 × 104 m3. Post-earthquake mountainous area response and recovery characteristics to a changing future climate can provide important information on future geohazard projections and measures to be taken. [ABSTRACT FROM AUTHOR]

• A spatial-temporal rain field generator is developed to reproduce regional rainfalls. • The generator produces likely future rainstorm scenarios considering climate change. • Correlations among temporal process parameters and different stations are considered. • Rain extremes may increase notably at the end of 21st century in Greater Bay Area. A stochastic rainfall generator is required to provide rainfall inputs for the analysis and mitigation of such hydrological or geologic hazards as floods and rain-induced landslides. This paper presents a new spatial-temporal rainstorm generator for generating simultaneous rainfall processes at numerous locations considering the spatial correlation among these locations and interpolating the point processes into an areal rain field. The generator is able to include the effect of climate change by adjusting the parameters of the marginal distributions of variables constituting rainfall events. A case study on the Guangdong-Hong Kong-Macau Greater Bay Area (GBA), one of the regions that are most prone to storm-related disasters in the world, is presented. The performance of the proposed generator is excellent in reproducing the historical statistical characteristics of regional rainfall. The model is adapted to climate change through extrapolation of the variation trend of the model parameters in the observation period to explore possible future scenarios of regional rainfall in GBA. The simulation results indicate a significant increase in rainfall extremes, especially for short-duration rainfall, at the end of 21st century in GBA. [ABSTRACT FROM AUTHOR]