Dynamic characteristics of monthly rainfall in the Korean Peninsula under climate change

Global climate change is one of the most serious issues we are facing today. While its exact impacts on our water resources are hard to predict, there is a general consensus among scientists that it will result in more frequent and more severe hydrologic extremes (e.g. floods, droughts). Since rainfall is the primary input for hydrologic and water resource studies, assessment of the effects of climate change on rainfall is essential for devising proper short-term emergency measures as well as long-term management strategies. This is particularly the case for a region like the Korean Peninsula, which is susceptible to both floods (because of its mountainous terrain and frequent intense rainfalls during the short rainy season) and droughts (because of its smaller area, long non-rainy season, and lack of storage facilities). In view of this, an attempt is made in the present study to investigate the potential impacts of climate change on rainfall in the Korean Peninsula. More specifically, the dynamics of ‘present rainfall’ and ‘future rainfall’ at the Seoul meteorological station in the Han River basin are examined and compared; monthly scale is considered in both cases. As for ‘present rainfall,’ two different data sets are used: (1) observed rainfall for the period 1971–1999; and (2) rainfall for the period 1951–1999 obtained through downscaling of coarse-scale climate outputs produced by the Bjerknes Center for Climate Research-Bergen Climate Model Version 2 (BCCR-BCM2.0) climate model with the Intergovernmental Panel on Climate Change Special Report on Emission Scenarios (IPCC SRES) 20th Century Climate in Coupled Models (20C3M) scenario. The ‘future rainfall’ (2000–2099) is obtained through downscaling of climate outputs projected by the BCCR-BCM2.0 with the A2 emission scenario. For downscaling of coarse-scale climate outputs to basin-scale rainfall, a K-nearest neighbor (K-NN) technique is used. Examination of the nature of rainfall dynamics is made through application of four methods: autocorrelation function, phase space reconstruction, correlation dimension, and close returns plot. The results are somewhat mixed, depending upon the method, as to whether the rainfall dynamics are chaotic or stochastic; however, the dynamics of the future rainfall seem more on the chaotic side than on the stochastic side, and more so when compared to that of the present rainfall.     

Identifying Adaptive Reservoir Operation for Future Climate Change Scenarios: A Case Study in Central Vietnam

The assessment of flood risk under climate change impacts is necessary for sustainable flood management strategies at national level. Referring to the aforesaid statement, this research aims to evaluate the potential impacts of climate change on reservoir operations in the Huong River Basin, Vietnam. To enable further representation of climate change impacts, the HadGEM3-RA Regional Climate Model (RCM) under Representative Concentration Pathways (RCPs) 8.5 climate change scenario was used in this study. For assessing the level of flood risk posed to the study area, a coupled HEC-HMS hydrologic model and HEC-RAS hydrodynamic model was used to represent the behaviour of flow regimes under climate change impacts in the Huong River Basin. The key results demonstrated that the mean temperature and mean annual rainfall would be increased in the future from 0.2–0.8°C, and 4.8–6.0%, respectively. Consequently, the mean annual runoff and mean water level would also be increased from 10–30%, and 0.1–0.3 m above mean sea level, respectively. Moreover, the proposed reservoir operation rules corresponding to flood control warning stages was also derived to reduce peak flows downstream during the rainy season. Finally, the main findings of this study can be a good example for future planning of flood control reservoir systems in Vietnam.

     

Hydrological assessment of proposed reservoirs in the Sonora River Basin,Mexico, under historical and future climate scenarios

Abstract

A semi-distributed hydrological model and reservoir optimization algorithm are used to evaluate the potential impacts of climate change on existing and proposed reservoirs in the Sonora River Basin, Mexico. Inter-annual climatic variability, a bimodal precipitation regime and climate change uncertainties present challenges to water resource management in the region. Hydrological assessments are conducted for three meteorological products during a historical period and a future climate change scenario. Historical (1990–2000) and future (2031–2040) projections were derived from a mesoscale model forced with boundary conditions from a general circulation model under a high emissions scenario. The results reveal significantly higher precipitation, reservoir inflows, elevations and releases in the future relative to historical simulations. Furthermore, hydrological seasonality might be altered with a shift toward earlier water supply during the North American monsoon. The proposed infrastructure would have a limited ability to ameliorate future conditions, with more benefits in a tributary with lower flood hazard. These projections of the impacts of climate change and its interaction with infrastructure should be of interest to water resources managers in arid and semi-arid regions.

Editor D. Koutsoyiannis     

Alteration of hydrologic indicators for Korean catchments under CMIP5 climate projections

The change of hydrological regimes may cause impacts on human and natural system. Therefore, investigation of hydrologic alteration induced by climate change is essential for preparing timely proper adaptation to the changes. This study employed 24 climate projections from the Coupled Model Intercomparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 scenario. The climate projections were downscaled at a station‐spacing for seven Korean catchments by a statistical downscaling method that preserves a long‐term trend in climate projections. Using an ensemble of future hydrologic projections simulated by three conceptual rainfall‐runoff models (GR4J, IHACRES, and Sacramento models), we calculated Hydrologic Alteration Factors (HAFs) to investigate degrees of variations in Indicators of Hydrologic Alteration (IHAs) derived from the hydrologic projections. The results showed that the seven catchments had similar trend in terms of the HAFs for the 24 IHAs. Given that more frequent severe floods and droughts were projected over Korean catchments, sound water supply strategies are definitely required to adapt to the alteration of streamflow. A wide range of HAFs between rainfall‐runoff models for each catchment was detected by large variations in the magnitude of HAFs with the hydrologic models and the difference could be the hydrologic prediction uncertainty. There were no‐consistent tendency in the order of HAFs between the hydrologic models. In addition, we found that the alterations of hydrologic regimes by climate change are smaller as the size of catchment is larger. Copyright © 2016 John Wiley & Sons, Ltd.     

Impact assessment of climatic and land-use changes on flood runoff in southeast Queensland

Abstract

Over the past century, land-use has changed in southeast Queensland, and when coupled with climatic change, the risk of flooding has increased. This research aims to examine impacts of climate and land-use changes on flood runoff in southeast Queensland, Australia. A rainfall–runoff model, RORB, was calibrated and validated using observed flood hydrographs for one rural and one urbanized catchment, for 1961–1990. The validated model was then used to generate flood hydrographs using projected rainfall based on two climate models: the Geophysical Fluid Dynamics Laboratory Climate Model 2.1 (GFDL CM2.1) and the Conformal-Cubic Atmospheric Model (CCAM), for 2016–2045. Projected daily rainfall for the two contrasting periods was used to derive adjustment factors for a given frequency of occurrence. Two land-use change scenarios were used to evaluate likely impacts. Based on the projected rainfall, the results showed that, in both catchments, future flood magnitudes are unlikely to increase for large flood events. Extreme land-use change would significantly impact flooding in the rural catchment, but not the urbanized catchment.

Editor Z.W. Kundzewicz; Associate editor Y. Gyasi-Agyei     

Climate change and fluvial flood risk in the UK: more of the same?

The potential impact of climate change on fluvial flooding is receiving considerable scientific and political interest thanks to evidence from climate model projections and a widely held belief that flood risk may be increasing at European levels. This review compares published work on historical trends in UK rainfall and river flow records with high‐resolution regional climate change projections, and attempts to reconcile apparent differences between the two. Attention is focused on the techniques used for climate change detection and attribution, as well as the potential confounding effects of land‐use change. International and domestic efforts to build adaptive capacity rest on improved quantification of uncertainty in flood risk at very local, catchment and regional scales. This will involve further research to better integrate climate and land‐management interactions, to understand changes in the dependence between different flood generating mechanisms, and to improve the characterization and communication of uncertainty at all stages of analysis. Resources are also needed to ensure that latest, but still uncertain, science is presented in an appropriate form to underpin policy development and is translated into sensible guidance for practitioners. Copyright © 2007 John Wiley & Sons, Ltd.     

Effects of climate change on thermal properties of lakes and reservoirs, and possible implications

Meteorologic-driven processes exert large and diverse impacts on lakes’ internal heating, cooling, and mixing. Thus, continued global warming and climate change will affect lakes’ thermal properties, dynamics, and ecosystem. The impact of climate change on Lake Tahoe (in the states of California and Nevada in the United States) is investigated here, as a case study of climate change effects on the physical processes occurring within a lake. In the Tahoe basin, air temperature data show upward trends and streamflow trends indicate earlier snowmelt. Precipitation in the basin is shifting from snow to rain, and the frequency of intense rainfall events is increasing. In-lake water temperature records of the past 38 years (1970–2007) show that Lake Tahoe is warming at an average rate of 0.013°C/year. The future trends of weather variables, such as air temperature, precipitation, longwave radiation, downward shortwave radiation, and wind speed are estimated from predictions of three General Circulation Models (GCMs) for the period 2001–2100. Future trends of weather variables of each GCM are found to be different to those of the other GCMs. A series of simulation years into the future (2000–2040) is established using streamflows and associated loadings, and meteorologic data sets for the period 1994–2004. Future simulation years and trends of weather variables are selected so that: (1) future simulated warming trend would be consistent with the observed warming trend (0.013°C/year); and (2) future mixing pattern frequency would closely match with the historical mixing pattern frequency. Results of 40-year simulations show that the lake continues to become warmer and more stable, and mixing is reduced. Continued warming in the Tahoe has important implications for efforts towards managing biodiversity and maintaining clarity of the lake.     

Flood seasonality across Scandinavia—Evidence of a shifting hydrograph?

Fluvial flood events have substantial impacts on humans, both socially and economically, as well as on ecosystems (e.g., hydroecology and pollutant transport). Concurrent with climate change, the seasonality of flooding in cold environments is expected to shift from a snowmelt‐dominated to a rainfall‐dominated flow regime. This would have profound impacts on water management strategies, that is, flood risk mitigation, drinking water supply, and hydro power. In addition, cold climate hydrological systems exhibit complex interactions with catchment properties and large‐scale climate fluctuations making the manifestation of changes difficult to detect and predict. Understanding a possible change in flood seasonality and defining related key drivers therefore is essential to mitigate risk and to keep management strategies viable under a changing climate. This study explores changes in flood seasonality across near‐natural catchments in Scandinavia using circular statistics and trend tests. Results indicate strong seasonality in flooding for snowmelt‐dominated catchments with a single peak occurring in spring and early summer (March through June), whereas flood peaks are more equally distributed throughout the year for catchments located close to the Atlantic coast and in the south of the study area. Flood seasonality has changed over the past century seen as decreasing trends in summer maximum daily flows and increasing winter and spring maximum daily flows with 5–35% of the catchments showing significant changes at the 5% significance level. Seasonal mean daily flows corroborate those findings with higher percentages (5–60%) of the catchments showing statistically significant changes. Alterations in annual flood occurrence also point towards a shift in flow regime from snowmelt‐dominated to rainfall‐dominated with consistent changes towards earlier timing of the flood peak (significant for 25% of the catchments). Regionally consistent patterns suggest a first‐order climate control as well as a local second‐order catchment control, which causes inter‐seasonal variability in the streamflow response.     

Assessment of future groundwater recharge in semi‐arid regions under climate change scenarios (Serral‐Salinas aquifer,SE Spain). Could increased rainfall variability increase the recharge rate?

The projected impact of climate change on groundwater recharge is a challenge in hydrogeological research because substantial doubts still remain, particularly in arid and semi‐arid zones. We present a methodology to generate future groundwater recharge scenarios using available information about regional climate change projections developed in European Projects. It involves an analysis of regional climate model (RCM) simulations and a proposal for ensemble models to assess the impacts of climate change. Future rainfall and temperature series are generated by modifying the mean and standard deviation of the historical series in accordance with estimates of their change provoked by climate change. Future recharge series will be obtained by simulating these new series within a continuous balance model of the aquifer. The proposed method is applied to the Serral‐Salinas aquifer, located in a semi‐arid zone of south‐east Spain. The results show important differences depending on the RCM used. Differences are also observed between the series generated by imposing only the changes in means or also in standard deviations. An increase in rainfall variability, as expected under future scenarios, could increase recharge rates for a given mean rainfall because the number of extreme events increases. For some RCMs, the simulations predict total recharge increases over the historical values, even though climate change would produce a reduction in the mean rainfall and an increased mean temperature. A method based on a multi‐objective analysis is proposed to provide ensemble predictions that give more value to the information obtained from the best calibrated models. The ensemble of predictions estimates a reduction in mean annual recharge of 14% for scenario A2 and 58% for scenario A1B. Lower values of future recharge are obtained if only the change in the mean is imposed. Copyright © 2014 John Wiley & Sons, Ltd.     

The impact of climate change on groundwater recharge and runoff in a humid,equatorial catchment: sensitivity of projections to rainfall intensity

Abstract

Projected warming in equatorial Africa, accompanied by greater evaporation and more frequent heavy precipitation events, may have substantial but uncertain impacts on terrestrial hydrology. Quantitative analyses of climate change impacts on catchment hydrology require high-resolution (<50 km) climate data provided by regional climate models (RCMs). We apply validated precipitation and temperature data from the RCM PRECIS (Providing Regional Climates for Impact Studies) to a semi-distributed soil moisture balance model (SMBM) in order to quantify the impacts of climate change on groundwater recharge and runoff in a medium-sized catchment (2098 km²) in the humid tropics of southwestern Uganda. The SMBM explicitly accounts for changes in soil moisture, and partitions effective precipitation into groundwater recharge and runoff. Under the A2 emissions scenario (2070–2100), climate projections from PRECIS feature not only rises in catchment precipitation and modelled potential evapotranspiration by 14% and 53%, respectively, but also increases in rainfall intensity. We show that the common application of the historical rainfall distribution using delta factors to the SMBM grossly underestimates groundwater recharge (i.e. 55% decrease relative to the baseline period of 1961–1990). By transforming the rainfall distribution to account for changes in rainfall intensity, we project increases in recharge and runoff of 53% and 137%, respectively, relative to the baseline period.     

Simulation of daily rainfall scenarios with interannual and multidecadal climate cycles for South Florida

Concerns about the potential effects of anthropogenic climate change have led to a closer examination of how climate varies in the long run, and how such variations may impact rainfall variations at daily to seasonal time scales. For South Florida in particular, the influences of the low-frequency climate phenomena, such as the El Nino Southern Oscillation (ENSO) and the Atlantic Multi-decadal Oscillation (AMO), have been identified with aggregate annual or seasonal rainfall variations. Since the combined effect of these variations is manifest as persistent multi-year variations in rainfall, the question of modeling these variations at the time and space scales relevant for use with the daily time step-driven hydrologic models in use by the South Florida Water Management District (SFWMD) has arisen. To address this problem, a general methodology for the hierarchical modeling of low- and high-frequency phenomenon at multiple rain gauge locations is developed and illustrated. The essential strategy is to use long-term proxies for regional climate to first develop stochastic scenarios for regional climate that include the low-frequency variations driving the regional rainfall process, and then to use these indicators to condition the concurrent simulation of daily rainfall at all rain gauges under consideration. A newly developed methodology, called Wavelet Autoregressive Modeling (WARM), is used in the first step after suitable climate proxies for regional rainfall are identified. These proxies typically have data available for a century to four centuries so that long-term quasi-periodic climate modes of interest can be identified more reliably. Correlation analyses with seasonal rainfall in the region are used to identify the specific proxies considered as candidates for subsequent conditioning of daily rainfall attributes using a Non-homogeneous hidden Markov model (NHMM). The combined strategy is illustrated for the May–June–July (MJJ) season. The details of the modeling methods and results for the MJJ season are presented in this study.     

Large scale climate and rainfall seasonality in a Mediterranean Area: Insights from a non‐homogeneous Markov model applied to the Agro‐Pontino plain

In the context of climate change and variability, there is considerable interest in how large scale climate indicators influence regional precipitation occurrence and its seasonality. Seasonal and longer climate projections from coupled ocean–atmosphere models need to be downscaled to regional levels for hydrologic applications, and the identification of appropriate state variables from such models that can best inform this process is also of direct interest. Here, a Non‐Homogeneous Hidden Markov Model (NHMM) for downscaling daily rainfall is developed for the Agro‐Pontino Plain, a coastal reclamation region very vulnerable to changes of hydrological cycle. The NHMM, through a set of atmospheric predictors, provides the link between large scale meteorological features and local rainfall patterns. Atmospheric data from the NCEP/NCAR archive and 56‐years record (1951–2004) of daily rainfall measurements from 7 stations in Agro‐Pontino Plain are analyzed. A number of validation tests are carried out, in order to: 1) identify the best set of atmospheric predictors to model local rainfall; 2) evaluate the model performance to capture realistically relevant rainfall attributes as the inter‐annual and seasonal variability, as well as average and extreme rainfall patterns. Validation tests show that the best set of atmospheric predictors are the following: mean sea level pressure, temperature at 1000 hPa, meridional and zonal wind at 850 hPa and precipitable water, from 20°N to 80°N of latitude and from 80°W to 60°E of longitude. Furthermore, the validation tests show that the rainfall attributes are simulated realistically and accurately. The capability of the NHMM to be used as a forecasting tool to quantify changes of rainfall patterns forced by alteration of atmospheric circulation under climate change and variability scenarios is discussed.     

Projected risks to groundwater‐dependent terrestrial vegetation caused by changing climate and groundwater abstraction in the Central Perth Basin,Western Australia

The effect of potential climate change on groundwater‐dependent vegetation largely depends on the nature of the climate change (drying or wetting) and the level of current ecosystem dependence on groundwater resources. In south‐western Australia, climate projections suggest a high likelihood of a warmer and drier climate. The paper examines the potential environmental impacts by 2030 at the regional scale on groundwater‐dependent terrestrial vegetation (GDTV) adapted to various watertable depths, on the basis of the combined consideration of groundwater modelling results and the framework for GDTV risk assessment. The methodology was tested for the historical period from 1984 to 2007, allowing validation of the groundwater model results' applicability to such an assessment. Climate change effects on GDTV were evaluated using nine global climate models under three greenhouse gas emission scenarios by applying the climate projections to groundwater models. It was estimated that under dry climate scenarios, GDTV is likely to be under high and severe risk over more than 20% of its current habitat area. The risk is also likely to be higher under an increase in groundwater abstraction above current volumes. The significance of climate change risk varied across the region, depending on both the intensity of the change in water regime and the sensitivity of the GDTV to such change. Greater effects were projected for terrestrial vegetation dependent on deeper groundwater (6–10 m). Copyright © 2013 John Wiley & Sons, Ltd.     

Evaluation of floodplain variability considering impacts of climate change

In this study, an approach is presented for handling hydraulic uncertainties in the prediction of floodplain. Different factors affect river flood characteristics. Furthermore, the high changeability of flooding conditions leads to high variability of the inundation. River morphology is one of the most effective factors in river flood characteristics. This factor is influenced by sedimentation and erosion in the river cross sections, which affects the discharge variation. The depth and the width of the river cross section lead to an increase or decrease in the river flow path. This results in changes in the extent of the floodplain based on the generated rainfall. The inundated region boundaries are determined by utilizing the mean first‐order second‐moment analysis. The proposed method is applied to the Kajoo River in the south‐eastern part of Iran. Determination of floodplain uncertainty is a damage‐reduction policy in this region. Also, it is useful to prepare the necessary activities for overcoming the flood hazards. Climate change is the second effective factor on the floodplain uncertainties. Climate change affects the magnitude, extent and depth of inundation and it may intensify the flood problem. Therefore, the future rainfall pattern of the study area under climate change is simulated to evaluate its impacts on the river flow characteristic. Subsequently, a hydraulic routing model is used to determine floodplain. Finally, the copula function is used to estimate the joint probability of the changes in the inundation area due to changes in river morphology and the rainfall changes due to impacts of climate change. Results show that the uncertainties of the extent of floodplain are affected by climate change and river morphology, leading to noticeable changes in the magnitude and frequency of floods. Evaluating these impacts and estimating corresponding river discharges will help in the study of river dynamics, and will also contribute towards devising effective mitigation and management strategies. Copyright © 2010 John Wiley & Sons, Ltd.     

Response of hydrological processes to land‐cover and climate changes in Kejie watershed,south‐west China

Land‐cover/climate changes and their impacts on hydrological processes are of widespread concern and a great challenge to researchers and policy makers. Kejie Watershed in the Salween River Basin in Yunnan, south‐west China, has been reforested extensively during the past two decades. In terms of climate change, there has been a marked increase in temperature. The impact of these changes on hydrological processes required investigation: hence, this paper assesses aspects of changes in land cover and climate. The response of hydrological processes to land‐cover/climate changes was examined using the Soil and Water Assessment Tool (SWAT) and impacts of single factor, land‐use/climate change on hydrological processes were differentiated. Land‐cover maps revealed extensive reforestation at the expense of grassland, cropland, and barren land. A significant monotonic trend and noticeable changes had occurred in annual temperature over the long term. Long‐term changes in annual rainfall and streamflow were weak; and changes in monthly rainfall (May, June, July, and September) were apparent. Hydrological simulations showed that the impact of climate change on surface water, baseflow, and streamflow was offset by the impact of land‐cover change. Seasonal variation in streamflow was influenced by seasonal variation in rainfall. The earlier onset of monsoon and the variability of rainfall resulted in extreme monthly streamflow. Land‐cover change played a dominant role in mean annual values; seasonal variation in surface water and streamflow was influenced mainly by seasonal variation in rainfall; and land‐cover change played a regulating role in this. Surface water is more sensitive to land‐cover change and climate change: an increase in surface water in September and May due to increased rainfall was offset by a decrease in surface water due to land‐cover change. A decrease in baseflow caused by changes in rainfall and temperature was offset by an increase in baseflow due to land‐cover change. Copyright © 2009 John Wiley & Sons, Ltd.     

Impacts of projected climate change on sediment yield and dredging costs

Changes in climate may significantly affect how sediment moves through watersheds into harbours and channels that are dredged for navigation or flood control. Here, we applied a hydrologic model driven by a large suite of climate change scenarios to simulate both historical and future sediment yield and transport in two large, adjacent watersheds in the Great Lakes region. Using historical dredging expenditure data from the U.S. Army Corps of Engineers, we then developed a pair of statistical models that link sediment discharge from each river to dredging costs at the watershed outlet. Although both watersheds show similar slight decreases in streamflow and sediment yield in the near‐term, by Mid‐Century, they diverge substantially. Dredging costs are projected to change in opposite directions for the two watersheds; we estimate that future dredging costs will decline in the St. Joseph River by 8–16% by Mid‐Century but increase by 1–6% in the Maumee River. Our results show that the impacts of climate change on sediment yield and dredging may vary significantly by watershed even within a region and that agricultural practices will play a large role in determining future streamflow and sediment loads. We also show that there are large variations in responses across climate projections that cause significant uncertainty in sediment and dredging projections.     

Vulnerability of water resources under a changing climate and human activity in the lower Great Lakes region

Globally, the number of people experiencing water stress is expected to increase by millions by the end of the century. The Great Lakes region, representing 20% of the world's surface freshwater, is not immune to stresses on water supply due to uncertainties on the impacts of climate and land use change. It is imperative for researchers and policy makers to assess the changing state of water resources, even if the region is water rich. This research developed the integrated surface water-groundwater GSFLOW model and investigated the effects of climate change and anthropogenic activities on water resources in the lower Great Lakes region of Western New York. To capture a range of scenarios, two climate emission pathways and three land development projections were used, specifically RCP 4.5, RCP 8.5, increased urbanization by 50%, decreased urbanization by 50%, and current land cover, respectively. Model outputs of surface water and groundwater discharge into the Great Lakes and groundwater storage for mid- and late century were compared to historical to determine the direction and amplitude of changes. Both surface water and groundwater systems show no statistically significant changes under RCP 4.5 but substantial and worrisome losses with RCP 8.5 by mid-century and end of century. Under RCP 8.5, streamflow decreased by 22% for mid-century and 42% for late century. Adjusting impervious surfaces revealed complex land use effects, resulting in spatially varying groundwater head fluctuations. For instance, increasing impervious surfaces lowered groundwater levels from 0.5 to 3.8 m under Buffalo, the largest city in the model domain, due to reduced recharge in surrounding suburban areas. Ultimately, results of this study highlight the necessity of integrated modelling in assessing temporal changes to water resources. This research has implications for other water-rich areas, which may not be immune to effects of climate change and human activities.     

Multi-scale variability and trends of precipitation in North China

The issue of water shortage and related eco-environmental degradation in North China is one of the major emerging problems in China. Precipitation is the most key factor for water resources. Based on the historical flood/dryness grade dataset during the period of 1470–2000 obtained from 25 gauging stations in North China, the multi-scale variability and trends are analyzed by means of power spectral and continuous wavelet transform. It is found that the precipitation is characterized by obvious seasonal changes, quasi biennial oscillations, inter-annual 4–7 year component and inter-decadal 19-year periodicity. The MK test results showe that step changes occurred around 1914 and 1964 in the annual precipitation. As for the historical flood/dryness grade time series, it is characterized by 4∼5 year ENSO mode inter-annual oscillation, quasi-10 year inter-decadal variability, quasi-24 year component and 50–80 year centurial periodicity. However, the scales of these variations have decreased significantly since the 1970s. The trend for precipitation change in North China has been negative for last 30 years. Further research shows that North China will continue to become dryer until 2015 and may change to a wetter regime after 2020. These findings should be helpful for future decision-making to ensure sustainable water resource management in North China.     

A Study on Simulation of Heavy Rainfall Events Over Indian Region with ARW-3DVAR Modeling System

An attempt is made to evaluate the impact of the three dimensional variational (3DVAR) data assimilation within the Weather Research Forecasting (WRF) modeling system to simulate two heavy rainfall events which occured on 26–27 July 2005 and 27–30 July 2006. During the 26–27 July 2005 event, the unprecedented localized intense rainfall 90–100 cm was recorded over the northeast parts of Mumbai city; however, southern parts received only 10 cm. Model simulation with the data assimilation experiment is reasonably well predicted for the rainfall intensity (800 mm) in 24 h and with accurate location over Mumbai agreeing with observation. Divergence, vorticity, vertical velocity and moisture parameters are evaluated during the various stages of the event. It is noticed that maximum convergence and vorticity during the mature stage; at the same time the vertical velocity also follows a similar trend during the period in the assimilation experiment. Vorticity budget terms over the location of heavy rainfall revealed that the contribution of the positive tilting term produced positive vorticity which triggered the convection and negative contribution to vorticity from the tilting term to precede the dissipation of the system. Model simulations from the second rain event, the off-shore trough at sea level along the west coast of India, is well represented after assimilation of observations during day-1 and day-2 as compared to the control simulations; the orientation of the off-shore trough is well matched with that of the observed. The intensity and spatial distribution of the rainfall has considerably improved in the assimilation simulation. The statistical skill scores also revealed that the precipitation forecast during the period has appreciably improved due to assimilation of observations. The results of this study indicate a positive impact of the 3DVAR assimilation on the simulation of heavy rainfall events.     

Using the present to estimate the future: A simplified approach for the quantification of climate change effects on urban flooding by scenario analysis

Understanding and modelling pluvial flood patterns is pivotal for the estimation of flood impacts in urban areas, especially in a climate change perspective. However, urban flood modelling under climate change conditions poses several challenges. On one hand, the identification and collection of climate change data suitable for flood-related evaluations requires consistent computational and scientific effort. On the other hand, large difficulties can arise in the reproduction of the rainfall-runoff transformation process in cases when only little information about the subsurface processes is known. In this perspective, a simplified approach is proposed to address the challenges regarding the quantitative estimation of climate change effects on urban flooding for real case applications. The approach is defined as “bottom-up” because climate change information is not included in flood modelling, but it is only invoked for the interpretation of results. In other words, the challenge faced in this work is the development of a modelling strategy that is expeditious, because it does not require flood simulations for future rainfall scenarios, but only under current climate conditions, thus reducing the overall computational effort; and it is flexible, because results can be easily updated once new climate change data, scenarios or methods become available, without the need of additional flood simulations. To simulate real case applications, the approach is tested for a scenario analysis, where different return periods and hyetograph shapes are used as input for urban inundation modelling in Naples, Italy. The approach can support public and private stakeholders, such as land administrators and water systems managers; moreover, it represents a valuable and effective basis for climate change risk communication strategies.