Impact of Climate Change on the Hydrology of Upper Tiber River Basin Using Bias Corrected Regional Climate Model

The use of regional climate model (RCM) outputs has been getting due attention in most European River basins because of the availability of large number of the models and modelling institutes in the continent; and the relative robustness the models to represent local climate. This paper presents the hydrological responses to climate change in the Upper Tiber River basin (Central Italy) using bias corrected daily regional climate model outputs. The hydrological analysis include both control (1961–1990) and future (2071–2100) climate scenarios. Three RCMs (RegCM, RCAO, and PROMES) that were forced by the same lateral boundary condition under A2 and B2 emission scenarios were used in this study. The projected climate variables from bias corrected models have shown that the precipitation and temperature tends to decrease and increase in summer season, respectively. The impact of climate change on the hydrology of the river basin was predicted using physically based Soil and Water Assessment Tool (SWAT). The SWAT model was first calibrated and validated using observed datasets at the sub-basin outlet. A total of six simulations were performed under each scenario and RCM combinations. The simulated result indicated that there is a significant annual and seasonal change in the hydrological water balance components. The annual water balance of the study area showed a decrease in surface runoff, aquifer recharge and total basin water yield under A2 scenario for RegCM and RCAO RCMs and an increase in PROMES RCM under B2 scenario. The overall hydrological behaviour of the basin indicated that there will be a reduction of water yield in the basin due to projected changes in temperature and precipitation. The changes in all other hydrological components are in agreement with the change in projected precipitation and temperature.     

Spatio-temporal effect of climate and land-use change on water balance of the Ganga river basin

The assessment of climate and land-use transformations upon the hydrologic response is crucial for decision-makers to accomplish various adaptation strategies. The Regional Climate Models (RCMs) have been extensively employed to study the impact of climate change on various hydrologic components. However, these climate models are subjected to a large number of uncertainties, which demands a careful selection of an appropriate climate model. To rationalize such uncertainties and select suitable models, a multi-criteria ranking technique has been employed. Ranking of RCMs has been done on its capability to simulate hydrologic components, i.e., simulations of the surface runoff by employing Soil Water Assessment Tool (SWAT), exercising Entropy, and PROMETHEE-2 approach. The spatial extent of changes in the hydrologic components is examined over the Ganga river basin, using the top three ranked RCMs, for a period from January 2021-December 2100. For the monsoon months (June-September), the future annual mean surface runoff will decrease substantially (−50% to −10%), while the flows for post-monsoon months (October-December) are projected to increase (10–20%). Extremes are noted to increase during the non-monsoon months, while a substantial decrease in medium events is also highlighted. Snow-melt is projected to increase during the months of November-March (50% to 400%). Major loss of recharge is expected to occur in the central part of the basin. The investigation presents not only a reliable impact assessment but also the valuation of future alterations in individual hydrological components and will furnish the administrators with substantive information, a prerequisite to formulating ameliorative policies.     

A Semi-Distributed Monthly Water Balance Model and its Application in a Climate Change Impact Study in the Middle and Lower Yellow River Basin

Abstract

Human activities and climatic change have greatly impacted hydrological cycles and water resources planning in the Yellow River basin. In order to assess these impacts, a semi-distributed monthly water balance model was proposed and developed to simulate and predict the hydrological processes in the middle and lower Yellow River basin. GIS techniques were used as a tool to analyze topography, river networks, land-use, human activities, vegetation, and soil characteristics. The model parameters were calibrated in 35 gauged sub-basins in the middle Yellow River, and then the relationships between the model parameters and the basin physical characteristics were established. A parameterization scheme was developed in which the model parameters were estimated for each grid element by regression and optimization methods. Based on the different outputs of general circulation models (GCMs) and regional climate models (RCMs), the sensitivities to global warming of hydrology and water resources for the Yellow River basin were studied. The proposed models are capable of producing both the magnitude and timing of runoff and water resources conditions. The runoffs are found to be very sensitive to temperature increases and rainfall decreases. Results of the study also indicated that runoff is more sensitive to variation in precipitation than to increase in temperature. The additional uncertainty of climate change has posed a challenge to the existing water resources management practices, and the integration of water resources management will be necessary to enhance the water use efficiency in the Yellow River basin.     

Future Scenarios of Surface Water Resources Availability in North African Dams

Climate change may have strong impacts on water resources in developing countries. In North Africa, many dams and reservoirs have been built to secure water availability in the context of a strong inter-annual variability of precipitation. The goal of this study is to evaluate climate change impacts on surface water resources for the largest dams in Algeria, Morocco and Tunisia using high-resolution (12 km) regional climate models (RCM) simulations. To evaluate the atmospheric demand (evapotranspiration), two approaches are compared: The direct use of actual evaporation simulated by the RCMs, or estimation of reference evapotranspiration computed with the Hargreaves-Samani (HAR) equation, relying on air temperature only, and the FAO-Penman Monteith (PM) equation, computed with temperature, wind, radiation and relative humidity. Results showed a strong convergence of the RCM simulations towards increased temperature and a decrease in precipitation, in particular during spring and the western part of North Africa. A decrease in actual evapotranspiration, highly correlated to the decrease in precipitations, is observed throughout the study area. On the opposite, an increase in reference evapotranspiration is observed, with similar changes between HAR and PM equations, indicating that the main driver of change is the temperature increase. Since the catchments are rather water-limited than energy-limited, despite opposite projections for actual and reference evapotranspiration a decrease of water availability is projected for all basins under all scenarios, with a strong east-to-west gradient. The projected decrease is stronger when considering reference evapotranspiration rather than actual evaporation. These pessimistic future projections are an incentive to adapt the current management of surface water resources to future climatic conditions.     

Climate change tendencies observable in the rainfall measurements since 1950 in the federal land of North Rhine-Westphalia and their consequences for urban hydrology

Climate change is present in climatological models - but did we already observe changes in the past measurement data? For the state of North Rhine Westphalia, the rainfall measurements since 1950 have been systematically analysed in order to find out whether there have already been trends and whether the behaviour of rainfall has changed in time. More than 600 station series have been screened for use in the project and quality controlled. Implausible data were discarded. For the analysis, standard values such as yearly sums, half-yearly sums, monthly sums, number of dry days, number of days with precipitation above a threshold, partial time series and extreme values statistics have been calculated and evaluated. Results show that also in the past 50 years, changes in precipitation regime could be observed. These changes have been regionally different. Consequences for urban hydrology include a development of more flexible design approaches.     

Evaluation of Simple Statistical Downscaling Methods for Monthly Regional Climate Model Simulations with Respect to the Estimated Changes in Runoff in the Czech Republic

An ensemble of fifteen regional climate model (RCM) simulations has been used to estimate the climate change impacts on runoff and several drought characteristics for 250 basins in the Czech Republic. The scenario series of precipitation and temperature have been derived with four simple statistical downscaling methods (SDMs): the delta change and bias correction method, both in two alternatives considering the changes/biases in the mean, and in the mean and variance. Bootstrap resampling has been used to assess the effect of sampling variability and the differences in the estimated changes in runoff obtained by different SDMs were evaluated. Further simplification of the SDMs (spatial-average changes/biases and ensemble-average changes in precipitation and temperature) have been considered. It was shown, that given the spread between the projections of individual RCM simulations and the sampling variability, the differences in the estimated changes in mean runoff between the SDMs are not very large. The same partly holds also for the effect of spatial averaging. In general, the SDMs accounting for variability have led to smaller decrease (or larger increase) in runoff and the decrease was also smaller for bias correction methods than in the case of delta change methods. In contrast to changes in mean runoff, significant differences between the estimates based on different SDMs were found for the drought characteristics. In addition, the averaging of the changes in precipitation and temperature over the RCMs resulted in much stronger decrease in runoff than indicated by ensemble average changes in runoff.     

Multi‐scale modelling of land‐use change and river training effects on floods in the Rhine basin

Land‐use changes effects on floods are investigated by a multi‐scale modelling study, where runoff generation in catchments of different sizes, different land uses and morphological characteristics are simulated in a nested manner. The macro‐scale covers the Rhine basin (excluding the alpine part), the upper meso‐scale covers various tributaries of the Rhine and three lower meso‐scale study areas (100–500 km²) represent different characteristic land‐use patterns. The main innovation is the combination of models at different scales and at different levels of process representation in order to account for the complexity of land‐use change impacts for a large river basin. The results showed that the influence of land‐use on storm runoff generation is stronger for convective storm events with high precipitation intensities than for long advective storms with low intensities. The simulated flood increase at the lower meso‐scale for a scenario of rather strong urbanization is in the order of 0 and 4% for advective rainfall events, and 10–30% for convective rain storms with a return period of 2–10 years. Convective storm events, however, are of hardly any relevance for the formation of floods in the large river basins of Central Europe, because the extent of convective rainstorms is restricted to local occurrence. Due to the dominance of advective precipitation for macro‐scale flooding, limited water retention capacity of antecedent wet soils and superposition of flood waves from different tributaries, the land‐use change effects at the macro‐scale are even smaller, for example at Cologne (catchment area 100 000 km²), land‐use change effects may result in not more than 1–5 cm water level of the Rhine. Water retention measures in polders along the Upper and Lower Rhine yield flood peak attenuation along the Rhine all the way down to the Dutch border between 1 and 15 cm. Copyright © 2007 John Wiley & Sons, Ltd.     

西北地区可利用年降水量趋势分析及预测

利用1951—2009年逐月降水量和气温资料,分析了近60 a来西北地区的年降水量、气温、年蒸发量及可利用年降水量的变化特征,采用逐步回归周期分析法对各气候要素及可利用年降水量建立预报模型,并对未来5 a上述要素的变化趋势进行了预测。结果表明:西北地区的年降水量、气温、年蒸发量及可利用年降水量随时间的变化特征各不相同;未来5 a内,西北地区年降水量、年均气温、年蒸发量及可利用年降水量均有减少或降低趋势。     

Potential outcomes of multi-variable climate change on water resources in the Santa Basin,Peru

Water resources in the Santa Basin in the Peruvian Andes are increasingly under pressure from climate change and population increase. Impacts of temperature-driven glacier retreat on streamflow are better studied than those of precipitation changes, yet present and future water resources are mostly dependent on precipitation, which is more difficult to predict with climate models. This study combines a broad range of projections from climate models with a hydrological model (WaterWorld), showing a general trend towards an increase in water availability due to precipitation increases over the basin. However, high uncertainties in these projections necessitate basin-wide policies aimed at increased adaptability.     

Assessment of Climate Change Impacts on River High Flows through Comparative Use of GR4J, HBV and Xinanjiang Models

This study analyses the extreme high flows in Jinhua River basin under the impact of climate change for the near future 2011–2040. The objective of this study is to investigate the effect of using the bias corrected RCM outputs as input on the extreme flows by hydrological models. The future projections are obtained through the PRECIS model with resolution of 50 km?×?50 km under climate scenario A1B. The daily precipitation from the PRECIS is bias corrected by distribution based scaling method. Afterwards, three hydrological models (GR4J, HBV and Xinanjiang) are calibrated and applied to simulate the daily discharge in the future. The hydrological models are driven with both bias corrected precipitation and raw precipitation from the PRECIS model for 2011–2040. It is found that after bias correction, the amount, frequency, intensity and variance of the precipitation from the regional climate model resemble the observation better. For the three hydrological models, the simulated annual maximum discharges are higher by using the raw precipitation from PRECIS than by bias corrected precipitation at any return period. Meanwhile, the uncertainties from different models cannot be neglected. The largest difference between three models is about 2,100 m³/s.     

环境变化对径流的影响研究综述

环境变化主要指气候变化(波动)和流域内的人类活动。径流是降水、气温等气候因素和人类活动对流域产汇流影响的结果,本文综述了定量分析气候变化和人类活动对径流影响的研究思路、确定基准期的方法、径流的还原方法及目前使用的各种模型,最后归纳总结了目前研究中存在的不足和今后研究的趋势。     

海河流域60年降水量的变化及未来情景分析

降水量是水文循环的重要因素。利用Mann-Kendall趋势检验方法,分析了1951—2010年海河流域降水量的历史演变规律;并根据大气环流数据分析了降水变化的原因;利用全球气候模式数据预测了未来降水量的可能变化情景。主要结论为:(1)1951—2010年,海河流域的年降水量呈显著减少趋势,达到了5%的显著性水平,其中夏季降水减少的幅度最大。(2)南方涛动指数(SOI)和海河流域降水具有较好的正相关,而太平洋年代波动(PDO)和太平洋年代内的波动(IPO)与海河流域降水具有较好的负相关。(3)在未来气候变化背景下,海河流域的年降水量和月降水量都将呈现出增加趋势;在A1B情景下,总体上流域东部降水量的增加幅度要大于流域西部。相关研究成果对于保障流域的水资源安全,支撑区域经济社会可持续发展,具有重要的科学价值和实际意义。     

统计降尺度方法及其评价指标比较研究

针对目前气候变化对水资源影响研究中关注的问题,以汉江白河上游为研究对象,比较研究统计降尺度方法及其评价指标。以美国环境预报中心/美国国家大气研究中心全球再分析资料、CGCM3和HadCM3的A2情景为大尺度气候背景资料,应用SSVM和SDSM统计降尺度方法对大尺度气候因子进行尺度降解,得到降水情景序列后作为水文模型的输入,通过模拟径流比较分析统计降尺度方法的优劣。研究结果表明,由不同统计降尺度方法得到的降水作为水文模型输入,模拟径流的结果相差很大;对广泛应用于统计降尺度方法的降水模拟评价指标和径流模拟结果进行比较,发现所采用的降水评价指标侧重于考虑降水的统计分布特征,不能完整地描述降水过程特性。分析认为,径流模拟结果应该作为气候变化对径流影响研究中统计降尺度方法评价的重要参考。     

Cross-Comparison of Climate Change Adaptation Strategies Across Large River Basins in Europe, Africa and Asia

A cross-comparison of climate change adaptation strategies across regions was performed, considering six large river basins as case study areas. Three of the basins, namely the Elbe, Guadiana, and Rhine, are located in Europe, the Nile Equatorial Lakes region and the Orange basin are in Africa, and the Amudarya basin is in Central Asia. The evaluation was based mainly on the opinions of policy makers and water management experts in the river basins. The adaptation strategies were evaluated considering the following issues: expected climate change, expected climate change impacts, drivers for development of adaptation strategy, barriers for adaptation, state of the implementation of a range of water management measures, and status of adaptation strategy implementation. The analysis of responses and cross-comparison were performed with rating the responses where possible. According to the expert opinions, there is an understanding in all six regions that climate change is happening. Different climate change impacts are expected in the basins, whereas decreasing annual water availability, and increasing frequency and intensity of droughts (and to a lesser extent floods) are expected in all of them. According to the responses, the two most important drivers for development of adaptation strategy are: climate-related disasters, and national and international policies. The following most important barriers for adaptation to climate change were identified by responders: spatial and temporal uncertainties in climate projections, lack of adequate financial resources, and lack of horizontal cooperation. The evaluated water resources management measures are on a relatively high level in the Elbe and Rhine basins, followed by the Orange and Guadiana. It is lower in the Amudarya basin, and the lowest in the NEL region, where many measures are only at the planning stage. Regarding the level of adaptation strategy implementation, it can be concluded that the adaptation to climate change has started in all basins, but progresses rather slowly.     

Uncertainty Modeling of Statistical Downscaling to Assess Climate Change Impacts on Temperature and Precipitation

Consideration of different Statistical Downscaling (SD) models and multi-sources global climate models’ (GCMs) data can provide a better range of uncertainty for climatic and statistical indices. In this study, results of two SD models, ASD (Automated Statistical Downscaling) and SDSM (Statistical Downscaling Model), were used for uncertainty analysis of temperature and precipitation prediction under climate change impacts for two meteorological stations in Iran. Uncertainty analysis was performed based on application of two GCMs and climate scenarios (A2, A1B, A2a and B2a) for 2011–2040, 2041–2070 and 2071–2100 future time slices. A new technique based on fuzzy logic was proposed and only used to describe uncertainties associated with downscaling methods in temperature and precipitation predictions. In this technique, different membership functions were defined to fuzzify results. Based on these functions width, precipitation had higher uncertainty in comparison with the temperature which could be attributed to the complexity of temporal and local distribution of rainfall. Moreover, little width of membership functions for temperatures in both stations indicated less uncertainty in cold months, whereas the results showed more uncertainty for summer. The results of this study highlight the significance of incorporating uncertainty associated with two downscaling approaches and outputs of GCMs (CGCM3 and HadCM3) under emission scenarios A2, A1B, A2a and B2a in hydrologic modeling and future predictions.     

Climate Change Risk Management in Transnational River Basins: The Rhine

Climate change is likely to have an impact on the discharge of the European river Rhine. To base adaptation strategies, to deal with these changing river discharges, on the best scientific and technical knowledge, it is important to understand potential climate impacts, as well as the capacity of social and natural systems to adapt. Both are characterized by large uncertainties, at different scales, that range from individual to local to regional to international. This review paper addresses three challenges. Dealing with climate change uncertainties for the development of adaptation strategies is the first challenge. We find that communication of uncertainties in support of river basin adaptation planning generally only covers a small part of the spectrum of prevailing uncertainties, e.g. by using only one model or scenario and one approach to deal with the uncertainties. The second challenge identified in this paper is to overcome the current mismatch of supply of scientific knowledge by scientists and the demand by policy makers. Early experiences with ‘assess-risk-of-policy’ approaches analysis of options, starting from the resilience of development plans, suggests that this approach better responds to policy makers’ needs. The third challenge is to adequately capture the transnational character of the Rhine river basin in research and policy. Development and implementation of adaptation options derived from integrated analysis at the full river basin level, rather than within the boundaries of the riparian countries, can offer new opportunities, but will also meet many practical challenges.     

Climatic change and the effect on hydrology and water management in the Rhine basin.

There has been a marked increase in recent years in the resources dedicated to investigating the problems arising from climate change with respect to hydrology and to some extent to water resource management. Many of these studies are concentrated on the river Rhine basin. In order to review the actual state of scientific findings a workshop, organised by the International Commission for the Hydrology of the Rhine (CHR), was held on 24 and 25 June 2003. The invited experts discussed the following topics: observed variability in climatic and hydrological data, the development and interpretation of climate scenarios, and assessment of changes in the discharge regimes and the occurrence of hydrological extremes. Based on the workshop the question of whether or not current knowledge and procedural strategies can be used as a basis for future water management was evaluated by an expert group of the CHR. In this paper the process of decision-making with regard to flood management is analysed. Hints are given to convince the decision-makers to take into account the impacts of climate change in water resources management. The special challenges arising in international river basins are discussed.     

2011~2060年长江上游流域降水变化 预估问题的探讨

对IPCC 第四次评估报告中12个全球气候模式集合平均制作的中国地区气候变化预估数据集（Version2.0）和长江上游流域逐日的降水观测数据进行了比较验证,结果表明：全球气候模式对长江上游流域的降水的时空变化具有一定的模拟能力,可以用来对长江上游流域未来的气候变化进行预估研究。在此基础上,进一步利用国家气候中心多模式模拟结果的降水数据开展了该流域未来50年降水的时间和空间分布变化的预估研究。结果表明,就2011~2060年整体而言,长江上游流域降水呈增加趋势。     

Swiss Rainfall Mass Curves and their Influence on Extreme Flood Simulation

Extreme flood estimates for dam safety are routinely obtained from hydrologic simulations driven by selected design storms. The temporal structure of such design storms can be obtained from Rainfall Mass Curves (RMCs), which are adimensionalized curves of the cumulative precipitation depth as a function of event duration. This paper assesses for the first time the spatialand temporal variability of observed RMCs for Switzerland, an Alpine region with complex topography. The relevance of the detected RMC variability for extreme flood estimation is illustrated based on an application to a high elevation catchment, the Mattmark dam catchment in the Swiss Alps. The obtained results underline that quantile RCMs represent a simple yet powerful tool to construct design storms for dam safety verification and that regional, seasonal and event-duration effects on RMCs are small enough to justify the use of a unique set of Swiss-wide quantile RMCs. The presented analysis could be refined in the future by explicitly accounting for orographic, convective or frontal precipitation events.     

Mixed General Extreme Value Distribution for Estimation of Future Precipitation Quantiles Using a Weighted Ensemble - Case Study of the Lim River Basin (Serbia)

Considering the recent extreme precipitation in southeast Europe, it has become necessity to investigate the impact of climate change on extreme precipitation. The aim of this study was to determine the change in precipitation quantiles with longer return periods under changing climate conditions. The study was conducted using the daily records gathered at 11 precipitation stations within the Lim River Basin, Serbia. The simulated precipitation datasets were collected from three regional climate models for the baseline period (1971–2000), as well as the future period (2006–2055) under the 2.6, 4.5 and 8.5 representative concentration pathways. The raw precipitation data from the climate models were transformed by employing four bias correction methods. Using the bias-corrected precipitation, an ensemble of annual maximum daily precipitation was developed. A weighted ensemble approach was applied to estimate the weights of each ensemble member favorizing the members whose quantiles were closer to observed measurements. The mixed general extreme value distribution was used to derive the projected quantiles with 100, 50, 25, 10, five and two year return periods based on the estimated quantiles and the normalized weights of all ensemble members. An overall increase of 69% and 56% for the 100 and 50 year return periods, respectively, can be expected within the northern part of the basin. Similarly, an overall increase of 50–57% and 39–42% for the 100 and 50 year return periods, respectively, may be expected for the central and southern parts of the Lim River Basin.