天生桥一级水电站月平均入库流量逐月滚动预测模型

由于江河流域的月平均流量变化与月尺度的短期气候变化密切相关,因此作为一种尝试,将月尺度短期气候变化的逐月滚动预测模型直接用于江河流域的月平均流量预测。文中从短期气候变化的逐月滚动预测模型出发,建立了天生桥一级水电站月平均入库流量的一种逐月滚动预测模型,并用该模型对天生桥一级水电站2004年1月以后的月平均入库流量进行预测,取得了较为满意的效果。     

Utility of Ten-Day Climate Model Ensemble Simulations for Water Resources Applications in Korean Watersheds

We demonstrate the use of a quantitative measure of the effectiveness of using climate model simulations of surface precipitation and temperature for water resources applications involving extremes of watershed average precipitation and temperature, and watershed discharge. This diagnostic measure is considered in association with the use of climate information to condition ensemble seasonal predictions of watershed variables. Seven watersheds in the Korean peninsula constitute the application sites. The climate model effectiveness is expressed by a utility index E_P that measures the ability of the climate model simulations of an indicator variable (i.e., nodal precipitation or temperature) to discriminate observed distributions of the highs and lows of a watershed target variable (i.e., mean areal precipitation and temperature as well as outlet discharge). Monte Carlo simulations provide estimates of the significance of the E_p values. For apparently the first time, ten-member ensemble simulations of daily surface precipitation and temperature from the Korean Meteorological Agency climate model are used to evaluate the climate-model utility index E_P for a temporal interval of 10 days for each application watershed. The results show that, in spite of the high uncertainty of climate simulations, there are several Korean watersheds that can benefit from the use of climate model simulations of high temporal resolution for planning and management studies that involve precipitation, temperature and discharge. In particular, seasonal ensemble prediction of watershed variables stands to gain from conditioning on high-temporal resolution climate forecasts.     

多GCM模型集合下开都河流域未来气候变化预估

基于逐步聚类分析的统计降尺度模型(SCADS模型),在多GCM模型集合的9个大尺度气象变量与开都河流域6个气象变量之间,建立统计降尺度关系,并进行开都河流域未来气候变化的预估。结果表明,SCADS模型生成的开都河流域各气象变量的模拟值与实测值拟合较好。各气象变量在率定期(1961年-1990年)和验证期(1991年-1999年)的NSE系数均大于0.55,精度较高。此外,利用SCADS模型进行开都河流域各气象变量的预估。发现在三个不同时期内(2011年-2040年,2041年-2070年和2071年-2100年),月均气温升高,月均蒸发量、降水量、日照时数增加,月均相对湿度升高。     

Impacts and Adaptation to Climate Change Using a Reservoir Management Tool to a Northern Watershed: Application to Lièvre River Watershed,Quebec, Canada

The purpose of this study is to evaluate the impact of climate change (CC) on the management of the three reservoirs in the Lièvre River watershed and to investigate adaptation strategies to CC. To accomplish this objective, a reservoir management tool was developed. The tool integrates: hydrological ensemble streamflow predictions; a stochastic optimization model; a neural network model; and a water balance model. Five climate projections from a regional climate model, under current (1961–2000) and future (2041–2070) climate scenarios, were used. Adjustments to the reservoirs operating rules were used as an adaptation strategy to limit flooding in the watershed and also in the Montreal Archipelago located downstream of the watershed. A number of constraints in the reservoirs of the Lièvre watershed are related to summer recreational activities, which would start earlier in future climate. Modifications of these constraints were simulated to take into account socio-economic impacts of climate change on reservoirs operation. Results show that greater quantities of water would have to be stored in the Lièvre River watershed in the future, to decrease the risk of flooding in the Montreal Archipelago. The reservoir located at the downstream end of the watershed would be more vulnerable and its reliability may decrease in the future. Adaptation measures reduced the inter-annual variability of the reservoir level under future climate conditions. The reservoir management tool is an example of a no-regrets strategy, as it will contribute to improve the tools currently available to manage the reservoirs of the Lièvre River watershed.     

Spatial planning for adapting to climate change.

During the past decades human interference in regional hydrologic systems has intensified. These systems act as an integrating medium. They link climate, human activities and ecologic processes through groundwater and surface water interactions. For simulating these linkages an integrated regional hydrologic model has been coupled to an ecologic evaluation model. The simulated ecologic effects of climate change on mesotrophic riverine grasslands are clearly positive. Simulation results also indicate a high sensitivity of the peak discharges to the precipitation. For modelling the long-term development of land use and water management an integrated 'bio-economic' model has been constructed. It includes a model for the development of agriculture. Results for the autonomous development in reaction to climate change indicate a strong increase of field drainage by agriculture. This development would substantially reduce the predicted positive effects of climate change on riverine grasslands. The challenge is to guide regional developments in such a manner that opportunities for improving nature are not lost, but that at the same time the peak discharges are kept under control. Flow retardation in the 'fine arteries' of the upstream areas appear to be a viable option for the latter. The bio-economic model can provide help in anticipating on climate change through spatial planning.     

Response to Late developers and the inequity of “equitable utilization” and the harm of “do no harm” by Kai Wegerich and Oliver Olsson,Water International, 35 (6), 707–717 (November 2010)

Abstract

A strategy is presented for predicting impacts of future climate change on water supply capabilities, which is based on using output from a general circulation model (GCM) developed by the Canadian Center for Climate Modeling and Analysis (CCCma) with a watershed hydrology model and a river/reservoir system management model. The GCM output was used to adjust input to a watershed hydrology model in order to predict the corresponding impacts on streamflows. Output from the watershed model was used to adjust naturalized streamflows in a river/reservoir system management model in order to determine the corresponding impacts on water supply reliabilities. The methodology was applied in an investigation of capabilities for supplying water to the City of Houston and other users in the San Jacinto River Basin of Texas. Historical versus 2040 to 2059 climate scenarios were compared. Study results indicate that long-term mean streamflows under 2040 to 2059 climate conditions were higher than under historical climate due to significant increases in floods and other high flows. However, flows were lower for the future climate scenario during periods of normal and low flows. Seasonal variations in flows were greater with the future climate scenario than the historical climate. Reservoir storage fluctuations increase under future climate. Due to relatively large storage capacities, reliabilities for water supply diversions were improved somewhat under future climate conditions.     

The effect of climate change on urban drainage: an evaluation based on regional climate model simulation.

That we are in a period of extraordinary rates of climate change is today evident. These climate changes are likely to impact local weather conditions with direct impacts on precipitation patterns and urban drainage. In recent years several studies have focused on revealing the nature, extent and consequences of climate change on urban drainage and urban runoff pollution issues. This study uses predictions from a regional climate model to look at the effects of climate change on extreme precipitation events. Results are presented in terms of point rainfall extremes. The analysis involves three steps: Firstly, hourly rainfall intensities from 16 point rain gauges are averaged to create a rain gauge equivalent intensity for a 25 x 25 km square corresponding to one grid cell in the climate model. Secondly, the differences between present and future in the climate model is used to project the hourly extreme statistics of the rain gauge surface into the future. Thirdly, the future extremes of the square surface area are downscaled to give point rainfall extremes of the future. The results and conclusions rely heavily on the regional model's suitability in describing extremes at timescales relevant to urban drainage. However, in spite of these uncertainties, and others raised in the discussion, the tendency is clear: extreme precipitation events effecting urban drainage and causing flooding will become more frequent as a result of climate change.     

Prediction of climate change effects of fish communities in the Mackinaw River watershed, Illinois, USA.

As part of an integrated assessment of multiple sector impacts produced by predicted changes in climate we have integrated a set of models, which provide predictions of fish populations under changing flow and temperature regimes. The core of the approach is the U. S. Fish and Wildlife Service Physical Habitat Simulation Model (PHABSIM). PHABSIM estimates habitat conditions based on flow, which are life stage specific. The output from PHABSIM is used to model fish populations, considering both flow and a temperature threshold, which affects spawning date. Water temperatures were modelled based on air temperature. The resulting assessment tool provides the means to evaluate the effect of multiple stressors produced by climate change scenarios. The model has been used to estimate smallmouth bass (Micropterus dolomieui) populations for representative reaches of the Mackinaw River, Illinois. The model has been used to illuminate population effects of changing flow and temperature under historical climate/weather conditions, as well as under climate change scenarios. The integrated models in the assessment tool have provided a useful addition to watershed management, improving our capacity to evaluate natural resources impact at temporal scales typical of climate change, and management response systems.     

Basin Scale Water Resources Systems Modeling Under Cascading Uncertainties

Global change in climate and consequent large impacts on regional hydrologic systems have, in recent years, motivated significant research efforts in water resources modeling under climate change. In an integrated future hydrologic scenario, it is likely that water availability and demands will change significantly due to modifications in hydro-climatic variables such as rainfall, reservoir inflows, temperature, net radiation, wind speed and humidity. An integrated regional water resources management model should capture the likely impacts of climate change on water demands and water availability along with uncertainties associated with climate change impacts and with management goals and objectives under non-stationary conditions. Uncertainties in an integrated regional water resources management model, accumulating from various stages of decision making include climate model and scenario uncertainty in the hydro-climatic impact assessment, uncertainty due to conflicting interests of the water users and uncertainty due to inherent variability of the reservoir inflows. This paper presents an integrated regional water resources management modeling approach considering uncertainties at various stages of decision making by an integration of a hydro-climatic variable projection model, a water demand quantification model, a water quantity management model and a water quality control model. Modeling tools of canonical correlation analysis, stochastic dynamic programming and fuzzy optimization are used in an integrated framework, in the approach presented here. The proposed modeling approach is demonstrated with the case study of the Bhadra Reservoir system in Karnataka, India.     

Impact of climate change on hydropower generation in Rio Jubones Basin,Ecuador

This study attempted to use the soil and water assessment tool(SWAT), integrated with geographic information systems(GIS), for assessment of climate change impacts on hydropower generation. This methodology of climate change impact modeling was developed and demonstrated through application to a hydropower plant in the Rio Jubones Basin in Ecuador. ArcSWAT 2012 was used to develop a model for simulating the river flow. The model parameters were calibrated and validated on a monthly scale with respect to the hydro-meteorological inputs observed from 1985 to 1991 and from 1992 to 1998, respectively. Statistical analyses produced Nash-Sutcliffe efficiencies(NSEs) of 0.66 and 0.61 for model calibration and validation, respectively, which were considered acceptable. Numerical simulation with the model indicated that climate change could alter the seasonal flow regime of the basin, and the hydropower potential could change due to the changing climate in the future.Scenario analysis indicates that, though the hydropower generation will increase in the wet season, the plant will face a significant power shortage during the dry season, up to 13.14% from the reference scenario, as a consequence of a 17% reduction of streamflow under an assumption of a 2.9℃ increase in temperature and a 15% decrease in rainfall. Overall, this study showed that hydrological processes are realistically modeled with SWAT and the model can be a useful tool for predicting the impact of climate change.     

流域水文模型识别方法研究与应用

基于模型产汇流机理,分析对比水文模型适用性,建立考虑气候特征、下垫面条件和人类活动影响的流域水文模型识别的指标体系,并以辽宁东部各中小流域为研究对象进行实例研究。分析了研究区域的气候特征,将新安江模型、大伙房模型和TOPMODEL模型作为备选模型,利用主成分分析法确定流域面积/主河道长度、河道比降、森林覆盖率、地形指数和气候类型作为流域水文模型识别的输入指标,进而采用层次分析法识别适用于各研究流域洪水模拟的水文模型。洪水模拟结果表明:所建立的流域水文模型识别指标体系有代表性,所识别的水文模型可很好地反映流域的产汇流特性。     

Urban stream overflow probability in a changing climate: Case study of the Seoul Uicheon Basin,Korea

Flooding from the overflow of rivers and streams can cause major disruption in urban areas that is likely to have significant effects on human activities and the environment. Such consequences could be exacerbated by enhanced levels of precipitation resulting from future climate change. Various options are available for responding to flooding; however, further studies are needed to improve the design flood criteria in order to cope with the uncertainties of a changing climate. This study investigated an improved methodology for the evaluation of the overflow probability of urban streams. This was achieved through the application of Monte Carlo simulations (MCSs) and climate change scenarios that incorporated an increased probability of overbank flooding. An estimation of the probability of future rainfall in the Uicheon Basin of Korea, using chaos disintegration with regional climate model (RCM) scenario data, indicated a projected increase of 4.4%–9.6%. The results for 100-year flooding under projected conditions of climate change, based on a hydrologic overflow inundation model, showed that flooded areas could increase by 58.1% compared with current levels, depending on the climate change scenarios. However, forecasts based on MCSs indicated that extreme rainfall could increase by 94.9%. Thus, an overflow analysis that reflects both extreme hydrologic events and more frequent flooding due to climate change could provide a more reliable means of forecasting extreme events, as well as helping to prevent natural disasters associated with unexpected extreme flooding. The results obtained in this study would provide useful data for stakeholders and decision makers to both enhance policy standards and formulate measures to reduce the risk of urban flooding within the context of a changing climate.     

Climate Change and Hydrological Response in the Trans-State Oologah Lake Watershed–Evaluating Dynamically Downscaled NARCCAP and Statistically Downscaled CMIP3 Simulations with VIC Model

Statistically and dynamically downscaled climate projections are the two important data sources for evaluation of climate change and its impact on water availability, water quality and ecosystems. Though bias correction helps to adjust the climate model output to behave more similarly to observations, the hydrologic response still can be biased. This study uses Variable Infiltration Capacity (VIC) model to evaluate the hydrologic response of the trans-state Oologah Lake watershed to climate change by using both statistically and dynamically downscaled multiple climate projections. Simulated historical and projected climate data from the North American Regional Climate Change Assessment Program (NARCCAP) and Bias-Corrected and Spatially Downscaled–Coupled Model Intercomparison Phase 3 (BCSD-CMIP3) forced the hydrologic model. In addition, different river network upscaling methods are also compared for a higher VIC model performance. Evaluation and comparison shows the following the results. (1) From the hydrologic point of view, the dynamically downscaled NARCCAP projection performed better, most likely in capturing a larger portion of mesoscale-driven convective rainfall than the statistically downscaled CMIP3 projections; hence, the VIC model generated higher seasonal streamflow amplitudes that are closer to observations. Additionally, the statistically downscaled GCMs are less likely to capture the hydrological simulation probably due to missing integration of climate variables of wind, solar radiation and others, even though their precipitation and temperature are bias corrected to be more favorably than the NARCCAP simulations. (2) Future water availability (precipitation, runoff, and baseflow) in the watershed would increase annually by 3–4 %, suggested by both NARCCAP and BCSD-CMIP3. Temperature increases (2.5–3 °C) are much more consistent between the two types of climate projections both seasonally and annually. However, NARCCAP suggested 2–3 times higher seasonal variability of precipitation and other water fluxes than the BCSD-CMIP3 models. (3) The hydrologic performance could be used as a potential metric to comparatively differentiate climate models, since the land surface and atmosphere processes are considered integrally.     

气候变化影响下黄河上游梯级水库群未来发电量预测

为分析气候变化影响下黄河上游大型水库入库来水过程及梯级发电量的时程变化规律,以黄河上游龙羊峡刘家峡梯级水库群为例,采用Mann-Kendall 突变检验方法对唐乃亥和小川水文序列进行突变识别,在此基础上构建了考虑融雪过程的HBV 水文模型,利用统计降尺度方法对CanESM2 和GFDL_ESM2G 两种气候模式3 种气候变化情景(RCP2. 6、RCP4. 5 和RCP8. 5) 下的降水、气温数据进行空间降尺度处理,并将其驱动水文模型预测未来入库来水过程,构建黄河上游梯级联合发电调度模型分析气候变化对未来发电调度过程的影响。结果表明:黄河上游径流序列突变年份集中于20 世纪80 年代,且2000 年之后径流量显著减少;气候变化将导致未来(2021—2050年)汛期6—9 月径流增加,非汛期径流显著减少;随着时间推移,不同气候变化情景下,龙羊峡和刘家峡两库的梯级发电量变化规律不同,RCP8.5 气候变化情景下,气候模式不确定性对其影响最大。     

Optimal Management of an Overexploited Aquifer under Climate Change: The Lake Karla Case

This paper presents a study for finding the optimal management plan of an overexploited aquifer under global climate change. The study area is the aquifer of the basin of Lake Karla, located in the eastern part of Thessaly in Greece. An optimization method has been used to evaluate the optimum volume of water that can be extracted from the aquifer and the optimum position of the wells with the objective of water table rise to a desirable sustainable level, taking into consideration the climate change forcing. The modelling system consists of a series of interlinked models: a hydrological, a lake-aquifer, a reservoir operation, a groundwater, and an optimization model. The climate change forcing on precipitation and temperature has been evaluated using the outputs of Canadian Centre for Climate Model Analysis General Circulation Model (CGCMa2) and a hybrid downscaling method which combines a multiple regression (MLR) model and a timeseries model for two socioeconomic emissions scenarios. The results of this study show that climate change plays an important role, as it affects the optimum volume of the extracted groundwater and the position of the irrigation wells.     

Climate change impact on water quality in the integrated Mahabad Dam watershed-reservoir system

Climate change, besides global warming, is expected to intensify the hydrological cycle, which can impact watershed nutrient yields and affect water quality in the receiving water bodies. The Mahabad Dam Reservoir in northwest Iran is a eutrophic reservoir due to excessive watershed nutrient input, which could be exacerbated due to climate change. In this regard, a holistic approach was employed by linking a climate model (CanESM2), watershed-scale model (SWAT), and reservoir water quality model (CE-QUAL-W2). The triple model investigates the cumulative climate change effects on hydrological parameters, watershed yields, and the reservoir’s water quality. The SDSM model downscaled the output of the climate model under moderate (RCP4.5) and extreme (RCP8.5) scenarios for the periods of 2021–2040 and 2041–2060. The impact of future climate conditions was investigated on the watershed runoff and total phosphorus (TP) load, and consequently, water quality status in the dam’s reservoir. The results of comparing future conditions (2021–2060) with observed present values under moderate to extreme climate scenarios showed a 4–7% temperature increase and a 6–11% precipitation decrease. Moreover, the SWAT model showed a 9–16% decline in streamflow and a 12–18% decline in the watershed TP load for the same comparative period. Finally, CE-QUAL-W2 model results showed a 3–8% increase in the reservoir water temperature and a 10–16% increase in TP concentration. It indicates that climate change would intensify the thermal stratification and eutrophication level in the reservoir, especially during the year’s warm months. This finding specifies an alarming condition that demands serious preventive and corrective measures.     

Reducing current and future risks: Using climate change scenarios to test an agricultural conservation framework

Evaluating the potential effects of changes in climate on conservation practices can help inform strategies to protect freshwater biodiversity that are robust, even as conditions change. Here we apply a climate change “test” to a framework for estimating the amount of agricultural conservation practices needed to achieve desired fish conservation outcomes for four watersheds in the Saginaw Bay region of Michigan, USA. We developed three climate scenarios from global climate model outputs (high emissions scenario, “2080s” timeframe) to provide insight on potential impacts of a climate driver that represents a key uncertainty for this management system, the amount and timing of spring and summer precipitation. These scenarios were used as inputs to agricultural watershed models, which produced water quality outputs that we compared to thresholds in fish biodiversity metrics at the subwatershed scale. Our results suggest that impacts of climate change on evaporation rates and other aspects of hydrology will shift the relative importance of key stressors for fish (i.e., sediment loadings vs. nutrient concentrations) across these different watersheds, highlighting the need to design resilient implementation plans and policies. Overall, we found that changes in climate are likely to increase the need for agricultural conservation practices, but that increasing the implementation rate above current levels will likely remain a good investment under current and future climate conditions.     

Integrated Reservoir Management System for Flood Risk Assessment Under Climate Change

Operations of existing reservoirs will be affected by climate change. Reservoir operating rules developed using historical information will not provide the optimal use of storage under changing hydrological conditions. In this paper, an integrated reservoir management system has been developed to adapt existing reservoir operations to changing climatic conditions. The reservoir management system integrates: (1) the K-Nearest Neighbor (K-NN) weather generator model; (2) the HEC-HMS hydrological model; and (3) the Differential Evolution (DE) optimization model. Six future weather scenarios are employed to verify the integrated reservoir management system using Upper Thames River basin in Canada as a case study. The results demonstrate that the integrated system provides optimal reservoir operation rule curves that reflect the hydrologic characteristics of future climate scenarios. Therefore, they may be useful for the development of reservoir climate change adaptation strategy.     

高寒山区融雪径流对气候变化的敏感性分析

以玛纳斯河流域为研究区,采用数理统计的方法以研究区1958—1987年实测的水文、气象资料为基础进行趋势变化及全球气候变化对降水、气温、径流影响的分析。以新安江模型为基础建立了研究区数字水文模型,并对1981年融雪径流进行模拟。利用该模型结合不同的气候情景假设分析高寒山区融雪径流对气候变化的敏感性。     

Vulnerability of Korean water resources to climate change and population growth.

Freshwater availability is affected by changes in climate and growth. We assessed the freshwater vulnerability for five major Korean river basins for 2015 and 2030. We used a regional climate model based on the IPCC SRES A2 scenario, US Geological Survey's Precipitation Rainfall Simulation Model, and population and industrial growth scenarios for impact assessment. The model simulation results suggest increasing spatial and temporal variations of water stress for the basins that are already developed. While freshwater is more vulnerable to growth scenarios than the climate change scenario, climate change alone could decrease mean annual runoff by 10% in four major river basins by 2030. As the first national assessment of climate change, we suggest possible adaptive water resource management and policy strategies for reducing climate related risks in Korea.