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1.
An ensemble of 10 hydrological models was applied to the same set of land use change scenarios. There was general agreement about the direction of changes in the mean annual discharge and 90% discharge percentile predicted by the ensemble members, although a considerable range in the magnitude of predictions for the scenarios and catchments under consideration was obvious. Differences in the magnitude of the increase were attributed to the different mean annual actual evapotranspiration rates for each land use type. The ensemble of model runs was further analyzed with deterministic and probabilistic ensemble methods. The deterministic ensemble method based on a trimmed mean resulted in a single somewhat more reliable scenario prediction. The probabilistic reliability ensemble averaging (REA) method allowed a quantification of the model structure uncertainty in the scenario predictions. It was concluded that the use of a model ensemble has greatly increased our confidence in the reliability of the model predictions.  相似文献   

2.
This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9-year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles, in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non-stationarity of the climate series and possible cross-correlations between models.  相似文献   

3.
Simulation of future climate scenarios with a weather generator   总被引：4，自引：0，他引：4  
Numerous studies across multiple disciplines search for insights on the effects of climate change at local spatial scales and at fine time resolutions. This study presents an overall methodology of using a weather generator for downscaling an ensemble of climate model outputs. The downscaled predictions can explicitly include climate model uncertainty, which offers valuable information for making probabilistic inferences about climate impacts. The hourly weather generator that serves as the downscaling tool is briefly presented. The generator is designed to reproduce a set of meteorological variables that can serve as input to hydrological, ecological, geomorphological, and agricultural models. The generator is capable of reproducing a wide set of climate statistics over a range of temporal scales, from extremes, to low-frequency interannual variability; its performance for many climate variables and their statistics over different aggregation periods is highly satisfactory. The use of the weather generator in simulations of future climate scenarios, as inferred from climate models, is described in detail. Using a previously developed methodology based on a Bayesian approach, the stochastic downscaling procedure derives the frequency distribution functions of factors of change for several climate statistics from a multi-model ensemble of outputs of General Circulation Models. The factors of change are subsequently applied to the statistics derived from observations to re-evaluate the parameters of the weather generator. Using embedded causal and statistical relationships, the generator simulates future realizations of climate for a specific point location at the hourly scale. Uncertainties present in the climate model realizations and the multi-model ensemble predictions are discussed. An application of the weather generator in reproducing present (1961-2000) and forecasting future (2081-2100) climate conditions is illustrated for the location of Tucson (AZ). The stochastic downscaling is carried out using simulations of eight General Circulation Models adopted in the IPCC 4AR, A1B emission scenario.  相似文献   

4.
Mountain and lowland watersheds are two distinct geographical units with considerably different hydrological processes. Understanding their hydrological processes in the context of future climate change and land use scenarios is important for water resource management. This study investigated hydrological processes and their driving factors and eco-hydrological impacts for these two geographical units in the Xitiaoxi watershed, East China, and quantified their differences through hydrological modelling. Hydrological processes in 24 mountain watersheds and 143 lowland watersheds were simulated based on a raster-based Xin'anjiang model and a Nitrogen Dynamic Polder (NDP) model, respectively. These two models were calibrated and validated with an acceptable performance (Nash-Sutcliffe efficiency coefficients of 0.81 and 0.50, respectively) for simulating discharge for mountain watersheds and water level for lowland watersheds. Then, an Indicators of Hydrological Alteration (IHA) model was used to help quantify the alterations to the hydrological process and their resulting eco-hydrological impacts. Based on the validated models, scenario analysis was conducted to evaluate the impacts of climate and land use changes on the hydrological processes. The simulation results revealed that (a) climate change would cause a larger increase in annual runoff than that under land use scenario in the mountain watersheds, with variations of 19.9 and 10.5% for the 2050s, respectively. (b) Land use change was more responsible for the streamflow increment than climate change in the lowland watersheds, causing an annual runoff to increase by 27.4 and 16.2% for the 2050s, respectively. (c) Land use can enhance the response of streamflow to the climatic variation. (d) The above-mentioned hydrological variations were notable in flood and dry season in the mountain watersheds, and they were significant in rice season in the lowland watersheds. (e) Their resulting degradation of ecological diversity was more susceptible to future climate change in the two watersheds. This study demonstrated that mountain and lowland watersheds showed distinct differences in hydrological processes and their responses to climate and land use changes.  相似文献   

5.
The Land Information System (LIS) is an established land surface modeling framework that integrates various community land surface models, ground measurements, satellite-based observations, high performance computing and data management tools. The use of advanced software engineering principles in LIS allows interoperability of individual system components and thus enables assessment and prediction of hydrologic conditions at various spatial and temporal scales. In this work, we describe a sequential data assimilation extension of LIS that incorporates multiple observational sources, land surface models and assimilation algorithms. These capabilities are demonstrated here in a suite of experiments that use the ensemble Kalman filter (EnKF) and assimilation through direct insertion. In a soil moisture experiment, we discuss the impact of differences in modeling approaches on assimilation performance. Provided careful choice of model error parameters, we find that two entirely different hydrological modeling approaches offer comparable assimilation results. In a snow assimilation experiment, we investigate the relative merits of assimilating different types of observations (snow cover area and snow water equivalent). The experiments show that data assimilation enhancements in LIS are uniquely suited to compare the assimilation of various data types into different land surface models within a single framework. The high performance infrastructure provides adequate support for efficient data assimilation integrations of high computational granularity.  相似文献   

6.
This paper analyses the effect of spatial resolution and distribution of model input data on the results of regional-scale land use scenarios using three different hydrological catchment models. A 25 m resolution data set of a mesoscale catchment and three land use scenarios are used. Data are systematically aggregated to resolutions up to 2 km. Land use scenarios are spatially redistributed, both randomly and topography based. Using these data, water fluxes are calculated on a daily time step for a 16 year time period without further calibration. Simulation results are used to identify grid size, distribution and model dependent scenario effects. In the case of data aggregation, all applied models react sensitively to grid size. WASIM and TOPLATS simulate constant water balances for grid sizes from 50 m to 300–500 m, SWAT is more sensitive to input data aggregation, simulating constant water balances between 50 m and 200 m grid size. The calculation of scenario effects is less robust to data aggregation. The maximum acceptable grid size reduces to 200–300 m for TOPLATS and WASIM. In case of spatial distribution, SWAT and TOPLATS are slightly sensitive to a redistribution of land use (below 1.5% for water balance terms), whereas WASIM shows almost no reaction. Because the aggregation effects were stronger than the redistribution effects, it is concluded that spatial discretisation is more important than spatial distribution. As the aggregation effect was mainly associated with a change in land use fraction, it is concluded that accuracy of data sets is much more important than a high spatial resolution.  相似文献   

7.
Two approaches can be distinguished in studies of climate change impacts on water resources when accounting for issues related to impact model performance: (1) using a multi-model ensemble disregarding model performance, and (2) using models after their evaluation and considering model performance. We discuss the implications of both approaches in terms of credibility of simulated hydrological indicators for climate change adaptation. For that, we discuss and confirm the hypothesis that a good performance of hydrological models in the historical period increases confidence in projected impacts under climate change, and decreases uncertainty of projections related to hydrological models. Based on this, we find the second approach more trustworthy and recommend using it for impact assessment, especially if results are intended to support adaptation strategies. Guidelines for evaluation of global- and basin-scale models in the historical period, as well as criteria for model rejection from an ensemble as an outlier, are also suggested.  相似文献   

8.
This study develops a novel approach for modelling and examining the impacts of time–space land‐use changes on hydrological components. The approach uses an empirical land‐use change allocation model (CLUE‐s) and a distributed hydrological model (DHSVM) to examine various land‐use change scenarios in the Wu‐Tu watershed in northern Taiwan. The study also uses a generalized likelihood uncertainty estimation approach to quantify the parameter uncertainty of the distributed hydrological model. The results indicate that various land‐use policies—such as no change, dynamic change and simultaneous change—have different levels of impact on simulating the spatial distributions of hydrological components in the watershed study. Peak flow rates under simultaneous and dynamic land‐use changes are 5·71% and 2·77%, respectively, greater than the rate under the no land‐use change scenario. Using dynamic land‐use changes to assess the effect of land‐use changes on hydrological components is more practical and feasible than using simultaneous land‐use change and no land‐use change scenarios. Furthermore, land‐use change is a spatial dynamic process that can lead to significant changes in the distributions of ground water and soil moisture. The spatial distributions of land‐use changes influence hydrological processes, such as the ground water level of whole areas, particularly in the downstream watershed. Copyright © 2010 John Wiley & Sons, Ltd.  相似文献   

9.
This paper describes the results of benchmark testing of land use change impact on direct runoff using Soil Conservation Service-Curve Number (SCS-CN) model in two ungauged neighbouring urban watersheds (Çınar and Kadıyakuplu) in Istanbul, Turkey. To examine this impact, the model was applied to daily rainfall data using three different dated (1982, 1996 and 2012) hydrological soil groups and land use of the two ungauged urban watersheds. Finally, the impact of land use change and model performance were evaluated with the rainfall-runoff regression, the coefficient of determination and the NSE test using benchmark runoff data based on 1982 land use conditions. The results of the analysis indicate that the changing of land use types from natural surfaces to impervious surfaces has a significant impact on surface runoff. Additionally, remarkable spatial variations of the land use changes and their impact on the runoff in 1996 and 2012 were more detected in the Çınar watershed compared with the Kadıyakuplu watershed. The planning decision on land use of the watersheds, has vital role in these differences. The results of this research also reveal that change to intensive land use in urban watersheds has a significantly larger impact on runoff generation than those rainfall.  相似文献   

10.
This paper describes the use of a continuous streamflow model to examine the effects of climate and land use change on flow duration in six urbanizing watersheds in the Maryland Piedmont region. The hydrologic model is coupled with an optimization routine to achieve an agreement between observed and simulated streamflow. Future predictions are made for three scenarios: future climate change, land use change, and jointly varying climate and land use. Future climate is modelled using precipitation and temperature predictions for the Canadian Climate Centre (CCC) and Hadley climate models. Results show that a significant increase in temperature under the CCC climate predictions produces a decreasing trend in low flows. A significant increasing trend in precipitation under the Hadley climate predictions produces an increasing trend in peak flows. Land use change by itself, as simulated by an additional 10% increase in imperviousness (from 20·5 to 30·5%), produces no significant changes in the simulated flow durations. However, coupling the effects of land use change with climate change leads to more significant decreasing trends in low flows under the CCC climate predictions and more significant increasing trends in peak flows under Hadley climate predictions than when climate change alone is employed. These findings indicate that combined land use and climate change can result in more significant hydrologic change than either driver acting alone. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

11.
We evaluated the potential impacts of future land cover change and climate variability on hydrological processes in the Neka River basin, northern Iran. This catchment is the main source of water for the intensively cultivated area of Neka County. Hydrological simulations were conducted using the Soil and Water Assessment Tool. An ensemble of 17 CMIP5 climate models was applied to assess changes in temperature and precipitation under the moderate and high emissions scenarios. To generate the business-as-usual scenario map for year 2050 we used the Land Change Modeler. With a combined change in land cover and climate, discharge is expected to decline in all seasons except the end of autumn and winter, based on the inter-model average and various climate models, which illustrated a high degree of uncertainty in discharge projections. Land cover change had a minor influence on discharge relative to that resulting from climate change.  相似文献   

12.
Catchment scale hydrological models are critical decision support tools for water resources management and environment remediation. However, the reliability of hydrological models is inevitably affected by limited measurements and imperfect models. Data assimilation techniques combine complementary information from measurements and models to enhance the model reliability and reduce predictive uncertainties. As a sequential data assimilation technique, the ensemble Kalman filter (EnKF) has been extensively studied in the earth sciences for assimilating in-situ measurements and remote sensing data. Although the EnKF has been demonstrated in land surface data assimilations, there are no systematic studies to investigate its performance in distributed modeling with high dimensional states and parameters. In this paper, we present an assessment on the EnKF with state augmentation for combined state-parameter estimation on the basis of a physical-based hydrological model, Soil and Water Assessment Tool (SWAT). Through synthetic simulation experiments, the capability of the EnKF is demonstrated by assimilating the runoff and other measurements, and its sensitivities are analyzed with respect to the error specification, the initial realization and the ensemble size. It is found that the EnKF provides an efficient approach for obtaining a set of acceptable model parameters and satisfactory runoff, soil water content and evapotranspiration estimations. The EnKF performance could be improved after augmenting with other complementary data, such as soil water content and evapotranspiration from remote sensing retrieval. Sensitivity studies demonstrate the importance of consistent error specification and the potential with small ensemble size in the data assimilation system.  相似文献   

13.
This study attempts to assess the uncertainty in the hydrological impacts of climate change using a multi-model approach combining multiple emission scenarios, GCMs and conceptual rainfall-runoff models to quantify uncertainty in future impacts at the catchment scale. The uncertainties associated with hydrological models have traditionally been given less attention in impact assessments until relatively recently. In order to examine the role of hydrological model uncertainty (parameter and structural uncertainty) in climate change impact studies a multi-model approach based on the Generalised Likelihood Uncertainty Estimation (GLUE) and Bayesian Model Averaging (BMA) methods is presented. Six sets of regionalised climate scenarios derived from three GCMs, two emission scenarios, and four conceptual hydrological models were used within the GLUE framework to define the uncertainty envelop for future estimates of stream flow, while the GLUE output is also post processed using BMA, where the probability density function from each model at any given time is modelled by a gamma distribution with heteroscedastic variance. The investigation on four Irish catchments shows that the role of hydrological model uncertainty is remarkably high and should therefore be routinely considered in impact studies. Although, the GLUE and BMA approaches used here differ fundamentally in their underlying philosophy and representation of error, both methods show comparable performance in terms of ensemble spread and predictive coverage. Moreover, the median prediction for future stream flow shows progressive increases of winter discharge and progressive decreases in summer discharge over the coming century.  相似文献   

14.
土地利用方式及其转移对区域氮素迁移和水体氮负荷产生重要影响,但量化自然发展、耕地保护和生态保护等多情景下土地利用方式氮排放时空变化特征,揭示流域水体氮负荷对土地利用变化的响应机制仍面临挑战。本研究以巢湖流域为研究区,通过遥感解译多时相土地利用类型数据,借助PLUS和InVEST模型探索不同情景下氮排放对各土地利用类型变化的响应机制。结果表明:(1)2000—2020年期间,巢湖流域建设用地面积的增加(626.14 km2)主要占据的是耕地(减少了775.64 km2),城市化建设成为土地利用方式变化的主要驱动力;(2)PLUS模型多情景预测结果显示:2020—2030年间土地利用变化特征与2000—2020年基本保持一致,但各用地间的转换频率降低;(3)经InVEST模拟,耕地面积缩减而导致氮排放的减少量(340.17 t)大于建设用地等面积增加带来的氮排放增加量(170.11 t),使2000—2020年间巢湖流域土地利用所排放的总氮量呈降低趋势,由2000年的4768.04 t降至2020年的4597.98 t;(4)不同情景下,2030年各土地利用方式的氮排放量较2020年均呈降低趋势。其中,生态保护情景既有效地保障了巢湖流域生态功能又展现出较好的氮减排效果(113.36 t);鉴于此,建议流域管理部门应通过合理规划各用地类型的发展,严格控制建设用地对林草地、水域等生态用地的侵占,以期削减流域水体氮负荷、缓解氮素治理压力。  相似文献   

15.
This paper comparatively assesses the performance of five data assimilation techniques for three-parameter Muskingum routing with a spatially lumped or distributed model structure. The assimilation techniques used include direct insertion (DI), nudging scheme (NS), Kalman filter (KF), ensemble Kalman filter (EnKF) and asynchronous ensemble Kalman filter (AEnKF), which are applied to river reaches in Texas and Louisiana, USA. For both lumped and distributed routing, results from KF, EnKF and AEnKF are sensitive to the error specification. As expected, DI outperformed the other models in the case of lumped modelling, while in distributed routing, KF approaches, particularly AEnKF and EnKF, performed better than DI or nudging, reflecting the benefit of updating distributed states through error covariance modelling in KF approaches. The results of this work would be useful in setting up data assimilation systems that employ increasingly abundant real-time observations using distributed hydrological routing models.  相似文献   

16.
Spatially explicit modeling plays a vital role in land use/cover change and urbanization research as well as resources management;however,current models lack proper validation and fail to incorporate uncertainty into the formulation of model predictions.Consequently,policy makers and the general public may develop opinions based on potentially misleading research,which fails to allow for truly informed decisions.Here we use an uncertainty strategy of spatially explicit modeling combined with the series stat...  相似文献   

17.
Changes in climate and land use can significantly influence the hydrological cycle and hence affect water resources. Understanding the impacts of climate and land‐use changes on streamflow can facilitate development of sustainable water resources strategies. This study investigates the flow variation of the Zamu River, an inland river in the arid area of northwest China, using the Soil and Water Assessment Tool distributed hydrological model. Three different land‐use and climate‐change scenarios were considered on the basis of measured climate data and land‐use cover, and then these data were input into the hydrological model. Based on the sensitivity analysis, model calibration and verification, the hydrological response to different land‐use and climate‐change scenarios was simulated. The results indicate that the runoff varied with different land‐use type, and the runoff of the mountain reaches of the catchment increased when grassland area increased and forestland decreased. The simulated runoff increased with increased precipitation, but the mean temperature increase decreased the runoff under the same precipitation condition. Application of grey correlation analysis showed that precipitation and temperature play a critical role in the runoff of the Zamu River basin. Sensitivity analysis of runoff to precipitation and temperature by considering the 1990s land use and climate conditions was also undertaken. Copyright © 2007 John Wiley & Sons, Ltd.  相似文献   

18.
Extensive land use changes have occurred in many areas of SE Spain as a result of reforestation and the abandonment of agricultural activities. Parallel to this the Spanish Administration spends large funds on hydrological control works to reduce erosion and sediment transport. However, it remains untested how these large land use changes affect the erosion processes at the catchment scale and if the hydrological control works efficiently reduce sediment export. A combination of field work, mapping and modelling was used to test the influence of land use scenarios with and without sediment control structures (check‐dams) on sediment yield at the catchment scale. The study catchment is located in SE Spain and suffered important land use changes, increasing the forest cover 3‐fold and decreasing the agricultural land 2·5‐fold from 1956 to 1997. In addition 58 check‐dams were constructed in the catchment in the 1970s accompanying reforestation works. The erosion model WATEM‐SEDEM was applied using six land use scenarios: land use in 1956, 1981 and 1997, each with and without check‐dams. Calibration of the model provided a model efficiency of 0·84 for absolute sediment yield. Model application showed that in a scenario without check dams, the land use changes between 1956 and 1997 caused a progressive decrease in sediment yield of 54%. In a scenario without land use changes but with check‐dams, about 77% of the sediment yield was retained behind the dams. Check‐dams can be efficient sediment control measures, but with a short‐lived effect. They have important side‐effects, such as inducing channel erosion downstream. While also having side‐effects, land use changes can have important long‐term effects on sediment yield. The application of either land use changes (i.e. reforestation) or check‐dams to control sediment yield depends on the objective of the management and the specific environmental conditions of each area. Copyright © 2008 John Wiley & Sons, Ltd.  相似文献   

19.
This study demonstrates the spatial variation in hydrologic processes across the Upper Mississippi River Basin (UMRB) by the end of 21st century, by ingesting FOREcasting Scenarios (FORE‐SCE) of Land‐use Change projections into a physics‐based hydrologic model—Soil and Water Assessment Tool. The model is created for UMRB (440,000 km2), using the National Landcover Database of year 2001 and climate data of 1991–2010. Considering 1991–2010 as the baseline reference period, FORE‐SCE projections of year 2091 under three scenarios (A1B, A2, and B1 from the Intergovernmental Panel on Climate Change) are separately assimilated into the calibrated model, whereas climate input is kept the same as in the baseline. Modeling results suggest an increase of 0.5% and 3.5% in the average annual streamflow at the basin outlet (Grafton, Illinois) during 2081–2100, respectively, for A1B and A2, whereas for B1, streamflow would decrease by 1.5%. Under the “worst case” A2 scenario, 6% and 133% increase, respectively, in agricultural and urban areas with 30% depletion of forest and grassland would result into 70% increase in surface runoff, 20% decrease in soil moisture, and 4% decrease in evapotranspiration in certain parts of the basin. Conversion of cropland, forest, or grassland to perennial hay/pasture areas would lower surface runoff by 25% especially in the central region, whereas persistent forest cover in the northern region would cause up to 7% increase in evapotranspiration. The ecosystem in the lower half of UMRB is likely to become adverse, as dictated by a composite water–energy balance indicator. Future land use change extents and resultant hydrologic responses are found significantly different under A2, A1B, and B1 scenarios, which resonates the need for multi‐scenario ensemble assessments towards characterizing a probable future. The spatial variation of hydrologic processes as shown here helps to identify potential “hot spots,” giving ways to adopt more effective policy alternatives at regional level.  相似文献   

20.
ABSTRACT

Model ensembles are possibly the most powerful tool to assess uncertainties in runoff predictions stemming from inadequacies in model structure. But in many applications little knowledge is gained about the specific weaknesses of the individual models. Here we introduce the ensemble range approach (ERA). Compared to other ensemble techniques, ERA is primarily intended to facilitate hydrological reasoning about model structural uncertainty. This is attempted by separate modelling of data uncertainty and structural uncertainty with two different error density functions that are combined in one likelihood function. The width of the structural error density is in accordance with the range of runoff predictions calculated by a small model ensemble at each individual time step. Albeit not the only choice, this study is restricted on the use of a modified beta density to represent structural uncertainty. The performance of ERA is assessed in some synthetic and real data case studies. Ensembles of two structurally identical models are applied, made possible by estimating the parameters of ERA and both models simultaneously.
Editor D. Koutsoyiannis; GUEST editor S. Weijs  相似文献   

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