The aim of this study is to estimate likely changes in flood indices under a future climate and t... more The aim of this study is to estimate likely changes in flood indices under a future climate and to assess the uncertainty in these estimates for selected catchments in Poland. Precipitation and temperature time series from climate simulations from the EURO-CORDEX initiative for the periods 1971–2000, 2021–2050 and 2071–2100 following the RCP4.5 and RCP8.5 emission scenarios have been used to produce hydrological simulations based on the HBV hydrological model. As the climate model outputs for Poland are highly biased, post processing in the form of bias correction was first performed so that the climate time series could be applied in hydrological simulations at a catchment-scale. The results indicate that bias correction significantly improves flow simulations and estimated flood indices based on comparisons with simulations from observed climate data for the control period. The estimated changes in the mean annual flood and in flood quantiles under a future climate indicate a large spread in the estimates both within and between the catchments. An ANOVA analysis was used to assess the relative contributions of the 2 emission scenarios, the 7 climate models and the 4 bias correction methods to the total spread in the projected changes in extreme river flow indices for each catchment. The analysis indicates that the differences between climate models generally make the largest contribution to the spread in the ensemble of the three factors considered. The results for bias corrected data show small differences between the four bias correction methods considered, and, in contrast with the results for uncorrected simulations, project increases in flood indices for most catchments under a future climate.
The nature of drought conditions is estimated using a range of indices describing different aspec... more The nature of drought conditions is estimated using a range of indices describing different aspects of drought events. Three drought indices are evaluated, namely the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Runoff Index (SRI), using observed hydroclimatic data and applying them to hydro-meteorological projections into the 21st century. The first two indices are evaluated using only meteorological variables and from this point of view, are better suited to meteorological drought projections than the third index, SRI, which is based on catchment discharge and represents hydrological drought. We assess information contained in those indices and their suitability to catchment scale climate projection drought assessment in ten selected Polish catchments, representing different hydro-climatic conditions, which are used as a case study. Projections of climatic variables (precipitation and temperature) are obtained from the EURO-CORDEX initiative derived from seven climate models at a grid resolution of 12.5 km for the time period 1971–2100. Future runoff projections for the catchments are obtained using a conceptual rainfall-runoff model (HBV). The results of analyses of indices based on observations in the reference period show consistent estimates for most of the catchments. Hydro-meteorological climate model projections for three periods, including the reference period 1971–2000, and two 30-year periods, near-future 2021–2050 and far-future 2071–2100, are used to estimate changes of future drought conditions in the catchments studied. The results show a substantial variation of temporal drought patterns over the catchments and their dependence on projected precipitation and temperature variables and the type of indices applied. Of the three indices studied, only SPEI projections indicate drier conditions in the catchments in the far-future period. The other two indices, SPI and SRI, indicate wetter climates in the future.
Possible future climate change effects on dryness conditions in Poland are estimated for six clim... more Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann– Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons .
This paper presents the background, objectives, and preliminary outcomes from the first year of a... more This paper presents the background, objectives, and preliminary outcomes from the first year of activities of the Polish–Norwegian project CHIHE (Climate Change Impact on Hydrological Extremes). The project aims to estimate the influence of climate changes on extreme river flows (low and high) and to evaluate the impact on the frequency of occurrence of hydrological extremes. Eight " twinned " catchments in Po-land and Norway serve as case studies. We present the procedures of the catchment selection applied in Norway and Poland and a database consisting of near-natural ten Polish and eight Norwegian catchments constructed for the purpose of climate impact assessment. Climate projections for selected catchments are described and compared with observations of temperature and precipitation available for the reference period. Future changes based on those projections are analysed and assessed for two periods, the near future (2021-2050) and the far-future (2071-2100). The results indicate increases in precipitation and temperature in the periods and regions studied both in Poland and Norway.
The thermal state of permafrost is a crucial indicator of environmental changes occurring in the ... more The thermal state of permafrost is a crucial indicator of environmental changes occurring in the Arctic. The monitoring of ground temperatures in Svalbard has been carried out in instrumented boreholes, although only few are deeper than 10 m and none are located in southern part of Spitsbergen. Only one of them, Janssonhaugen, located in central part of the island, provides the ground temperature data down to 100 m. Recent studies have proved that significant warming of the ground surface temperatures, observed especially in the last three decades, can be detected not only just few meters below the surface, but reaches much deeper layers. The aim of this paper is evaluation of the permafrost state in the vicinity of the Polish Polar Station in Hornsund using the numerical heat transfer model CryoGrid 2. The model is calibrated with ground temperature data collected from a 2 m deep borehole established in 2013 and then validated with data from the period 1990–2014 from five depths up to 1 m, measured routinely at the Hornsund meteorological station. The study estimates modelled ground thermal profile down to 100 m in depth and presents the evolution of the ground thermal regime in the last 25 years. The simulated subsurface temperature trumpet shows that multiannual variability in that period can reach 25 m in depth. The changes of the ground thermal regime correspond to an increasing trend of air temperatures observed in Hornsund and general warming across Svalbard.
Possible future climate change effects on dryness conditions in Poland are estimated for six clim... more Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann– Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons .
Nature-inspired metaheuristics found various applications in different fields of science, includi... more Nature-inspired metaheuristics found various applications in different fields of science, including the problem of artificial neural networks (ANN) training. However, very versatile opinions regarding the performance of metaheuristics applied to ANN training may be found in the literature. Both nature-inspired metaheuristics and ANNs are widely applied to various geophysical and environmental problems. Among them the water temperature forecasting in a natural river, especially in colder climate zones where the seasonality plays important role, is of great importance, as water temperature has strong impact on aquatic life and chemistry. As the impact of possible future climate change on water temperature is not trivial, models are needed to allow projection of streamwater temperature based on simple hydro-meteorological variables. In this paper the detailed comparison of the performance of nature-inspired optimization methods and Levenberg–Marquardt (LM) algorithm in ANNs training is performed, based on the case study of water temperature forecasting in a natural stream, namely Biala Tarnowska river in southern Poland. Over 50 variants of 22 various metaheuristics, including a large number of Differential Evolution, as well as some Particle Swarm Optimization, Evolution Strategies, multialgorithms and Direct Search methods are compared with LM algorithm on ANN training for the described case study. The impact of population size and some control parameters of particular metaheuristics on the ANN training performance are verified. It is found that despite widely claimed large improvement in nature-inspired methods during last years, the vast majority of them are still outperformed by LM algorithm on the selected problem. The only methods that, based on this case study, seem competitive to LM algorithm in terms of the final performance (but not speed) are Differential Evolution algorithms that benefit from the concept of Global and Local neighborhood-based mutation operators. The streamwater forecasting performance of the neural networks is adequate, the major prediction errors are related to the river freezing and melting processes that occur during winter in the mountainous catchment under study.
The derivation of the flood risk maps requires an estimation of maximum inundation extent for a f... more The derivation of the flood risk maps requires an estimation of maximum inundation extent for a flood with a given return period, e.g. 100 or 500 yr. The results of numerical simulations of flood wave propagation are used to overcome the lack of relevant observations. In practice, determin-istic 1-D models are used for that purpose. The solution of a 1-D model depends on the initial and boundary conditions and estimates of model parameters based on the available noisy observations. Therefore, there is a large uncertainty involved in the derivation of flood risk maps using a single realisation of a flow model. Bayesian conditioning based on multiple model simulations can be used to quantify this uncertainty ; however, it is too computer-time demanding to be applied in flood risk assessment in practice, without further flow routing model simplifications. We propose robust and feasible methodology for estimating flood risk. In order to decrease the computation times the assumption of a gradually varied flow and the application of a steady state flow routing model is introduced. The aim of this work is an analysis of the influence of those simplifying assumptions and uncertainty of observations and modelling errors on flood inunda-tion mapping and a quantitative comparison with determin-istic flood extent maps. Apart from the uncertainty related to the model structure and its parameters, the uncertainty of the estimated flood wave with a specified probability of return period (so-called 1-in-10 yr, or 1-in-100 yr flood) is also taken into account. In order to derive the uncertainty of inun-dation extent conditioned on the design flood, the probabilities related to the design wave and flow model uncertainties are integrated. In the present paper that integration is done whilst taking into account the dependence of roughness coefficients on discharge. The roughness is parameterised based on maximum annual discharges. This approach allows for the relationship between flood extent and flow values to be derived , thus giving a cumulative assessment of flood risk. The methods are illustrated using the Warsaw reach of the River Vistula as a case study. The results indicate that determin-istic and stochastic flood inundation maps cannot be quantitatively compared. We show that the proposed simplified approach to flood risk assessment can be applied even when breaching of the embankment occurs, with the condition that the flooded area is small enough to be filled rapidly.
Despite the development of new measuring techniques, monitoring systems and advances in computer ... more Despite the development of new measuring techniques, monitoring systems and advances in computer technology, rainfall-flow modelling is still a challenge. The reasons are multiple and fairly well known. They include the distributed, heterogeneous nature of the environmental variables affecting flow from the catchment. These are precipitation, evapo-transpiration and in some seasons and catchments in Poland, snow melt also. This paper presents a review of work done on the calibration and validation of rainfall-runoff modelling, with a focus on the conceptual HBV model. We give a synthesis of the problems and propose a practical guide to the calibration and validation of rainfall-runoff models.
The aim of this work is the development of an integrated Data Based Mechanistic (DBM) rainfall-fl... more The aim of this work is the development of an integrated Data Based Mechanistic (DBM) rainfall-flow and flow-routing model suitable for scenario analysis of the Upper River Narew catchment in northeast Poland. This area encloses valuable wetland ecosystems of the Narew National Park (NPN). The available data include daily rainfall observations, temperature measurements and water level measurements at 7 gauging
This paper evaluates uncertainties in two solute transport models based on tracer experiment data... more This paper evaluates uncertainties in two solute transport models based on tracer experiment data from the Upper River Narew. Data Based Mechanistic and transient storage models were applied to Rhodamine WT tracer observations. We focus on the analysis of uncertainty and the sensitivity of model predictions to varying physical parameters, such as dispersion and channel geometry. An advection-dispersion model with dead zones (Transient Storage model) adequately describes the transport of pollutants in a single channel river with multiple storage. The applied transient storage model is deterministic; it assumes that observations are free of errors and the model structure perfectly describes the process of transport of conservative pollutants. In order to take into account the model and observation errors, an uncertainty analysis is required. In this study we used a combination of the Generalized Likelihood Uncertainty Estimation technique (GLUE) and the variance based Global Sensitivi...
Main goal of this study was to develop techniques for the a priori estimation parameters of hydro... more Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.
Physics and Chemistry of the Earth, Parts A/B/C, 2011
This study presents an analysis of the influence of two different water management policies on th... more This study presents an analysis of the influence of two different water management policies on the natural river ecosystem of the Upper Narew valley. A Global Sensitivity Analysis is used to estimate their impact on water conditions in an important wetland area. The River Narew is modelled using a 1-D flow routing model.The Upper Narew Basin is situated in north-east
This paper discusses methods of deriving flood inundation maps for the purpose of flood
risk asse... more This paper discusses methods of deriving flood inundation maps for the purpose of flood risk assessment. The deterministic approach, commonly used in practice, is compared with the stochastic approach that takes into account the uncertainty related to model parameters and initial and boundary conditions. The discussion is illustrated by the example of the Upper Narew river reach. The 1-D HEC-RAS model is used for flow routing. It is calibrated and validated using historical data from the site. The deterministic approach consists of simulating the propagation of a flood wave with an assumed probability of exceedence. The maps of inundation outlines are derived from maximum water levels simulated by a distributed flow routing model (here the HEC-RAS). The stochastic approach applies multiple sampling from the a priori distribution of parameters and random initial and boundary conditions. The same HEC-RAS model is used for the flow routing and the resulting posterior distributions of parameters are used to build the maps of flood inundation probabilities. We apply Bayesian conditioning of the posterior distribution of parameters based on available historical observations. A comparison of the results of both approaches is possible only when the deterministic inundation outlines are given a specific probability value. The paper demonstrates the ambiguity of the deterministic procedure in the derivation of flood inundation probabilities.
The aim of this study is to estimate likely changes in flood indices under a future climate and t... more The aim of this study is to estimate likely changes in flood indices under a future climate and to assess the uncertainty in these estimates for selected catchments in Poland. Precipitation and temperature time series from climate simulations from the EURO-CORDEX initiative for the periods 1971–2000, 2021–2050 and 2071–2100 following the RCP4.5 and RCP8.5 emission scenarios have been used to produce hydrological simulations based on the HBV hydrological model. As the climate model outputs for Poland are highly biased, post processing in the form of bias correction was first performed so that the climate time series could be applied in hydrological simulations at a catchment-scale. The results indicate that bias correction significantly improves flow simulations and estimated flood indices based on comparisons with simulations from observed climate data for the control period. The estimated changes in the mean annual flood and in flood quantiles under a future climate indicate a large spread in the estimates both within and between the catchments. An ANOVA analysis was used to assess the relative contributions of the 2 emission scenarios, the 7 climate models and the 4 bias correction methods to the total spread in the projected changes in extreme river flow indices for each catchment. The analysis indicates that the differences between climate models generally make the largest contribution to the spread in the ensemble of the three factors considered. The results for bias corrected data show small differences between the four bias correction methods considered, and, in contrast with the results for uncorrected simulations, project increases in flood indices for most catchments under a future climate.
The nature of drought conditions is estimated using a range of indices describing different aspec... more The nature of drought conditions is estimated using a range of indices describing different aspects of drought events. Three drought indices are evaluated, namely the Standardized Precipitation Index (SPI), Standardized Precipitation Evapotranspiration Index (SPEI) and Standardized Runoff Index (SRI), using observed hydroclimatic data and applying them to hydro-meteorological projections into the 21st century. The first two indices are evaluated using only meteorological variables and from this point of view, are better suited to meteorological drought projections than the third index, SRI, which is based on catchment discharge and represents hydrological drought. We assess information contained in those indices and their suitability to catchment scale climate projection drought assessment in ten selected Polish catchments, representing different hydro-climatic conditions, which are used as a case study. Projections of climatic variables (precipitation and temperature) are obtained from the EURO-CORDEX initiative derived from seven climate models at a grid resolution of 12.5 km for the time period 1971–2100. Future runoff projections for the catchments are obtained using a conceptual rainfall-runoff model (HBV). The results of analyses of indices based on observations in the reference period show consistent estimates for most of the catchments. Hydro-meteorological climate model projections for three periods, including the reference period 1971–2000, and two 30-year periods, near-future 2021–2050 and far-future 2071–2100, are used to estimate changes of future drought conditions in the catchments studied. The results show a substantial variation of temporal drought patterns over the catchments and their dependence on projected precipitation and temperature variables and the type of indices applied. Of the three indices studied, only SPEI projections indicate drier conditions in the catchments in the far-future period. The other two indices, SPI and SRI, indicate wetter climates in the future.
Possible future climate change effects on dryness conditions in Poland are estimated for six clim... more Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann– Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons .
This paper presents the background, objectives, and preliminary outcomes from the first year of a... more This paper presents the background, objectives, and preliminary outcomes from the first year of activities of the Polish–Norwegian project CHIHE (Climate Change Impact on Hydrological Extremes). The project aims to estimate the influence of climate changes on extreme river flows (low and high) and to evaluate the impact on the frequency of occurrence of hydrological extremes. Eight " twinned " catchments in Po-land and Norway serve as case studies. We present the procedures of the catchment selection applied in Norway and Poland and a database consisting of near-natural ten Polish and eight Norwegian catchments constructed for the purpose of climate impact assessment. Climate projections for selected catchments are described and compared with observations of temperature and precipitation available for the reference period. Future changes based on those projections are analysed and assessed for two periods, the near future (2021-2050) and the far-future (2071-2100). The results indicate increases in precipitation and temperature in the periods and regions studied both in Poland and Norway.
The thermal state of permafrost is a crucial indicator of environmental changes occurring in the ... more The thermal state of permafrost is a crucial indicator of environmental changes occurring in the Arctic. The monitoring of ground temperatures in Svalbard has been carried out in instrumented boreholes, although only few are deeper than 10 m and none are located in southern part of Spitsbergen. Only one of them, Janssonhaugen, located in central part of the island, provides the ground temperature data down to 100 m. Recent studies have proved that significant warming of the ground surface temperatures, observed especially in the last three decades, can be detected not only just few meters below the surface, but reaches much deeper layers. The aim of this paper is evaluation of the permafrost state in the vicinity of the Polish Polar Station in Hornsund using the numerical heat transfer model CryoGrid 2. The model is calibrated with ground temperature data collected from a 2 m deep borehole established in 2013 and then validated with data from the period 1990–2014 from five depths up to 1 m, measured routinely at the Hornsund meteorological station. The study estimates modelled ground thermal profile down to 100 m in depth and presents the evolution of the ground thermal regime in the last 25 years. The simulated subsurface temperature trumpet shows that multiannual variability in that period can reach 25 m in depth. The changes of the ground thermal regime correspond to an increasing trend of air temperatures observed in Hornsund and general warming across Svalbard.
Possible future climate change effects on dryness conditions in Poland are estimated for six clim... more Possible future climate change effects on dryness conditions in Poland are estimated for six climate projections using the standardized precipitation index (SPI). The time series of precipitation represent six different climate model runs under the selected emission scenario for the period 1971–2099. Monthly precipitation values were used to estimate the SPI for multiple timescales (1, 3, 6, 12, and 24 months) for a spatial resolution of 25 km for the whole country. Trends in the SPI were analysed using the Mann– Kendall test with Sen's slope estimator for each grid cell for each climate model projection and aggregation scale, and results obtained for uncorrected precipitation and bias corrected precipitation were compared. Bias correction was achieved using a distribution-based quantile mapping (QM) method in which the climate model precipitation series were adjusted relative to gridded precipitation data for Poland. The results show that the spatial pattern of the trend depends on the climate model, the timescale considered and on the bias correction. The effect of change on the projected trend due to bias correction is small compared to the variability among climate models. We also summarize the mechanisms underlying the influence of bias correction on trends in precipitation and the SPI using a simple example of a linear bias correction procedure. In both cases, the bias correction by QM does not change the direction of changes but can change the slope of trend, and the influence of bias correction on SPI is much reduced. We also have noticed that the results for the same global climate model, driving different regional climate model, are characterized by a similar pattern of changes, although this behaviour is not seen at all timescales and seasons .
Nature-inspired metaheuristics found various applications in different fields of science, includi... more Nature-inspired metaheuristics found various applications in different fields of science, including the problem of artificial neural networks (ANN) training. However, very versatile opinions regarding the performance of metaheuristics applied to ANN training may be found in the literature. Both nature-inspired metaheuristics and ANNs are widely applied to various geophysical and environmental problems. Among them the water temperature forecasting in a natural river, especially in colder climate zones where the seasonality plays important role, is of great importance, as water temperature has strong impact on aquatic life and chemistry. As the impact of possible future climate change on water temperature is not trivial, models are needed to allow projection of streamwater temperature based on simple hydro-meteorological variables. In this paper the detailed comparison of the performance of nature-inspired optimization methods and Levenberg–Marquardt (LM) algorithm in ANNs training is performed, based on the case study of water temperature forecasting in a natural stream, namely Biala Tarnowska river in southern Poland. Over 50 variants of 22 various metaheuristics, including a large number of Differential Evolution, as well as some Particle Swarm Optimization, Evolution Strategies, multialgorithms and Direct Search methods are compared with LM algorithm on ANN training for the described case study. The impact of population size and some control parameters of particular metaheuristics on the ANN training performance are verified. It is found that despite widely claimed large improvement in nature-inspired methods during last years, the vast majority of them are still outperformed by LM algorithm on the selected problem. The only methods that, based on this case study, seem competitive to LM algorithm in terms of the final performance (but not speed) are Differential Evolution algorithms that benefit from the concept of Global and Local neighborhood-based mutation operators. The streamwater forecasting performance of the neural networks is adequate, the major prediction errors are related to the river freezing and melting processes that occur during winter in the mountainous catchment under study.
The derivation of the flood risk maps requires an estimation of maximum inundation extent for a f... more The derivation of the flood risk maps requires an estimation of maximum inundation extent for a flood with a given return period, e.g. 100 or 500 yr. The results of numerical simulations of flood wave propagation are used to overcome the lack of relevant observations. In practice, determin-istic 1-D models are used for that purpose. The solution of a 1-D model depends on the initial and boundary conditions and estimates of model parameters based on the available noisy observations. Therefore, there is a large uncertainty involved in the derivation of flood risk maps using a single realisation of a flow model. Bayesian conditioning based on multiple model simulations can be used to quantify this uncertainty ; however, it is too computer-time demanding to be applied in flood risk assessment in practice, without further flow routing model simplifications. We propose robust and feasible methodology for estimating flood risk. In order to decrease the computation times the assumption of a gradually varied flow and the application of a steady state flow routing model is introduced. The aim of this work is an analysis of the influence of those simplifying assumptions and uncertainty of observations and modelling errors on flood inunda-tion mapping and a quantitative comparison with determin-istic flood extent maps. Apart from the uncertainty related to the model structure and its parameters, the uncertainty of the estimated flood wave with a specified probability of return period (so-called 1-in-10 yr, or 1-in-100 yr flood) is also taken into account. In order to derive the uncertainty of inun-dation extent conditioned on the design flood, the probabilities related to the design wave and flow model uncertainties are integrated. In the present paper that integration is done whilst taking into account the dependence of roughness coefficients on discharge. The roughness is parameterised based on maximum annual discharges. This approach allows for the relationship between flood extent and flow values to be derived , thus giving a cumulative assessment of flood risk. The methods are illustrated using the Warsaw reach of the River Vistula as a case study. The results indicate that determin-istic and stochastic flood inundation maps cannot be quantitatively compared. We show that the proposed simplified approach to flood risk assessment can be applied even when breaching of the embankment occurs, with the condition that the flooded area is small enough to be filled rapidly.
Despite the development of new measuring techniques, monitoring systems and advances in computer ... more Despite the development of new measuring techniques, monitoring systems and advances in computer technology, rainfall-flow modelling is still a challenge. The reasons are multiple and fairly well known. They include the distributed, heterogeneous nature of the environmental variables affecting flow from the catchment. These are precipitation, evapo-transpiration and in some seasons and catchments in Poland, snow melt also. This paper presents a review of work done on the calibration and validation of rainfall-runoff modelling, with a focus on the conceptual HBV model. We give a synthesis of the problems and propose a practical guide to the calibration and validation of rainfall-runoff models.
The aim of this work is the development of an integrated Data Based Mechanistic (DBM) rainfall-fl... more The aim of this work is the development of an integrated Data Based Mechanistic (DBM) rainfall-flow and flow-routing model suitable for scenario analysis of the Upper River Narew catchment in northeast Poland. This area encloses valuable wetland ecosystems of the Narew National Park (NPN). The available data include daily rainfall observations, temperature measurements and water level measurements at 7 gauging
This paper evaluates uncertainties in two solute transport models based on tracer experiment data... more This paper evaluates uncertainties in two solute transport models based on tracer experiment data from the Upper River Narew. Data Based Mechanistic and transient storage models were applied to Rhodamine WT tracer observations. We focus on the analysis of uncertainty and the sensitivity of model predictions to varying physical parameters, such as dispersion and channel geometry. An advection-dispersion model with dead zones (Transient Storage model) adequately describes the transport of pollutants in a single channel river with multiple storage. The applied transient storage model is deterministic; it assumes that observations are free of errors and the model structure perfectly describes the process of transport of conservative pollutants. In order to take into account the model and observation errors, an uncertainty analysis is required. In this study we used a combination of the Generalized Likelihood Uncertainty Estimation technique (GLUE) and the variance based Global Sensitivi...
Main goal of this study was to develop techniques for the a priori estimation parameters of hydro... more Main goal of this study was to develop techniques for the a priori estimation parameters of hydrological model. Conceptual hydrological model CLIRUN was applied to around 50 catchment in Poland. The size of catchments range from 1 000 to 100 000 km2. The model was calibrated for a number of gauged catchments with different catchment characteristics. The parameters of model were related to different climatic and physical catchment characteristics (topography, land use, vegetation and soil type). The relationships were tested by comparing observed and simulated runoff series from the gauged catchment that were not used in the calibration. The model performance using regional parameters was promising for most of the calibration and validation catchments.
Physics and Chemistry of the Earth, Parts A/B/C, 2011
This study presents an analysis of the influence of two different water management policies on th... more This study presents an analysis of the influence of two different water management policies on the natural river ecosystem of the Upper Narew valley. A Global Sensitivity Analysis is used to estimate their impact on water conditions in an important wetland area. The River Narew is modelled using a 1-D flow routing model.The Upper Narew Basin is situated in north-east
This paper discusses methods of deriving flood inundation maps for the purpose of flood
risk asse... more This paper discusses methods of deriving flood inundation maps for the purpose of flood risk assessment. The deterministic approach, commonly used in practice, is compared with the stochastic approach that takes into account the uncertainty related to model parameters and initial and boundary conditions. The discussion is illustrated by the example of the Upper Narew river reach. The 1-D HEC-RAS model is used for flow routing. It is calibrated and validated using historical data from the site. The deterministic approach consists of simulating the propagation of a flood wave with an assumed probability of exceedence. The maps of inundation outlines are derived from maximum water levels simulated by a distributed flow routing model (here the HEC-RAS). The stochastic approach applies multiple sampling from the a priori distribution of parameters and random initial and boundary conditions. The same HEC-RAS model is used for the flow routing and the resulting posterior distributions of parameters are used to build the maps of flood inundation probabilities. We apply Bayesian conditioning of the posterior distribution of parameters based on available historical observations. A comparison of the results of both approaches is possible only when the deterministic inundation outlines are given a specific probability value. The paper demonstrates the ambiguity of the deterministic procedure in the derivation of flood inundation probabilities.
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Papers by M. Osuch
risk assessment. The deterministic approach, commonly used in practice, is compared with the
stochastic approach that takes into account the uncertainty related to model parameters and initial and
boundary conditions. The discussion is illustrated by the example of the Upper Narew river reach. The
1-D HEC-RAS model is used for flow routing. It is calibrated and validated using historical data from
the site. The deterministic approach consists of simulating the propagation of a flood wave with an
assumed probability of exceedence. The maps of inundation outlines are derived from maximum
water levels simulated by a distributed flow routing model (here the HEC-RAS). The stochastic
approach applies multiple sampling from the a priori distribution of parameters and random initial
and boundary conditions. The same HEC-RAS model is used for the flow routing and the resulting
posterior distributions of parameters are used to build the maps of flood inundation probabilities.
We apply Bayesian conditioning of the posterior distribution of parameters based on available
historical observations. A comparison of the results of both approaches is possible only when the
deterministic inundation outlines are given a specific probability value. The paper demonstrates the
ambiguity of the deterministic procedure in the derivation of flood inundation probabilities.
risk assessment. The deterministic approach, commonly used in practice, is compared with the
stochastic approach that takes into account the uncertainty related to model parameters and initial and
boundary conditions. The discussion is illustrated by the example of the Upper Narew river reach. The
1-D HEC-RAS model is used for flow routing. It is calibrated and validated using historical data from
the site. The deterministic approach consists of simulating the propagation of a flood wave with an
assumed probability of exceedence. The maps of inundation outlines are derived from maximum
water levels simulated by a distributed flow routing model (here the HEC-RAS). The stochastic
approach applies multiple sampling from the a priori distribution of parameters and random initial
and boundary conditions. The same HEC-RAS model is used for the flow routing and the resulting
posterior distributions of parameters are used to build the maps of flood inundation probabilities.
We apply Bayesian conditioning of the posterior distribution of parameters based on available
historical observations. A comparison of the results of both approaches is possible only when the
deterministic inundation outlines are given a specific probability value. The paper demonstrates the
ambiguity of the deterministic procedure in the derivation of flood inundation probabilities.