TY - JOUR A1 - Kumar, Satish A1 - Guntu, Ravi Kumar A1 - Agarwal, Ankit A1 - Villuri, Vasant Govind Kumar A1 - Pasupuleti, Srinivas A1 - Kaushal, Deo Raj A1 - Gosian, Ashwin Kumar A1 - Bronstert, Axel T1 - Multi-objective optimization for stormwater management by green-roofs and infiltration trenches to reduce urban flooding in central Delhi JF - Journal of hydrology N2 - Urban surface runoff management via best management practices (BMP) and low impact development (LID) has earned significant recognition owing to positive environmental and ecological impacts. However, due to the complexity of the parameters involved, the estimation of LID efficiency in attenuating the urban surface runoff at the watershed scale is challenging. A planning analysis of employing Green Roofs and Infiltration Trenches as BMPs/LIDs practices for urban surface runoff control is presented in this study. A multi-objective optimization decision-making framework is established by coupling SWMM (Storm Water Management Model) with NSGA-II models to check the performance of BMPs/LIDs concerning the cost-benefit analysis of LID at the watershed scale. Two urbanized areas belonging to Central Delhi in India were used as case studies. The results showed that the SWMM model is useful in simulating optimization problems for managing urban surface runoff. The optimum scenarios efficiently minimized the urban runoff volume while maintaining the BMPs/LIDs implementation costs and size. With BMPs/LIDs implementation, the reduction in runoff volume increases as expenses increase initially; however, there is no noticeable reduction in flood volume after a certain threshold. Contrasted with the haphazard arrangement of BMPs/LIDs, the proposed approach demonstrates 22%-24% runoff reductions for the same expenditures in watershed 1 and 23%-26% in watershed 2. The result of the study provides insights into planning and management of the urban surface runoff control with LID practices. The proposed framework assists the hydrologists in optimum selection and placements of BMPs/LIDs practices to acquire the most extreme ecological advantages with the least expenses. KW - Storm water management model KW - Genetic algorithm KW - NSGA-II KW - Best management practice KW - Low impact development KW - Cost-benefit Y1 - 2022 U6 - https://doi.org/10.1016/j.jhydrol.2022.127455 SN - 0022-1694 SN - 1879-2707 VL - 606 PB - Elsevier CY - Amsterdam ER - TY - GEN A1 - Fernandez-Palomino, Carlos Antonio A1 - Hattermann, Fred F. A1 - Krysanova, Valentina A1 - Vega-Jacome, Fiorella A1 - Bronstert, Axel T1 - Towards a more consistent eco-hydrological modelling through multi-objective calibration BT - a case study in the Andean Vilcanota River basin, Perú T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Most hydrological studies rely on a model calibrated using discharge alone. However, judging the model reliability based on such calibration is problematic, as it does not guarantee the correct representation of internal hydrological processes. This study aims (a) to develop a comprehensive multi-objective calibration framework using remote sensing vegetation data and hydrological signatures (flow duration curve - FDC, and baseflow index) in addition to discharge, and (b) to apply this framework for calibration of the Soil and Water Assessment Tool (SWAT) in a typical Andean catchment. Overall, our calibration approach outperformed traditional discharge-based and FDC signature-based calibration strategies in terms of vegetation, streamflow, and flow partitioning simulation. New hydrological insights for the region are the following: baseflow is the main component of the streamflow sustaining the long dry-season flow, and pasture areas offer higher water yield and baseflow than other land-cover types. The proposed approach could be used in other data-scarce regions with complex topography. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1377 KW - Andes KW - eco-hydrology KW - SWAT KW - hydrological signatures KW - remote sensing KW - equifinality Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-568766 SN - 1866-8372 IS - 1 ER - TY - GEN A1 - Rottler, Erwin A1 - Francke, Till A1 - Bürger, Gerd A1 - Bronstert, Axel T1 - Long-term changes in central European river discharge for 1869–2016 BT - Impact of changing snow covers, reservoir constructions and an intensified hydrological cycle T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Recent climatic changes have the potential to severely alter river runoff, particularly in snow-dominated river basins. Effects of changing snow covers superimpose with changes in precipitation and anthropogenic modifications of the watershed and river network. In the attempt to identify and disentangle long-term effects of different mechanisms, we employ a set of analytical tools to extract long-term changes in river runoff at high resolution. We combine quantile sampling with moving average trend statistics and empirical mode decomposition and apply these tools to discharge data recorded along rivers with nival, pluvial and mixed flow regimes as well as temperature and precipitation data covering the time frame 1869-2016. With a focus on central Europe, we analyse the long-term impact of snow cover and precipitation changes along with their interaction with reservoir constructions. Our results show that runoff seasonality of snow-dominated rivers decreases. Runoff increases in winter and spring, while discharge decreases in summer and at the beginning of autumn. We attribute this redistribution of annual flow mainly to reservoir constructions in the Alpine ridge. During the course of the last century, large fractions of the Alpine rivers were dammed to produce hydropower. In recent decades, runoff changes induced by reservoir constructions seem to overlap with changes in snow cover. We suggest that Alpine signals propagate downstream and affect runoff far outside the Alpine area in river segments with mixed flow regimes. Furthermore, our results hint at more (intense) rain-fall in recent decades. Detected increases in high discharge can be traced back to corresponding changes in precipitation. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1412 KW - empirical mode decomposition KW - atmospheric blocking KW - heavy precipitation KW - streamflow trends KW - climate-change KW - rhine basin KW - time-series KW - events KW - Switzerland KW - variability Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-517763 SN - 1866-8372 IS - 4 ER - TY - JOUR A1 - Mtilatila, Lucy Mphatso Ng'ombe A1 - Bronstert, Axel A1 - Shrestha, Pallav A1 - Kadewere, Peter A1 - Vormoor, Klaus Josef T1 - Susceptibility of water resources and hydropower production to climate change in the tropics BT - the case of Lake Malawi and Shire River Basins, SE Africa JF - Hydrology : open access journal N2 - The sensitivity of key hydrologic variables and hydropower generation to climate change in the Lake Malawi and Shire River basins is assessed. The study adapts the mesoscale Hydrological Model (mHM) which is applied separately in the Upper Lake Malawi and Shire River basins. A particular Lake Malawi model, which focuses on reservoir routing and lake water balance, has been developed and is interlinked between the two basins. Climate change projections from 20 Coordinated Regional Climate Downscaling Experiment (CORDEX) models for Africa based on two scenarios (RCP4.5 and RCP8.5) for the periods 2021-2050 and 2071-2100 are used. An annual temperature increase of 1 degrees C decreases mean lake level and outflow by 0.3 m and 17%, respectively, signifying the importance of intensified evaporation for Lake Malawi's water budget. Meanwhile, a +5% (-5%) deviation in annual rainfall changes mean lake level by +0.7 m (-0.6 m). The combined effects of temperature increase and rainfall decrease result in significantly lower flows in the Shire River. The hydrological river regime may change from perennial to seasonal with the combination of annual temperature increase and precipitation decrease beyond 1.5 degrees C (3.5 degrees C) and -20% (-15%). The study further projects a reduction in annual hydropower production between 1% (RCP8.5) and 2.5% (RCP4.5) during 2021-2050 and between 5% (RCP4.5) and 24% (RCP8.5) during 2071-2100. The results show that it is of great importance that a further development of hydro energy on the Shire River should take into account the effects of climate change, e.g., longer low flow periods and/or higher discharge fluctuations, and thus uncertainty in the amount of electricity produced. KW - Lake Malawi Basin KW - Shire River Basin KW - lake water balance KW - climate change impacts in the tropics KW - hydropower generation KW - response surface analysis KW - sensitivity analysis Y1 - 2020 U6 - https://doi.org/10.3390/hydrology7030054 SN - 2306-5338 VL - 7 IS - 3 PB - MDPI CY - Basel ER - TY - JOUR A1 - Rottler, Erwin A1 - Vormoor, Klaus Josef A1 - Francke, Till A1 - Warscher, Michael A1 - Strasser, Ulrich A1 - Bronstert, Axel T1 - Elevation-dependent compensation effects in snowmelt in the Rhine River Basin upstream gauge Basel JF - Hydrology research : an international journal / Nordic Association of Hydrology ; British Hydrological Society N2 - In snow-dominated river basins, floods often occur during early summer, when snowmelt-induced runoff superimposes with rainfall-induced runoff. An earlier onset of seasonal snowmelt as a consequence of a warming climate is often expected to shift snowmelt contribution to river runoff and potential flooding to an earlier date. Against this background, we assess the impact of rising temperatures on seasonal snowpacks and quantify changes in timing, magnitude and elevation of snowmelt. We analyse in situ snow measurements, conduct snow simulations and examine changes in river runoff at key gauging stations. With regard to snowmelt, we detect a threefold effect of rising temperatures: snowmelt becomes weaker, occurs earlier and forms at higher elevations. Due to the wide range of elevations in the catchment, snowmelt does not occur simultaneously at all elevations. Results indicate that elevation bands melt together in blocks. We hypothesise that in a warmer world with similar sequences of weather conditions, snowmelt is moved upward to higher elevation. The movement upward the elevation range makes snowmelt in individual elevation bands occur earlier, although the timing of the snowmelt-induced runoff stays the same. Meltwater from higher elevations, at least partly, replaces meltwater from elevations below. KW - compensation effects KW - elevation-dependency KW - Rhine River KW - snowmelt KW - timing Y1 - 2021 U6 - https://doi.org/10.2166/nh.2021.092 SN - 2224-7955 VL - 52 IS - 2 SP - 536 EP - 557 PB - IWA Publ. CY - London ER - TY - JOUR A1 - Mtilatila, Lucy Mphatso Ng'ombe A1 - Bronstert, Axel A1 - Vormoor, Klaus Josef T1 - Temporal evaluation and projections of meteorological droughts in the Greater Lake Malawi Basin, Southeast Africa JF - Frontiers in water N2 - The study examined the potential future changes of drought characteristics in the Greater Lake Malawi Basin in Southeast Africa. This region strongly depends on water resources to generate electricity and food. Future projections (considering both moderate and high emission scenarios) of temperature and precipitation from an ensemble of 16 bias-corrected climate model combinations were blended with a scenario-neutral response surface approach to analyses changes in: (i) the meteorological conditions, (ii) the meteorological water balance, and (iii) selected drought characteristics such as drought intensity, drought months, and drought events, which were derived from the Standardized Precipitation and Evapotranspiration Index. Changes were analyzed for a near-term (2021-2050) and far-term period (2071-2100) with reference to 1976-2005. The effect of bias-correction (i.e., empirical quantile mapping) on the ability of the climate model ensemble to reproduce observed drought characteristics as compared to raw climate projections was also investigated. Results suggest that the bias-correction improves the climate models in terms of reproducing temperature and precipitation statistics but not drought characteristics. Still, despite the differences in the internal structures and uncertainties that exist among the climate models, they all agree on an increase of meteorological droughts in the future in terms of higher drought intensity and longer events. Drought intensity is projected to increase between +25 and +50% during 2021-2050 and between +131 and +388% during 2071-2100. This translates into +3 to +5, and +7 to +8 more drought months per year during both periods, respectively. With longer lasting drought events, the number of drought events decreases. Projected droughts based on the high emission scenario are 1.7 times more severe than droughts based on the moderate scenario. That means that droughts in this region will likely become more severe in the coming decades. Despite the inherent high uncertainties of climate projections, the results provide a basis in planning and (water-)managing activities for climate change adaptation measures in Malawi. This is of particular relevance for water management issues referring hydro power generation and food production, both for rain-fed and irrigated agriculture. KW - meteorological drought KW - drought intensity KW - climate change KW - drought KW - events KW - Lake Malawi KW - Shire River KW - drought projections KW - South-Eastern KW - Africa Y1 - 2022 U6 - https://doi.org/10.3389/frwa.2022.1041452 SN - 2624-9375 VL - 4 PB - Frontiers Media CY - Lausanne ER - TY - GEN A1 - Seleem, Omar A1 - Ayzel, Georgy A1 - Bronstert, Axel A1 - Heistermann, Maik T1 - Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Data-driven models have been recently suggested to surrogate computationally expensive hydrodynamic models to map flood hazards. However, most studies focused on developing models for the same area or the same precipitation event. It is thus not obvious how transferable the models are in space. This study evaluates the performance of a convolutional neural network (CNN) based on the U-Net architecture and the random forest (RF) algorithm to predict flood water depth, the models' transferability in space and performance improvement using transfer learning techniques. We used three study areas in Berlin to train, validate and test the models. The results showed that (1) the RF models outperformed the CNN models for predictions within the training domain, presumable at the cost of overfitting; (2) the CNN models had significantly higher potential than the RF models to generalize beyond the training domain; and (3) the CNN models could better benefit from transfer learning technique to boost their performance outside training domains than RF models. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1323 Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-589168 SN - 1866-8372 IS - 1323 SP - 809 EP - 822 ER - TY - JOUR A1 - Seleem, Omar A1 - Ayzel, Georgy A1 - Bronstert, Axel A1 - Heistermann, Maik T1 - Transferability of data-driven models to predict urban pluvial flood water depth in Berlin, Germany JF - Natural Hazards and Earth System Sciences N2 - Data-driven models have been recently suggested to surrogate computationally expensive hydrodynamic models to map flood hazards. However, most studies focused on developing models for the same area or the same precipitation event. It is thus not obvious how transferable the models are in space. This study evaluates the performance of a convolutional neural network (CNN) based on the U-Net architecture and the random forest (RF) algorithm to predict flood water depth, the models' transferability in space and performance improvement using transfer learning techniques. We used three study areas in Berlin to train, validate and test the models. The results showed that (1) the RF models outperformed the CNN models for predictions within the training domain, presumable at the cost of overfitting; (2) the CNN models had significantly higher potential than the RF models to generalize beyond the training domain; and (3) the CNN models could better benefit from transfer learning technique to boost their performance outside training domains than RF models. Y1 - 2023 U6 - https://doi.org/10.5194/nhess-23-809-2023 SN - 1684-9981 SN - 1561-8633 VL - 23 IS - 2 SP - 809 EP - 822 PB - Copernicus CY - Göttingen ER - TY - GEN A1 - Seleem, Omar A1 - Ayzel, Georgy A1 - Costa Tomaz de Souza, Arthur A1 - Bronstert, Axel A1 - Heistermann, Maik T1 - Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany T2 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1297 KW - Urban pluvial flood susceptibility KW - convolutional neural network KW - deep learning KW - random forest KW - support vector machine KW - spatial resolution KW - flood predictors Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-576806 SN - 1866-8372 IS - 1297 SP - 1640 EP - 1662 ER - TY - JOUR A1 - Schmidt, Lena Katharina A1 - Francke, Till A1 - Rottler, Erwin A1 - Blume, Theresa A1 - Schöber, Johannes A1 - Bronstert, Axel T1 - Suspended sediment and discharge dynamics in a glaciated alpine environment BT - identifying crucial areas and time periods on several spatial and temporal scales in the Ötztal, Austria JF - Earth surface dynamics N2 - Glaciated high-alpine areas are fundamentally altered by climate change, with well-known implications for hydrology, e.g., due to glacier retreat, longer snow-free periods, and more frequent and intense summer rainstorms. While knowledge on how these hydrological changes will propagate to suspended sediment dynamics is still scarce, it is needed to inform mitigation and adaptation strategies. To understand the processes and source areas most relevant to sediment dynamics, we analyzed discharge and sediment dynamics in high temporal resolution as well as their patterns on several spatial scales, which to date few studies have done. We used a nested catchment setup in the Upper Ötztal in Tyrol, Austria, where high-resolution (15 min) time series of discharge and suspended sediment concentrations are available for up to 15 years (2006–2020). The catchments of the gauges in Vent, Sölden and Tumpen range from 100 to almost 800 km2 with 10 % to 30 % glacier cover and span an elevation range of 930 to 3772 m a.s.l. We analyzed discharge and suspended sediment yields (SSY), their distribution in space, their seasonality and spatial differences therein, and the relative importance of short-term events. We complemented our analysis by linking the observations to satellite-based snow cover maps, glacier inventories, mass balances and precipitation data. Our results indicate that the areas above 2500 m a.s.l., characterized by glacier tongues and the most recently deglaciated areas, are crucial for sediment generation in all sub-catchments. This notion is supported by the synchronous spring onset of sediment export at the three gauges, which coincides with snowmelt above 2500 m but lags behind spring discharge onsets. This points at a limitation of suspended sediment supply as long as the areas above 2500 m are snow-covered. The positive correlation of annual SSY with glacier cover (among catchments) and glacier mass balances (within a catchment) further supports the importance of the glacier-dominated areas. The analysis of short-term events showed that summer precipitation events were associated with peak sediment concentrations and yields but on average accounted for only 21 % of the annual SSY in the headwaters. These results indicate that under current conditions, thermally induced sediment export (through snow and glacier melt) is dominant in the study area. Our results extend the scientific knowledge on current hydro-sedimentological conditions in glaciated high-alpine areas and provide a baseline for studies on projected future changes in hydro-sedimentological system dynamics. Y1 - 2022 U6 - https://doi.org/10.5194/esurf-10-653-2022 SN - 2196-632X SN - 2196-6311 VL - 10 IS - 3 SP - 653 EP - 669 PB - Copernicus Publications CY - Göttingen ER -