Flood estimation in ungauged basins is important for flood design, and for improving our understanding of the sensitivity of flood magnitude to changes in climate and land cover. Flood estimates by current methods (e.g. statistical regression, unit hydrograph) have high uncertainty, even in places with dense observing networks (e.g. +/- 50-100% in the UK). Reductions in this uncertainty are being sought by using alternative methods, such as continuous simulation using hydrological models (spatially-distributed or lumped), and event-scale derived distribution approaches. There are very significant challenges for reliable application of continuous simulation models to extreme events in ungauged catchments.

The event-scale derived distribution approach also has challenges, which we explore below. The derived distribution approach at the event scale typically combines the following elements: a stochastic rainfall model, an event-scale rainfall-runoff model (including “losses” and a “baseflow” component), and a runoff routing model. In principle, every element of this approach may be considered as a (seasonally varying) random variable. The flood peak distribution is obtained by integrating over joint distributions of the model elements.

First challenge: what is the physical basis for estimating the event runoff coefficient? In the 1970s, this was addressed using infiltration theory, but other runoff generation mechanisms are often more important. We suggest: (i) begin with locations which are dominated by a small number of runoff generation mechanisms (ii) make use of existing theory on links between climate, catchment characteristics and seasonal water balance (iii) exploit large samples of data where available. I will briefly summarise our progress on this topic in the UK, using a largely empirical approach, though with an eye to later exploring a process-based explanation.

Second challenge: how do we parsimoniously quantify the impacts of within-storm temporal and spatial rainfall patterns on the flood hydrograph? Existing approaches use stochastic rainfall models to explicitly generate (hourly) time series (or fields) of rainfall; since catchments damp out high frequency forcing, these rainfall series often contain excessive detail and obscure the most informative interactions between rainfall and catchment response. We propose stochastic models that can generate hydrologically relevant attributes of rainfall events (e.g. intensity/depth/duration, spatial and temporal moments), and then apply rainfall-runoff transformations which operate on rainfall moments, and do not require excess detail in temporal (or spatial) patterns of rainfall. I will present recent results showing that it is feasible to summarise rainfall characteristics in this way, and that spatial patterns in rainfall do play a role in determining flood magnitude, but only in some events.

Third challenge: How well does existing theory (Woods & Sivapalan et al 1999, Viglione et al 2010, Gaál et al, 2012) combine the spatial and temporal moments of a rainfall event with catchment characteristics, in order to predict the hydrograph temporal characteristics, especially the temporal variance, a measure of temporal dispersion? Successful applications of this theory (which depends ultimately on geomorphological dispersion) will require (i) neglect of some covariance terms (ii) a strategy for estimating hillslope travel times relevant to floods (iii) reasonable estimates of the characteristic river network celerity for ungauged catchments.

How to cite: Woods, R., Zheng, Y., Quaglia, R., Yin, Y., Giani, G., Coxon, G., Han, D., Rico-Ramirez, M., and Rosolem, R.: Recent Developments in the Application of the Derived Distribution Approach to Flood Frequency, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-3382, https://doi.org/10.5194/egusphere-egu23-3382, 2023.

The observed variability in shape and timing characteristics of event hydrographs emerges from the variability in the types and structure of the corresponding hydrometeorological events and their interaction with the variable catchment states. The increasing temporal resolution of available hydrometeorological data provide a possibility for deciphering the effect of space-time dynamics of precipitation on the characteristics of event hydrographs and might provide useful insights into the differences on the controls of small and large runoff events. In this study, we comprehensively analysed the effects of the spatio-temporal dynamics of precipitation on the characteristics of hourly event hydrographs using the analytical framework of Viglione et al. (2010). We examined eight properties reflecting the shape and timing characteristics of 2026 hourly event hydrographs and 20 indicators describing the spatio-temporal structure of precipitation and pre-event wetness states in seven contrasting catchments in the Bode River basin, located in central Germany, using random forests and Accumulated Local Effects (ALE) techniques.

We found that the steepness of the rising limbs of event hydrographs is controlled by the intensity of precipitation, its temporal dispersion, and the catchment-averaged storm velocity. The contribution of these indicators is even more apparent for large runoff events (i.e., events with larger peak discharges). Instead, the event time scale of the hydrographs is rather affected by the volume of precipitation and antecedent base flow in combination with the spatial properties of precipitation (its spatial spread and proximity to the catchment outlet). Moreover, we found that the duration of precipitation events plays a major role in defining the response time of catchments. Finally, our results demonstrate that the effects of spatio-temporal structure of precipitation for the shape and timing characteristics of hydrographs are especially prominent for larger events, indicating the potential importance of these features for accurate flood forecasting and constructing of design synthetic hydrographs. The future effort will focus on examining the validity of identified controls for a larger and more diverse set of catchments in Germany.

References

Viglione, A., Chirico, G. B., Komma, J., Woods, R., Borga, M., and Blöschl, G. (2010). Quantifying space-time dynamics of flood event types. Journal of Hydrology, 394 (1-2):213–229.

How to cite: Tarasova, L., Aala, S., Ribbe, L., and Kumar, R.: Effects of space-time dynamics of precipitation on timing and shape characteristics of runoff events, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-7769, https://doi.org/10.5194/egusphere-egu23-7769, 2023.

In flood events, in order to evaluate the hydrological dam safety, it should be assessed the frequency curve of maximum reservoir water levels. For this purpose, a large set of inflow hydrographs are routed through the reservoir. In this approach, the result will depend on several variables, such as flood peak and hydrograph volume frequency curves and the dependence structure between variables. In addition, for this process several hydrometeorological simulations are performed in order to characterise the catchment response in flood events, obtaining hydrograph shapes that can be generated in the catchment. However, first, the hydrological model calibration requires, as input data, given hyetograph shapes.

This study presents the application of a bivariate analyses to assess the hydrological safety of dams based on hydrometeorological simulations. The analysis is carried out in the Cuerda del Pozo Dam in central Spain. In this catchment, flood hydrographs associated with annual maximum peak flows are usually generated by storms with a duration of several days. Consequently, hyetographs of several days obtained from intensity-duration-frequency curves are required, in order to obtain the runoff volumes given by the univariate frequency curve of hydrograph volumes. However, hydrological simulations with such long hyetographs present different problems. If a small time step is considered in the design hyetographs of several days, sharp hydrographs will be generated with peak flows greater than required. Unreasonable model parameters would be used to smooth the concentration and diffusion processes, reducing simulated flood peaks. On the other hand, if a large time step is considered, smooth hydrographs could be obtained with flood peaks smaller than quantiles in the flood frequency curve. Therefore, a detailed analysis is carried out to calibrate both flood peaks and hydrograph volumes, obtaining an appropriate hyetograph shape that will lead to acceptable values of the hydrological model parameters.

The calibrated rainfall-runoff model is used to generate a set of possible synthetic hydrograph shapes. A bivariate analysis is performed to generate random pairs of peak flow and hydrograph volume that fit the univariate frequency curves and keep the dependence structure between variables. A given synthetic hydrograph shape is assigned to each pair of peak flow and hydrograph volume. A long set of 500 000 inflow hydrographs is used. Hydrological safety of the Cuerda del Pozo Dam is assessed by using the frequency curve of maximum reservoir water levels.

How to cite: Carril-Rojas, D. and Mediero, L.: Selection of hyetograph shapes for generating synthetic hydrographs in a bivariate analysis for hydrological dam safety assessment., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12146, https://doi.org/10.5194/egusphere-egu23-12146, 2023.

Traditional regionalization methods allow estimating hydrological variables in stationary conditions: in the context of climate change new techniques are sought, which take into account the non-stationarity of climate variables. As part of a project in collaboration between universities and the Po basin authority, different approaches including regionalization procedures are used to characterize the hydrological extremes in the Po River basin. In particular, we use the Spatially Smooth Regional Estimation method, which is based on multiregressive estimation of L-moments that do not require the definition of homogeneous regions. The regression models are based on morpho-climatic descriptors including climate variables such as the mean annual precipitation, and the coefficients of a model for the  IDF  curves. By analyzing the multi-year variability of the climatic variables in each basin, with this work we aim at: (i) comparing the trends of the climatic variables and the trend of discharges associated with different return periods, (ii) analyzing the sensitivity of the regression equations to changes in time of these variables. Moreover, we compare the rainfall and flood quantiles for each sub-basin, to evaluate the percentage change of the standardised flood discharge for the percentage change in extreme rainfall. This approach allows us to investigate the effects of rainfall mechanisms and catchment characteristics on flood probabilities in the Po River basin.

How to cite: Cafiero, L., Mazzoglio, P., Monforte, I., Claps, P., Viglione, A., and Laio, F.: Non-stationary flood frequency analysis: case study in the Po river basin, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5694, https://doi.org/10.5194/egusphere-egu23-5694, 2023.

Widespread riverine flood events wherein most subbasins simultaneously experience flooding have relatively higher socio-economic implications relative to localized flooding within a river basin. Extreme precipitation covering a large area, favourable antecedent soil moisture conditions and unique atmospheric characteristics are often associated with these rare extreme events. Notwithstanding the huge death toll and economic consequences of flooding, there exists only a couple of studies that explore the causative factors of riverine flooding in India. Here, we identify widespread flooding in seven major river basins in India using streamflow simulations from a well-calibrated Variable Infiltration Capacity (VIC) hydrological model. We use an area-weighted threshold to determine the occurrence of widespread flooding. We estimated the probability of widespread flooding In Indian river basins during the observational period from 1959 to 2020. We find a high probability of widespread flooding  (>10% of high flow events in all subbasins) in the peninsular river basins, while the transboundary rivers of Ganga and Brahmaputra exhibit a low probability. Further, using the VIC simulated top layer soil moisture, gridded precipitation observations from India Meteorological Department (IMD) and ERA5 atmospheric variables; we investigate the antecedent soil moisture conditions and atmospheric characteristics associated with widespread flooding. The study results further our understanding of the causes of widespread flooding in Indian river basins and hence have major implications in managing these extreme events. 

How to cite: Sobhana, N. J. and Mishra, V.: Drivers of Widespread Flooding in Indian River Basins, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-11194, https://doi.org/10.5194/egusphere-egu23-11194, 2023.

Poland is characterized by hydrometeorological variability, where conditions such as snowmelt, extreme precipitation, or soil moisture excess could be the main natural mechanisms causing fluvial flooding. The interplay of these factors may be additionally modified by climate change. Therefore, it is of high interest to attribute the occurrence of floods over Poland to single or multiple drivers as well as to analyse how this attribution evolved over time.

To meet this objective in the present study, we used the dataset covering components of the water balance with a daily time step at the sub-basin level over Poland for the period 1951-2020. The data set was derived from the previously calibrated and validated Soil & Water Assessment Tool (SWAT) model for over 4,000 sub-basins. The high spatial and temporal resolution of the dataset as well as its temporal continuity allowed us to comprehensively analyse the flood drivers over the country and their evolution over time. We used a method based on the circular statistics approach, using dates of occurrence of annual maximum floods and flood-generating mechanisms to estimate the relative importance of each flood driver. In addition, two sub-periods (1952-1985 and 1986-2020) were considered in order to detect the climate change signal.

The analysis of the relative importance of flood drivers showed that snowmelt is the most important cause of flooding throughout the country, followed by soil moisture excess and precipitation. The latter appeared to be the dominant driver only in a small, mountain-dominated region in the south. Soil moisture excess gained importance mainly in the northern part, although not in a uniform way, suggesting that the spatial pattern of flood generation mechanisms is also governed by other features. We also found a strong signal of climate change in large parts of northern Poland, where snowmelt is losing importance in the second sub-period in favor of soil moisture excess, which can be explained by the temperature warming and the diminishing role of snow processes. This study for the first time quantified the importance of different flood generating mechanisms over Poland, suggesting that more attention should be paid to soil moisture excess. This work also shows the potential of using high-resolution simulated water balance data sets in flood attribution studies.

How to cite: Venegas-Cordero, N., Cherrat, C., W. Kundzewicz, Z., Singh, J., and Piniewski, M.: Model-based flood attribution over Poland: the roles of precipitation, snowmelt and soil moisture excess, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-12799, https://doi.org/10.5194/egusphere-egu23-12799, 2023.

Long-term trends in flood losses are regulated by multiple factors including climate variation, demographic dynamics, economic growth, land-use transitions, reservoir construction and flood adaptation measures. Attributing losses to any of those factors for historical flood events would require the ability to recalculate reported impacts (such as area inundated, fatalities, persons affected or economic loss) under counterfactual scenarios. Here, we present how observed flood impacts that have occurred in 42 European countries since 1950 can be compared with model simulations as a step towards climate change attribution of flood losses. Firstly, we reconstructed the potential footprints and inundation depths of individual riverine and coastal flood events. This was made possible by combining continuous simulations of river discharges (based on the LISFLOOD model) and storm surge heights (based on the Delft3D model) with flood hazard maps derived through hydrodynamic modelling. Then, the flood footprints were intersected with a set of time-varying, high-resolution exposure maps of land use, population and asset values in Europe since 1950 (based on the HANZE-Exposure v2.0 model). Modelled potential flood damage can then be evaluated against historical records of flood occurrences and their impacts. To this end, we are collecting dates, locations and, where available, impact statistics of floods in an updated HANZE-Events database. By comparing which potential floods did cause impacts, in which locations and to what magnitude, and which floods were prevented by flood protection, it will be possible to infer flood vulnerability and preparedness across time and space. Available preliminary results enable presenting the space-time dynamics of European flood damages under different exposure scenarios.

How to cite: Paprotny, D., Tilloy, A., Vousdoukas, M. I., Treu, S., Feyen, L., Kreibich, H., Rhein, B., and Mengel, M.: Improving estimation of space-time dynamics of floods in Europe by combining modelled and observed flood impact data, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-5152, https://doi.org/10.5194/egusphere-egu23-5152, 2023.

Regarding existing qualitative evaluations for flood risks, the researcher is to use the food risk map made by the flood risk map made by applying extreme rainfall to national, local, and small rivers. The submerged range is the same regardless of rainfall intensity. Therefore, this study prepares a flood risk map by frequency and conducted IBA (Indicator-Based Approach) flood risk assessment from 2016 to 2020 for metropolitan cities. In addition, by calculating climate change through the future flood risk index, the researcher will analyze this trend with the Mann-Kendall method. This study individually prepares a flood risk map according to rainfall intensity by calculating the design flood discharge by frequency. In this case, not only hazard but also changes in the exposure and vulnerability indexes as the area of the flood risk map changes. In the case of exposure and vulnerability, extracted and calculated flood risk map includes the population and the number of buildings, so the index of the relevant items changes according to the area of the flood risk map. This study conducts a future flood risk assessment using the climate change scenario when flood risks for future metropolitan cities can be analyzed and used to cope with environmental changes. In addition, if there is a trend towards increasing at specific rainfall observatories around metropolitan cities through trend analysis, it can be shown as evidence that the probability of rainfall by future frequency is extensively estimated given these characteristics. Using these results, a local government can make a plan to manage flood risks.

How to cite: Kang, Y., Lee, H., Kim, S., and Kim, H. S.: A Study On Applicability Of Flood Risk Maps For Flood Risk Assessment, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14526, https://doi.org/10.5194/egusphere-egu23-14526, 2023.

Due to climate change, rainfall occurs at a higher frequency than the design frequency, and flood damage has occurred in excess of the river design standard. Currently, river management in general is gray infrastructure such as embankments and weirs for irrigation and flood control. However, the river management plan through the gray infrastructure emits carbon dioxide, increasing the occurrence of extreme weather due to climate change and intensifying flood damage, causing a vicious cycle to repeat. Therefore, since the river management method by gray infrastructure cannot be adopted as a sustainable solution, the concept of Nature-based Solutions(NbS), which seeks to solve environmental and social problems through ecosystem services, is attracting attention recently. Therefore, in this study, the flood reduction effect of river management using NbS was quantitatively analyzed for the Hwang River, which is directly downstream of Hapcheon Dam. In addition, using the climate change scenarios of the IPCC 6th Assessment Report, the study tried to confirm the ability to respond to climate change through NbS. We used SSP5-8.5(Shared Socioeconomic Pathways5-8.5) and SSP2-4.5 scenarios for future precipitation, and the design flood discharge was calculated through HEC-HMS. Floodplain excavation and dyke relocation, which are included in the NbS, were applied to the flood risk area of the Huang River. As a result of analyzing the flood level of the river through the unsteady flow analysis of HEC-RAS, it was possible to confirm the effect of reducing the flood level by 5 to 7 cm for each scenario at the confluence of the Nakdong River. The results of this study can be expected to be sufficiently utilized as a basis for use as a management plan through NbS rather than the river management with grey infrastructure.

How to cite: Lee, H., Kang, Y., Kim, H. S., Kim, S., and Kim, K.: Analysis of Climate Change Mitigation and Flood Reduction Effects of Nature-based Solutions, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-14527, https://doi.org/10.5194/egusphere-egu23-14527, 2023.

Urban flood mostly is pluvial flood, caused by high rainfall intensities combined with the unsuitable drainage system and land cover. Because of the heterogeneous drainage system and the storm distribution dynamics, urban floods are rapid and spontaneous in space and time. Flood risk analysis was created to understand and assess the flood behavior, manage and mitigate the flood damage. However, flood risk assessments recently only have focused on the spatial distribution of the flood while temporal flood evolution in urban area is still an open question. This research aims to provide a spatio-temporal analysis of the urban flood by implementing the simplified model-based representation of flood evolution/development in space and time (spatiotemporal patterns) including time to flood the manhole, the location, spatial and temporal sequences of flood.

To specify, 3 precipitation distribution patterns were collected from rainfall incidents in 2008, 2019, 2020, then extrapolated to create 21 scenarios following the return periods (i.e. 1.25-year, 2-year, 2.5-year, 5-year, 10-year, 20-year, 50-year). In each scenario, the dynamics of flood was estimated using the urban drainage system by SWMM5. Case study (Do Lo, Yen Nghia, Ha Dong, Ha Noi, Viet Nam) was divided into 115 sub-catchtments based on the Digital Elevation Model (DEM) and the drainage system map of this area. Land cover was created based on the LANDSAT images. Domestic waste water distribution was included in the model. The model is validated with the extreme events in 2020 and 2022.

A spatio-temporal risk map was generated to show the flooding spatio-temporal sequences and non-flood region. Flood evolution on the time scale was shown in this map. The rate of flood change diagrams shows the flood responses from urban areas which vary from 1 to 107 mins in different scenarios.

Rain gauge distribution sensitivity is examined under ranges of rain gauge distribution combinations in term of space and time.

How to cite: Do Minh, H., Corzo Perez, G., Barreto, W., and Zevenbergen, C.: A Spatiotemporal hydrological response of extreme urban floods in Ha Noi – Vietnam., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-6891, https://doi.org/10.5194/egusphere-egu23-6891, 2023.

One of the most sensitive areas to climate change impacts are coastal-near and low-relief areas. While these coastal zones often are places of high population density and important infrastructure, they are also particularly exposed to multiple future climate change hazards such as sea level rise, intensified storm surges, rising groundwater and high-intense precipitation events. Thus, elevated risks of overbank spilling, dam breaks and flooding events are expected in a future climate in temperate wet regions such as Denmark. To mitigate and adapt to such elevated risks, prediction of future flooding events is vital, and here hydrological modelling is an essential tool. However, such impact evaluations are subject to a range of uncertainties such as emission, climate and sea level prediction uncertainties as well as impact model uncertainty.

In this study, we investigate the uncertainties of predicted flooding from a river course and the groundwater system using a hydrodynamic model coupled with a 3D groundwater model. The model is forced with different climate scenarios and inputs from two different approaches of downscaled global sea level rise implemented using an indirect and direct bias correction procedure. The indirect procedure uses a simple delta change approach perturbing future climate and sea level change on observations, while the direct method uses bias-corrected climate model data, corresponding ocean model run data (for internal oceanic response to climate change), combined with global sea level change. This approach makes it possible to investigate the relative importance (sensitivity) of the flood prediction of sea level projection and bias correction procedure as well as the identification of past and future origin (surface or groundwater) of flooding events.

How to cite: Seidenfaden, I. K., Skjerbæk, M. R., Sonnenborg, T. O., Henriksen, H. J., Payne, M. R., Su, J., William, C., and Kjeldsen, K. K.: Flooding in marsh areas caused by climate change – sensitivity to the accuracy of sea level projections and bias correction procedure, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15155, https://doi.org/10.5194/egusphere-egu23-15155, 2023.

The present research focuses on evaluating the prediction capacity of the hydrological flood model called Rainfall-Runoff-Inundation (RRI), using observed data and satellite remote sensing in order to produce flood maps of the Alto Huallaga basin in Peru. The RRI model required as input data the topographic map of the region (we use FABDEM product), information on vegetation cover and land use obtained from FAO-UNESCO, and precipitation and evapotranspiration data from the Peruvian Interpolation data of the SENAMHI's Climatological and Hydrological observations (PISCO).

The RRI model was evaluated for the 2014-2019 period, previously carrying out a sensitivity analysis process of the parameters and estimating the geometric parameters of the RRI model using information from satellite altimetry and remote sensing. The hydrological part of the model is calibrated at 2 hydrological stations on the Huallaga River (Tingo María and Tocache), obtaining acceptable results with Kling-Gupta (KGE) coefficients above 0.7 for both stations during the calibration and validation period. In addition, satellite images of the MODIS product were used for the part of flood maps, compared with the results of the RRI (flood areas), obtaining acceptable statistics when comparing the resulting images.

This work is part of the results of the Enandes project (Enhancing Adaptive Capacity of Andean Communities through Climate Services) implemented in Peru that seeks to improve climate services in Peru with an emphasis on disaster risk management in Andean basins regarding floods.

How to cite: Lavado-Casimiro, W., Qquenta, J., Montesinos, C., Asencios, H., and Felipe, O.: Spatio-temporal flood inundation modeling in the Andes Huallaga basin in Peru, EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-2938, https://doi.org/10.5194/egusphere-egu23-2938, 2023.

There is a global consensus in the scientific community that urbanization and climate change are posing high uncertainty and challenges for the 21st century, exacerbating the flood risk in different cities or urban sub-catchments which also hinders resilience building. Land Use/Land Cover (LULC) change as a result of anthropogenic activity such as complex urban growth, is a critical aspect to study due to its main role on the hydrological response of river basins. Therefore, it is crucial to understand a basin response during hydrological extremes and how shifts in urban extension or any other complex LULC change impact on it, in order to make informed decisions and deploy strategies for mitigating flood risk. This research is aimed to implement a multi-scenario hazard assessment approach which couples GeoSOS-FLUS (Cellular Automata + Markov chains), a event-based hydrological model (HEC-HMS) and a 2D hydrodynamic model (HEC-RAS) simulations including multi-type natural and urban land uses in 3 Peruvian catchments which flow into the Pacific Ocean. Here, several cities currently face a lack of capacity and scientific understanding to respond to hydrological extremes and deal effectively with the uncertainty of complex LULC transitions and urbanization. HEC-HMS modelling system incorporates spatially varied land use parameters and simulates key hydrologic processes at sub-catchment scale which are impacted by LULC transitions. Flood events are studied in experiments for different return periods. The assessment was carried out using daily downscaled CMIP6 meteorological datasets under Shared Socioeconomic Pathways (SSPs) scenarios at 0.25° of resolution from 2030 to 2050. According to the predicted flood extension, new built-up zones are also exhibiting a significant flood exposure. The rising flood hazard data generated by model simulations aids in our comprehension of future distribution of flood-prone zones at sub-catchment and city level. Our work and its ongoing improvements are pointed to be a promising method in several flood risk studies in Peru. The findings also encourage rethinking urban development and measures in high hazard intensity areas, overcoming the lack of scientific understanding and quantifiable evidence of climate change and urbanization effects.

How to cite: Montenegro Gambini, J. I.: Urban flood hazard assessment in Pacific Peruvian catchments: Coupling hydrological, hydrodynamic and future land use modelling under climate change., EGU General Assembly 2023, Vienna, Austria, 23–28 Apr 2023, EGU23-15996, https://doi.org/10.5194/egusphere-egu23-15996, 2023.