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Emerging approaches: Hydrologic-hydraulic modelling for urban floods and Thresholds in hydrology

Hydrological forecasting can benefit from a better understanding of urban floods and of the thresholds values of the hydrological variables that are crucial for making decisions. This session addresses these two aspects.
Urban flooding is becoming a major issue in many megacities around the world due to a lack of adequate storm water management, hydrologic design, and failure of aging hydrologic infrastructure. To model such extreme flood events, it is of utmost importance to develop state-of-the-art disaster mitigation and damage reduction measures, as well as one and two-dimensional hydrologic and coupled hydrodynamic modelling approaches. Innovative methods are needed to address the modelling and management of urban floods and their spatial and temporal complexity. The session discusses urban floods analysis and measures to mitigate the effects of these events, emerging (e.g., Internet-of-Things (IoT)-based) flood monitoring systems, street-level flood forecasting, dissemination of flood warnings and measures to evacuate people, case studies that provide a better understanding of urban flood management, and innovative methods of floodwater conservation, including strategies and practices to control surface runoff at its sources in a sustainable way.
In hydrological forecasting, where the stochastic nature of the processes makes impossible a deterministic forecast of both the magnitude of the processes and their effects, threshold values can be of great importance and usefulness. Thresholds can be simple (e.g., the threshold of rainfall intensity that might separate stratiform from convective rainfall) or complex and multi-variate (e.g., the threshold for damaging snow-melt flooding, or the threshold for intense hillslope erosion in an agricultural field). They can be useful for real-time forecasts based on simple thresholds on rainfall data (e.g., activation of mass movements such as landslides, debris flow, rill and inter-rill erosion, etc.), for the adoption of satellite data in the management of ground actions (e.g., values of the satellite indexes to be used in irrigation management), for distinguishing among water flow regimes, among other applications.

Co-organized by NH1
Convener: Sanjaykumar Yadav | Co-conveners: Ramesh Teegavarapu, Biswa Bhattacharya, Rashmi YadavECSECS, Francesca Todisco, Vincenzo Pampalone, Lorenzo Vergni
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Wed, 28 Apr, 09:00–10:30

Chairpersons: Sanjaykumar Yadav, Ramesh Teegavarapu, Francesca Todisco

5-minute convener introduction

Ruijie Liang et al.

Stormwater infrastructure will require investments in the order of $100s of millions per local government area to maintain current levels of urban flood protection. This investment is likely to increase in the future as a result of the impact of climate change, population growth and increased urban densification. Traditional solutions aimed at increasing the capacity of stormwater systems have been directed towards pipe upgrades. An alternative approach is the use of smart storages, which have the following advantages:

  • Extension of the lifespan of existing stormwater systems
  • Provision of water supply
  • Reduction in pollution levels in receiving waters.

The development of smart technologies enables the use of real-time control for increasing the effectiveness of storages. If forecasts of the timing and magnitude of impending rainfall events are available, storage outlet controls can be optimised to release stored water prior to and during the rainfall event to enable the peak flows to be reduced. In addition, by jointly controlling the outflows from multiple, distributed storages, rather than using a single storage or controlling multiple storages independently, coincident flood peaks from different sub-catchments can be minimised, further reducing peak flows at critical locations.

In this study, the potential benefits of real-time time control for distributed storages are compared with a system that uses storages without real-time controls. The impacts were assessed using a two-storage system, which is modelled using the software package SWMM with the real-time control schemes of the storages being optimised using a genetic algorithm. The case study was conducted for two storage sizes (2 and 10 m3) under a wide range of design rainfall conditions, with storm durations ranging from short (30mins) to long (24hrs), and annual exceedance probability ranging from frequent (50%AEP), to rare (1%AEP) for three different Australian climates (sub-tropical/Mediterranean). This results in a total of 75 different combinations. Results show there is a generic relationship between percentage peak flow reduction and the ratio of storage size to storm runoff volume irrespective of location and storm characteristics. The benefits of real-time control of smart storage systems identified were:

  • Significant peak flow reductions ranging from 85% (for a larger storage size of 80% of storm volume) to 35% (for small storages size of 15% of runoff volume).
  • Importantly, real-time control of storages significantly outperforms storages without real-time control, with additional peak flow reduction of between 35% to 50%.

These results highlight the potential for using distributed storages for mitigating urban flooding, even for extreme events. The potential benefits of smart storages in more realistic cases studies (uncertain rainfall forecasts and larger scales) are also discussed.

How to cite: Liang, R., Thyer, M., Maier, H., Di Matteo, M., and Dandy, G.: Potential benefits of real-time control to reduce urban flooding using distributed smart stormwater storage systems, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8158, https://doi.org/10.5194/egusphere-egu21-8158, 2021.

Joao Guilherme Caldas Steinstraesser et al.

We present a new multi-OS platform named SW2D-LEMON (SW2D for Shallow Water 2D) developed by the LEMON research team in Montpellier.

SW2D-LEMON is a multi-model software focusing on shallow water-based models. It includes an unprecedented collection of upscaled (porosity) models used for shallow water equations and transport-reaction processes. Porosity models are obtained by averaging the two-dimensional shallow water equations over large areas containing both a water and a solid phase. The size of a computational cell can be increased by a factor 10 to 50 compared to a 2D shallow water model, with CPU times reduced by 2 to 3 orders of magnitude. Applications include urban flood simulations as well as flows over complex topography. Besides the standard shallow water equations (the default model), several porosity models are included in the platform: (i) Single Porosity, (ii) Dual Integral Porosity, (iii) Depth-dependent Porosity. Various flow processes (friction, head losses, wind, momentum diffusion, precipitation/infiltration) can be included in a modular way by activating specific execution flags.

Classical input data are required by SW2D-Lemon software: mesh file (several formats available) with elements having an arbitrary number of edges; geometric and hydraulic parameter fields: bathymetry, porosity, Boussinesq/Coriolis momentum distribution coefficient, friction coefficient fields, etc.; initial and boundary conditions (several types available) and forcings (wind, rainfall).

SW2D can be used in two ways: in command-line mode or via a dedicated graphic user interface (GUI). Both features are available on all Windows, MacOS and Linux operating systems. SW2D is available under three license modes: Academic Research (source code, developer manual and basic configurations are freely available in the framework of a scientific partnership with the LEMON team), Industry and education.

Various real-world test cases will be presented to illustrate the potential of SW2D and the contribution of porosity based models to urban flood modelling:

    - Flood simulation on Sacramento city induced by the breach of a dike;
    - Marine submersion on Valras Plage;
    - Fast rain flood on the Abidjan Riviera district.


How to cite: Caldas Steinstraesser, J. G., Delenne, C., Finaud-Guyot, P., Guinot, V., Kahn Casapia, J. L., and Rousseau, A.: Upscaled shallow water modeling with SW2D-Lemon for urban flood simulation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8212, https://doi.org/10.5194/egusphere-egu21-8212, 2021.

Heiko Apel et al.

Urban flash floods caused by heavy convective precipitation pose an increasing threat to communes world-wide due to the increasing intensity and frequency of convective precipitation caused by a warming atmosphere. Thus, flood risk management plans adapted to the current flood risk but also capable of managing future risks are of high importance. These plans necessarily need model based pluvial flood risk simulations. In an urban environment these simulations have to have a high spatial and temporal resolution in order to site-specific management solutions. Moreover, the effect of the sewer systems needs to be included to achieve realistic inundation simulations, but also to assess the effectiveness of the sewer system and its fitness to future changes in the pluvial hazard. The setup of these models, however, typically requires a large amount of input data, a high degree of modelling expertise, a long time for setting up the model setup and to finally run the simulations. Therefor most communes cannot perform this task.

 In order to provide model-based pluvial urban flood hazard and finally risk assessments for a large number of communes, the model system RIMurban was developed. The core of the system consists of a simplified raster-based 2D hydraulic model simulating the urban surface inundation in high spatial resolution. The model is implemented on GPUs for massive parallelization. The specific urban hydrology is considered by a capacity-based simulation of the sewer system and infiltration on non-sealed surfaces, and flow routing around buildings. The model thus considers the specific urban hydrological features, but with simplified approaches. Due to these simplifications the model setup can be performed with comparatively low data requirements, which can be covered with open data in most cases. The core data required are a high-resolution DEM, a layer of showing the buildings, and a land use map.

The spatially distributed rainfall input can be derived local precipitation records, or from an analysis of weather radar records of heavy precipitation events. A catalogue of heavy rain storms all over Germany is derived based on radar observations of the past 19 years. This catalogue serves as input for pluvial risk simulations for individual communes in Germany, as well as a catalogue of possible extreme events for the current climate. Future changes in these extreme events will be estimated based on regional climate simulations of a ΔT (1.5°C, 2°C) warmer world.

RIMurban simulates the urban inundation caused by these events, as well as the stress on the sewer system. Based on the inundation maps the damage to residential buildings will be estimated and further developed to a pluvial urban flood risk assessment. Because of the comparatively simple model structure and low data demand, the model setup can be easily automatized and transferred to most small to medium sized communes in Europe and even beyond, if the damage estimation is modified. RIMurban is thus seen as a generally appölicable screening tool for urban pluvial flood risk and a starting point for adapted risk management plans.

How to cite: Apel, H., Vorogushyn, S., Farrag, M., Dung, N. V., Karremann, M., Kreibich, H., and Merz, B.: RIMurban – A generalized GPU-based model for urban pluvial flood risk modelling and forecasting, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2985, https://doi.org/10.5194/egusphere-egu21-2985, 2021.

Giovanna Grossi et al.

Flood risk management is one of priorities set by the European Union to protect population and assets. In a very recent report of the European Environment Agency dealing with urban adaptation to climate change (EEA, 2020), extreme weather events (heatwaves, heavy precipitation, flooding and droughts) are expected to cause the most pronounced impacts in European cities, besides vector‑borne diseases. Italian regions are taclking flood risk management also by setting regulations on the runoff production in urban areas.

According to a recent regulation approved by Regione Lombardia municipalities are requested to prepare the Hydraulic Risk Management Plan, including measures to ensure compliance with the principle of the ‘hydraulic’ and ‘hydrological’ invariance for the urban area, in which runoff volumes generated by an intense meteoric event must remain unchanged or at least must be limited. The idea arises from the need to manage the rainwater drainage in urban contexts, where the existing sewerage system has been designed based on an inadequate return time period.

The planning activity requires a modelling framework accounting for both the open channel network (mainly addressing irrigation demand) and the sewer pipe network. While separate hydraulic models might help the management provided by separate authorities, an integrated model is ensuring a complete representation of the system hydrodynamics. This type of model is characterized by a much more complex structure which requires greater data accuracy for the construction and calibration of the model in order to obtain realistic results.

Some critical issues are being presented for Brescia, a town located in Northern Italy, at the foothills of the Alps.  Potential flood risk is linked to the dense historical irrigation and drainage channels network that cross the urban area from north to south and the old city centre. Critical areas are those hosting the post-war urban development where the waterways have been uncovered and covered in a chaotic and uncontrolled way, in some cases even under houses and other buildings.

How to cite: Grossi, G., Berteni, F., Dada, A., and Leoni, P.: Combining open channel and sewer system network modelling to develop the Hydraulic Risk Management Plan for Brescia (Northern Italy), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14655, https://doi.org/10.5194/egusphere-egu21-14655, 2021.

Rashmi Yadav and Sanjay M. Yadav

In the era of increased extreme events, the assessment and management of the consequences become a necessity. Since the past twenty years floods affected more than two billion people worldwide. Urbanisation, overpopulation, insufficient drainage systems, spatio-temporal variation of rainfall events, climate change, unplanned settlements over the coastal areas and flood-prone areas can be few of the causes of floods. 1D, 2D and 1D/2D coupled hydro-dynamic models are developed to study such flood events. Some of the popular models used for the analysis of floods are HEC RAS, MIKE 11, MIKE 21, MIKE Urban, SWMM, SOBEK, FLO-2D and SWAT. These models use implicit and explicit finite difference schemes are used for solving one and two-dimensional hyperbolic partial differential equations. The data requirements and methodology for the development and assessment of modelling extreme flood events across the globe is highlighted and presented in the paper. Importance of developing the framework beforehand for optimising of model suitability, availability of data and objective function is reviewed. The present study discusses important 1D/2D coupled models case studies used for flood inundation studies.

Keywords: Floods, extreme events, modelling, HEC RAS, shallow water equations.

How to cite: Yadav, R. and Yadav, S. M.: Assessment of 1D/2D coupled model for prediction of flood inundation, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4881, https://doi.org/10.5194/egusphere-egu21-4881, 2021.

sejal chandel and suvarna shah

In recent study, Gujarat has become one of the India’s most urbanized state, causing severe flash flooding. The Sabarmati river is one of the major west-flowing rivers in India and biggest river of north Gujarat.Urbanization should meet the population’s need by enlargement of paved areas, which has unusually changed the catchment’s hydrological and hydraulic characteristic. Therefor, the frequency of flash flooding in Sabarmati river has been increased. The Sabarmati river basin experienced eight times devastating flooding coendition between 1972 to 2020.Among which July 2017 flooding event breakdown a 112 years old record of 1905. The Dharoi dam and Wasna barrage on Sabarmati river and surrounding district Kheda, Mehsana, Gandhinagar, Ahmedabad received a huge rainfall caused anomalous inflow to tributary which forced the dam authorities to release huge discharge in short duration which leads to flooding. The Sabarmati riverfront of Ahmedabad had been going under water for five days due incessant rainfall in the city that leads to swelling of the Sabarmati river in 2017. In order to determine extent of Inundation, Hydrodynamic Model HEC-RAS(5.0.6) with Arc GIS was used. Various scenarios were run with HEC-RAS to study the impact of flow simulation on flood inundation(with & without riverfront project). The simulated flood depths have been compared with actual depths obtained at gauging station, which were collected from Government authorities. Ultimately, the analysis was used to create maps for different return periods with RAS Mapper and ArcMap that visually show the reach of the floodplains, illustrating the affected areas. Results demonstrate the usefulness of  modelling system to predict the extent of flood inundation and thus support analyses of management strategies to deal with risk associated with infrastructure in an urban setting.

How to cite: chandel, S. and shah, S.: Integrating 1D-2D Hydrodynamic Model For Sabarmati Upper River Basin With Special Reference to Ahmedabad City Area, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-12680, https://doi.org/10.5194/egusphere-egu21-12680, 2021.

Yasir Abduljaleel

Evaluate the Use of Wetland Performance Includes Multi-Scale Tests to Emphasize the Runoff Control Volume Based on Climate Change Adaptation Strategy

Yasir Abduljaleela, *

a Department of Civil and Environmental Engineering Washington State University

* Corresponding Author: Yasir.abduljaleel@wsu.edu, h3h111@gmail.com



Climate change has affected environmental and weather hazards, such as flooding, stormwater, and droughts. Extreme storms have wide and heavy impacts on lives and property. Nowadays, according to the urbanization phenomena, there are different changes over the surfaces. Indeed, the surfaces are mainly covered by impermeable materials, such as creating buildings, concrete, asphalt, etc., so these elements can intensify the water movements. In this regard, researchers have concentrated on evaluating LID (Low Impact Development) hydrological performance and hydraulic behavior on flooding in the last years. Therefore, assessing the performances of the wetland under climate change conditions can proved to be a robust solution to emphasize the runoff control volume based on the climate change adaptation strategy. In this study, we assessed the performance of wetlands by simulating the runoff module with the original scenario considering no wetlands implementation to calculate the original runoff volume. Subsequently, the drainage model will be simulated in scenarios with wetlands controls to get the adapted runoff volume and achieving the desired runoff mitigation and reduction through applying the Stormwater Management Model (SWMM) to an urban watershed. The study area is located at the Boeing Commercial Airplane, which is on the southern shore of Lake Washington, within the City of Renton, Washington. Downstream analysis was conducted considering the natural point-of-discharge is a wetland that eventually drains to Springbrook Creek located about ¼ mile from the southeast corner of the study area. The Cedar River's facility is bordered to the west, and Logan Avenue to the east, and surrounding land use is predominantly commercial, industrial, and retail. The observed runoff data (1995–2014) from the situ gauging station were used for calibration and validation. The calibration period for long time-series is from 1995 to 2008, and the validation period is 2009–2014. The result shows that the NSE coefficients of the parameter sets with the best simulation of the Watershed dynamics calibration and validation periods are 0.73 and 0.71. Also, we concluded that the wetland provides better amounts of peak flow reduction. The selection of SWMM parameters for calibration can be evaluated the sensitivity of SWMM calibration parameters, and the result revealed that the parameters conduit CN, percent zero, imperviousness, and sub-catchment width have relatively significant effect.

 Keywords: Keywords: Wetlands, Hydrology, Climate change, SWMM; Hydrological Model; Calibration model, Sensitivity Analysis.

How to cite: Abduljaleel, Y.: Evaluate the Use of Wetland Performance Includes Multi-Scale Tests to Emphasize the Runoff Control Volume Based on Climate Change Adaptation Strategy , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-8143, https://doi.org/10.5194/egusphere-egu21-8143, 2021.

Shahin Khosh Bin Ghomash and Daniel Bachmann

Precipitation time series with high spatial and temporal resolutions are the driving force for hydrodynamic modelling of floods. Spatially-uniform precipitation correlated to a certain return period which typically is derived based on point rainfall records have been used for flood risk evaluation. This is mainly due to reasons such as limited observed data, low-density measuring networks or merely the inherent simplicity of using spatially-uniform rain storms in flood simulations. While the use of such rainfalls is convenient, spatially-uniform design storms tend to neglect the impact of rain spatial variability on the hydrological response of the hydrological catchment. Additionally, extreme storm events with high temporal and spatial variability are predicted to occur more often as a result of climate change.

In this work, we study the extent spatially explicit precipitation can affect flooded areas, water levels and surface flow generation in catchment areas in flood modelling. Moreover, the influence of rainfall spatial resolution is also taken into account. This is achieved by means of physically-based, spatially explicit surface flow simulations using the tool ProMaIDes (2021), a free software for risk-based evaluation of flood risk mitigation measures. Precipitation data is generated based on the Poisson distribution and furthermore spatially interpolated in different resolutions using interpolation methods such as the Inversed Distance Squared method and Kriging.

Our study area is the Kan river catchment located in the province of Tehran (Iran) with a total area of 836 km², which has experienced multiple flooding events in recent years. Due to its semi-arid climate and steep topography, the area has high potential for flash flood occurrence as a result of high intensity precipitation.

The results of this study show a range of possible magnitudes of influence of rainfall spatial variability on the catchment´s runoff response. The resulting flood maps highlight the importance of rainfall spatial-temporal variability in the estimation of flood likelihood in urban catchment areas. Moreover, the flood maps resulting from spatially explicit rain signals provide a more comprehensive assessment of flooding in contrast to the spatially-uniform rainfall events, which allows for better flood risk mitigation decisions.

ProMaIDes (2021): Protection Measures against Inundation Decision support. https://tinyurl.com/promaides77 (last access 11.1.2021)

Acknowledgment: This work is part of the BMBF-IKARIM funded project HoWaMan (Sustainable Strategies and Technologies for Flood Risk Management in Arid and Semi-arid Areas)

How to cite: Khosh Bin Ghomash, S. and Bachmann, D.: Effects of rainfall spatial-temporal variability on flash flood modelling, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2804, https://doi.org/10.5194/egusphere-egu21-2804, 2021.

Mohamedmaroof Shaikh et al.

Floods are among the severe weather disasters that cause catastrophic damage to surroundings and adversely impact populations. This study aims to create a one-dimensional (1D) hydraulic model using HEC-RAS for the Rel River in Banaskantha, Gujarat, India. The model has been developed for the extreme flood event of July 2017. A total of hundred cross-sections have been used as geometric data. The peak discharge of 3355 m3/s and the river slope has been applied as upstream and downstream boundary conditions. The model has been calibrated and validated using observed water depth at Railway bridge and Highway bridge. Critical cross-sections have been identified using the 1D hydraulic model. Eight out of the hundred cross-sections were safe for a flood discharge of 3355 m3/s. The villages at high flood risk are identified for this discharge. To mitigating floods, the construction of a retaining wall or levees is recommended to protect these villages. This study can help a disaster management strategy for the cities and town in the River’s vicinity.

How to cite: Shaikh, M., Yadav, S., and Manekar, V.: Hydraulic modelling of extreme flood event of semi-arid river basin, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10218, https://doi.org/10.5194/egusphere-egu21-10218, 2021.

Prem Lal Patel et al.

The prediction of total and peak streamflows are essential for effective management of water resources systems. A data-driven approach, Model Tree (MT), is applied to predict daily streamflows for a tropical river basin in India. The Tapi River drains a total area of 65,225 km2, wherein more than 20 million people are directly or indirectly dependent on it for their water and food requirements. The MT approach executes piece-wise linearization of a non-linear process for the input parameter space and develops linear regression models for each sub-space. The large-scale oceanic-atmospheric oscillations, such as El Niño-Southern Oscillation (ENSO), exert considerable influence on the hydroclimatic conditions across the globe. Based on the Oceanic Niño Index, the warm and cool phases of ENSO are identified as El Niño and La Niña, respectively. It is found that the El Niño and La Niña are associated with drier and wetter than normal conditions respectively across the Tapi basin. Hence, the hypothesis that incorporation of climate variability information would help in enhancing the predictive performance of the model is being tested. A daily-time step model for streamflow prediction is developed considering various hydrometerological inputs observed for the period 1975-2013 to predict streamflows at the catchment outlet. Additionally, two separate models, viz., El Niño- and La Niña-specific models, are developed considering the observed variables corresponding to these phases, and their skill of prediction with respect to the overall model is evaluated. The evaluation of the developed models is further carried out through a suite of statistical error and performance indices, and inferences are drawn.

How to cite: Patel, P. L., Sharma, P., and Teegavarapu, R.: Assessing the utility of climate variability information in streamflow forecasting, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14633, https://doi.org/10.5194/egusphere-egu21-14633, 2021.

Alessandra Vinci

The identification of thresholds of simple and practical determination capable of operating a separation between non-erosive and erosive rains has considerable importance from both a practical and scientific point of view. It allows reducing the work necessary to manage and process erosive events and provides useful information to determine the triggering of erosion processes of different entities and nature and consequently to understand their dynamics better.

In previous work, Todisco et al. (2019) analyzed 528 rainfall events from 2008 to 2017 at the Masse experimental station (central Italy) to define and evaluate several thresholds of rainfall characteristics able to classify non-erosive and erosive events. Each threshold value was obtained by imposing that the long-term erosivity of the events above the threshold is equal to the long-term erosivity of all erosive events observed. The evaluation criteria of the thresholds were mainly based on the percentage of correct selections, CSI (number of erosive events selected to the total number of erosive events) and the percentage of wrong selection, WSI (number of non-erosive events to the total number of events selected). The analysis was performed on the basis of a 5-min rainfall dataset.

This work aims to evaluate the influence of the rainfall data acquisition time on the thresholds (both in terms of value and accuracy). For this purpose, the Masse experimental station's rainfall dataset was aggregated at a 30-min time interval and then subjected to the same analysis carried out in the previous study. The 30-min time interval has a practical interest since it represents the typical time interval of the Regional Hydrographic Service data.

The results indicate that some of the best thresholds identified on the basis of the 5-min database are the best also working on the 30-minute data, with small performance variations (CSI ranging between 55 to 75% and WSI  between 15 to 30%). Among the best thresholds can be mentioned: the total event rainfall, Pe (14.4 and 15.2mm for the 5-min and 30-min database, respectively), the kinetic energy of the event, E (2.4 and 2.7MJ ha−1), the rainfall duration above a pre-determined intensity, Drun (0.3 and 0.5h), and the Maximum rainfall amount in a rain shower, P_max_burst (7.6 and 10.2mm). It is evident that the threshold value tends to slightly increase, passing from a 5-min to a 30-min rainfall dataset. Moreover, some thresholds considered effective working on the 5-min dataset, obtained very poor performance on the 30-min database. This happened for some rainfall variables related to the number of runs or showers during the event, such as the Maximum rainfall depth cumulated from the start of the rainfall event to the rain shower, Max_P_pre_burst. This poor performance depends on the fact that in the 30-min dataset, the internal structure of the event hyetograph is smoothed and not able to provide relevant information as in the 5-min dataset.

The best thresholds identified from the 30-min rainfall dataset will be used in a regional analysis aimed to map the spatial variability of the return periods of erosive events.

How to cite: Vinci, A.: Practical rainfall thresholds for separating non-erosive and erosive storms , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14843, https://doi.org/10.5194/egusphere-egu21-14843, 2021.

Lorenzo Vergni and Francesca Todisco

As many other natural hazards, the crop water stress has a typical multivariate nature, i.e., it is characterized by the contemporary presence of multiple characteristics correlated with each other (e.g., duration, severity, peak, areal extension, etc.). In this situation, a risk analysis based on a traditional univariate approach is inadequate for a complete interpretation of the phenomenon. Copula models can effectively solve the probabilistic joint analysis of two or more random correlated variables. Copulas are functions that join univariate probability distributions to form multivariate probability distributions, modelling the dependence structure among random variables independently of their marginal distributions. This work illustrates how the joint probability and return periods of the Duration (D, days) and Severity (S, mm) of the crop water stress can be used to obtain information useful in defining drought management strategies. The case study refers to some localities of central Italy and olive crops, widely cultivated in the region considered, mainly under rainfed conditions. In the case study, 65 years of daily precipitation and maximum and minimum temperature were used to obtain a rough estimation (following the FAO 56 guidelines) of the daily soil water dynamics (SWt), available for the olive crops at each locality considered. Then, by applying the Theory of Runs to SWt, with a threshold equal to the crop critical point (SWcrit), the water stress events were identified and characterized by their D (days) and S (i.e., the cumulative evapotranspiration deficit, mm) for each locality. A 2-parameter Gamma distribution was fitted to both D and S, whilst a Frank copula modelled their dependence structure. These joint probability models were then used to quantify the return periods associated with specific user-defined critical threshold events; in this work, the critical threshold events were simply defined on the basis of a statistical approach (e.g., combining the values of D and S corresponding to the 90th percentiles). However, in a real case application, the critical thresholds could arise from considerations on the crop impacts deriving from specific D and S values. Despite the modest areal extension of the case study, results show that the climatic conditions significantly affect the bivariate return period of the critical threshold events, which varies between 3 and 15 years in the localities considered. We also evaluated the return time increment due to some drought management strategies, such as the application of rescue irrigation. For example, the application of an irrigation volume of 50 mm in the mid of the growing season is able to produce a relevant change of the return period, thus varies between 5 and 77 years.


How to cite: Vergni, L. and Todisco, F.: Joint return periods of critical thresholds of duration and severity of crop water stress in some areas of central Italy, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-14925, https://doi.org/10.5194/egusphere-egu21-14925, 2021.

Aliva Nanda and Sumit Sen

The non-linear behaviour of soil moisture and rainfall influences the hillslope runoff generation mechanism and its thresholds. Inherent complexities of the hydrological processes at micro- to macro-scale hydrological systems need to be studied for identifying dominant connections. In this context, complex network theory is a beneficial tool to deal with all kinds of hydrological connections. To understand the practical implication of complex network theory and to explore out the runoff thresholds of infiltration-excess hillslope, we have selected two experimental hillslopes under two different landuse conditions i.e., agro-forested (AgF) and Grassed (GA) hillslopes. The hillslopes are situated at the Lesser Himalayan region of India. These are instrumented with ten soil moisture and water level sensors for capturing spatio-temporal variation of soil moisture and hillslope runoff at the outlet, respectively. After analyzing 59 rainfall events, we found that runoff generation in GA hillslope is significantly triggered when the 5-min peak rainfall intensity and initial soil moisture conditions exceed 50 mm/h and 0.25 m3/m3, respectively. The runoff generation in AgF hillslope is triggered when the 5-min peak rainfall intensity and initial soil moisture condition exceeds the mark of 12 mm/h and 0.20 m3/m3, accordingly. High intensity with very less duration event cannot generate any runoff at hillslope outlet; however, a low intensity with long duration (> 15h) event could generate small runoff volume at both the hillslopes. After analyzing the runoff threshold, we used complex network theory to understand the connection between runoff and soil moisture for different runoff generating groups. Further, events having high rainfall intensity and high soil moisture condition show the more robust network connectivity between the runoff and the soil moisture points and moderate connectivity among the soil moisture stations. Primarily, in high-intensity events, the strongly connected soil moisture and the runoff nodes represents less runoff from that zone in an infiltration-excess dominated hillslope. The low-intensity rainfall of both the hillslope shows stronger network connectivity among the soil moisture, and the weak network connectivity between the runoff points and the soil moisture points as the events result in less runoff. Networks often contain clusters among the nodes and to measure the local density of these nodes, we calculated the global clustering coefficient (GCC). The GCC of all the selected events declines with an increase in correlation threshold (CT) values which indicate a decrease in network connectivity between the nodes for higher CT. For CT≥ 0.8, the GCC values for the low-intensity events were higher than the high-intensity events, as the soil moisture networks are strong and dense during low-intensity events for high CT values. This study shows the first-time application of network theory to understand the linkage between network topology and hillslope runoff behaviour. However, we encourage the researchers to explore similar approaches in saturation-excess dominated hillslopes where the twining between soil moisture and runoff are different.

How to cite: Nanda, A. and Sen, S.: Exploring Hydrological Connections: A Threshold and Complex Network Based Approach , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7526, https://doi.org/10.5194/egusphere-egu21-7526, 2021.

Alessio Nicosia and Vito Ferro

Rills are small, steep sloping and ephemeral channels, shaped in soils, in which shallow flows move. Rill erosion strictly depends on hydraulic characteristics of the rill flow and for this reason flow discharge Q, rill width w, water depth h, mean flow velocity V, and friction factor are required to model the rill erosion process.

Erosive phenomena strictly depend on the attitude of the soil particles to be detached (detachability) and to be transported (transportability). These properties are affected by soil texture and influence the sediment load G to be transported by flow. The actual sediment load depends on the transport capacity Tc of the flow, which is the maximum amount of sediment, with given sizes and specific weight, that can be transported by a flow of known hydraulic characteristics.

According to Jiang et al. (2018) the hydraulic mechanisms of soil erosion for steep slopes are different from those for gentle slopes. Recent research on Tc equations exploring slopes steeper than 18% (Ali et al., 2013; Zhang et al., 2009; Wu et al., 2016) established that Tc relationships designed for gentle slopes (<18%) are unsuitable to be applied to steep slopes (17–47%). Also Peng et al. (2015) noticed that <<there has been little research concerning rill flow on steep slopes (e.g. slope gradients higher than 10°)>>. In other words, the slope of 18% could be used to distinguish between the “gentle slope” and the “steep slope” case for the recognized difference in hydraulic and sediment transport variables.

The applicability of a theoretical rill flow resistance equation, based on the integration of a power velocity distribution (Barenblatt, 1979; 1987), was tested using measurements carried out in mobile rills shaped on plots having different slopes (9, 14, 15, 18, 22, 24, 25 and 26%) and soil textures (clay fractions ranging from 32.7% to 73% and silt of 19.9% – 30.9%), and measurements available in literature (Jiang et al. (2018), Huang et al. (2020) and Yang et al. (2020)).

The Darcy-Weisbach friction factor resulted dependent on slope, Froude number, Reynolds number and CLAY and SILT percentages, which represent soil transportability and detachability, respectively. This theoretical approach was applied to two different databases distinguished by the slope threshold of 18%. The results showed that, for gentle slopes (< 18%), the Darcy-Weisbach friction factor increases with slope, CLAY and SILT content. Taking into account that for gentle slopes the hydraulic characteristics limit the transport capacity, for this condition Tc and the sediment load G are both limiting factors.

For steep slopes (> 18%), the flow resistance increases with slope and the ratio between SILT and CLAY percentage. Steep slopes determine high values of the transport capacity, which is consequently not a limiting factor. Thus, in this condition the actual sediment load is determined exclusively by the ratio between SILT and CLAY percentage. In other words, the only limiting factor for a steep slope condition is the sediment which can be transported (i.e. the sediment load G), affected by its soil detachability and transportability.

How to cite: Nicosia, A. and Ferro, V.: Slope threshold in rill flow resistance, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10212, https://doi.org/10.5194/egusphere-egu21-10212, 2021.

Dexin Gao et al.

Understanding the constraints on light-use efficiency (LUE) created by high evaporative water demand (vapor-pressure deficit; VPD) and restricted water supply (soil moisture content; SMC) is crucial for understanding and simulating vegetation productivity, particularly in arid and semi-arid regions. However, the relative impacts of VPD and SMC on photosynthesis are unclear, as we lack a mechanistic understanding of them and their interactions. In this study, we quantified the relative roles of VPD and SMC in limiting LUE and analyzed the interactions among VPD, SMC, and LUE in China’s Heihe River Basin using data from CO2 and water flux stations and weather stations along a climatic gradient. We found a threshold for VPD’s restriction of LUE; above the threshold, LUE decreased at only 3.6% to 23.1% of the rate below the threshold. As SMC decreased, however, the VPD threshold increased, and the reduction of LUE caused by VPD decreased significantly, which is more than half lower than that in moister regions. Therefore, both VPD and SMC played essential roles in LUE limitation and the resulting reduction of photosynthesis caused by water stress. A threshold also existed for heat flux and the correlation between SMC and LUE; the strength of the correlation first decreased and then increased with increasing VPD. Our results clarified the relative impacts of VPD and SMC on photosynthesis, and can improve simulation and prediction of plant productivity.

How to cite: Gao, D., Wang, S., Li, Z., Wei, F., Chen, P., Fu, B., Song, S., and Wang, Y.: Restriction threshold of vapor pressure deficit for light use efficiency varied with soil water content, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-13941, https://doi.org/10.5194/egusphere-egu21-13941, 2021.

Pasquale Marino et al.

Operational early warning systems for rainfall-induced landslides (LEWS) usually rely on simple empirical thresholds based on the statistical analysis of either triggering rainfall characteristics, e.g. intensity and duration (Guzzetti et al., 2007). The main pro of this simplified approach is that it requires only rainfall records, at the desired spatial and temporal resolution, and a database of landslides with known time and location. The effect of the hydrologic conditions of the slopes prior the onset of the triggering rainfall is usually neglected, limiting the performance of the LEWS, which often give rise to false and missing alarms. To address this issue, antecedent precipitation is sometimes included in the definition of the threshold, but the identification of the antecedent precipitation duration is doubtful, as this approach neglects non-linear hydrological processes affecting slope response. Hydro-meteorological thresholds, linking a variable accounting for the antecedent hydrologic conditions with a characteristic of the triggering rainfall, have been recently proposed (Bogaard and Greco, 2018).

In this study, hydro-meteorological thresholds for landslide prediction are identified for a slope in southern Italy, characterized by an unsaturated pyroclastic soil cover laying upon fractured limestone bedrock and subject to rainfall-induced shallow landslides. To this aim, a synthetic 1000 years long hourly point rainfall record is generated with the Neyman-Scott rectangular pulse stochastic model, calibrated thanks to available measured rainfall. The response of the slope to the synthetic rainfall record is simulated by means of a physically-based model, which couples unsaturated flow in the soil cover with a temporary perched aquifer in the limestone bedrock, and allows estimating all the terms of slope water balance (Greco et al., 2018). The stability of the slope is eventually assessed under the infinite slope hypothesis, allowing the identification of the occurrence of landslides.

The obtained synthetic dataset of rainfall and hydrologic variables has been exploited for the definition of hydro-meteorological thresholds. All the combinations of hydrologic variables with triggering rainfall height have been analyzed with several clustering techniques, so to identify the most effective combinations for landslide predictions.



Bogaard TA, Greco R (2018). Invited perspectives: Hydrological perspectives on precipitation intensity-duration thresholds for landslide initiation: proposing hydro-meteorological thresholds, Nat Hazards Earth Syst Sci, 18: 31–39.

Greco R, Marino P, Santonastaso GF, Damiano E (2018). Interaction between Perched Epikarst Aquifer and Unsaturated Soil Cover in the Initiation of Shallow Landslides in Pyroclastic Soils, Water, 10: 948.

Guzzetti F, Peruccacci S, Rossi M, Stark CP (2007). Rainfall thresholds for the initiation of landslides in central and southern Europe, Meteorol Atmos Phys, 98: 239–267.

How to cite: Marino, P., Giudicianni, C., Santonastaso, G. F., and Greco, R.: Identification of hydro-meteorological thresholds for rainfall-induced landslide prediction with clustering techniques, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-356, https://doi.org/10.5194/egusphere-egu21-356, 2020.

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