HS4.7

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.

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.

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.

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.

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

Yasir Abduljaleel^{a, *}

^a Department of Civil and Environmental Engineering Washington State University

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

Abstract

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.

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, D_run (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.

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 90^th 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.

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.

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 T_c 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 T_c equations exploring slopes steeper than 18% (Ali et al., 2013; Zhang et al., 2009; Wu et al., 2016) established that T_c 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 T_c 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.

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.