Water, climate, food and health



Hydroclimatic conditions and the availability of water resources in space and time constitute important factors for maintaining an adequate food supply, the quality of the environment, and the welfare of inhabitants, in the context of sustainable growth and economic development. This session is designed to explore the impacts of hydroclimatic variability, climate change, and the temporal and spatial availability of water resources on: food production, population health, the quality of the environment, and the welfare of local ecosystems. We particularly welcome submissions on the following topics:

- Complex inter-linkages between hydroclimatic conditions, food production, and population health, including: extreme weather events, surface and subsurface water resources, surface temperatures, and their impacts on food security, livelihoods, and water- and food-borne illnesses in urban and rural environments.
- Quantitative assessment of surface-water and groundwater resources, and their contribution to agricultural system and ecosystem statuses.
- Spatiotemporal modeling of the availability of water resources, flooding, droughts, and climate change, in the context of water quality and usage for food production, agricultural irrigation, and health impacts over a wide range of spatiotemporal scales.
- Intelligent infrastructure for water usage, irrigation, environmental and ecological health monitoring, such as development of advanced sensors, remote sensing, data collection, and associated modeling approaches.
- Modelling tools for organizing integrated solutions for water, precision agriculture, ecosystem health monitoring, and characterization of environmental conditions.
- Water re-allocation and treatment for agricultural, environmental, and health related purposes.
- Impact assessment of water-related natural disasters, and anthropogenic forcings (e.g. inappropriate agricultural practices, and land usage) on the natural environment; e.g. health impacts from water and air, fragmentation of habitats, etc.

Co-organized by CL3.2/NH10/NP8
Convener: George Christakos | Co-conveners: Alin Andrei Carsteanu, Elena Cristiano, Andreas Langousis, Hwa-Lung Yu
vPICO presentations
| Tue, 27 Apr, 09:00–10:30 (CEST)

vPICO presentations: Tue, 27 Apr

Chairpersons: Elena Cristiano, Alin Andrei Carsteanu, Hwa-Lung Yu
Yu-Ting Lin and Yuan-Chien Lin

Air pollution has always been one of the serious issues around the world, not only related to the large-scale climate environment, but also related to local-scale vehicles-caused air pollutants in the city. Generally, diesel-burning vehicles emit NOX, SO2, CO; gasoline burning vehicles emit CO, CO2, NOX respectively. The common air pollutants CO and NOX are widely regarded as the primary traffic-caused air pollutants. Therefore in this study, we take vehicle detector data including car speed, car volume, lane occupy as well as meteorological data and the air pollutants concentration in consider. Firstly, we use the Stepwise Regression Model(SRM) to select the significant factors for the target air pollutants and predict them with multivariate linear regression. Secondly, we also combine Long Short-Terms Memory (LSTM) Model to simulate the highly nonlinear and unstationary complex chemical interaction between air pollutants. In this study we got high model accuracy performance in primary pollutants prediction (CO,NOX) by including the vehicle detector data with both Multivariate linear regression Model and LSTM model which conclude that the vehicle detector data can significantly improve the quality of model prediction. This process select the statistically significant factors of the pollutants, and also establishes a neural network model including traffic, meteorological factors and air quality which contribute to the air pollutants risk management of government agency.

Keywords: traffic pollutants, air quality, stepwise regression, LSTM model

How to cite: Lin, Y.-T. and Lin, Y.-C.: The impact analysis of traffic and meteorological factors on air pollution risk in Taiwan, Taipei City, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7446, https://doi.org/10.5194/egusphere-egu21-7446, 2021.

Shih-Yao Lee, Mengchieh Tsai, and Hwa-Lung Yu

Water scarcity, which is a critical issue worldwide, is exacerbated by geomorphic characteristics and highly uneven spatiotemporal distribution of rainfall in Taiwan. The annual water availability per capita in Taiwan is less than one-fifth of the world average despite the high annual rainfall. Hence, stable water supply and efficient water resources management are challenging tasks for related authorities, and a decision support tool is required for the optimal decision. This study proposes a risk assessment framework for water shortage based upon a dynamic Bayesian network. Standardized precipitation index (SPI), standardized runoff index (SRI) and long-term weather forecasts are included in the framework. Taoyuan, a northern city in Taiwan with rapid growth of population and industries, is particularly vulnerable to water shortage and thereby chosen as our study site.

How to cite: Lee, S.-Y., Tsai, M., and Yu, H.-L.: Integrating drought indices and long-term weather forecasts with a dynamic Bayesian network for assessing water shortage risk – a case study in Taoyuan, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-5753, https://doi.org/10.5194/egusphere-egu21-5753, 2021.

Siti Talitha Rachma and Yuan-Chien Lin

Each year, average of Earth’s temperature rises and the urbanized cities, are warming at a significant rate than the surrounding rural areas. This phenomenon is called Urban Heat Island (UHI). UHI is a consequence of human activities in urban area and it has possibilities to impact weather and climate on regional or global scale. Precipitation is one of the basic hydro-meteorological phenomena that could be affected by UHI trend with thunderstorm as a part of precipitation. As the UHI level rises from year to year, the pattern of precipitation could change. However, this issue is still underdeveloped, thus, this work tries to comprehensively understand the hydrological response to UHI.


This research selects Taipei city as the study area and explores the connection between UHI and precipitation pattern’s change. The data used here are hourly temperature and precipitation data collected from 21 Taipei weather stations collected from Central Weather Bureau (CWB) Taiwan. In order to reveal specific details and trend of non-linear relation from both time domain and frequency, Hilbert-Huang Transform (HHT) is adopted in this study. The HHT results are compared between each station. Later, empirical orthogonal function (EOF) also being used to extract main spatial pattern of precipitation in Taipei city.


The results show that the urbanization in Taipei city contribute to increasing trend of 0.5 – 1 oC in daily UHI and also increase of 27% in the afternoon thunderstorm frequency for this past 20 years. The increase of thunderstorm would result into a bigger rain water flow to the river and a fewer time for it to percolate to the ground. If there are more thunderstorms in the future, it is possible the phenomenon could lead to the lack of groundwater discharge and depletion of groundwater reserve. This result could be utilized in the future to understand more about UHI mitigation and thunderstorm in Taipei.


Keywords: urban heat island, thunderstorm, Hilbert-Huang Transform, empirical orthogonal function

How to cite: Rachma, S. T. and Lin, Y.-C.: An analysis of urban heat island impact toward increasing of afternoon thunderstorm frequency in Taipei, Taiwan, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-10522, https://doi.org/10.5194/egusphere-egu21-10522, 2021.

Catherine Bradshaw, Edward Pope, Gillian Kay, Jemma Davie, Andrew Cottrell, James Bacon, Stewart Jennings, Andrew Challinor, Sarah Chapman, Cathryn Birch, and Susannah Sallu

Sub-Saharan Africa is one of the most food-insecure regions in the world, and is particularly vulnerable to the impacts of extreme climate events and climate change.  To gain a better understanding of the present-day likelihood of extreme seasonal temperature and rainfall events, and their joint occurrence, we apply the UNprecedented Simulated Extremes using ENsembles (UNSEEN) approach  to a large ensemble of high-resolution initialised climate simulations in three countries of Sub-Saharan Africa: Tanzania, Zambia and South Africa. We assess the annual likelihood of unprecedented seasonal temperature and precipitation extremes during the maize growing season (October-April), as key variables for maize productivity , and investigate the large-scale dynamics of the climate system that govern their occurrence. We estimate that there is a 3-4% chance per year of exceeding the present-day seasonal temperature records in the maize growing regions of these countries, and a 1-3.5% chance per year of exceeding the present-day seasonal precipitation records.  Conversely, whilst we find a 2% and 5% chance per year of subceeding the present-day seasonal precipitation records in Zambia and Tanzania respectively, we find a very low chance (0-1% per year) of subceeding the present-day seasonal precipitation records in South Africa.  We also use the large ensemble to investigate the large-scale dynamics of the climate extremes, finding that high temperature extremes tend to be associated with El Niño and positive IOD/SIOD events and low temperature extremes with La Niña and negative IOD/SIOD events. The drivers of precipitation extremes, however, differ between the countries. In South Africa, high (low) precipitation extremes are associated with La Niña (El Niño) events but otherwise the influence on extremes of ENSO, and even more so the IOD/SIOD, is weak or not seen in the ensemble, which invites further investigation. To explore implications for growing maize in these regions, we convert our unprecedented seasonal temperature estimates to daily maximum temperatures and our seasonal precipitation estimates to monthly precipitation indices and compare to climatic thresholds for maize. Combined with projected changes to crop suitability in much of sub-Saharan Africa, our analysis suggests the need for significant adaptation strategies that build food system resilience in the near and longer term.

How to cite: Bradshaw, C., Pope, E., Kay, G., Davie, J., Cottrell, A., Bacon, J., Jennings, S., Challinor, A., Chapman, S., Birch, C., and Sallu, S.: Unprecedented climate extremes in Sub-Saharan Africa and implications for maize production, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15485, https://doi.org/10.5194/egusphere-egu21-15485, 2021.

Huan-Sheng Lin and Yuan-Chien Lin

Groundwater is a reliable freshwater resource in many areas, and it is also an important source of backup water during the drought. Therefore, understanding the characteristics of groundwater resources is crucial and can be explored by building correct hydrogeological models for simulation. To build a perfect hydrogeological model, it is necessary to grasp the correct geological conditions and hydrogeological parameters to establish an effective numerical simulation of groundwater flow. However, geological conditions always contain some uncertainties, which may cause a certain impact on the spatiotemporal changes of groundwater.

Therefore, this study uses the groundwater flow numerical model, MODFLOW, to build the groundwater simulation model. The ideal case and real case at Touqiao Minshiung Industrial Zone in Chiayi is built from 2009 to 2013. The results show that under different hydrogeological parameters, geology, and other conditions, groundwater will have different patterns of variation. The Empirical Orthogonal Function (EOF) method is also used to compare the dominated patterns. The simulation results show the R2 can all reach 0.9 compare with the groundwater real observation data. This study can further explore the drought-resistant availability of groundwater in various regions under different geological conditions, it will help relevant agencies and local governments to better manage groundwater resources.

Keywords: groundwater simulation, MODFLOW, uncertainty, hydrogeology, EOF



*Department of Civil Engineering, National Central University

How to cite: Lin, H.-S. and Lin, Y.-C.: The simulation of groundwater spatiotemporal changes under the uncertainty of hydrogeological conditions, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4770, https://doi.org/10.5194/egusphere-egu21-4770, 2021.

Ting-An Lin and Hwa-Lung Yu

In the applications and studies of subsurface flow, it is necessary to understand the geological lithological composition in the study area. So as to find out the lithological distribution in the study area, many geological spatial statistical methods used to analyze the lithological composition on unsampled points. One of the drawbacks in the traditional two-point based geostatistical methods(e.g., Kriging) is that they based on variogram, thus, inability to handle complex and heterogeneous spatial structures. Furthermore, they produce excessively smooth results. The goal of Multiple-point geostatistics is to overcome the limitations of the variogram. Multiple-point geostatistics is a general statistical framework to model spatial fields with complex structures. It uses training image(TI) instead of variogram to estimate the conditional probability at interpolation location by the observed data and the already interpolated data. Take advantage of TI helps extracting spatial structure information and precisely describing more complex structures. This study focuses on Choshui river alluvial fan, using multiple-point geostatistics method to do simulation of lithological classification.

How to cite: Lin, T.-A. and Yu, H.-L.: Simulation of Lithological Classification in Choshui river Alluvial Fan based on Muliple-point geostastics, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7505, https://doi.org/10.5194/egusphere-egu21-7505, 2021.

Tsai-Ning Weng, Chu-Chun Hsu, and Yuan-Chien Lin


Groundwater, as a vital existence in human life and economic development, is also one of the stable sources of water resources. Therefore, how to properly utilize groundwater becomes a very important issue when faced with water shortages. However, most of the previous literature uses monthly data as the time scale, and usually uses the historical water level data of the area as the only input factor in the modeling process without considering pumping information and rainfall. This shows that the current studies of small-scale data which is based on the use of multiple factors with hydrological mechanisms to explore and predict the groundwater level is still quite lacking.

Therefore, this study proposed a novel framework combining wavelet analysis and deep learning models called wavelet-deep learning models and taking the Daliao area of ​​Kaohsiung as an example. From the historical hourly observation data during 2017/08/23-2020/01/30, including groundwater level, smart pumping measurement, tidal, and meteorological data. After abstracting important features of each factor with groundwater level by wavelet transform, using deep learning algorithms such as recurrent neural networks (RNN) and long short-term memory (LSTM) model to summarize and predict the impact of multiple variable factors on the groundwater level under different time lags. The results of hourly prediction show that the performance of the LSTM model and RNN model are both reliable in which values of the coefficient of determination () were obtained 0.813 and 0.784, respectively.

This study provides a feasible and accurate approach for groundwater level prediction by understanding and predicting different water level changes that may occur in the Daliao area in advance. As a result, the study will be an important reference for groundwater resources management and risk assessment, and achieve the goal of sustainable use of groundwater resources.


Keywords Groundwater prediction, Wavelet transform, Risk assessment, LSTM

How to cite: Weng, T.-N., Hsu, C.-C., and Lin, Y.-C.: Development of risk assessment model for groundwater level by wavelet-deep learning approach with smart pumping data, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4624, https://doi.org/10.5194/egusphere-egu21-4624, 2021.

Ahmad Al Bitar, Taeken Wijmer, Ludovic Arnaud, Remy Fieuzal, Gaetan Pique, and Eric Ceschia

Achieving the United Nations Sustainable Development Goal 2 that addresses food security and sustainable agriculture requires the promotion of readily transferable and scalable agronomical solutions. The combination of high-resolution remote sensing data, field information, and physical models is identified as a robust way of answering this requirement.  Here, we present the AgriCarbon-EO tool, a decision support system that provides the yield, biomass, water and carbon budget components of agricultural fields at a 10m resolution and at a regional scale. The tool assimilates high resolution optical remote sensing data from Copernicus Sentinel-2 satellites into a  radiative transfer model and a crop model. First, the application of a spatial Bayesian retrieval approach to the PROSAIL radiative transfer model provides Leaf Area Index (LAI) with its associated uncertainty. Second, LAI is assimilated into the SAFYE-CO2 crop model using a temporal Bayesian retrieval that enables the calculation of the yield, biomass, carbon and water budgets components with their associated uncertainties. In addition to remote sensing data, input datasets of crop types, weather and soil data are used to constrain the system. The concise weather data is provided from local weather stations or weather forecasts and is used to force the crop model (SAFYE-CO2) dynamics. The soil data are used in two folds. First to better parametrize the soil emissions in the radiative model retrievals and second to parametrise the water infiltration in the soil module of the crop model. The AgriCarbon-EO tool has been optimized to enable the computation of the yield, carbon, and water budget at high spatial resolution (10m) and large scale (100km2). The model is applied over the South-West of France covered by 3 Sentinel-2 tiles for major crops (wheat, maize,  sunflower). The outputs are validated over experimental plots for biomass, yield, soil moisture, and CO2 fluxes located all in the South-West of France. The experimental sites include the FR-AUR and FR-LAM ICOS sites and 22 cropland fields (biomass sampling). The validation exercise is done for the 2017-2018 and 2019-2020 cultural years. We show the added value of the use of high resolution in driving the crop model to take into account the impact of complex processes that are embedded in the LAI signal like vegetation water stress, disease, and agricultural practices. We show that the system is capable of providing the yield, carbon, and water budget of major crops accurately.  At the regional scale, we give global estimates of the carbon budget, water needs, and yields per crop type. We present the impact of intra-plot heterogeneity in the estimation of yield and the annual carbon and water budget showing the added value for high-resolution intra-plot modeling.

How to cite: Al Bitar, A., Wijmer, T., Arnaud, L., Fieuzal, R., Pique, G., and Ceschia, E.: Quantification of Yield, Water, and Carbon budget at intra-field scale using the AgriCarbon-EO tool, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-15413, https://doi.org/10.5194/egusphere-egu21-15413, 2021.

Maria Meirelles

Climate change cause large, long-term impacts on human well-being and adds more pressure to terrestrial and marine ecosystems. The archipelago of the Azores is located in the subtropical region of the North Atlantic and is therefore highly influenced by the North Atlantic Subtropical Anticyclone. As it is an almost stationary high pressure system, whose development and orientation determine the nature and characteristics of the air masses that reach the region. The motivation for this research has two phases; the first was to study the effects of some meteorological parameters (temperature, radiation, wind speed, humidity, precipitation, evaporation, tank temperature and tank level) for the period 2010-2012, on the biodiversity of phytoplankton communities in relation to the abundance of these organisms in the lagoons of Fogo, Furnas, and Sete Cidades of the island of São Miguel - Azores, for the period 2010-2012, using an analysis in Principal  Components, which will allow correlating the meteorological parameters and the abundance of phytoplankton. The phytoplankton and meteorological community data were obtained from the website of the Regional Secretariat for the Environment and Climate Change of the Azores Government. In a second phase, the European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis of the ERA5 project (ECMWF Re-Analyzes) was used for the 1979-2019 observation period and for the Azores region. For this region, the deviations of the surface air temperature, average annual precipitation and climatological extremes were calculated, this referring to the maximum number of consecutive days with precipitation <1 mm, and also, the number of tropical nights using the ERA5 reanalysis series in the period 1979-2019 with reference to 1961-1990. Projections were also estimated up to 2100 and according to scenarios RCP 2.6, 4.5 and 8.5 for the referred parameters. Finally, variations for the end of the century (2071-2100) were estimated with reference to the most recent situation of 1991-2020.

The thermal balance of a lagoon is associated with climatic and meteorological conditions. Much of the biological processes in the lagoons are directly affected by thermal changes in the water, and therefore, indirectly affected by climatic variation. Understanding the interaction between the lagoon-atmosphere system is important to predict the consequences of the effects of climate change on the abundance of phytoplankton. In this study, a positive correlation was verified between precipitation and abundance of Bacillariophyta, Dinophyta and Cryptophyta. From the calculations performed, the average of the models results in an increase in the maximum number of consecutive days with low rainfall (<1mm) from + 0.2 to 4.8 days / year until the year 2100, with a lower abundance of these algae being expected. On the other hand, Cyanophyta, Chlorophyta and Chrisophyta are well correlated with high values ​​of air temperature, lagoon water temperature and solar radiation. Thus, it is estimated an increase in the abundance of these algae, due to the forecasts of several models, that point to an increase in the average annual temperature in this region between 1 and 3 K until the year 2100, with reference to the period from 1961 to 1990.

How to cite: Meirelles, M.: Climate Change and the Evolution of Phytoplankton (Abundance) in Some Lagoons on the São Miguel Island – Azores, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-1621, https://doi.org/10.5194/egusphere-egu21-1621, 2021.

Md. Arif Hossen, Md Salauddin, Asiful Hoque, and Sudip Kumar Pal

Rainwater is considered as a dependable potable and non-potable water source, used for domestic purposes as well as for human consumption in many cases. While it is usually believed that rainwater is safe for drinking purposes, many studies have explored the existence of trace metals in harvested rainwater, which can impose a serious health risk to human beings when present in relatively high concentrations. The concentration of trace elements in atmospheric precipitation including rainwater also provides a good indication of the environmental pollution caused by anthropogenic activities.

Chattogram, located in the south-eastern side of Bangladesh, is the busiest port city and the second-largest city in the country with a population of around 4.5 million people. With the presence of high salinity and arsenic in groundwater and poor quality of surface water in the region, rainwater harvesting is the most sustainable solution to be considered in the water system management for the area, particularly given annual mean precipitation of 2488 mm during the rainy season. In recent years, extensive studies have been carried out on the potential application of different rainwater harvesting systems across the region, but there have been very few studies devoted to the identification of the composition of trace elements in rainwater considering site-specific influences in the trace metal distribution in the rainwater.

The purpose of this study was to investigate the composition and source appointment of trace metals (Fe, Cu, Zn, Pb, Mn, Cr, and Cd) in rainwater in the south-eastern region of Bangladesh. To determine their sources and relative contributions in rainwater, a total of ninety-five rainwater samples were collected in this study from five different locations representing different land-use patterns (industrial, commercial, urban, and sub-urban) within the study area, from June 2018 to October 2019. The collected water samples were analyzed for Fe, Cu, Zn, Pb, Mn, Cr, and Cd using Atomic Absorption Spectrophotometer maintaining standard protocols. The measured trace elements from the collected rainwater samples were then compared with the WHO and Bangladesh drinking water standards.

The resulting concentration of trace metals in this study was found within the allowable limits in accordance with WHO and Bangladesh drinking water standards, confirming the suitability of rainwater as a potable water source for human consumption. The average concentration of trace metals in rainwater was found in the order of Zn ˃ Cu ˃ Fe ˃ Cr ˃ Mn ˃ Pb ˃ Cd for the tested samples. Overall, the trace metal concentrations of Cu and Zn were predominantly observed in rainwater samples collected from the industrial area, indicating the influence of anthropogenic activities on atmospheric pollution. The concentrations of the trace elements in this work were found to be overall higher when compared to those reported in other investigations around the world. The measurements of this study would provide an indication of atmospheric pollution in rainwater caused by the anthropogenic origins of trace metals as well as provide a database of trace metals in rainwater for further relevant research studies across the country.

How to cite: Hossen, Md. A., Salauddin, M., Hoque, A., and Pal, S. K.: Assessment of source apportionment and composition of trace elements in rainwater in the south-eastern region of Bangladesh , EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-635, https://doi.org/10.5194/egusphere-egu21-635, 2021.

Geographical Information System Based Sensitivity Analysis Accurately Predicts Hydrocarbons Contamination Using Drastic Index and Multicriteria Analysis
Zaharatu Babika and Thomas Kjeldsen
Giulio Castelli, Aixa Mestrallet, Aida Cuni Sanchez, Limber Cruz Montaño, Teresa Lopez de Armentia, Fabio Salbitano, and Elena Bresci

The rural region of “Valles Cruceños”, located in South-Eastern Bolivia experiences recurrent droughts and an increasing pressure on water and land resources driven by the interconnected effects of climate change and the expansion of neighboring and rapidly growing city of Santa Cruz de la Sierra. Despite the relative scarcity of rainfall, orographic fog events are recurrent all year round. Under these climate conditions, water can be easily harvested by fog using simple fog collectors consisting of a vertical plastic meshes supported by two posts, which are set up perpendicularly to the predominant wind direction. The access to sustainable water supply improves farmers’ resilience to dry spells, while promoting food security and livelihood thanks to water harvesting technique of fog collection.

The work describes a first assessment of fog collection in the eastern Andean escarpment of Bolivia based on a 12-month analysis made through 1-m2 fog collectors placed in 10 different locations. Results showed that, on an annual basis, an average of 6.3 l/m2/d can be obtained from most productive areas, with peaks up to 9.4 l/m2/d. Starting from experimental data collected in 2018, a linear model based on Multiple Linear Regression (MLR) analysis was built for extrapolating longer time series of fog volumes collected, using global climate reanalysis data products as explanatory variables. Synthetic time series from 2016 to 2018 were used to design a fog water irrigation system for a standard theoretical field with four local popular crops (maize, green beans, potatoes and tomatoes) to be grown throughout the dry season.

This paper represents the first study on fog collection in Bolivia, showing how fog can represent an unconventional water resource capable of securing food production and improving family and community livelihood. Moreover, while a large part of the scientific literature focuses on advection fog, mostly occurring in the Pacific Coast of South America, this is one of the first consistent studies on the productive use of orographic fog in inland locations.

How to cite: Castelli, G., Mestrallet, A., Cuni Sanchez, A., Cruz Montaño, L., Lopez de Armentia, T., Salbitano, F., and Bresci, E.: Fog as an unconventional water resource for securing food production in Eastern Andes, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-4529, https://doi.org/10.5194/egusphere-egu21-4529, 2021.

Mar Pérez Cambra, Dolors Martínez Santafé, and Josep Roca Cladera

PÉREZ CAMBRA, María del Mar
Technical University of Catalonia (UPC) Barcelona School of Architecture
Department of Architectural Technology I (TA), Centre of Land Policy and Valuations (CPSV)
Assistant Professor, Ph.D. Candidate.
Av. Diagonal 649, 08028, Barcelona, Spain
Orcid : 0000-0003-2456-3302
E-mail: mar.perez@upc.edu
Telephone: +34 934012576

Technical University of Catalonia (UPC) Barcelona School of Architecture
Department of Architectural Technology I (TA), Centre of Land Policy and Valuations (CPSV)
Av. Diagonal 649, 08028, Barcelona, Spain
Orcid : 0000-0001-8200-183X
E-mail: dolors.martinez@upc.edu
Telephone: +34 934016378

Technical University of Catalonia (UPC)
Department of Architectural Technology I(TA), Centre of Land Policy and Valuations (CPSV)
Full Professor
Av. Diagonal 649, 08028, Barcelona, Spain.
Orcid : 0000-0003-3970-6505
E-mail: josep.roca@upc.edu
Telephone: +34 934016396

Key words: WSUDs; thermal behavior; water

“Reduction in water consumption and environmental improvements in Barcelona through WSUDs (Water Sensitive Urban Design Systems”

The aim of this communication is showing the research done during the last years to try to reduce water consumption in Barcelona with the WSUDs (Water Urban Design Systems) while reducing surface temperatures with the chosen WSUDs and reducing rainwater runoff especially in the flood areas of the city.

Water sensitive urban design (WSUD) have been chosen in this research as an approach to planning and designing urban areas of Barcelona as a resource to reduce the damage urban areas cause to water cycle when we change natural pervious surfaces into impervious ones. Thus, while recuperating in some areas water cycle we can reduce rainwater runoff.
This same WSUDs used to reduce rainwater runoff can not only infiltrate and transport water but also to harvest it where it can be more efficient. Water harvesting and reducing he rainwater runoff in a floods area calculations for an area as an example will be shown in this communication. This descentralization of the water treatment will save energy by saving the transportation a long distance away to the water sewage treatment plants. It also avoids diffuse pollution of the runoff since water quality is not worsed due to its transportation to the depuration plant.

On the other hand, since we have climate change not all the materials and construction systems are the proper ones. This part is mainly experimental and has taken almost three years measuring surfaces temperatures of some WSUDs of Barcelona and treating its data to stablish a criteria to choose WSUDs which can help to reduce surface temperatures, even in some cases, underneath the environmental temperatures. It means we can produce a better thermal effect while planning and implementing the WSUDs in this case in Barcelona and in homoclimatic cities.

Therefore, with this WSUDs specific urbanistic micro-acupuncture we can improve some effects of climatic change such as: water scarcity, floods and heat island effect. This communication will focus and deep on it.

How to cite: Pérez Cambra, M., Martínez Santafé, D., and Roca Cladera, J.: “Reduction in water consumption and environmental improvements inBarcelona through WSUDs (Water Sensitive Urban Design Systems”, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-7681, https://doi.org/10.5194/egusphere-egu21-7681, 2021.

Anastasios Perdios, Georgia Papacharalampous, Athanasios Dimas, Georgios Horsch, Irene Karathanasi, Fotis Katrivesis, Demetris Stergiopoulos, Maria Zarkadoula, Eleftheria Zappa, Olga Koutsogianni, Vasileios Alexandrou, Theodoros Pappas, Pavlos Paraskevopoulos, Athanasios Venizelos, and Andreas Langousis

Research project “PerManeNt” aims at developing an integrated platform for operational monitoring, smart control, and sustainable energy management of the external aqueduct system of the city of Patras in western Greece, which consists of more than 60 km of pressurized pipeline, 44 pumping wells, 3 springs, 22 regulating tanks, and 14 pumping stations. Given the significance of the existing infrastructure, 5 main pipelines, 7 pumping wells, 9 reservoirs, and 5 pumping stations were selected to be monitored in the context of: a) real-time data collection, processing and visualization, b) near real-time detection of system malfunctioning and automatic alarm generation, and c) generation of short and longer term forecasts for the water demand and corresponding energy consumption rates, based on hydrometeorological data and environmental indices. The development of the integrated platform is expected to have significant scientific, financial, societal and environmental impacts including: i) efficient water resources management and environmental protection, ii) reduction of the operational costs and regulator expenses for system maintenance and management, iii) promotion of citizens’ awareness regarding environmental issues, and iv) significant improvement of the quality of services offered, including pricing and emergency planning.


This research is co‐financed by the European Regional Development Fund of the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call RESEARCH – CREATE – INNOVATE (project code: T2EDK-4177.

How to cite: Perdios, A., Papacharalampous, G., Dimas, A., Horsch, G., Karathanasi, I., Katrivesis, F., Stergiopoulos, D., Zarkadoula, M., Zappa, E., Koutsogianni, O., Alexandrou, V., Pappas, T., Paraskevopoulos, P., Venizelos, A., and Langousis, A.: Integrated Platform for Smart Operational Monitoring and Efficient Energy Management of Water Supply Networks, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3364, https://doi.org/10.5194/egusphere-egu21-3364, 2021.

Athanasios V. Serafeim, Irene Karathanasi, George Kokosalakis, Roberto Deidda, and Andreas Langousis


In the present work we develop and test a non-parametric statistical methodology to obtain point estimates of Minimum Night Flow (MNF) in Water Distribution Networks (WDNs). The methodology constitutes a simplified version of the approach of Serafeim et al. (2021) for confidence interval estimation of background losses in WDNs, that simultaneously analyzes all night flow measurements, producing robust estimates independent of the nominal resolution of the available data.

In addition to being simpler to apply and computationally more efficient, the developed method can be applied to any WDN independent of its size, age and overall condition, its  specific geometric characteristics (intensity of altimetry, average diameter etc.), inlet/operating pressures, and the nominal resolution of the flow data.

The effectiveness of the method is tested via a large-scale application to the WDN of the City of Patras in western Greece, which consists of 79 Pressure Management Areas (PMAs) with more than 700 km of pipeline grid. To do so, we use flow data at 1 min temporal resolution, provided by the Municipal Enterprise of Water Supply and Sewerage of the City of Patras, for the 4-month winter period from 01 November 2018 – 28 February 2019, which are progressively averaged to coarser temporal resolutions, in an effort to test the sensitivity of the developed method to the nominal resolution of the data.  

The obtained point estimates of MNF are assessed on the basis of the confidence intervals obtained by the approach of Serafeim et al. (2021), highlighting the accuracy and robustness of a simple non-parametric approach in providing MNF point estimates at a minimum of effort.


The research work was supported by the Hellenic Foundation for Research and Innovation (H.F.R.I.) under the “First Call for H.F.R.I. Research Projects to support Faculty members and Researchers and the procurement of high-cost research equipment grant” (Project Number: 1162).


Serafeim, A.V., G. Kokosalakis, R. Deidda, I. Karathanasi and A. Langousis, (2021) Probabilistic Estimation of Minimum Night Flow in Water Distribution Networks: Large-scale Application to the City of Patras in Western Greece (submitted).

How to cite: Serafeim, A. V., Karathanasi, I., Kokosalakis, G., Deidda, R., and Langousis, A.: Practical Estimation of Minimum Night Flow in Water Distribution Networks: Large-scale Application to the City of Patras in Western Greece, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-2235, https://doi.org/10.5194/egusphere-egu21-2235, 2021.

Anna Klamerus-Iwan, Maria Iwan, and Karolina Bigaj

Mosses (bryophyta) have the ability to absorb and retain large amounts of water. This property results from the specific way in which these organisms uptake, conduct, and store water.

The aim of the study was to investigate the water storage capacity (S) of red-stemmed feathermoss Pleurozium schreberi (Mitt.) in the fresh state (current capacity) and after drying (maximum capacity), depending on the initial moisture content, and depending on the percentage of the various structural parts of the moss sample which included soil.

Forty moss samples of equal size were used in the study; they were sprayed with a constant dose of water in laboratory conditions. The actual water capacity was obtained from the difference in the weight of the sample after spraying with a constant dose of water, and the weight of the sample in the fresh state. After the stimulated rainfall cycle, the samples were divided into individual fractions (part with green leaves, stalks and rhizoids, and soil) and dried in an airoven for 24 hours at 105oC.

The weight of the dry sample, the initial moisture, the maximum water capacity, and the current water capacity were calculated. The analyses conducted led to the conclusion that water capacity of moss is extremely important for the water cycle as it retained, on average, as much as 29% of the total rainfall.

The initial moisture depends above all on the amount of soil that dominated the entire sample volume. Retention capacity of the moss must be higher than that of the soil, as each additional gram of soil reduced the initial moisture content of the samples.

Experiments have additionally shown that the higher the initial moisture, i.e. the more water in the fresh moss samples collected with the soil lump, the higher the maximum capacity. The calculated maximum water capacity relates to the dry weight of the entire sample. This conclusion can be compared to the water properties of soil where the wetter fresh soil is able to retain more water, and the excessively dry soil becomes hydrophobic.

In turn, the higher the initial moisture, the less water is retained in the fresh moss sample after rainfall. This observation is similar to the actual situation that occurs in natural conditions, e.g. in a forest. This may be due to the fact that the more water is contained in the moss assimilation apparatus, the higher the cell turgor pressure, which makes the surface tighter. The moss absorbs water from the atmosphere, and the largest increases in retained water are recorded for drier samples. This may also result from external and internal structure of moss, which is different than in vascular plants. The leaves of bryophytes have characteristic vertical rows of cells of the collenchyma on their upper surface. Such arrangement of cells promotes water absorption.

The obtained results remain in line with the research on the hydrological properties of forest ecosystems, and they show that the role of moss in the forest is very important but not yet fully understood.

How to cite: Klamerus-Iwan, A., Iwan, M., and Bigaj, K.: Water capacity of red-stemmed feathermoss (Pleurozium schreberi Mitt.), EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-3067, https://doi.org/10.5194/egusphere-egu21-3067, 2021.