In the Netherlands the natural water system has been altered significantly to address human needs. Historically, the main water issues were related to water excess. However, recent dry years (2018-2020, 2022) have made it clear that drought affects many sectors as well. To deal with both extremes, a transition of the water system is needed with integral solutions.

Exploring the effects of measures needed to improve the water system is challenging and needs to be done in an integrated way that considers the natural water system as well as the anthropogenic influence on that system. Often these effects are investigated using complex, spatially-distributed models that usually don’t include all interactions between water users and the water system, have long calculation times and require a certain computer capacity. To attain a first crude estimate of the effects, it is also possible to use a different approach like system dynamics models. System dynamics models provide less details and include less spatial variation, but can include more interactions between the different subsystems and have short calculation times.

We have developed a system dynamics model, the Water System Explorer, that can be used to simulate the effect of human interventions on the water system. The Water System Explorer provides insight into the water system at a regional scale and can be used as a tool to support conversations between different stakeholders in a region. It is a strong simplification of reality, so it serves to give a first indication of potential measures and their effects, including trade-offs, in a specific region.

The Water System Explorer includes the natural and anthropogenic system. For the natural system, four different landuse types are defined: agriculture, urban area, groundwater-dependent nature and groundwater-independent nature. The phreatic groundwater level is determined for each land use type, which interacts with the surface water and deep groundwater. The anthropogenic system includes the water demand of industry and households, drinking water supply and a wastewater treatment plant. Several interventions are included, for example, a ban on water abstractions for agriculture, introducing separated sewers, increasing surface water levels, applying managed aquifer recharge and re-use of effluent in agriculture, industry, or drinking water supply.

The Water System Explorer has been applied for a region in the Netherlands. The tool reproduced general characteristics of the water system and illustrated the side-effects of water system interventions as a result of feedback mechanisms. The tool shows much potential for gaining insight into a regional water system to discuss measures with all stakeholders and for education purposes. 

How to cite: van Huijgevoort, M., Stofberg, S., Raat, K., and Bartholomeus, R.: The Water System Explorer: understanding interactions between the natural and anthropogenic water system on a regional scale, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5621, https://doi.org/10.5194/egusphere-egu24-5621, 2024.

Over the past decade, water conflicts have risen, and cooperation has declined. Research highlights multiple factors driving this change, with climate change acting as a threat multiplier. Human activities, like dam construction and irrigation, and climate-induced hydro-climatic shifts, including extreme precipitation and prolonged droughts, contribute to the risk of increased water conflicts. To guide interventions and reverse this trend, our focus is on enhancing the understanding of factors that facilitate successful cooperation and mitigate water conflicts effectively. In this study, we investigate cooperation and conflict events worldwide in the last 70 years, together with climatic and socioeconomic factors, such as wealth, export dependency, demographics, water use, and hydro-climate trends. The dataset on cooperation and conflict events used is based on the Transboundary Freshwater Dispute Database and Water Conflict Chronology in combination with more current cooperation events extracted from media news reports. Relationships between investigated factors and cooperation are analyzed by combining panel data analysis and qualitative text content analysis of events. The results provide a deeper understanding of the factors behind why certain events are more successful in achieving conflict mitigation than others. We found that cooperation between countries struggling with water-related challenges can reduce expected conflicts over the next five years. The economic benefits of cooperation show a positive correlation between water-related cooperation and improved wealth (measured by GDP growth), particularly in countries with high export dependency. As such, economic collaboration can be an effective tool for enhancing resilience in high-water stress areas, where collaboration in these areas can contribute to a substantial reduction in future conflicts while simultaneously improving economic prosperity. Engaging in cooperation with other countries can therefore contribute to economic growth and resilience, as well as decreasing conflict risk. Understanding successful conflict mitigation factors can provide helpful insights to global policymakers and leaders in water management to avoid future conflict based on current and projected water availability.

Keywords: water conflict; collaboration; conflict mitigation; mixed methods; socioeconomic factors;

How to cite: Kåresdotter, E., Cai, Z., Pan, H., and Kalantari, Z.: Societal Pathways of Cooperation for Water-related Conflict Mitigation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7616, https://doi.org/10.5194/egusphere-egu24-7616, 2024.

How to cite: Mijic, A. and Liu, L.: An exploratory bottom-up resilience assessment framework for coupled human-water systems, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6073, https://doi.org/10.5194/egusphere-egu24-6073, 2024.

Farmers' risk preferences significantly shape their decision-making processes, influencing key strategies like crop selection and irrigation practices. Concurrently, climate change poses significant threats to agricultural activities, necessitating an in-depth examination of coupled human-nature systems. Farmers perceive changes in climate patterns, such as severe and more frequent droughts, but their reactions to these changes may be highly heterogeneous, influenced by factors such as individual risk aversion, satisfaction, uncertainty, interaction and comparison with other farmers. Agent-based modeling (ABM) has emerged as a powerful tool to capture the complexities of agricultural systems and simulate the interactions between farmers, their environment, and climate change. However, despite increasing calls to incorporate realistic human behavior, the prevailing paradigm remains the use of representative rational agents.

This study presents an ABM application in the Adda River basin, Italy, where agents represent farmers who make decisions on crop type and irrigation method. The main goal is to understand how the system reacts and withstands the impact of emerging climate-change-driven scenarios. The study attempts to find a more realistic approach to agents' decision-making by implementing different behavioral models. The first model assumes profit maximization under perfect foresight, a traditional approach commonly used in ABM literature. The second model introduces uncertainty about future climate conditions and heterogeneity in farmers' risk aversion preferences on the basis of past performances. The third model embraces a more comprehensive approach to behavioral modeling, incorporating behavioral concepts such as reference points and loss aversion. This model acknowledges that farmers' decision-making is not solely guided by profit maximization, but also influenced by their prior experiences, perceptions of losses, and the potential for regret. This more comprehensive approach aims to offer a more comprehensive representation of farmers' decisions on crop selection and irrigation practices, under conditions of uncertainty and risk.  Agents’ individual preferences have been calibrated using survey data from the domain’s field.

Implementing these different decision modules, we tested the agents’ response to various climate change scenarios, including historical conditions and future projections for representative storylines. Preliminary results reveal notable differences in system dynamics and resilience across the behavioral models and risk aversion levels. These findings provide insights into the appropriateness of behavioral modeling tools for understanding agricultural decision-making under evolving climatic conditions.

How to cite: Gazzotti, P., Ricart, S., Gandolfi, C., and Castelletti, A.: Modeling heterogeneous farmers' response to climate change via agent-based simulation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11816, https://doi.org/10.5194/egusphere-egu24-11816, 2024.

The shifting precipitation patterns and rising temperatures in Central Europe and Germany present an existential challenge for farmers. Recent severe summer droughts, such as those in 2003 and 2018, underscore the imperative for farmers to adapt to evolving climatic conditions, for instance through the application of irrigation in areas where it was previously unnecessary or economically unfeasible. However, expanding the currently only 3% irrigated agricultural area in Germany has the potential to significantly impact freshwater resources and hydrological processes.

Here, we model the adaptive behavior of farmers regarding irrigation, by employing an empirically validated multi-agent system (MAS) model. This model simultaneously simulates decisions about annual crop choices, acreages, and irrigation water application. Spatially disaggregated, the MAS model is calibrated using an Econometric Mathematical Programming (EMP) approach, based on historical land use data for eight major field crops. To account for the implications of future climate change, we couple the MAS model with a statistical crop yield model driven by meteorological indicators and soil moisture anomalies derived from the mesoscale Hydrologic Model (mHM) for a EURO-CORDEX scenario ensemble (RCP2.6, RCP4.5, RCP8.5). Socioeconomic variables that influence farmers' decisions, including changes in crop prices, costs, and subsidies, are projected based on Shared Socioeconomic Pathway (SSP) scenarios.

Across various combinations of SSP and RCP scenarios, we find a notable surge in irrigation water demand. This development is particularly pronounced in SSP3-RCP8.5, where the MAS model projects several irrigation hotspots with a high irrigation water demand. Shifts in cropping patterns thereby significantly affect the resulting irrigation water demand. To dissect the effects of hydrometeorological, socioeconomic, and policy changes on irrigation water demand, we conduct sensitivity analyses on individual parameters.

The MAS model emerges as a robust tool for analyzing farmers' adaptive behavior and assessing the impact of diverse policies on future irrigation water demand. This research contributes valuable insights into agricultural adaption under changing environmental and socioeconomic conditions.

How to cite: Heilemann, J., Nagpal, M., Werner, S., Klassert, C., Klauer, B., and Gawel, E.: More Droughts, More Irrigation? Modeling the Adaptive Behavior of German Farmers to Hydrometeorological and Socioeconomic Change , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11342, https://doi.org/10.5194/egusphere-egu24-11342, 2024.

Drought poses a thread in the already existing water challenges in dryland regions. Drought hazard and risk are, however, not merely a natural phenomenon. Instead they are shaped and influenced by human behaviour and interventions. This raises questions about how to distribute the limited available water in an equitable manner, especially in drought prone areas such as drylands where water is key to people’s livelihood and fragile ecosystems.

In the Horn of Africa Drylands (HAD) conflict over water and vegetation is prominent. On top of that, large-scale land acquisitions (LSLAs) are increasing the competition of water, putting local communities at increased risk. A key impact of increasing LSLA's is the decrease in water and land availability for vulnerable agropastoral communities. For such communities, drought adaptation is key to reduce drought risk, especially under climate change. Despite these recent studies, there is still a lack of research that includes the influence of upstream-downstream dynamics on drought risk and adaptation behaviour with a focus on the impacts of agropastoralists.

This study, therefore, further develops an agent-based model (ADOPT-AP) to investigate how upstream large scale commercial farms influence downstream drought risk and adaptation of agropastoralists. We apply and test the ADOPT-AP model for the Ewaso N’giro north catchment in Kenya. Main novelties of our method are the ability to capture heterogeneous and dynamic drought-human interactions (including different water users) in a spatially-explicit manner. After the model has been calibrated and validated, we test how commercial exporting farms affect drought risk and impact of downstream communities by simulating different scenarios. We show for various drought periods how both drought characteristics (soil moisture, discharge and groundwater levels) and impacts (milk production, crop production, distance to water) differ among the scenarios.

How to cite: Streefkerk, I., Aerts, J., de Bruijn, J., Hassaballah, K., Odongo, R., Schrieks, T., Wasonga, O., and Van Loon, A.: The effect of commercial export farms on drought risk and adaptation of agropastoral communities in the drylands of Kenya, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-676, https://doi.org/10.5194/egusphere-egu24-676, 2024.

 Emphasis has been placed worldwide recently on the need to view social sensing and geospatial big data as an analogue of remote sensing data. The attempt to establishing a firm footing of this kind of data is essential, for example, to: 1) understand the complex coupling of human and natural systems and 2) make useful policy interventions related to sustainable land and water management. However, most vulnerable communities to natural disasters, whose livelihood and economies are dependent on farming, lack such data. Without suitable socio-economic and farm management data, agricultural governance becomes less responsive or even fails, particularly when the agricultural systems are affected by natural disasters. In this study, we highlight nine lessons learned from our first experience during extensive and comprehensive household surveys of farm management practices recently conducted in the arid and semi-arid zones of Sudan. The aim here is to offer guidelines for researchers and practitioners to carry out successful campaigns in similar settings. These campaigns were implemented as part of the DFG funded SHADRESS project, “Sociohydrological analysis of drought resilience in Sahelian Sudan farming systems”. The surveys were conducted by means of Information and Communication Technology (ICT) via smartphone app and traditional paper-based approach. Two hypotheses were assessed: First, the two survey methods can be integrated and utilized to generate direct and ongoing communication between farming stakeholders. Second, this stakeholder network and dialogue can help acquire big social datasets to fill the data gap within the agriculture sector and, subsequently, address water and food security. We categorize the lessons and guidelines as logistics, technology, culture and behavior related. More than 70 questions related to the socio-hydrological farming system were addressed. The surveys resulted in capturing responses from ~1640 households distributed over three farming systems, namely traditional rainfed, mechanized rainfed and irrigated systems. This dataset contains rich information to enable detailed spatial analyses of farm management strategies and understanding of generic concepts of farmer-water interactions in a drought-vulnerable region. 

How to cite: Elagib, N. A., Ahmed, B. M., Sulieman, H. M., Rahma, A. E., Ali, M. M. A., and Schneider, K.: Capturing geospatial data on farm management practices in vulnerable farmer-water systems: Lessons from the Sahel, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1415, https://doi.org/10.5194/egusphere-egu24-1415, 2024.

Human drivers significantly influence flood occurrence and impacts  through multiple avenues. In this work, we explore how human drivers contributed to flood risk in 42 European countries between 1950 and 2020, with particular focus on 1504 historical floods that caused significant socioeconomic impacts. Our modelling chain covers both riverine and coastal floods and is able to reconstruct past extreme events including the influence of (1) human impact on catchment hydrology through changing land use, water demand and reservoir capacity, (2) increase in exposure related to land use change, demographic and economic growth, and evolving structure of the economy, and (3) changes in flood preparedness, exhibited by flood protection levels (primarily from structural defences) and flood vulnerability (relative loss at given intensity of hazard). The results indicate that although construction of large reservoirs (the number of which increased six-fold in the study area since 1950) has locally led to a pronounced decline in riverine flood risk, human alterations to catchments overall increased the flood risk in Europe due to land-use change, particularly through strong increase in soil sealing caused by urbanization. An even stronger relative effect on the increase in flood impacts is caused by exposure growth, consisting of population growth, particularly in cities, a rapid increase in gross domestic product per capita, and further compounded by growth in capital-to-income ratio. Exposure growth is more pronounced for coastal floods compared to riverine floods. On the other hand, historical flood impact data analysed in this study show evidence of improving preparedness over time. Flood defences currently protect against higher return periods of floods than before, particularly for coastal floods, though they are mostly much lower than assumed in previous pan-European studies. A decline in flood vulnerability (relative losses) over time is also observed, partially compensating for negative human influences on flood risk.

How to cite: Paprotny, D., Tilloy, A., Vousdoukas, M. I., Kreibich, H., Feyen, L., Morales Nápoles, O., and Mengel, M.: Human drivers of flood losses in Europe since 1950, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9372, https://doi.org/10.5194/egusphere-egu24-9372, 2024.

Social media platforms play a key role in enhancing human response to natural hazards. They serve as tools for individuals to share first-hand observations, insights, and experiences, thus contributing to improved resilience. Increased attention of social and communication media content toward natural hazards has the potential to foster take up of private precaution and resilience measures such as purchasing a flood insurance. This study investigates the driving factors behind flood insurance purchase decisions in the US, with a focus on the roles of risk perception and social media as potential drivers for such decisions. We investigate the relationship between household flood insurance uptake and social media attention for flood events that occurred in the continental US from 2014 to 2021. We argue that the surge in insurance uptake in counties affected by flood events is primarily attributed to heightened risk perception resulting from direct exposure to flooding and from citizens’ awareness due to exposure to flood related information. We compare the time series of insurance take-up rate in a county with the number of flood-related social media posts in the adjacent counties using Dynamic Time Warping, which measures the similarity between two time series by optimally aligning their temporal structures. Additionally, we control for time passed since the last flood as well as the number of communities participating in the Community Rating System since these factors have shown to be important drivers of insurance uptake and may otherwise distort the temporal patterns associated to social media exposure. With our data-driven analysis we first evaluate the correlation between exposure to flood-related content on platforms like X (formerly Twitter) and an increased likelihood of purchasing flood insurance. Consecutively, we quantify variations in risk perception and resilience due to exposure to flood-related content on social media. This analysis provides a comprehensive view of risk communication through social media and its implications for resilience-building efforts.

How to cite: Veigel, N., Kreibich, H., de Bruijn, J., Aerts, J. C. J. H., and Cominola, A.: Correlation of Social Media-Driven Risk Perception and Flood Insurance Uptake for Floods in the US, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11646, https://doi.org/10.5194/egusphere-egu24-11646, 2024.

Human displacements due to climate and weather extremes are dramatically increasing worldwide, mainly across areas where extreme events interact with high vulnerability and low adaptive capacity, such that they are now recognized as a primary humanitarian challenge of the 21st century. Human mobility from droughts is multifaceted and depends on environmental, political, social, demographic and economic factors. Although droughts cannot be considered as the single trigger, they significantly influence people's decision to move. Yet, the ways in which droughts influence patterns of human settlements have remained poorly understood.

Here we explore the relationships between drought occurrences and changes in the spatial distribution of human settlements across 50 African countries for the period 1992–2013. Since long-term yearly data on human displacements are not consistently available for the entire African continent, we employ both country-based and spatially explicit data sets as reliable proxies. We base our continental study on urban population data and nighttime lights, as a proxy for the spatial and temporal distribution of human settlements. For each country, we evaluate annual relative urban population and human distance to rivers. To identify drought years, we extract annual drought occurrences from two indicators, the international disaster database EM-DAT and the standardized precipitation evapotranspiration index (SPEI-12) records. We then compute human displacements as variations in human distribution between adjacent years, which are then associated with drought (or non-drought) years. We finally examine the consistency between drought occurrences and changes in human settlement patterns to identify macroscopic trends at the continental scale.

Our results show that drought occurrences across Africa are often associated with (other things being equal) human mobility toward rivers or cities. In particular, we found that human settlements tend to get closer to water bodies or urban areas during drought conditions, as compared to non-drought periods, in 70%–81% of African countries.

This large-scale trend clearly highlights that the occurrence of drought events, although not being the single driving factor, significantly influences human mobility. By interpreting this outcome from a broader perspective, which includes consecutive drought-to-flood events, adverse consequences might occur. An increased human presence in urban areas and close to rivers may result into an increased human exposure to floods, and thus leading to a potentially increased flood risk. Therefore, further investigations are foreseen and encouraged to better understand the interplay between human mobility and climate change in order to increase the resilience of vulnerable areas and population to hydrological extreme events and support the development of sustainable and effective planning strategies for the near future.

How to cite: Ceola, S., Maard, J., and Di Baldassarre, G.: Droughts influence changes in human settlement patterns in Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9602, https://doi.org/10.5194/egusphere-egu24-9602, 2024.

Drought-heatwave events increase water use mainly for domestic and irrigation water use sectors (Cárdenas et al., 2023). Moreover, water quality deterioration caused by human activities is exacerbated by more frequent and longer-lasting extreme hydro-climatic events, such as droughts and heatwaves. These circumstances challenge the supply of water of suitable quality and increase the cross-sectoral competition forclean water.

Water use models are useful in estimating responses in water demand and use ‑in terms of consumption and withdrawals‑ of the main water use sectors (i.e., irrigation, livestock, domestic, energy and manufacturing); however, there are few water use models that account for both water quantity and quality dimensions simultaneously. The main objective of our research is to assess the cross-sectoral water deficit due to sectoral competition for limited clean water resources, explicitly considering water quantity and water quality requirements.

To address this objective a new sectoral water use model framework has been developed, that evaluates simultaneously water quantity and water quality requirements for the main water use sectors. This globally applicable model framework builds on the PCR-GLOBWB 2 hydrological model (Sutanudjaja et al, 2018) and DynQual v1.0 global surface water quality model (Jones et al, 2023), which simulates surface water temperature, salinity as indicated by total dissolved solids (TDS), organic pollution as indicated by biochemical oxygen demand (BOD), and pathogen pollution as indicated by faecal coliform (FC).

Preliminary results show that high salinity (TDS) is the predominant water quality constituent limiting water use for irrigation most of the year; while for the domestic sector it is organic pollution, particularly in regions with limited water treatment capacities. For such sectors, accounting for water quality requirements lead to substantial reductions in surface water withdrawals over the Conterminous United States when compared to results obtained from only water quantity-based models.

This modelling framework provides the basis for an integrated water scarcity assessment driven by changes in water quantity and quality under current and future droughts and heatwaves.

References

Cárdenas B., G.A., Bierkens, M.F.P., van Vliet, M.T.H.: Sectoral water use responses to droughts and heatwaves: analyses from local to global scales for 1990-2019. Environ. Res. Lett. 18 104008. https://doi.org/10.1088/1748-9326/acf82e, 2023.

Sutanudjaja, E. H., van Beek, L. P. H., de Jong, S. M., van Geer, F. C., and Bierkens, M. F. P.: Calibrating a large-extent high-resolution coupled groundwater-land surface model using soil moisture and discharge data, Water Resour. https://doi.org/10.5194/gmd-11-2429-2018, 2018.

Jones, E. R., Bierkens, M. F. P., Wanders, N., Sutanudjaja, E. H., van Beek, L. P. H., and van Vliet, M. T. H.: DynQual v1.0: a high-resolution global surface water quality model, Geosci. Model Dev., 16, 4481–4500, https://doi.org/10.5194/gmd-16-4481-2023, 2023.

How to cite: Cárdenas Belleza, G. A., van Beek, L. P. H. (., Bierkens, M. F. P., and van Vliet, M. T. H.: Too little or too dirty? Global modelling framework for analyses of sectoral water use responses under droughts and heatwaves, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12542, https://doi.org/10.5194/egusphere-egu24-12542, 2024.

Climate change presents a pressing challenge to global water availability resulting in ‎increased variability in precipitation and increased temperatures, imposing more stress ‎on existing water resources and the economic activities that depend on them. The ‎Tormes catchment, located in a semi-arid region, is facing increasingly severe water ‎shortages, which may be further aggravated under climate change. This catchment is ‎extensively employed for agricultural purposes, and a potential reduction in the ‎availability of water for irrigation emerges as a significant concern.‎
This study evaluates the impact of climate change on water availability, and the ‎responses implemented by irrigators to adapt to growing scarcity, in the Tormes ‎catchment. To this end, we develop a human-water system model that couples the Soil ‎and Water Assessment Tool (SWAT) model and a Positive Multi-Attribute Utility ‎Programming (PMAUP) model using a dynamic and modular approach. The coupled ‎model runs the water (SWAT) and human (PMAUP) system models iteratively and ‎over time using inputs from six different bias-corrected Global Climate ‎Models(GCMs) under CMIP6 scenarios, as follows: i) CMIP6 climate change scenario ‎simulations are fed to the SWAT model to estimate relevant hydrological data ‎including water availability in March (beginning of the irrigation campaign); ii) ‎information on water availability is fed to the PMAUP model to simulate the adaptive ‎responses of irrigators in terms of water and land allocation; iii) land and water use ‎choices by irrigators are fed into the SWAT model, which reproduces the ‎consequences of human decisions on the water system; iv) when the hydrological year ‎is over, a new iteration starts where CMIP6 climate change scenario simulations for ‎the following year are fed into the SWAT model and the process is repeated again. The ‎non-linearity and modular approach in both the hydrological and economic models ‎imply complex and interconnected interactions within these systems, with behaviors ‎that may or may not follow linear patterns.‎
Six bias-corrected GCMs under CMIP6 scenarios were employed for the climate ‎change scenario simulations. The dataset covered precipitation, maximum and ‎minimum temperatures for the historical period (1981–2010) and projections for ‎SSP245 and SSP585. Future data was analyzed for three periods: 2020–2039, 2040–‎‎2059, and 2060–2100. A multi-model ensemble approach was applied, averaging ‎outputs from the six models. Precipitation and temperature data were integrated into ‎the SWAT model.‎
The hydrological analysis revealed a downward trend in projected precipitation, with ‎reductions of 0.7% (2020s), 0.3% (2040s), and up to 5.3% (2060s) under SSP245. ‎SSP585 showed declines of 6.4% (2020s), 6.6% (2040s), and 16.1% (2060s). ‎Maximum and minimum temperatures exhibited an upward trend under both ‎scenarios. Simulated mean annual runoff under SSP245 experienced a drastic ‎reduction of 48.1% in the 2020s, followed by 43.8% (2040s) and 53% (2060s). ‎Similarly, under SSP585, mean annual runoff decreased by 47.2% over the entire ‎projection period. While the hydrological analysis reveals concerning trends in ‎precipitation, temperature, and mean annual runoff under different scenarios, the ‎economic results, reflecting the effects of these hydrological changes on human ‎activities, are still being investigated and are not yet finalized.‎

How to cite: Hassan, O. G. B., Pérez-Blanco, C. D., and González-López, H.: Assessing the Impact of Climate Change on Water Scarcity in the Tormes ‎Catchment, Spain: A Human-Water System Modeling Approach, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4678, https://doi.org/10.5194/egusphere-egu24-4678, 2024.

The threat of climate change and water resource overexploitation to river network ecosystems and their natural flows is evident, particularly in mountainous regions where hydropower production is also responsible for significant alterations of the natural streamflow. Hydrological modeling in these watersheds is hindered by limited knowledge of technical and geometrical information. Key characteristics and parameters related to hydropower operating schedule and their hydraulic infrastructures are usually hard to obtain as they are mostly confidential data producers hold. Consequently, modeling hydropower systems over large domains often relies on simplified methods which may decrease the reliability of these studies. In response to these challenges, we created a comprehensive inventory designed to model the interaction between natural stream networks and hydropower-related infrastructures at the mesoscale. This inventory, tailored for the large hydropower systems in the northern mountainous region of Italy (Italian Alpine Region - IAR), includes detailed hydraulic parameters essential for the reliability of water-energy-nexus modeling implementations. The selected region includes over 300 large hydropower systems with complex infrastructures, among those, nearly 160 plants are reservoir-fed, causing a significant alteration in streamflow. To assess the reliability of the provided inventory, we employed HYPERstreamHS as the reference hydrological model. We assessed the accuracy of our designed inventory by comparing the modelled hydropower production with the finest observations available, which are province-aggregated monthly hydropower production data from 1995 to 2008. The outcomes revealed a commendable similarity ranging from 83% to 100% across simulated areas, with an overall average of 90%, solidly confirming the accuracy of the crafted inventory.

How to cite: Zarghami Dastjerdi, S., Galletti, A., and Majone, B.: A comprehensive inventory of large hydropower systems in the Italian Alpine Region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15100, https://doi.org/10.5194/egusphere-egu24-15100, 2024.

We have developed a methodology for constructing diachronic views of the chemical state of water that infiltrates soils and forms perched aquifers in the north and south of Paris (France). These waters have been drained for centuries and distributed by historic underground aqueducts. The CaCO3 layers deposited by these waters in the aqueducts have been studied.

The first challenge is to construct chronologies of these deposits, using uranium-thorium or 14C chronometers and/or lamina counting.

Past water quality has been reconstructed using trace elements measured along the growth axis of CaCO3 deposits, combined with isotope analysis (lead, sulfur and strontium) and, in some cases, carbon isotopes.

With this methodology, we demonstrate that in Paris, over the last 300 years, the transformation of land use is the most important factor affecting water quality, not only through the presence or absence of building industries, but also through the use of certain materials for construction or embankment. 

We use this methodology for the study of ancient aqueducts in archaeological sites to discuss water provenance and quality.

How to cite: Pons-Branchu, E., Branchu, P., Dapoigny, A., Douville, E., Dumont, E., Fernandez, M., Progam, A., and Jean Soro, L.: Carbonate deposits from historical aqueducts in urban area: an archive for human impact on water management and quality, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13415, https://doi.org/10.5194/egusphere-egu24-13415, 2024.