Urban water resources planning is complicated by unprecedented uncertainty in supply and demand. Real-world planning often simplifies the full range of uncertainty faced by a system into a limited set of deterministic scenarios to enhance accessibility for decision-makers and the public. However, overlooking uncertainty can expose the system to failures. The academic literature has developed tools, such as scenario analysis, to test water systems across various uncertain futures, assessing their responses to diverse drivers. Applying scenario analysis to the full set of uncertain drivers can identify system vulnerabilities, but current approaches to visualizing this information are difficult to communicate and therefore have limited practical applications. There is a lack of water planning frameworks that effectively integrate a rigorous treatment of uncertainty with accessible, user-friendly visual and interactive tools to enhance understanding and implementation for users.

In this work, we develop an example of such framework for the case study of the city of Santa Barbara, CA. Santa Barbara faces multiple uncertainties in their water supply portfolio and demand, from pending state and federal regulations, to changing hydrology and water demand. The city seeks to increase their water portfolio robustness by expanding its seawater desalination plant, but must determine the expansion capacity. We introduced computational tools that enable a comprehensive assessment of uncertainty across nine uncertain drivers, identified with the help of water planners in Santa Barbara. To allow public participation in the desalination expansion decision, we develop interactive visual analytics to aid decision-makers and stakeholders in navigating complex scenario analysis outcomes. Our results quantify the tradeoffs between increased capacity and system robustness. We also categorize uncertain drivers according to their criticality and the level of control that the municipality can exert over them, for instance the city's water demand can be partially controlled through water efficiency campaigns. This work aims to enhance participation and uncertainty characterization of urban water planning efforts.

How to cite: Zaniolo, M., Fletcher, S., and Mauter, M.: Interactive decision-support for participatory water planning under multiple sources of uncertainty, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12437, https://doi.org/10.5194/egusphere-egu24-12437, 2024.

The use of information and models is key to making decisions related to water management, considering the interaction between the natural supply and the economic and socio-cultural systems. However this data-based decision-making is generally complex due to the uncertainties associated with these models, the various individual interests that stakeholders have regarding the water that prevail over the collective interest, and the institutional framework that frames the decisions. In a system limited by the quantity and quality of water available, and where users want to respond to their growing water needs, it requires tools that allow objective decisions to be made based on the common benefit of concurrent users. In this context, a methodological guide has been developed for the development of water resource planning processes based on data and models, which integrates the robust decision support framework (Purkey, David et al., 2018) with the development of serious games or scenathons, called guidelines for scenathons.

Robust Decision Support is a framework that guides water resource planning processes through a series of steps starting from defining decision space, mapping key actors, problem formulation, tool construction, scenario definition, system vulnerability, options analysis, results exploration, and decision-making. The process includes three workshops for problem definition and vulnerability These participatory processes have shown the usefulness of having systematized information and models that make it possible, on the one hand, to understand the vulnerabilities of the system in its current condition, and to simulate scenarios of analysis of the impacts that may be generated by climate change, population growth and economic activities.

In these processes, it has been understood that it is not only important to have models that accurately and precisely describe reality, but it is also fundamental how the model is built, using information and models that have credibility in the region and validating the results with the actors knowledgeable about their environment.

However, interaction with stakeholders directly using the models is not easy due to multiple user profiles and knowledge. To this end, methodologies have been developed that allow interaction with complex data through visualization platforms for model results and various simulated scenarios. This interaction has been complemented with the use of serious games to generate an exchange with users using a narrative that allows transcending from existing roles and conflicts to a more purposeful dialogue. Examples of the serious games and visualization tools will be provided in the presentation https://latinoamericasei.shinyapps.io/Juego_Serio_POMCA_Campoalegre/

In this context, in the framework of the TRANSCEND project (Transformational and Robust AdaptatioN to water Scarcity and ClimatE chaNge under Deep uncertainty) we proposed a guideline for scenathons, which integrates the process of participation in the four years of the project and the development of each Scenathon for the co-creation of TAPs. The guidelines for scenathons is the roadmap to guide the process of co-creation of TAPs using models in 7 living labs and considering the associated uncertainty that may affect decision-making. We are currently developing the first year of the project where the main problems have been identified.

How to cite: Santos, T., Ayala, G., and Purkey, D.: Guidelines for Scenathons. A framework for co-creating Transformational Adaptation Policies., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-21381, https://doi.org/10.5194/egusphere-egu24-21381, 2024.

As water scarcity becomes the new norm in the Western United States, states such as California have increased their efforts to improve water resilience. Achieving water security under climate change and population growth requires an integrated multi-sectoral approach, where adaptation strategies combine water supply and demand management interventions. Yet, most studies consider supply-side and demand-side water management strategies separately. Further, publicly available data to assess the effectiveness of these strategies and their dependency on individual and collective human behavior is often hard to find and unstructured. Water conservation efforts are driven by water scarcity and policy requirements, with conservation targets and water use restrictions often designed assuming a degree of rationality of human behavior and based on cost-effective options and ease of implementation.

In this work, we develop a data-driven analysis aimed at evaluating historical synergies and possible trade-offs between water supply and demand management strategies in California. Our analysis is based on CaRDS – the statewide California Residential water Demand and Supply open dataset, which contains monthly values of water supply and residential water demand for 404 water suppliers in California from 2013 to 2021. In this time span, Californian water agencies had to adapt and mitigate the effects of two droughts (in 2012-2016 and 2020-2022) through residential water demand reductions, as well as address rapid changes in demand associated with the global COVID-19 pandemic (2020). Our trade-off analysis integrates the following three sequential steps: (i) trend analysis – we use Random Forest regression to control for seasonal factors (i.e., temperature and precipitation) that affect water supply and demand at the utility scale; (ii) multi-criteria trade-off analysis – we examine the temporal relationship between water supply and demand by utilizing Dynamic Time Warping to identify trade-offs and management patterns. Next, we cluster water suppliers in 6 groups based on their combined management patterns; (iii) and driver analysis – we utilize explainable Machine Learning by combining SHAP (Shapley values) with LGBM (Light Gradient Boosting Method) to identify the drivers of each cluster. Potential drivers include climatic region, water supply portfolio, indoor vs. outdoor water use, local and state policies,  population, supplier size, and income. We finally validate the results of our analysis by comparing our findings with responses from water supplier interviews carried out in 2017 and reveal differences between intended and actual water management outcomes. This research contributes insights into the combined effects of policies on water supply and demand at a statewide level. Further it facilitates the formulation of adaptive resilience strategies for human actors in water management and decision makers alike to address vulnerability of small and large water systems to a rapidly changing climate and a society with non-linear changes in human behavior.

How to cite: Gross, M.-P., Escriva-Bou, A., Porse, E., and Cominola, A.: Leveraging explainable Machine Learning to discover trade-offs between water supply and demand management strategies in California, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16197, https://doi.org/10.5194/egusphere-egu24-16197, 2024.

The Mediterranean region is increasingly suffering from water scarcity in summer as a consequence of climate change. Drier conditions call for increased use of irrigation to avoid severe production losses, increasing the pressure on overexploited surface and subsurface water resources. The use of non-conventional waters (NCW) - such as desalination, water reuse and water harvesting - can provide a sustainable alternative to face future climate change conditions. However, the adoption of NCW has several barriers and challenges related to environmental, technical, socio-economic and policy issues. These barriers need to be holistically addressed for effective delivery of NCW solutions. We present the implementation of Living Labs (LL) as tools for testing technical solutions in field conditions, with the involvement of stakeholders in a participatory co-production approach. The four LLs span from Italy, Spain, Egypt and include a transboundary LL between Algeria and Tunisia. Workshops were carried out according to the principles of Responsible Research and Innovation, with  stakeholders’ involvement through a series of methodologies such as World Cafè and SWOT analyses.

The main insights from the workshop concerned inefficient regulations in water-related infrastructures, insufficient funding availability for farmers, groundwater overexploitation, poor water quality and water scarcity as the main challenges. Actions which could contribute to tackle these problems could be farmer education and training, the introduction of drought and salt-tolerant plant cultivars, soil and water conservation practices, community-managed irrigation instead of individual one and better coordination among water management institutions.

Our study provides a unique example of application of the LL approach in rural contexts across the Mediterranean. The same procedure can be applied in any similar contexts to involve stakeholders in water management and allocation and to help them familiarize with the use of NCW. 

This research was carried out within the AG-WaMED project, funded by the Partnership for Research and Innovation in the Mediterranean Area Programme (PRIMA), an Art.185 initiative supported and funded under Horizon 2020, the European Union’s Framework Programme for Research and Innovation, Grant Agreement Number No. [Italy: 391 del 20/10/2022, Egypt: ٍSTDF #45878, Tunisia: 0005874-004-18-2022-3, Greece: ΓΓP21-0474657, Spain: PCI2022-132929, Algeria N° 04/PRIMA_section 2/2021].

The content of this abstract reflects the views of the authors, and the Commission cannot be held responsible for any use that may be made of the information contained therein.

How to cite: Bresci, E., Forzini, E., Villani, L., Piemontese, L., Bahnassy, M., Hassan, B., Badr, R., Rady, O., Mohamed, S. Z., Karaouli, F., Abdelli, F., Rahal, O., Gouaidia, L., Garrote, L., Sordo-Ward, A., Bianucci, P., Caporali, E., Bertoli, G., Pacetti, T., and Castelli, G.: Participatory approaches for fostering non-conventional waters in agriculture: insights from 4 Living Labs in the Mediterranean region, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11969, https://doi.org/10.5194/egusphere-egu24-11969, 2024.

Agriculture is one of the most sensitive and vulnerable activities to climate variations, motivating farmers’ actions to face climate change-induced stressors and shocks. Traditional management approaches based on linear growth optimization strategies, overseen by command-and-control policies, have proven inadequate for effective water management and climate change adaptation because they partially failed to account for the inherent unpredictability and irreducible uncertain risk conditions. Furthermore, this approach overlooks the necessity of addressing changes in human behavior, knowledge sharing, and motivations as part of climate change adaptation pathways. Conversely, accurate bottom-up approaches focusing on social learning input, enhance system transformation by building collaborative problem solving. Surveys and interviews, both forms of associative processing, have proven effective in delving into knowledge-based information and tracking the impact of personal experiences on water management and climate change action. Additionally, Agent-Based Models (ABM) have been utilized to enhance the interplay between social and physical surroundings, depicting individuals’ and stakeholders’ narratives, and charting the hydrosocial landscape.

Assuming water has different physical, social, political, and symbolic value(s) for individuals and communities, it is crucial to strengthen the involvement of stakeholders in order to gain a deeper understanding of their preferences, potential solutions and persistent constraints that are conditioning decision-making processes in coupled human-nature systems. This underscores the need for holistic and systemic approaches that can integrate the domains of water and climate in specific arrangements, fostering direct engagement among users, stakeholders, and decision-makers through social learning. In this context, the insights and observations of farmers and irrigation districts managers are highly valuable in gauging climate change awareness, perceived impacts, and adaptive capacity. Their understanding is imperative to provide informed decisions to policy-makers, and the first step to minimizing misconceptions or maladaptation practices that could affect the water management and governance processes.

This work presents a transdisciplinary approach that combines farmers’ clustering with behavior and agrohydrological modelling to support water management and address climate change risks. We consider a case study in northern Italy 1) to identify farmers’ and managers’ perspectives regarding climate change, 2) to anticipate farmers’ decisions by testing different rationality and risk preferences in an ABM, and 3) to assess how farmers’ and managers’ feedback loops can be incorporated into regional adaptation strategies. Results indicate that farmers and managers are aware of climate change, perceive climate variability and impacts, and combine preventive and reactive measures to reduce climate vulnerability. After first running simulations, the ABM effectively represents the heterogeneity of farmers, creating a more diverse representation of their behavior, while identifying how risk aversion influences how farmers adopt cropping patterns and irrigation methods. A better understanding of the farmers’ behavior in terms of risk assessment and adaptability can facilitate the transferability of bottom-up findings and the customization of targeted and flexible adaptation instruments to avoid maladaptation or inefficient transformation when facing water management and climate change in coupled human-nature systems.

How to cite: Ricart, S., Gazzotti, P., Gandolfi, C., and Castelletti, A.: Merging social learning and behavior modelling to reinforce farmers adaptation to climate change, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2433, https://doi.org/10.5194/egusphere-egu24-2433, 2024.

The disruptions in weather patterns and intensified drought imposed by climate change in arid and semi-arid areas require prompt adaptation of irrigation strategies to sustain production and build resilience. Our research develops a quantitative methodological framework outlining irrigation management strategies, focusing on groundwater governance and drip irrigation adoption, to pinpoint influential factors steering decision-making. Extensive interviews undertaken in Al Haouz Basin, Morocco, provided insights into irrigation choices. We identified themes through inductive encoding and translated these into an integrative modelling framework relying on a fusion of planned behaviour theory and structural equation modelling. This enabled analysis of relationships among attitudes, norms, perceived behavioural control and intentions to adopt practices and technologies. We tested hypothesized pathways through which these factors influence adoption. Structural equation modelling estimates relationship strengths while accounting for interacting variables. The results show farmers' attitudes towards the efficiency of drip irrigation, the sustainability of groundwater resources, and salinity increase in groundwater play a crucial role in their decision-making processes regarding water usage. Land ownership provides a sense of long-term control over sustainable water usage. However, complexities in subsidy applications and uncertainties in land tenure present substantial barriers to adopting drip irrigation, particularly for small-scale farmers, thereby limiting their capacity to adapt to climate change. Our study uncovers the key factors influencing evolving agricultural practices and delves into the policy implications surrounding these changes. By examining the adaptive strategies of farmers, our research lays a foundation for formulating evidence-based policy reforms to increase agricultural resilience and water sustainability in arid and semi-arid climates.

How to cite: El Fartassi, I., Metcalfe, H., Milne, A. E., El Alami, R., Diarra, A., Alonso-Chavez, V., Waine, T. W., Zawadzka, J., and Corstanje, R.: Adaptations in agricultural water management in arid regions: modelling farmer behaviour and cooperation on irrigation sustainability, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19852, https://doi.org/10.5194/egusphere-egu24-19852, 2024.

Against a backdrop of increasing scarcity and pressure on water resources in the Mediterranean, technical informational innovations for existing irrigation systems have potential to support farmers and Water User Association in these critical times. The capacity to track water flows and transfers at various spatial and temporal scales is now clearly identified as one avenue to improve irrigation management. Information and Communication Technologies (ICT) are being developed at an unprecedented rate, but they are still not as widespread as the increasing conflictual situations may require. The objective of this communication is to propose a methodology to overcome barriers to larger uptake of ICT due to technical and organizational specificities. We developed a specific method, cross-referencing spatial information and analyzing innovation processes. It relies on a reflexive and analytical project perspective and a corresponding process between physical and social sciences. Following-up eight local experimentations of the participatory design of tailor-made decision support systems (https://prima-hubis.org/, 2020-2024), in the course of the project we focused on the how to widen local developments in space and time. We suppose the existence of common pathways, or patterns, that unfold in collaborations at different scales, from the plot, farm, scheme spatial scales, to the territory, watershed, or administrative region. The methodology consist of two simultaneous steps:

• building of a Geographic Information System to support the agro-hydrological description of irrigated systems to understand the possibility for geographical expansion, e.g. developing a Multi-Criteria Analysis integrating spatial analysis with collective expertise to draw patterns of irrigation technical infrastructures at a Mediterranean scale;
• recomposing social patterns of local innovation temporalities: using a context-mechanism-outcome framework to guide research on multifaceted collaboration, we draw and analyze innovation timelines and storylines to understand how contextual factors hinder or foster causal chains.

This research was triggered from an overall aim of HubIS project’s consortium to build recommendations at the regional Mediterranean scale to improve local irrigation performance. Acknowledging the importance of contextual conditions on the success of projects, we suppose that innovation “scaling potential”, or percolation rate, depends both on local socio-hydrological system dynamics and on trends at other scales.

We believe that this case of searching common interfaces between disciplines based on a set of collaborative innovation situations may profit the environmental scientific community. Indeed, as any other multi-site projects, spatially and temporally bounded, it remains difficult to understand the processes of diffusion of technological innovations. System dynamics are often ignored in conventional policy approaches, assuming a singular path to progress and a singular view of the problem, and hybrid methods not so common. We want to prove here that we may begin to draw generalizations through multiple case-study comparisons. A composition work is under progress. Obviously, mapping of the ability of irrigated areas to “receive” water-conservation technologies is very ambitious. We finally want to open a discussion about the potential development of some kind of digital platform which would be dedicated to the observation of sustainability narratives, that may help analyze and represent sociotechnical dynamics and model future trajectories.

How to cite: Daudin, K., Belaud, G., Bouzidi, Z., Leauthaud, C., Lejars, C., and Schwien, L.: A social-physical approach to question the scaling of local innovations for improving agricultural water management in the Mediterranean, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16137, https://doi.org/10.5194/egusphere-egu24-16137, 2024.

Water regulators in England and Wales have called on water companies to meet higher standards of supply resilience in response to growing pressures from climate change, environmental needs and growth whilst still maintaining affordability. New national and regional governance structures have been established with the aim of enabling better collaboration across regulators, water companies (also known as public water supply (PWS) abstractors), other abstractors (non-PWS), and wider stakeholders to find and deliver the most efficient and robust water supply infrastructure schemes and demand initiatives.

This study uses qualitative data from interviews, workshops, observations, and planning documents. It identifies successes (e.g., increased ambition, improved consistency, collaboration, and nationally consistent water transfers) and failures (e.g., uncertainty, complexity, and lack of investment frameworks beyond PWS). To address gaps, a phased approach towards an explicit multi-scale governance framework is recommended, starting with national program management and trust-building across regulators, PWS, non-PWS, and stakeholders.

If new forums are set up to improve water resources planning there are difficult choices at each level regarding form, function and funding that require consideration of trade-offs, possible unintended consequences, and feasibility within the constraints of broader structures of decision-making and politics. A process of information gathering and engagement is necessary to bring on board relevant stakeholders. This engagement would provide insight on how best to implement the proposed collaborative multi-scale architecture, and would help clarify (1) the vision, (2) the approach, (3) appropriate metrics and performance indicators, (4) the compliance model, and (5) reporting requirements etc.

Decision-makers will always face gaps in understanding, new issues will continue to arise, and approaches and methods will continually evolve. Therefore, it is important to build adaptive structures of collaboration and scrutiny that can accommodate the changing and imperfect landscape. Transparency is at the core of this challenge, enabling feedback loops to (1) improve our understanding supported by evidence, and therefore (2) refine our objectives, and (3) the rules and governance required to achieve them.

As lessons are learnt through transparent, collaborative engagement with stakeholders across scales, the framework can be built upon to enable a more informed transition to adaptive, integrated water management at multiple scales.

How to cite: Leonard, A., Amezaga, J., Blackwell, R., Lewis, E., and Kilsby, C.: Collaborative mutli-scale water resources planning in England and Wales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-30, https://doi.org/10.5194/egusphere-egu24-30, 2024.

Water scarcity is a major constraint to agricultural productivity, food security, and economic development, in particular in low- and middle-income countries in regions such as Sub-Saharan Africa (SSA). However, our ability to effectively design, target, and implement interventions to reduce agricultural water insecurity is limited by a lack of data on the locations, dynamics, and outcomes of irrigated croplands in these regions. In this talk, we demonstrate how satellite remote sensing can be combined with machine learning methods to develop continuous fine-resolution maps of irrigated cropland areas in data-sparse environments distributed across SSA. Our results demonstrate that past large-scale irrigation projects initiated by governments and donors in SSA have failed to deliver on promises of agricultural expansion and intensification. In contrast, our mapping shows a more rapid recent growth in small-scale informal irrigation in SSA, typically initiated by farmers themselves and outside of official irrigation infrastructure and monitoring systems. We contextualise the economic, political, and social drivers of these historic irrigated cropland dynamics in SSA, while also discussing some of the opportunities and challenges that exist for mainstreaming use of satellite-based monitoring in future water management and policy in SSA.

How to cite: Foster, T., Higginbottom, T., Adhikari, R., and Redicker, S.: Satellite-based monitoring of irrigated cropland dynamics in data-sparse environments, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3886, https://doi.org/10.5194/egusphere-egu24-3886, 2024.

Many of the 500+ internationally shared aquifers are rapidly depleting but poorly regulated with less than 10 international treaties focusing on shared groundwater. The common-pool nature of groundwater has long been identified as an important complicating factor.  Pumping by any user increases pumping costs for all users by decreasing groundwater levels throughout the aquifer. This creates a tragedy of the commons, where all users have incentives to over-pump, thus prematurely depleting the resource. While this mechanism is well documented in domestic aquifers, large geographic distances between demand centers and heterogeneous economic and hydrogeologic conditions on either side of the border affects  incentives to over-pump in transboundary aquifers.   Whether -- and where -- common-pool incentives might lead to the premature depletion of transboundary aquifers remain poorly understood. 

We fill these gaps by combining remote sensing and large scale hydrologic and agricultural modeling datasets in a global analysis of known transboundary aquifers. We first evaluate the proportion of global irrigation water demand that is sourced from transboundary aquifers, and the proportion of these withdrawals associated with unsustainable pumping. We then identify regions, where unsustainable irrigation arises close enough to a political border to affect transboundary groundwater levels and pumping costs. Finally, we leverage recent theoretical results to identify the subset of these regions where heterogeneous economic conditions on either side of the border creates substantial incentives to over-pump. Results provide key insights on the role played by common-pool overdraft incentives on the premature depletion of transboundary aquifers and identify hotspots where international groundwater regulation is most urgently needed. 

How to cite: Muller, M. F., Hung, F., Davis, K., and Chiarelli, D.: Do tragedies of the commons contribute to the premature depletion of transboundary aquifers?, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-1816, https://doi.org/10.5194/egusphere-egu24-1816, 2024.

The latest update on planetary boundaries states both the blue and green freshwater change are beyond the safe operating space for the first time since the initial findings in 2009. Moreover, agricultural water use, which nowadays accounts for about two-thirds of global freshwater resources, is projected to increase by 2080. Under this scenario, river basin management plans include short-term crop water requirements projections. The presented abstract therefore proposes a remote sensing-based approach combined with climate change scenarios to provide short-, medium- and long-term green and blue crop water use (CWU) projections at 5 different European locations for irrigated maize.

The methodological framework for the Remote Sensing-based Agricultural Water Accounting  Projections (RS-AWA^↑) here presented is based on: a) using current and locally adapted crop behaviour monitored through remote sensing Sentinel 2 satellite images time series to derive NDVI crop pattern profile; b) using daily future climate projections (temperature and precipitation) based on an ensemble of 4 different Regional Climate Models that are driven by 3 different Global Climate Models, under the Representative Concentration Pathways (RCP) 4.5 and RCP 8.5; c) combining actual crop behaviour and daily climate projections in a Remote Sensing-based Soil Water Balance based on FAO56 to obtain both the green and blue CWU along short-, medium- and long-term periods; and d) obtaining changes in CWU regarding the baseline period. It was applied for irrigated maize within the Júcar River Basin (Spain), the Isonzo River Basin (Italy), the Soča River Basin (Slovenia), the Pinios River Basin (Greece) and the Dolj municipality (Lower Danube River Basin, Romania).

The 5 locations' results showed a common decline in the green CWU and a rise in the blue CWU, indicating lower CWU from precipitation events with the consequent increase in blue CWU from groundwater or superficial reservoirs, hence more irrigation requirements. By location, Pinios and Júcar present the lower increasements in irrigation requirements ranging from 6 to 10 % (RCP 4.5) and 10 to 17 % (RCP 8.5), followed by the Dolj location that ranges from 15 to 20 % (RCP 4.5) and 10 to 17 % (RCP 8.5), then the Isonzo location where ranges from 26 % (RCP 4.5) and 14 to 59 % (RCP 8.5), and finally the highest increasements corresponds to the Soča location that ranges from 45 to 73 % (RCP 4.5) and 50 to 147 % (RCP 8.5).

The presented results incorporate to the climate change family results and indicators, a locally adapted crop pattern derived from actual NDVI time series that will support better knowledge to water managers, as it could be adapted to the crops that are most interested in their managing areas, as we did in the project that support these research, the EU Horizon 2020 project REXUS (Managing Resilient Nexus Systems Through Participatory Systems Dynamics Modelling), in which stakeholders from water user associations to river basin water managers are evaluating the information. Finally, the authors acknowledge the contribution of land use map providers for irrigated maize in each of the locations considered.

How to cite: Garrido-Rubio, J., González-Piqueras, J., Osann, A., Antoniadou, M., Papadaskalopoulou, C., and Tassopoulos, D.: Remote Sensing-based Agricultural Water Accounting Projections for irrigated maize under different climate change scenarios in 5 European locations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7777, https://doi.org/10.5194/egusphere-egu24-7777, 2024.

Being the most extensive water infrastructure in Spain, the future of the Tagus-Segura interbasin transfer is contested by climate change and increasing controversy regarding its use. It is a crucial infrastructure for regional socioeconomic development since it significantly contributes to the sustainability of one of Europe's most important agricultural areas. Diverse stakeholders' interests have generated conflicts impacting its decision-making processes. Several regulations have established maximum transferable volumes in the last decades depending on water availability and demands in the involved basins. However, the volumes transferred do not only account for those limits but also include expert criteria and ad-hoc considerations, making it complex to predict them. Artificial intelligence emerges as an effective solution to address this challenge and to reconcile all the factors affecting its current operating rules.

To this end, this contribution combines artificial intelligence (fuzzy logic) with climate change scenarios and hydrological and water resource management models to predict future water transfers from the upper Tagus (donor basin) to the Segura (receiver basin). Climate change scenarios refer to five CMIP6 (Coupled Model Intercomparison Project Phase 6) climate models and four scenarios: historical (1979-2014), SSP126, SSP370, and SSP585 (2015-2100). Using their meteorological projections, the eco-hydrological model TETIS is used to obtain future time series of streamflows in response to them. The current operation of the water transfer is inferred through fuzzy logic systems that take into account the hydrological discharge of the upper Tagus estimated by TETIS, the storage level of the upper Tagus reservoirs (Entrepeñas and Buendia), the storage levels of the rest of the Tagus and the Segura basins, the regulatory limits, and the month of the year. The results show how foreseen streamflows in the upper Tagus would affect the transfer, providing valuable information for water planning in both basins, particularly in the Segura, for its adaptation to any decrease in water received from the Tagus basin.

Acknowledgments

This study has received funding from the European Union's Horizon 2020 research and innovation programme under the GoNEXUS project (grant agreement No 101003722); and from the SOS-WATER project under the European Union's Horizon Europe research and innovation programme under grant agreement No. 101059264.

How to cite: Lagos-Castro, I., Pulido-Velazquez, M., Macian-Sorribes, H., Mason, S., and Aranda-Domingo, J.: Assessing climate change impacts in the Tagus-Segura water transfer (Spain) through artificial intelligence, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-17698, https://doi.org/10.5194/egusphere-egu24-17698, 2024.

      Trade linkages within the supply chain can be mapped onto a complex network. Disruptions in regional resource supplies (i.e., water scarcity) have the potential to generate industrial losses in remote areas due to the interconnected flow of goods and services. While numerous studies have assessed the economic and virtual water supply networks, they assumed rapid and linear transmission of industrial risks in the network, without modeling the transmission process and vulnerability between nodes. Such oversights can lead to the misestimation of risks, especially in the context of climate change. Therefore, it is urgent to construct a cascading model for the supply economic and water supply network that consider step-by-step avalanche in nodes, to help identify vulnerable sectors and mitigate economic risks.

      In this research, we utilize the 2017 multi-region environmental multiregional input-output (E-MRIO) table in China to construct a comprehensive multilayer network. Each province is represented as a distinct layer within this network, incorporating 42 economic sectors(nodes). These layers and nodes are interconnected through trade linkages. To simulate the cascade process, we introduce the concept of net fragility for a node, calculated as the difference between the ratio of the sum of net inflows and net outflows of a node to its own total output and the threshold. Once a node fails (i.e., net fragility less than 1) the cascade process is triggered, then we quantify the total number of collapsed adjacent nodes, i.e., avalanche size. The bigger avalanche size refers to the province-sector higher vulnerability to economic shocks. Furthermore, we use the risk probability of province-sectors suffering from water scarcity as external shocks to describe the supply network response process under different water quantity and quality constraints. By comparing with the economic impact results, we can further identify vulnerable nodes affected by the dual restraints of water scarcity and economic shocks.

How to cite: Li, J., Wu, K., Liu, M., Yang, J., Shan, Y., and Bi, J.: Mapping the water-economic cascading risks within a multilayer network of supply chains, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8398, https://doi.org/10.5194/egusphere-egu24-8398, 2024.

Globally, industries act as one of the key consumers of water, driving a critical need for responsible and sustainable water usage practices to address the escalating water demands. Despite the industry’s significant impact on water availability, a notable void exists in the accessibility of precise, reliable, and readily available hydrological data essential for understanding water-related risks and formulating effective mitigation strategies. In addressing the challenge of water risk identification and management within the industrial sector, Waterplan, a Y-Combinator startup and science-driven B2B SaaS company, has developed a user-friendly and value-driven water risk framework. This comprehensive water risk framework assesses three distinct water risks: scarcity, flooding, and water quality. Each category of risk is evaluated using a set of hydrologically relevant basin-level indicators. The framework incorporates a total of 17 indicators (including 5 dynamic ones), derived from ground-based and remotely sensed observations or advanced state-of-the-art hydrological models. Using this framework, Waterplan ranked over 53,000 basins across the globe for various water risks, aiding basin assessment and strategic decision-making for industrial clients. The ranking of basins involves an evaluation of historical average hydrologic characteristics from 1988 to 2017 (called baseline), coupled with an analysis of the historical (1988 to 2023) and recent (2018 to 2023) trends (called direction) in these attributes. Both components are established through the application of globally comparable thresholds. Moreover, the scores for each risk type (scarcity, flood, and water quality) were computed using a default equal-weight ensemble method, with the added flexibility to customize the weights of indicators according to the specific client requirements. The framework finds applications in strategic basin/facility prioritization, resource allocation, raw material sourcing decisions, and evidence-based budgeting. Notably, the framework demonstrated strong agreement with locally collected data, showcasing its reliability. While designed for industrial clients, the framework's versatility suggests potential value for water managers and policymakers seeking insights into basin hydrological conditions. This holistic risk framework, integrating advanced technology, scientific rigor, and user-friendly design, can revolutionize how we understand, assess, and manage industrial water risks on a global scale.

How to cite: Mohan, C., Begue, A., Misa, J., Servia, H., and Comercio, M.: Revolutionizing water risk management in industry: A comprehensive framework for strategic basin prioritization, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6257, https://doi.org/10.5194/egusphere-egu24-6257, 2024.

As cities globally face climate change risks, they are increasingly adopting innovative climate adaptation policies, including 'Nature-based Solutions (NBS)' and advanced planning and social policies. However, the implementation of these strategies by local governments remains limited. Integrating these strategies into urban governance requires interdisciplinary collaboration and inclusive interventions to overcome existing governance inertia (Hölscher et al., 2023). Effective policymaking must align these innovative strategies with new narratives considering wider urban development goals, fostering synergies and co-benefits (Keith et al., 2023). Multi-objective optimisation models play a key role here, involving stakeholders in generating and evaluating alternative land use proposals within spatial decision-making processes. These models focus on balancing competing objectives, using Pareto-optimal solutions to find practical compromises in urban development.

Our focus is on exploring (1) flood-resilient land use and (2) the compatibility of land uses between prioritising flood resilience and compactness, through scenario-based analysis using land use spatial optimisation (LUSO). The target is Toyohashi City, a central city in Japan, which confronts issues dealing with flood risk and strategic land use under the shrinking population. In previous LUSO models, the unit of each objective is different; therefore, it has been difficult to discuss its marginal cost (Yoon et al., 2017). To address this issue, our model adopts the city's 'profit' as a scalarised objective of LUSO, encompassing revenue and expenses influenced by flood resistance, compactness, and minimal land use conversions. (1) Flood-resilient land use is analysed under two types of hazard scenarios: 'uncertain' and 'deterministic'. These scenarios reflect our understanding of which part of the levee might break during a flood. In the 'uncertain' scenario, the specific point of the levee breach is unknown, leading the city to incorporate flood considerations into land use planning across the entire area. Conversely, the 'deterministic' scenario operates on the assumption that the weak point in the levee is known, thereby focusing hazard considerations only on the area surrounding the anticipated breach point. (2) The compatibility of land uses is examined by comparing the land use pattern of ‘never considering compactness’ with that of ‘never considering flood occurrence’. As a result of two analyses, we found that the 'uncertain' scenario is not better than the 'deterministic' scenario in terms of the city’s total 'profit': ensuring equity of flood hazard risk may be costly. In addition, the compatibility analysis identified specific areas that could confront trade-offs between flood avoidance and urban development. This research contributes to understanding the complex dynamics of land use planning in the context of climate change adaptation and demographic shifts.

Hölscher et al. (2023) ‘Strategies for Mainstreaming Nature-Based Solutions in Urban Governance Capacities in Ten European Cities’. Npj Urban Sustainability 3, no. 1. https://doi.org/10.1038/s42949-023-00134-9.

Keith et al. (2023). ‘A New Urban Narrative for Sustainable Development’. Nature Sustainability 6, no. 2: 115–17. https://doi.org/10.1038/s41893-022-00979-5.

Yoon et al. (2017) ‘Multi-Objective Land-Use Allocation Considering Landslide Risk under Climate Change: Case Study in Pyeongchang-Gun, Korea’. Sustainability (Switzerland) 9, no. 12. https://doi.org/10.3390/su9122306.

How to cite: Nakai, F., Kito, S., and Okubo, K.: Analysing Trade-offs and Synergies in Land Use for Flood Resilience and Compactness, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13450, https://doi.org/10.5194/egusphere-egu24-13450, 2024.

As the longest river in Asia, the Yangtze River has shown its impact on human societies with floods recorded since 12^th century. In 1931, the Yangtze River has manifested its force again with one of the deadliest floods ever recorded in Chinese history, causing 422,499 deaths, damages to more than 25.2 million people and 58.7 billion m² farmland. Similar flood occurred again in 1954, resulting in 31,762 deaths, damages to 18.9 million people and 31.7 billion m² farmland. Researches have shown that 1954 flood being larger and higher compared to 1931 flood. However, it is still unclear for what reason that a more severe flood leading to less damage. Here we assumed such discrepancy could be ascribed to drastic society transformation in 1930s and 1950s (e.g., increase of absentee landlords in 1930s, and the land reform movement in 1950s). To further understand its effect on flood responses among farmers, an agent-based model named Farmer Landlord Inundation Production (FLIP) was developed. The model was constructed by simulating each farmer’s movement decision during floods based on different hydrological and economic circumstances. Then it was applied to the simulation of multiple villages in Hubei Province (along the mid-reach of Yangtze River) on the basis of reconstructed daily inundation from July to September, 1931 and 1954. Our results have shown that the farmers’ mitigation decision was highly sensitive to the relief amount and distribution timing, indicating a possible decrease of refugees from 70% to 15% between 1931 and 1954. Overall, we demonstrate how society transformation are likely to affect the damage of and response to floods in a different (sometimes more important) way from traditional countermeasures in modern Chinese history. We anticipate our research to be a starting point towards deeper understanding of human and hazard, and the knowledge of which is likely to be applicable to many other regions and times.

How to cite: Liu, C., Kawasaki, A., and Shiroyama, T.: Exploring the effect of abrupt society transformation on flood responses among farmers in China using an agent-based model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6870, https://doi.org/10.5194/egusphere-egu24-6870, 2024.