Intermittent rivers and ephemeral streams: what water managers need to know

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ScenaLand: a simple methodology for developing land use and management scenarios

Scenarios serve science by testing the sensitivity of a system and/or society to adapt to the future. In this study, we present a new land use scenario methodology called ScenaLand. This methodology aims to develop plausible and contrasting land use and management (LUM) scenarios, useful to explore how LUM (e.g. soil and water conservation techniques) may afect ecosystem services under global change in a wide range of environments. ScenaLand is a method for constructing narrative and spatially explicit land use scenarios that are useful for end-users and impact modellers. This method is innovative because it merges literature and expert knowledge, and its low data requirement makes it easy to be implemented in the context of inter-site comparison, including global change projections. ScenaLand was developed and tested on six diferent Mediterranean agroecological and socioeconomic contexts during the MASCC research project (Mediterranean agricultural soil conservation under global change). The method frst highlights the socioeconomic trends of each study site including emerging trends such as new government laws, LUM techniques through a qualitative survey addressed to local experts. Then, the method includes a ranking of driving factors, a matrix about land use evolution, and soil and water conservation techniques. ScenaLand also includes a framework to develop narratives along with two priority axes (contextualized to environmental protection vs. land productivity in this study). In the context of this research project, four contrasting scenarios are proposed: S1 (business-as-usual), S2 (market-oriented), S3 (environmental protection), and S4 (sustainable). Land use maps are then built with the creation of LUM allocation rules based on agroecological zoning. ScenaLand resulted in a robust and easy method to apply with the creation of 24 contrasted scenarios. These scenarios come not only with narratives but also with spatially explicit maps that are potentially used by impact modellers and other endusers. The last part of our study discusses the way the method can be implemented including a comparison between sites and the possibilities to implement ScenaLand in other contexts.info:eu-repo/semantics/publishedVersio

River ecosystem conceptual models and non‐perennial rivers: A critical review

Conceptual models underpin river ecosystem research. However, current models focus on continuously flowing rivers and few explicitly address characteristics such as flow cessation and drying. The applicability of existing conceptual models to nonperennial rivers that cease to flow (intermittent rivers and ephemeral streams, IRES) has not been evaluated. We reviewed 18 models, finding that they collectively describe main drivers of biogeochemical and ecological patterns and processes longitudinally (upstream-downstream), laterally (channel-riparian-floodplain), vertically (surface water-groundwater), and temporally across local and landscape scales. However, perennial rivers are longitudinally continuous while IRES are longitudinally discontinuous. Whereas perennial rivers have bidirectional lateral connections between aquatic and terrestrial ecosystems, in IRES, this connection is unidirectional for much of the time, from terrestrial-to-aquatic only. Vertical connectivity between surface and subsurface water occurs bidirectionally and is temporally consistent in perennial rivers. However, in IRES, this exchange is temporally variable, and can become unidirectional during drying or rewetting phases. Finally, drying adds another dimension of flow variation to be considered across temporal and spatial scales in IRES, much as flooding is considered as a temporally and spatially dynamic process in perennial rivers. Here, we focus on ways in which existing models could be modified to accommodate drying as a fundamental process that can alter these patterns and processes across spatial and temporal dimensions in streams. This perspective is needed to support river science and management in our era of rapid global change, including increasing duration, frequency, and occurrence of drying.info:eu-repo/semantics/publishedVersio

Quantifying Earth system interactions for sustainable food production via expert elicitation

Several safe boundaries of critical Earth system processes have already been crossed due to human perturbations; not accounting for their interactions may further narrow the safe operating space for humanity. Using expert knowledge elicitation, we explored interactions among seven variables representing Earth system processes relevant to food production, identifying many interactions little explored in Earth system literature. We found that green water and land system change affect other Earth system processes strongly, while land, freshwater and ocean components of biosphere integrity are the most impacted by other Earth system processes, most notably blue water and biogeochemical flows. We also mapped a complex network of mechanisms mediating these interactions and created a future research prioritization scheme based on interaction strengths and existing knowledge gaps. Our study improves the understanding of Earth system interactions, with sustainability implications including improved Earth system modelling and more explicit biophysical limits for future food production

How uncertainties are tackled in multi-disciplinary science? A review of integrated assessments under global change

Integrated assessment (IA) modelling can be an effective tool to gain insight into the dynamics of coupled earth system (land use, climate etc.) and socio-economic components. Quantifying and communicating uncertainties is a challenge of any scientific assessment, but is here magnified by the complex and boundary-crossing nature of IA models. Understanding the dynamics of coupled earth and socio-economic systems require data and methods from multiple disciplines, each with its own perspective on epistemological uncertainties (parametric and structural uncertainties), and its own protocols for assessing uncertainty. During the Paris Agreement, the lack of uncertainty analyses (UA) in IAs was risen (Rogelj et al. 2017) and calls for close collaboration of scientists coming from different fields. In this study, we review how uncertainties are tackled in a range of science disciplines that are related to global change including climate, hydrology, energy and land use, and which contribute to IA modelling. We conducted a meta-analysis to identify the contributing disciplines, and review which type of uncertainties are assessed. We then describe sources of uncertainty (e.g. parameter values, model structure), and present opportunities for improved assessment and communication of uncertainties in IA modelling. We show in our meta-analysis that parametric uncertainty is the uncertainty analysis that has been applied the most, while structural uncertainty is less commonly applied, with the exception of the energy scientific discipline. We finish our study with key recommendations to improve uncertainty analysis such as including risk analysis. By embracing uncertainties, resilient and effective solutions for climate change mitigation and adaptation could be better communicated, identified and implemented.info:eu-repo/semantics/publishedVersio

Soil erosion control in a pasture‐dominated Mediterranean mountain environment under global change

Soil erosion control is critical to global food production and ecosystem health worldwide, and particularly in the Mediterranean region, which is prone to erosion and is expected to be strongly affected by climatic and anthropogenic changes. In this paper, we explore how land use and management (LUM) can mitigate climate change impacts and increase agricultural attractiveness in pasture-dominated Mediterranean mountain environments. One originality of the proposed research is to combine LUM scenarios incorporating environmental and socio-economic behaviour with distributed process-based modelling to simulate the impacts of global change. Specifically, soil erosion for different combinations of current and plausible future climate and LUM conditions were simulated on a small watershed located in eastern Sicily (Italy) using the LandSoil model. LUM scenarios were established as a modulation of environmental protection and agricultural production/diversification. The main management distinctions tested in this paper included intensive versus extensive practices for pasture, and conventional versus conservative practices for cereals and orchards. Simulations showed that the impact of climate change was very low and not significant in the studied watershed (i.e., −1.78% of erosion on average). Under current climate and compared to the baseline, LUM scenarios reported an increase in erosion for the business-as-usual (S1, +6.0%), market-oriented (S2, +57.2%) and sustainability-oriented (S4, +0.9) scenarios, respectively, whereas the nature-oriented scenario led to a slight reduction in erosion (S3, −11.3%). Our results also emphasised that agricultural diversification coupled with adaptations in practices and management can improve the attractiveness of agriculture in pasture-dominated environments while maintaining soil protection at an acceptable level.info:eu-repo/semantics/publishedVersio

Integrating a hydrological model into regional water policies: co-creation of climate change dynamic adaptive policy pathways for water resources in southern Portugal

Irrigation is essential for a large part of Mediterranean agricultural systems, but scarce resources may cause conflicts between agricultural and domestic uses. These conflicts might be exacerbated by climate change, which could bring a drier climate and thus increase irrigation water demands while lowering supplies. These issues were addressed when designing a climate change adaptation plan for water resources in the Algarve region (southern Portugal), which was co-created between hydrologists and local stakeholders and policy-makers, by using the Dynamic Adaptive Policy Pathways (DAPP) approach to synthetize and communicate the results from hydrological modelling of future scenarios. The evolution of water availability and irrigation demands for key water assets in Algarve (southern Portugal) were simulated until 2100 for climate scenarios RCP4.5 and RCP8.5, using a modified version of Thornthwaite-Mather. The results show an increase in water stress, mainly in the RCP8.5 scenario. The results and need for adaptation were discussed with local and regional decision-makers and other stakeholders, and a set of adaptation measures was agreed upon. The discussed adaptation measures were then modelled and integrated the design of tailor-made DAPP. Finally, decision-makers and stakeholders were presented with DAPP and selected the most suitable and political reliable adaptation pathway that tackles projected climate change impacts in water resources until the end of the 21 st century. Stakeholders showed a strong preference for incremental and distributed small-scale measures, including the promotion of water use efficiency and landscape water retention, to large-scale measures such as wastewater recycling or new dams. A decrease in irrigation water use for agriculture was not considered socially desirable. Desalination was considered too costly for irrigation in the short term but kept in reserve in case other measures fail to keep water supplies at an acceptable level.info:eu-repo/semantics/publishedVersio

Water scarcity in Brazil: part 2—uncertainty assessment in regionalized characterization factors

Purpose: Despite recommendations, uncertainty results are rarely incorporated in Life Cycle Assessment (LCA) studies, especially regarding characterization factors (CF). Part 1 of this study conducted AWARE CF regionalization for Brazil, concluding that the Semiarid region had maximum scarcity values. The goal of this study is to evaluate the uncertainties of regionalized AWARE CF in the Semiarid region. Methods: Data used to obtain the AWARE BR CF for Brazil were qualitatively and quantitatively assessed. An adapted Pedigree Matrix was adopted to assess qualitative uncertainties. Classical statistical analysis was used for quantitative uncertainty assessment, and 10,000 Monte Carlo simulations were computed for uncertainty propagation. Results and discussion: Qualitative results indicated that the natural flow’s parameter was very uncertain due to poor spatial correlation and low reliability, as it is based on empirical models. Quantitative results showed that water availability data, which had large temporal variability, typical of the Brazilian Semiarid region, was the main responsible for uncertainties in input data. Area uncertainty had a good performance in both qualitative and quantitative assessments. Regarding output data, moderate CF were found to be more uncertain, while more extreme CF exhibited lower variation, corroborating with previous analyses. Moreover, the adoption of shorter datasets led to a reduction in average and standard deviation values for CF. Conclusion: Findings from this study showed two important reasons why the quantitative and qualitative assessments should be conducted simultaneously. The first one was to avoid bias, as availability data and natural flow performed differently in each evaluation. The second one was to confirm results, as the area proved to be very little uncertain in both assessments. An adaptation of Pedigree Matrix and a penalty factor for missing data could be used as a base for quantitative uncertainty parameters for LCIA. Generating SD and k-factor was very positive in terms of results for AWARE method and comparison with other methods. Both indicators had similar results and led to a common conclusion: uncertainties are mainly low and very low for AWARE BR CF in the Semiarid region.info:eu-repo/semantics/publishedVersio

Water scarcity in Brazil: part 1—regionalization of the AWARE model characterization factors

Purpose This paper presents the regionalized water scarcity characterization factors (CFs) of the available water remaining (AWARE) model, which was found by a previous study, on the water scarcity in Brazil, to be the most indicative characterization model for the water-scarce regions in Brazil. We used the national database and hydrographic delimitations defined by the National Water Agency (Agência Nacional de Águas — ANA) to generate the regionalized AWARE BR CFs. Methods The CFs were regionalized by hydrographic delimitations used by ANA: (i) State Hydrographic Units (SHU) and (ii) Hydrographic Regions (HR). These AWARE BR CFs were compared with the factors originally proposed by WULCA (2018) and with the Scarcity Index used by ANA to identify the scarcest regions in the country. Finally, the AWARE and AWARE BR factors were applied to a case study of Brazilian melons, evaluating the regionalization effects on the results of water scarcity analysis. Results and discussion The AWARE BR CFs demonstrate most consistency with the regions recognized by ANA to have water scarcity problems, such as the semiarid region. Approximately 12% of the SHUs exhibited maximum water scarcity (CF = 100) during the entire year, while 11% presented minimum scarcity factors (CF = 0.1). The comparison of hydrologic data from ANA with those from WaterGAP indicated that water availability was overestimated in WaterGAP, while demand was underestimated in different basins. The comparison of AWARE BR CFs with ANA Scarcity Index values indicated more similarity (smaller residual error) than the comparison of AWARE BR CFs with AWARE. The case study regarding the impact of water scarcity on melons showed a significant difference between characterization factors and, consequently, in the values of impact. Conclusions AWARE BR factors generated with national characterization data are adapted to the different regions of Brazil, exhibiting higher sensitivity to the semiarid region. This regionalization provided a more accurate representation of the scarcity in smaller basins located in larger basins, characterized by large climate variation.info:eu-repo/semantics/publishedVersio