Predicting hydrologic flows under climate change: The Tâmega Basin as an analog for the Mediterranean region

Water Quality Predictions Through Linear Regression - A Brute Force Algorithm Approach

Linear regression is one of the oldest statistical modeling approaches. Still, it is a valuable tool, particularly when it is necessary to create forecast models with low sample sizes. When researchers use this method and have numerous potential regressors, choosing the group of regressors for a model that fulfills all the required assumptions can be challenging. In this sense, the authors developed an open-source Python script that automatically tests all the combinations of regressors under a brute-force approach. The output displays the best linear regression models, regarding the thresholds set by users for the required assumptions: statistical significance of the estimations, multicollinearity, error normality, and homoscedasticity. Further, the script allows the selection of linear regressions with regression coefficients according to the user's expectations. This script was tested with an environmental dataset to predict surface water quality parameters based on landscape metrics and contaminant loads. Among millions of possible combinations, less than 0.1 % of the regressor combinations fulfilled the requirements. The resulting combinations were also tested in geographically weighted regression, with similar results to linear regression. The model's performance was higher for pH and total nitrate and lower for total alkalinity and electrical conductivity.•A Python script was developed to find the best linear regressions within a dataset.•Output regressions are automatically selected based on regression coefficient expectations set by the user and the linear regression assumptions.•The algorithm was successfully validated through an environmental dataset.

Identifying monitoring information needs that support the management of fish in large rivers

Management actions intended to benefit fish in large rivers can directly or indirectly affect multiple ecosystem components. Without consideration of the effects of management on non-target ecosystem components, unintended consequences may limit management efficacy. Monitoring can help clarify the effects of management actions, including on non-target ecosystem components, but only if data are collected to characterize key ecosystem processes that could affect the outcome. Scientists from across the U.S. convened to develop a conceptual model that would help identify monitoring information needed to better understand how natural and anthropogenic factors affect large river fishes. We applied the conceptual model to case studies in four large U.S. rivers. The application of the conceptual model indicates the model is flexible and relevant to large rivers in different geographic settings and with different management challenges. By visualizing how natural and anthropogenic drivers directly or indirectly affect cascading ecosystem tiers, our model identified critical information gaps and uncertainties that, if resolved, could inform how to best meet management objectives. Despite large differences in the physical and ecological contexts of the river systems, the case studies also demonstrated substantial commonalities in the data needed to better understand how stressors affect fish in these systems. For example, in most systems information on river discharge and water temperature were needed and available. Conversely, information regarding trophic relationships and the habitat requirements of larval fishes were generally lacking. This result suggests that there is a need to better understand a set of common factors across large-river systems. We provide a stepwise procedure to facilitate the application of our conceptual model to other river systems and management goals.

Sub-Hourly Precipitation Extremes in Mainland Portugal and Their Driving Mechanisms

Sub-hourly heavy precipitation events (SHHPs) frequently underlie major meteorological hazards, but their comprehensive analysis is still lacking in Portugal. A 71-weather-station dataset for 2000–2020 is used in this article to (1) diagnose SHHPs corresponding to a 10-min precipitation event of at least 5.0 mm, (2) characterize their spatial-temporal distribution, and (3) identify their associated synoptic-scale conditions. Two synoptic types are associated with SHHPs: remote (RemL) and regional (RegL) low-pressure systems. RegL SHHPs display two marked maxima in spring and autumn, while RemL SHHPs show a single maximum in autumn. Most RegL events occur in the afternoon/evening, while RemL events show a slight bias toward midday occurrences. In the case of RemL, the wind is stronger for 2 to 3 h before and during SHHPs, veers from 180° to 210° near the event, the pressure decreases until 20 min before the event, and the wet-bulb temperature decreases around the time of the event and remains low, thus reflecting cold-front passages. For RegL, maximum winds coincide with precipitation peaks, and the wet-bulb temperature briefly decreases in association with downdrafts. A preliminary relationship between the SHHPs and mesoscale convective systems is established by detecting sudden surface-pressure surges, which are indicative of mesohighs caused by evaporatively cooled downdrafts. A calendar of mesohigh episodes linked to SHHPs is provided herein and their signatures are illustrated for the “Pedrógão-Grande” fires. Indicators of several downbursts, cold pools, and mesohighs were identified by the AROME forecast. This first, systematized analysis paves the way to identifying dynamic precursors, enabling their integration into early warning systems and climate projections.

On the development of a regional climate change adaptation plan: Integrating model-assisted projections and stakeholders' perceptions

Climate change is expected to have strong social-ecological implications, with global but especially regional and local challenges. To assess the climatic vulnerability of a given territory, it is necessary to evaluate its exposure to climate change and its adaptive capacity. This study describes the development of an Action Plan for Adapting to Climate Change in the Tâmega and Sousa Region, a mountainous inter-municipal community in the North of Portugal. The goals were to identify the main impacts of climate change on water resources, agriculture, forests, biodiversity, and socioeconomic sectors, as well as to develop a plan, merging local and scientific knowledge through a transdisciplinary lens. This study describes an approach that combines modelling methods, applied in the different sectors, and participatory methods, based on the analysis of the perceptions of local actors. Results indicate that the target region will experience a generalized increase in temperature and a decrease in precipitation, which will negatively impact all studied social-ecological dimensions. Overall, local business and institutional agents perceive the primary and tourism sectors as the most vulnerable in the region. The described framework demonstrates the engagement process between relevant scientific experts and local practitioners, as well as how it is critical to understand the impacts of climate change and to support the co-design of an adaptation plan, which in turn can guide political and economic decision-making towards effective implementation of the plan. In addition, the difficulties and challenges encountered during this process are discussed to support future plans and strategies for local adaptation.

A combined GIS-MCDA approach to prioritize stream water quality interventions, based on the contamination risk and intervention complexity

Water management decisions are complex ever since they are dependent on adopted politics, social objectives, environmental impacts, and economic determinants. To adequately address hydric resources issues, it is crucial to rely on scientific data and models guiding decision-makers. The present study brings a new methodology, consisting of a combined GIS-MCDA, to prioritize catchments that require environmental interventions to improve surface water quality. A Portuguese catchment, Ave River Basin, was selected to test this methodology due to the low water quality. First, it was calculated the contamination risk of each catchment, based on a GIS-MCDA using point source pressures, landscape metrics, and diffuse emissions as criteria. This analysis was compared to local data of ecological and chemical status through ANOVA and the Tukey test. The results showed the efficiency of the method since the contamination risk was lower for catchments under a good status and higher in catchments with a lower classification. In a second task, it was calculated the intervention complexity using a different GIS-MCDA. For this approach, it was chosen five criteria that condition environmental interventions, population density, slope, percentage of burned areas, Strahler order, and the number of effluent discharge sites. Both multicriteria methods were combined in a graphical analysis to rank the catchments intervention priority, subdividing the prioritization into four categories from 1st to 4th^, giving a higher preference for catchments with high contamination risk and low intervention complexity. As a result, catchments with a good status were dominantly placed under low intervention priority, and catchments with a lower ecological status were classified as a high priority, 1st and 2nd. In total, 248 catchments were spatially ranked, which is an essential finding for decision-makers, that are willing to safeguard the catchment water quality.

Modeling Climate Change Impacts on Water Balance of a Mediterranean Watershed Using SWAT+

The consequences of climate change on food security in arid and semi-arid regions can be serious. Understanding climate change impacts on water balance is critical to assess future crop performance and develop sustainable adaptation strategies. This paper presents a climate change impact study on the water balance components of an agricultural watershed in the Mediterranean region. The restructured version of the Soil and Water Assessment Tool (SWAT+) model was used to simulate the hydrological components in the Sulcis watershed (Sardinia, Italy) for the baseline period and compared to future climate projections at the end of the 21st century. The model was forced using data from two Regional Climate Models under the representative concentration pathways RCP4.5 and RCP8.5 scenarios developed at a high resolution over the European domain. River discharge data were used to calibrate and validate the SWAT+ model for the baseline period, while the future hydrological response was evaluated for the mid-century (2006–2050) and late-century (2051–2098). The model simulations indicated a future increase in temperature, decrease in precipitation, and consequently increase in potential evapotranspiration in both RCP scenarios. Results show that these changes will significantly decrease water yield, surface runoff, groundwater recharge, and baseflow. These results highlight how hydrological components alteration by climate change can benefit from modelling high-resolution future scenarios that are useful for planning mitigation measures in agricultural semi-arid Mediterranean regions.

Perceptions of Public Officers Towards the Effects of Climate Change on Ecosystem Services: A Case-Study From Northern Portugal

How institutional stakeholders perceive the supply and demand of ecosystem services (ES) under distinct contexts determines which planning actions are deemed priority or not. Public officers play a crucial role in social-ecological management and decision-making processes, but there is a paucity of research exploring their perceptions on ES supply and demand under a changing climate. We address this gap through an exploratory study that analyses the views of public officers on the potential impacts of climate-change related drivers on multiple ES in a major administrative region from Portugal (EU NUTS 3). We combined qualitative spatial data from participatory maps and semi-quantitative answers from questionnaire-based surveys with 22 officers from public institutions contributing to territorial planning. Contrary to other similar studies, public officers shared a common view on the importance of ES. This view aligns with scientific projections on how a changing climate is expected to influence ES in the region over the next decade. In agreement with other observations in Mediterranean regions, the most perceivably valued ES concerned tangible socio-economic benefits (e.g., periurban agriculture and wine production). Surprisingly, despite the region’s potential for cultural ES, and considering the impacts that climate change may hold on them, recreation and tourism did not seem to be embedded in the officers’ views. We explore the implications of our findings for territorial planning and social-ecological adaptation, considering that the way stakeholders manage the territory in response to climate change depends on the extent to which they are aware and expect to experience climatic consequences in the future.

Projected hydrologic changes over the north of the Iberian Peninsula using a Euro-CORDEX multi-model ensemble

This study explores the impacts of climate change on the hydrology of the headwater areas of the Duero River Basin, the largest basin of the Iberian Peninsula. To this end, an ensemble of 18 Euro-CORDEX model experiments was gathered for two periods, 1975-2005 and 2021-2100, under two Representative Concentration Pathways (RCP4.5 and RCP8.5), and were used as the meteorological forcings of the Variable Infiltration Capacity (VIC) during the hydrological modelling exercise. The projected hydrologic changes for the future period were analyzed at annual and seasonal scales using several evaluation metrics, such as the delta changes of the atmospheric and land variables, the runoff and evapotranspiration ratios of the overall water balance, the snowmelt contribution to the total streamflow and the centroid position for the daily hydrograph of the average hydrologic year. Annual streamflow reductions of up to 40% were attained in various parts of the basin for the period 2071-2100 under the RCP8.5 scenario, and resulted from the precipitation decreases in the southern subwatersheds and the combined effect of the precipitation decreases and evapotranspiration increases in the north. The runoff and the evapotranspiration ratios evinced a tendency towards an evaporative regime in the north part of the basin and a strengthening of the evaporative response in the south. Seasonal streamflow changes were mostly negative and dependent on the season considered, with greater detriments in spring and summer, and less intense ones in autumn and winter. The snowmelt contribution to the total streamflow was strongly diminished with decreases reaching -80% in autumn and spring, thus pointing to a change in the snow regime for the Duero mountains. Finally, the annual and seasonal changes of the centroid position accounted for the shape changes of the hydrograph, constituting a measure of seasonality and reflecting high correlations degrees with the streamflow delta changes.

Alteration of the Ecohydrological Status of the Intermittent Flow Rivers and Ephemeral Streams due to the Climate Change Impact (Case Study: Tsiknias River)

Climate change projections predict the increase of no-rain periods and storm intensity resulting in high hydrologic alteration of the Mediterranean rivers. Intermittent flow Rivers and Ephemeral Streams (IRES) are particularly vulnerable to spatiotemporal variation of climate variables, land use changes and other anthropogenic factors. In this work, the impact of climate change on the aquatic state of IRES is assessed by the combination of the hydrological model Soil and Water Assessment Tool (SWAT) and the Temporary Rivers Ecological and Hydrological Status (TREHS) tool under two different Representative Concentration Pathways (RCP 4.5 and RCP 8.5) using CORDEX model simulations. A significant decrease of 20–40% of the annual flow of the examined river (Tsiknias River, Greece) is predicted during the next 100 years with an increase in the frequency of extreme flood events as captured with almost all Regional Climate Models (RCMs) simulations. The occurrence patterns of hyporheic and edaphic aquatic states show a temporal extension of these states through the whole year due to the elongation of the dry period. A shift to the Intermittent-Pools regime type shows dominance according to numerous climate change scenarios, harming, as a consequence, both the ecological system and the social-economic one.

Current and Future Ecological Status Assessment: A New Holistic Approach for Watershed Management

The Paiva River catchment, located in Portugal, integrates the Natura 2000 network of European Union nature protection areas. Resorting to topography, climate and land-use data, a semi-distributed hydrological model (Hydrological Simulation Program–FORTRAN) was run in order to simulate the hydrological cycle of the river and its tributaries. The model was calibrated over a 25-year period and validated within a 31-year period. Its performance was verified by comparing the recorded and simulated daily flows. The values of the Nash–Sutcliffe coefficient of efficiency of 0.95 and 0.76, and coefficient of determination of 0.95 and 0.82, were achieved for calibration and validation, respectively, thus showing a quite satisfactory model performance. Subsequently, the climate change impacts on temperature and precipitation, as well as their extremes, and on the flowrates were also assessed for a future period (2041–2070) under two anthropogenic forcing scenarios (representative concentration pathways 4.5 and 8.5). A procedure for selecting the most relevant metrics for assessing the ecological condition of the Paiva River was developed based upon a set of 52 invertebrate families sampled. Correspondence analyses were carried out for biological datasets (traits/metrics) with physicochemical and land use/land cover matrices separately. Out of all variables, water quality and flow and agriculture land use explained most of the variance observed. The integrated analysis undertaken in the present study is an important advance when compared to previous studies and it provides key information to stakeholders and decision-makers, particularly when planning suitable adaptation measures to cope with changing climates in the forthcoming decades.

Selection of Effective GCM Bias Correction Methods and Evaluation of Hydrological Response under Future Climate Scenarios

Global climate change is presenting a variety of challenges to hydrology and water resources because it strongly affects the hydrologic cycle, runoff, and water supply and demand. In this study, we assessed the effects of climate change scenarios on hydrological variables (i.e., evapotranspiration and runoff) by linking the outputs from the global climate model (GCM) with the Soil and Water Assessment Tool (SWAT) for a case study in the Lijiang River Basin, China. We selected a variety of bias correction methods and their combinations to correct the lower resolution GCM outputs of both precipitation and temperature. Then, the SWAT model was calibrated and validated using the observed flow data and corrected historical GCM with the optimal correction method selected. Hydrological variables were simulated using the SWAT model under emission scenarios RCP2.6, RCP4.5, and RCP8.5. The results demonstrated that correcting methods have a positive effect on both daily precipitation and temperature, and a hybrid method of bias correction contributes to increased performance in most cases and scenarios. Based on the bias corrected scenarios, precipitation annual average, temperature, and evapotranspiration will increase. In the case of precipitation and runoff, projection scenarios show an increase compared with the historical trends, and the monthly distribution of precipitation, evapotranspiration, and runoff shows an uneven distribution compared with baseline. This study provides an insight on how to choose a proper GCM and bias correction method and a helpful guide for local water resources management.

Analysis of a Flash Flood in a Small Basin in Crete

Climate change will have a greater impact on the severity of flash floods, since precipitation intensity is expected to increase, even in areas where a reduction of precipitation is possible. This change in climate is expected to increase flood wave speed and its flood wave area extent. A case study of a small basin in the island of Crete was conducted to examine this effect, following the calibration and validation of the flow hydrograph of a flash flood event, in order to achieve model verification with the post-flood data. It was found that the most important parameters that affect the timing and magnitude of the peak discharge are the storage coefficient, the impervious rate and the curve number, as well as the time of concentration. Rainfall distribution was examined in different time intervals in order to study the effect of the intensity of precipitation on the peak hydrograph. From the precipitation records and according to the size of the watershed, the time step of the precipitation in the simulation model is recommended to be less than an hour. In other areas around the basin of interest, severe storms known as Medicanes that pass over Crete can produce higher precipitation in shorter time intervals. The impact of climate change scenarios results in an increase on the peak discharge by creating precipitation of higher intensity. Furthermore, the intensification of precipitation due to climate change results in higher flood depths and flooded area extent, as well as wave velocities.