PatagoniaMet: A multi-source hydrometeorological dataset for Western Patagonia.

Western Patagonia (40-56°S) is a clear example of how the systematic lack of publicly available data and poor quality control protocols have hindered further hydrometeorological studies. To address these limitations, we present PatagoniaMet (PMET), a compilation of ground-based hydrometeorological data (PMET-obs; 1950-2020), and a daily gridded product of precipitation and temperature (PMET-sim; 1980-2020). PMET-obs was developed considering a 4-step quality control process applied to 523 hydrometeorological time series obtained from eight institutions in Chile and Argentina. Following current guidelines for hydrological datasets, several climatic and geographic attributes were derived for each catchment. PMET-sim was developed using statistical bias correction procedures, spatial regression models and hydrological methods, and was compared against other bias-corrected alternatives using hydrological modelling. PMET-sim was able to achieve Kling-Gupta efficiencies greater than 0.7 in 72% of the catchments, while other alternatives exceeded this threshold in only 50% of the catchments. PatagoniaMet represents an important milestone in the availability of hydro-meteorological data that will facilitate new studies in one of the largest freshwater ecosystems in the world.

A new method to map groundwater-dependent ecosystem zones in semi-arid environments: A case study in Chile.

Groundwater (GW) use has intensified in recent decades, threatening the ecological integrity of groundwater-dependent ecosystems (GDEs). The study of GDEs is limited; therefore, integrated, interdisciplinary environmental approaches that guarantee their monitoring and management amid current climate and anthropogenic changes are needed. A new geospatial method with an integrated and temporal approach was developed through a multicriteria approximation, taking into account expert opinion, remote sensing-GIS, and fieldwork to map groundwater-dependent ecosystem zones (GDEZ). A survey of experts (N = 26) was conducted to assign degrees of importance to the various geospatial parameters, and the mapping was carried out using 14 parameters. The reclassified parameters were normalized on a scale of 1 to 5 according to the degree of probability of the presence of GDE. The validation was carried out through fieldwork and statistical analysis. Then, the spatio-temporal changes amid changing GW levels were assessed using the summer season normalized difference vegetation index (NDVI). Two GDEZ maps were obtained, for 2002 and 2017, between which the high- and very-high-probability zones of GDEs decreased by 31,887 ha (~ 38%). The most sensitive temporal parameters that most influenced the spatio-temporal changes on GDEs were precipitation and land use, with rain exerting a slightly the greatest influence. It was also demonstrated that identified ecosystems decreased in area or were affected by aquifer depletion (NDVI-GW, r Pearson ≥0.74). This validated method allows spatio-temporal changes in GDEs to be mapped and analyzed at an annual scale and is transferable to other arid and semi-arid environments.

Contrasting land-uses in two small river basins impact the colored dissolved organic matter concentration and carbonate system along a river-coastal ocean continuum.

Human activities have led to an increase in land use change, with effects on the structure and functioning of ecosystems. The impact of contrasting land uses along river basins on the concentration of colored dissolved organic matter (CDOM) reaching the coastal zone, and its relationship with the carbonate system of the adjacent coastal ocean, is poorly known. To understand the relationship between land use change, CDOM and its influence on the carbonate system, two watersheds with contrasting land uses in southern Chile were studied. The samples were collected at eight stations between river and adjacent coastal areas, during three sampling campaigns in the austral summer and spring. Chemical and biological samples were analyzed in the laboratory according to standard protocols. Landsat 8 satellite images of the study area were used for identification and supervised classification using remote sensing tools. The Yaldad River basin showed 82% of native forest and the Colu River basin around 38% of grassland (agriculture). Low total alkalinity (AT) and Dissolved Inorganic Carbon (DIC), but high CDOM proportions were typically observed in freshwater. A higher CDOM and humic-like compounds concentration was observed along the river-coastal ocean continuum in the Yaldad basin, characterized by a predominance of native forests. In contrast, nutrient concentrations, AT and DIC, were higher in the Colu area. Low CaCO3 saturation state (ΩAr < 2) and even undersaturation conditions were observed at the coastal ocean at Yaldad. A strong negative correlation between AT, DIC and ΩAr with CDOM/fDOM, suggested the influence of terrestrial material on the seawater carbon chemistry. Our results provide robust evidence that land uses in river basins can influence CDOM/fDOM proportion and its influence on the carbonate chemistry of the adjacent coastal, with potential implications for the shellfish farming activity in this region.

Anaerobic co-digestion plants for the revaluation of agricultural waste: Sustainable location sites from a GIS analysis.

The aim of this study was to establish sustainably feasible areas for the implementation of anaerobic co-digestion plants for agricultural wastes (cattle/swine slurries and cereal crop wastes). The methodology was based on the use of geographic information systems (GIS), the analytic hierarchy process (AHP) and map algebra generated from hedges related to environmental, social and economic constraints. The GIS model obtained was applied to a region of Chile (Bío Bío Region) as a case study showing the energy potential (205 MW-h) of agricultural wastes (swine/cattle manures and cereal crop wastes) and thereby assessing its energy contribution (3.5%) at country level (Chile). From this model, it was possible to spatially identify the influence of each factor (environmental, economic and social) when defining suitable areas for the siting of anaerobic co-digestion plants. In conclusion, GIS-based models establish appropriate areas for the location of anaerobic co-digestion plants in the revaluation of agricultural waste from the production of energy through biogas production.