Water footprint and virtual water flows from the Global South: Foundations for sustainable agriculture in periods of drought

Freshwater availability has decreased alarmingly worldwide, with agriculture playing a vital role in this trend. The assessment of the agricultural water footprint (WF_agricultural) and virtual water flows (VWF) is fundamental not only in local water resources management and protection, but also in our understanding of the synergies between local water consumption and global markets. Thus, the WF_agricultural - broken down into its components (blue, green, and gray) - of the leading 21 crops (grouped in fruit, legumes, cereals, and vegetables), grown in four basins with the most significant agricultural activity in central Chile was determined, estimated in two consecutive years 2017-2018. In addition, due to their great importance in exports, VWFs were assessed, establishing connections according to their origins and destinations. The results show that the green and gray water footprints increased significantly in the south-central basins, while blue water consumption increased in the basins of the central zone, reflecting an evident WF_agricultural transition in accord with latitude and climate conditions. Furthermore, VWF showed an annual increase of 44 %, in about 116 destinations, with Asia, Europe, and North America being the preferred destinations, with annual variations of VWF_{blue- gray} associated with increases in exports of apples, cherries, grapes, blueberries, and walnuts, market preferences and growing areas. The present study is an initial step toward sustainable agriculture in a commodity exporting country, one that is relevant in the exploitation of virtual water yet faces severe water deficit problems, distribution, and local water policies. Therefore, contributing to encouraging the efficiency and value of water in the process of a new institutional framework.

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.

Understanding agricultural water footprint variability to improve water management in Chile

Understanding water consumption is crucial for sustainable management of water resources. Under climate change scenarios that project highly variable water availability, the need for public policies that assure efficiency and equity in water resources is increasing. This work analyzes the case of the Cachapoal River agricultural basin (34°S 71°W), which presents temperature increases and a precipitation deficit, with a drought period that began more than eleven years ago having significantly decreased water availability. Water consumption in the basin for food production was determined from the agricultural water footprint (WF_agricultural), using the green (WF_green), blue (WF_blue) and gray water footprint (WF_gray) indicators, which were measured in the upper, middle and lower basin under conditions of climate variability (dry, wet and normal years). The greatest WF_agricultural was established in the dry year, with a total of 18,221 m³ t^-1, followed by 15,902 m³ t^-1 in the wet year and 14,091 m³ t^-1 in the normal year. Likewise, the greatest WF_blue and WF_gray, of 12,000 m³ t^-1 and 4934 m³ t^-1, respectively, were also observed in the dry year. The greatest WF_green, 2000 m³ t^-1, was calculated for a normal year. The 63% of agricultural area of the basin was covered by avocado (Persea americana), olive (Olea europaea), corn (Zea mays) and grape (Vitis sp) crops, which presented the greatest WF_agricultural. This water footprint data provides a quantitative basis for the assessment of water consumption and degradation, considering agricultural production and its multiple variables. The success of the application of these results lies in the use of indicators to understand change processes and complement future water allocation plans with more rational water management models.

A new method to evaluate the vulnerability of watersheds facing several stressors: A case study in mediterranean Chile

Freshwater systems are subjected to multiple anthropogenic stressors and natural disturbances that act as debilitating agents and modifiers of river systems, causing cumulative and synergistic effects that deteriorate their health and result in watershed vulnerability. This study proposes an easy-to-apply spatial method of watershed vulnerability evaluation using Geographic Information Systems (GIS) in the Andalién River watershed, located in the Chilean mediterranean. A watershed vulnerability index (WVI) based on three sub-indices - anthropogenic stressors, environmental fragility and natural disturbances - was developed. To determine the index grouping weights, expert surveys were carried out using the Delphi method. We subsequently normalized and integrated the factors of each sub-index with relative weights. The ranges of each thematic layer were re-classified to establish vulnerability scores. The watershed was divided into three sections: headwaters zone, transfer zone and depositional zone. The watershed vulnerability index showed that 41% of the watershed had very low vulnerability and 42% had medium vulnerability, while only 1% - in the depositional zone - had high vulnerability. A one-way ANOVA was carried out to analyze the vulnerability differences among the three sections of the watershed; it showed significant differences (F (2, 16) = 8.15: p < 0.05). The a posteriori test showed differences between the headwaters and depositional zones (Tukey test, p = 0.005) and between the transfer and depositional zones (Tukey test, p = 0.014). To validate the WVI, water quality was measured at 16 stations in the watershed; there was a significant correlation between vulnerability level and NO₂^- levels (r = 0.8; p = 0.87; α = 0.05) and pH (r = 0.8; p = 0.80; α = 0.05). The WVI showed the cumulative effects of multiple stressors in the depositional zone of the watershed. This is the first study to evaluate and validate non-regulated watershed vulnerability with GIS using multiple anthropogenic and natural stressors.

Simulation of regional irrigation requirement with SWAT in different agro-climatic zones driven by observed climate and two reanalysis datasets

Irrigation water is one of the most substantial water uses worldwide. Thus, global simulation studies about water availability and demand typically include irrigation. Nowadays, regional scale is of major interest for water resources management but irrigation lacks attention in many catchment modelling studies. This study evaluated the performance of the agro-hydrological model SWAT (Soil and Water Assessment Tool) for simulating streamflow, evapotranspiration and irrigation in four catchments of different agro-climatic zones at meso-scale (Baitarani/India: Subtropical monsoon; Ilmenau/Germany: Humid; Itata/Chile: Mediterranean; Thubon/Vietnam: Tropical). The models were calibrated well with Kling-Gupta Efficiency (KGE) varying from 0.74-0.89 and percentage bias (PBIAS) from 5.66-6.43%. The simulated irrigation is higher when irrigation is triggered by soil-water deficit compared to plant-water stress. The simulated irrigation scheduling scenarios showed that a significant amount of water can be saved by applying deficit irrigation (25-48%) with a small reduction in annual average crop yield (0-3.3%) in all climatic zones. Many catchments with a high share of irrigated agriculture are located in developing countries with a low availability of input data. For that reason, the application of uncorrected and bias-corrected National Centers for Environmental Prediction (NCEP) and ERA-interim (ERA) reanalysis data was evaluated for all model scenarios. The simulated streamflow under bias-corrected climate variables is close to the observed streamflow with ERA performing better than NCEP. However, the deviation in simulated irrigation between observed and reanalysis climate varies from -25.5-45.3%, whereas the relative irrigation water savings by deficit irrigation could be shown by all climate input data. The overall variability in simulated irrigation requirement depends mainly on the climate input data. Studies about irrigation requirement in data scarce areas must address this in particular when using reanalysis data.

A methodology to identify representative configurations of sensors for monitoring soil moisture

Soil moisture is the key link among hydroecological compartments, responding dynamically to sequences of atmospheric processes and management conditions and modulating physical, chemical, and biological processes in the soil. Currently, there are a variety of monitoring techniques to measure, directly or indirectly, the soil moisture. However, some practical issues remain open like the definition a priori of the number, location and depth of the monitoring points, and the impact of failing or poor performance soil moisture sensors. Here, we present a set of techniques, namely Δθ time series, wavelet filtering, and time stability, to identify representative points and monitoring depths through an analysis of hourly soil moisture time series for different configuration of the monitoring network. We used real data from a monitoring network consisting of seven monitoring points, each one with four EC-5 probes (Decagon Devices Inc., Pullman, WA) at 20, 40, 60, and 100 cm. The use of simple time series of Δθ allowed us to assess the spatiotemporal influence of the monitoring points, while the wavelet periodograms allowed us to get insight about the response of the monitoring points at different time scales. Both methods are easy to implement or adapt to specific conditions, being coherent to the results derived from time stability analysis. For our case study, we concluded that we could reallocate 16 sensors (out of 28) without a significant loss of information. However, the final decision strongly relies on a deep knowledge of the site features and the objectives of the monitoring network.

A simple method to identify areas of environmental risk due to manure application

The management of swine manure is becoming an important environmental issue in Chile. One option for the final disposal of manure is to use it as a biofertilizer, but this practice could impact the surrounding environment. To assess the potential environmental impacts of the use of swine manure as a biofertilizer, we propose a method to identify zones of environmental risk through indices. The method considers two processes: nutrient runoff and solute leaching, and uses available information about soils, crops and management practices (irrigation, fertilization, and rotation). We applied the method to qualitatively assess the environmental risk associated with the use of swine manure as a biofertilizer in an 8,000-pig farm located in Central Chile. Results showed that the farm has a moderate environmental risk, but some specific locations have high environmental risks, especially those associated with impacts on areas surrounding water resources. This information could assist the definition of better farm-level management practices, as well as the preservation of riparian vegetation acting as buffer strips. The main advantage of our approach is that it combines qualitative and quantitative information, including particular situations or field features based on expert knowledge. The method is flexible, simple, and can be easily extended or adapted to other processes.