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Climate change includes the change of the long-term average values and the change of the tails of probability density functions, where the extreme events are located. However, obtaining average values are more straightforward than the high temporal resolution information necessary to catch the extreme events on those tails. Such information is difficult to get in areas lacking sufficient rain stations. Thanks to the development of Satellite Precipitation Estimates with a daily resolution, this problem has been overcome, so Extreme Precipitation Indices (EPI) can be calculated for the entire Colombian territory. However, Colombia is strongly affected by the ENSO (El Niño—Southern Oscillation) phenomenon. Therefore, it is pertinent to ask if the EPI’s long-term change due to climate change is more critical than the anomalies due to climate variability induced by the warm and cold phases of ENSO (El Niño and La Niña, respectively). In this work, we built EPI annual time series at each grid-point of the selected Satellite Precipitation Estimate (CHIRPSv2) over Colombia to answer the previous question. Then, the Mann-Whitney-Wilcoxon test was used to compare the samples drawn in each case (i.e., change tests due to both long-term and climatic variability). After performing the analyses, we realized that the importance of the change depends on the region analyzed and the considered EPI. However, some general conclusions became evident: during El Niño years (La Niña), EPI’s anomaly follows the general trend of reduction -drier conditions- (increase; -wetter conditions-) observed in Colombian annual precipitation amount, but only on the Pacific, the Caribbean, and the Andean region. In the Eastern plains of Colombia (Orinoquía and Amazonian region), EPI show a certain insensitivity to change due to climatic variability. On the other hand, EPI’s long-term changes in the Pacific, the Caribbean, and the Andean region are spatially scattered. Still, long-term changes in the eastern plains have a moderate spatial consistency with statistical significance.

Climate model outputs can be used as climate forcing for hydrological models to study the impact of climate change on the water cycle. This usually propagates cumulative uncertainties, transferring the errors from the climate models to the hydrological models. Then, methodologies are needed to evaluate the impact of climate change at basin scale by reducing the uncertainties involved in the modeling chain. The paper aims to assess the impact of climate change on the runoff, considering a novel approach to build a Regional Climate Model (RCM) ensemble as climate forcing for a parsimonious spatially distributed hydrological model. A semiarid basin of southeast of Spain was selected for the study. The RCM ensembles were built based on seasonal and annual variability of rainfall and temperature. If the runoff projections for 2021–2050 are compared to the 1961–1990 observed period, a significant decrease in runoff equal to −20% (p-value t-test 0.05) was projected. However, by changing the observed period to 1971–2000, a despicable change (2.5%) is identified. This fact demonstrates that trends based on short records are very sensitive to the beginning and end dates, due to the natural variability. Special attention should be paid to the selection of the period for impact studies.

In this work, the influence of the El Niño Southern Oscillation (ENSO) on the Extreme Precipitation Indices (EPIs) was analyzed, and these ENSO-forced anomalies were compared with the long-term change in the EPIs. The annual time series of the EPIs were built from 880 precipitation stations that contained daily records between 1979 and 2022. These daily time series were filled, then the eleven (11) annual time series of the EPIs were built. To calculate ENSO-driven anomalies, the several phases of the phenomenon were considered (i.e., warm phase or El Niño years, cold phase or La Niña years, and normal or neutral years). For a particular EPI, the values calculated for the extreme phases of the ENSO were grouped, and these groups were compared with the group made up of the EPI values for the neutral years. To calculate the long-term change, two periods (1979–1996 and 2004–2021) were considered to group the EPI values. Maps showing the magnitude and significance of the assessed change/anomaly were constructed. The results allowed us to identify that the EPIs are generally “wetter” (i.e., higher extreme precipitation, longer wet periods, shorter dry periods, etc.) during La Niña hydrological years, while the opposite changes are observed during El Niño years. Furthermore, ENSO-induced anomalies are more important than the long-term changes.

Improvements in satellite remote sensing techniques have allowed the development of several platforms that are able to capture multitemporal data with a wide range of spatial and temporal resolutions [...]

In Colombia, most of the energy is produced by using water resources. However, the morphological impact of damming has not been thoroughly studied yet. Therefore, upstream and downstream changes in the channel width and sinuosity along the river due to the Betania, Prado, Salvajina, and Urrá I Dams, four of the oldest hydroelectric projects, were estimated. These changes were reported by using aerial photographs and satellite images to compare the river before and after dam construction. The analysis was complemented by including hydrological trends and geological characteristics of the areas to evaluate their relevance on the impacts on channel morphology. It was shown that factors such as valley confinement and the bank’s composition are key to determining the magnitude of the impact downstream of the dam. Upstream of the dam, contrastingly, the influence of the reservoir geometry controls the magnitude of the morphological changes, marking the boundaries of affected areas. The impacts of dam construction on river morphology vary notably, but including the geological characteristics of the river reach can be useful to improve predictions of the channel morphology response. The proposed methodology can be used to identify biotic compensation measures for new projects, a task that is not well defined in several countries.

Vast sections of the planet face either a dearth of ground-based weather stations or are hampered by the poor quality of those in service. In response, researchers are forced to turn to climate field databases, as they constitute a source of reliable information for local studies. Insofar as the Amazon region, these databases prove to be valuable given their open-access platform and the fact that this expansive region possesses few quality stations (coupled with insufficient temporal coverage). However, before basing research on such archives, this information should be compared against in situ station measurements. Then, the present study assesses the validity of temperature and precipitation information furnished by University of Delaware’s database (UD-ATP) by means of a comparison with the open-access information available from Climate Explorer project (CLIMEXP). Results show that UD-ATP database offers better precipitation data representation, especially on Brazil, which is perhaps the effect of higher-quality and larger-quantity observed data.

Population growth and intense consumptive water uses are generating pressures on water resources in the southeast of Spain. Improving the knowledge of the climate change impacts on water cycle processes at the basin scale is a step to building adaptive capacity. In this work, regional climate model (RCM) ensembles are considered as an input to the hydrological model, for improving the reliability of hydroclimatic projections. To build the RCMs ensembles, the work focuses on probability density function (PDF)-based evaluation of the ability of RCMs to simulate of rainfall and temperature at the basin scale. To improve the spatial calibration of the continuous hydrological model used, an algorithm for remote sensing actual evapotranspiration (AET) retrieval was applied. From the results, a clear decrease in runoff is expected for 2050 in the headwater basin studied. The plausible future scenario of water shortage will produce negative impacts on the regional economy, where the main activity is irrigated agriculture.

The current study aims at developing a regional frequency analysis for Maximum Annual Temperature (MAT) in the hydrographic basins of Colombia. The methodology that was implemented for the regionalization is the L-Moments, proposed by Hosking (1990). The work was performed in five stages: data analysis, computing of L-Moments, identification of homogeneous regions, selection of probability and distribution of the density function and estimation of quantities, and finally the construction of regionalized maps. Overall, fifteen (15) homogeneous regions were identified and selected for annual maximum temperature, which meet certain criteria of homogeneity and discordance. Several distributions for regional frequency analysis were tested in order to select the best probability function: the ZDIST statistic was used, considering that the absolute value must be smaller than 1,64. Finally, temperature maps were generated for different return periods. Using the L-Moments methodology, the regionalization procedure was done using the annual average maximum temperature as the key scale parameter. However, the regionalization procedure was done using the geographic location; the physical parameters by gauging stations (Wallis, 2007), with stations located in the same catchment, and considering the coherent-basins approach.

Debido a la carencia de estaciones en tierra, o a la mala calidad de éstas, en amplias regiones del planeta, las bases de datos de campos climáticos emergen como fuentes de información confiable para realizar estudios locales. En el caso específico de la Amazonía, estas bases de datos son valiosas porque son de libre acceso, y porque este vasto territorio cuenta con pocas estaciones de calidad y suficiente longitud. Sin embargo, previo a su utilización, es necesario comparar estos datos con la información disponible de las estaciones. Se verificó la validez de la información de precipitación y temperatura contenida en la base de datos de la Universidad de Delaware (UD-ATP), contrastándola con la información de libre acceso disponible en el Climate Explorer (CLIMEXP). Se encontró que la precipitación es mejor representada por la base de datos UD-ATP, y que los resultados son mejores sobre el territorio brasilero, posiblemente por la mejor calidad de los registros observados.

The global manufacturing sector faces a significant challenge about minimizing environmental impacts without witnessing the adverse effects on the market competitiveness. A cleaner production methodology must involve different approaches for minimizing or recycling waste streams, obtaining at the same time economical and environmental advantages for manufacturing companies (Severo et al., J Clean Prod 142:87–97, 2017 ). In the polypropylene production process, more than 60 grades of polypropylene are produced. To achieve this target, changes in the process variables are carried out, due to the continuous operation process. Those changes generate a mixture of resins with intermediate properties (transition), which must be minimized. Moreover, failures during the transitions process generate a large extra amount of material that represents a significant impact on the environment, when it is considered as waste. In this paper, an environmental analysis was made by applying a waste reduction algorithm (WAR) to establish the potential impact of a polypropylene production process over the environment, applying grade transitions strategies and then to demonstrate how the improvement of transition times implies a significant reduction of plastic waste. It was found that the reduction of transitions time minimizes the environmental impact based on real industry data. Last should be considered for the real polymer plant analyzed and future projects.