Assessment of climate Change impact on water supply in Peru

In this work, the simulation of the water supply has been carried out using the SWAT hydrological model to generate streamflows throughout Peru. For this purpose, 35 hydrological stations distributed in the 3 drainages of Peru have been used, simulating the entire country for the first time considering 4,355 sub-basins and 168 hydrographic units (HU); obtaining time series of streamflows for the period 1981-2016. To evaluate the impact of climate change on water supply of Peru, three regional climate models based on dynamic regionalization have been used, obtaining time series from 1981 to 2065 with a spatial resolution of ~ 10 km. Based on these data, and using the delta change method, the streamflows generated in the period 2035-2065 versus 1981-2016 have been compared

Climate Change Impact on Peruvian Biomes

The biodiversity present in Peru will be affected by climatic and anthropogenic changes; therefore, understanding these changes will help generate biodiversity conservation policies. This study analyzes the potential distributions of biomes (B) in Peru under the effects of climate change. The evaluation was carried out using the random forest (RF) method, six bioclimatic variables, and digital topography for the classification of current B in Peru. Subsequently, the calibrated RF model was assimilated to three downscaled regional climate models to project future B distributions for the 2035–2065 horizon. We evaluated possible changes in extension and elevation as well as most susceptible B. Our projections show that future scenarios agreed that 82% of current B coverage will remain stable. Approximately 6% of the study area will change its current conditions to conditions of higher humidity; 4.5% will maintain a stable physiognomy, but with an increase in humidity; and finally, 6% will experience a decrease in humidity but maintain its appearance. Additionally, glaciers and swamps are indicated as the most vulnerable B, with probable losses greater than 50% of their current area. These results demonstrate the need to generate public policies for the adaptation and mitigation of climate effects on B at a national scal

Análisis regional de frecuencia para determinación de mapas de eventos de sequía en Perú

Se aplicó el análisis regional de frecuencia basado en L momentos y el procedimiento de índice de avenida, este enfoque metodológico permite incorporar datos provenientes de estaciones dentro de una región homogénea para mejorar la precisión en las estimaciones de la relación probabilidad cuantil en todos los sitios, de esta manera permite solucionar la escasez de datos en el tiempo con el aumento de datos en el espacio; para la determinación de mapas de periodos de retorno de sequias meteorológicas teóricas correspondientes a 0.2, 0.4 y 0.6 de la precipitación media anual a escala de todo el Perú. Entre los resultados, se identificó 32 regiones homogéneas de lluvia: 16 en la Región Hidrográfica del Pacífico (RHP), 1 en la Región Hidrográfica del Titicaca (RHT) y 15 en la Región Hidrográfica del Amazonas (RHA); utilizando una combinación del análisis de clúster y el enfoque L momentos, sobre la base de 254 estaciones con récords históricos entre 1964 – 2020 provenientes de la red de observación del SENAMHI, para el análisis regional de frecuencia se seleccionó la distribución logística generalizada por su mejor ajuste en 20/32 regiones utilizando el estadístico ZDIST, el cual permitió determinar la curva de crecimiento regional o cuantiles para el país. Finalmente, se obtuvo ecuaciones exponenciales predictoras a escala regional para relacionar los L momentos y la precipitación media anual que permitió generar los mapas de recurrencia de sequias meteorológicas. Se concluye que las zonas con régimen de precipitación más húmedo (mayor precipitación media anual, PMA) se asocian con menor frecuencia de déficit de precipitación respecto de la condición normal, y corresponden a L-Cv de valores menores (RHA) sin embargo en zonas con régimen de precipitación más seco (menor PMA) se asocia con mayor frecuencia de déficit de precipitación y corresponden a L-Cv de valores mayores (RHP). Asimismo, las zonas potenciales a presentar sequias meteorológicas se localizan hacia la RHP y RHT con intervalos de ocurrencia de 3 a 20 años y 5 a 200 años respectivamente, mientras que en la RHA se presentarían con intervalos entre 10 a más de 200 años; por tanto, la mayor frecuencia de sequía se esperaría hacia las zonas baja y media de la RHP (cuencas Chira hasta la Concordia, con mayor extensión hacia el extremo sur del territorio peruano) principalmente por sus características semi áridas a hiperáridas

Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data

The objective of this work was to generate and evaluate regional rainfall thresholds obtained from a combination of high-resolution gridded precipitation data (PISCOpd_Op), developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI), and information from observed shallow landslide events. The landslide data were associated with rainfall data, determining triggering and non-triggering rainfall events with rainfall properties from which rainfall thresholds were determined. The validation of the performance of the thresholds was carried out with events that occurred during 2020 and focused on evaluating the operability of these thresholds in landslide warning systems in Peru. Thresholds were determined for 11 rainfall regions. The method of determining the thresholds was based on an empirical–statistical approach, and the predictive performance of the thresholds was evaluated from the “true skill statistics” (TSS) and the area under the curve (AUC). The best predictive performance was obtained by the mean daily intensity-duration (Imean – D) threshold curve, followed by accumulated rainfall E. This work is the first attempt to estimate regional thresholds on a country scale in order to better understand landslides, and the results obtained reveal the potential of using thresholds in the monitoring and forecasting of shallow landslides caused by intense rainfall and in supporting the actions of disaster risk management

Rainfall thresholds estimation for shallow landslides in Peru from gridded daily data

This work aims to generate and evaluate regional rainfall thresholds obtained from a combination of high-resolution gridded rainfall data, developed by the National Service of Meteorology and Hydrology of Peru, and information from observed shallow landslide events. The landslide data were associated with rainfall data, determining triggering and non-triggering rainfall events with rainfall properties from which rainfall thresholds are determined. The validation of the performance of the thresholds is carried out with events that occurred during 2020 and focuses on evaluating the operability of these thresholds in landslide warning systems in Peru. The thresholds are determined for 11 rainfall regions. The method of determining the thresholds is based on an empirical–statistical approach, and the predictive performance of the thresholds is evaluated with true skill statistics. The best predictive performance is the mean daily intensity–duration (Imean−D) threshold curve, followed by accumulated rainfall E. This work is the first estimation of regional thresholds on a country scale to better understand landslides in Peru, and the results obtained reveal the potential of using thresholds in the monitoring and forecasting of shallow landslides caused by intense rainfall and in supporting the actions of disaster risk management

Hydrological Modeling of the Peruvian-Ecuadorian Amazon Basin Using GPM-IMERG Satellite-Based Precipitation Dataset

In the last two decades, rainfall estimates provided by the Tropical Rainfall Measurement Mission (TRMM) have proven applicable in hydrological studies. The Global Precipitation Measurement (GPM) mission, which provides the new generation of rainfall estimates, is now considered a global successor to TRMM. The usefulness of GPM data in hydrological applications, however, has not yet been evaluated over the Andean and Amazonian regions. This study uses GPM data provided by the Integrated Multi-satellite Retrievals (IMERG) (productfinal run) as input to a distributed hydrological model for the Amazon Basin of Peru and Ecuador for a 16-month period (from March 2014 to June 2015) when all datasets are available. TRMM products (TMPA V7, TMPA RT datasets) and a gridded precipitation dataset processed from observed rainfall are used for comparison. The results indicate that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, compared to observed rainfall (by 11.1 and 15.7 , respectively). In general, GPM-IMERG, TMPA V7 and TMPA RT correlate with observed rainfall, with a similar number of rain events correctly detected (20). Statistical analysis of modeled streamflows indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets in southern regions (Ucayali basin). GPM-IMERG, TMPA V7 and TMPA RT do not properly simulate streamflows in northern regions (Maran and Napo basins), probably because of the lack of adequate rainfall estimates in northern Peru and the Ecuadorian Amazon

Trends and space–time patterns of near-surface temperatures on Maxwell Bay, King George Island, Antarctica

There is growing interest in the international scientific community in characterizing climate variability in Antarctica because of the continent's fundamental role in regulating the world's climate. Researchers have intensively studied the Antarctic Peninsula since the warming that began in the mid-1950s. This was followed by a subsequent cooling period over the last decades. For this paper, using the available data, we analyzed the variability in surface air temperatures at five meteorological stations located on King George Island (KGI) (a subantarctic island that is part of the South Shetland Islands); we also investigated the relationships between the air temperatures and large-scale atmospheric patterns from 1968 to 2019. In this study we found that summer temperatures are above 0°C from December to March and close to melting temperatures (extreme values) in spring and autumn; consequently, a small increase in temperature can have a significant impact on the cryosphere. The statistical analysis of the mean temperatures confirmed a trend toward cooling during the summer and in the mean monthly maximum temperatures over the 1990s at most of the weather stations whose data we analyzed. Analyzing the teleconnection patterns showed that the Southern Annular Mode (SAM) had strong, direct, and positive correlations during the autumn and less strong connections in spring, winter, and on an annual scale. Furthermore, we observed a lesser influence of El Niño-Southern Oscillation (ENSO)

Impacto del cambio climático y uso del suelo en la propagación de la sequía meteorológica a la hidrológica en cuencas amazónicas del Perú

La sequía es uno de los fenómenos naturales más devastadores a nivel global, debido a sus impactos en los sectores económicos y principalmente en la agricultura, afectando a un 40% de la población mundial (FAO, 2022). En esta línea, los cambios de usos de suelo en la propagación de la sequía meteorológica a la hidrológica son de gran importancia para el pronóstico de sequias hidrológicas y prevención y mitigación de desastres por sequía. El presente trabajo tuvo por objetivo: (1) Analizar las características espaciales y temporales de la propagación de la sequía meteorológica a la sequía hidrológica en cuencas amazónicas en el Perú en los últimos 40 años. (2) Determinar los cambios de uso de suelo en la propagación de la sequía meteorológica e hidrológica. La metodología consistió en el cálculo de índices de sequía meteorológica e hidrológica utilizando índices estandarizados a distintas escalas de tiempo, posteriormente se realizó un análisis de correlación de Pearson para medir el grado de relación entre la sequía meteorológica e hidrológica y un método de machine learning para el cálculo de cambios de usos de suelo para la cuenca Intermedio Alto Huallaga. Los resultados mostraron, una tendencia positiva en la sequía meteorológica en los últimos 40 años, este aumento se debe en intensidad de la sequía en todas las cuencas analizadas. En cuanto a la sequía hidrológica ha habido menor intensidad desde los 80s a los 20s pero con mayor frecuencia en las últimas décadas. Así, una fuerte propagación de la sequía meteorológica a la hidrológica en las primeras dos décadas sobre todo en la estación de verano de diciembre a febrero en términos estacionales evidenciando valores de DPI mayores a 1. A la escala mensual según el SPI-1 y el SRI-1 las mayores correlaciones positivas y significativas se tiene con un lag=0, esto indica que si sucede una sequía meteorológica podría suceder en simultáneo un hidrológica en las cuencas andinas amazónicas

Construction of a daily streamflow dataset for Peru using a similarity-based regionalization approach and a hybrid hydrological modeling framework

This paper aims to develop a national hydrological model using physiographic and climatic characteristics to identify donor and receptor sub-catchments (sub-zones). Therefore, we use the hydrometeorological PISCO dataset (0.1º x 0.1º) to drive a sub-catchment conceptual rainfall-runoff (ARNO/VIC) model and a river-routing (RAPID) model in thousands of river reaches. We identify 43 hydrological zones (with 122 sub-zones) to run the hybrid hydrological modeling framework (ARNO/VIC+RAPID) with previously calibrated and validated parameters with 43 fluviometric stations for 1981–2020. Simulated flow series show a higher performance at daily scale (KGE ≥ 0.75, NSEsqrt ≥ 0.65, MARE ≤ 1, and −25% ≤ PBIAS ≤ 25%) for catchments located at the Pacific coast and the Andes-Amazon transition, and good representation (R≥0.75) of seasonal and interannual variability

Desarrollo de datos grillados de precipitación horaria para el Perú, estudio final

Los datos de precipitación con alta resolución espacial y temporal son muy esenciales para múltiples campos en las ciencias climatológicas, ecológicas, hidrológicas y ambientales. En este trabajo desarrollamos e implementamos la construcción de un producto grillado (0.1°) de precipitación horaria a escala de todo el Perú (PISCOp_h). Esta nueva base de datos se desarrolla a partir de la disgregación temporal de un establecido producto diario de precipitación en conjunto con la combinación de estimaciones de precipitación de tres productos satelitales y estaciones meteorológicas automáticas. Los principales resultados demuestran que PISCOp_h presenta un moderado a alto acople de la precipitación horaria; caracteriza bastante bien la frecuencia e intensidad de la precipitación horaria, principalmente en la parte central y sur del país. Asimismo, caracteriza de forma eficiente la frecuencia, intensidad y ciclo diurno promedio de la precipitación horaria. Esta base de datos representa un importante avance en el desarrollo de productos de precipitación horaria, primordialmente en regiones montañosas de terreno complejo. Nosotros esperamos que el nuevo producto sea de utilidad para las diferentes aplicaciones hidrometeorológicas a nivel nacional