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artículo
Publicado 2025
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Land use and land cover (LULC) changes in the Piura River Basin, Peru, were analyzed from 2001 to 2022 using global MODIS and ESA-CCI datasets harmonized into six major land cover classes (Forest, Non-Forest Vegetation, Cropland, Bare Soil, Water and Urban) for comparative analysis. Pearson correlation analyses with hydroclimatic variables, including precipitation (PP), maximum (Tx) and minimum (Tn) temperatures, and El Niño Southern Oscillation (ENSO) indices (Eastern Pacific, Central Pacific, and Coastal El Niño), complemented the intensity analysis to explore environmental drivers. The analyses focused on the lower-middle and upper basin regions during wet (December-May) and dry (June-November) seasons. MODIS detected more dynamic LULC transitions, with 32.8% of pixels showing changes, compared to 6.8% detected by the ESA-CCI product. These differences reflect the distinct sensitivi...
2
tesis de maestría
Publicado 2024
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Artículo sustentado el 10 de abril 2024 para la obtención del grado académico de Maestra en Ingeniería Civil.
3
artículo
Publicado 2023
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In regions with limited precipitation information, like Peru, many studies rely on precipitation data derived from satellite products (SPP) and model reanalysis. These products provide near-real-time information and offer global spatial coverage, making them attractive for various applications. However, it is essential to consider their uncertainties when conducting hydrological simulations, especially in a key region like the Pacific drainage (Pd), where 56% of the Peruvian population resides (including the capital, Lima). This study, for the first time, assessed the performance of two bottom-up Satellite-based Precipitation Products (SPP), GPM + SM2RAIN and SM2RAIN-ASCAT, and one top-down approach SPP, ERA5-Land, for runoff simulation in the Pacific drainage of Peru. Hydrological modeling was conducted on 30 basins distributed across the Pd, which were grouped into 5 regions (I–V, or...
4
informe técnico
Publicado 2023
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In soil erosion estimation models, the variable with the greatest impact is rainfall erosivity (RE), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (ED), which relates RE to precipitation. The RE requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for RE estimation. This study evaluates the performance of a new gridded dataset of RE and ED in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000-2020. By using this method, a correlation of 0.7 was found between the PISCO_reed and RE o...
5
artículo
Publicado 2023
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The watershed hydrologic conditions in the Madre de Dios (MDD) Basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area, primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD Basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in a significant increase in surface runoff, by 38% monthly, a 1% annual reduction of evapotranspiration, and an average monthly streamflow increase of 12%. Changes in sp...
6
artículo
Publicado 2023
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In soil erosion estimation models, the variables with the greatest impact are rainfall erosivity (), which is the measurement of precipitation energy and its potential capacity to cause erosion, and erosivity density (), which relates to precipitation. The requires high temporal resolution records for its estimation. However, due to the limited observed information and the increasing availability of rainfall estimates based on remote sensing, recent research has shown the usefulness of using observed-corrected satellite data for estimation. This study evaluates the performance of a new gridded dataset of and in Peru (PISCO_reed) by merging data from the IMERG v06 product, through a new calibration approach with hourly records of automatic weather stations, during the period of 2000–2020. By using this method, a correlation of 0.94 was found between PISCO_reed and obtained by the observ...
7
artículo
Publicado 2024
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The watershed hydrologic conditions in the Madre de Dios (MDD) Basin in the Peruvian Amazon have been irreversibly impacted by deforestation and changes in land cover. These changes have also had detrimental effects on the geomorphology, water quality, and aquatic habitat within the basin. However, there is a scarcity of hydrological modeling studies in this area, primarily due to the limited availability of hydrometeorological data. The primary objective of this study was to examine how deforestation impacts the hydrological conditions in the MDD Basin. By implementing the Soil and Water Assessment Tool (SWAT) model, this study determined that replacing 12% of the evergreen broadleaf forest area with bare land resulted in a significant increase in surface runoff, by 38% monthly, a 1% annual reduction of evapotranspiration, and an average monthly streamflow increase of 12%. Changes in sp...
8
artículo
Risk management has reduced vulnerability to floods and droughts globally1,2, yet their impacts are still increasing3. An improved understanding of the causes of changing impacts is therefore needed, but has been hampered by a lack of empirical data4,5. On the basis of a global dataset of 45 pairs of events that occurred within the same area, we show that risk management generally reduces the impacts of floods and droughts but faces difficulties in reducing the impacts of unprecedented events of a magnitude not previously experienced. If the second event was much more hazardous than the first, its impact was almost always higher. This is because management was not designed to deal with such extreme events: for example, they exceeded the design levels of levees and reservoirs. In two success stories, the impact of the second, more hazardous, event was lower, as a result of improved risk...
9
artículo
Publicado 2023
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As the adverse impacts of hydrological extremes increase in many regions of the world, a better understanding of the drivers of changes in risk and impacts is essential for effective flood and drought risk management and climate adaptation. However, there is currently a lack of comprehensive, empirical data about the processes, interactions, and feedbacks in complex human–water systems leading to flood and drought impacts. Here we present a benchmark dataset containing socio-hydrological data of paired events, i.e. two floods or two droughts that occurred in the same area. The 45 paired events occurred in 42 different study areas and cover a wide range of socio-economic and hydro-climatic conditions. The dataset is unique in covering both floods and droughts, in the number of cases assessed and in the quantity of socio-hydrological data. The benchmark dataset comprises (1) detailed rev...
