Comparación de los productos TRMM [Tropical Rainfall Measuring Mission] y GPM [Global Precipitation Measurement] para el modelamiento hidrológico en la cuenca del río Huancané

Universidad Nacional Agraria La Molina. Facultad de Ingeniería Agrícola. Departamento Académico de Recursos HídricosLa presente investigación tiene por objetivo evaluar la capacidad de los productos grillados de precipitación de la Tropical Rainfall Measuring Mission (TRMM) y de la Global Precipitation Measurement (GPM), en su aplicación al modelamiento hidrológico. Para ello, se realizó una comparación cuantitativa de estos productos satelitales con la precipitación observada, obtenida de una cuenca con baja densidad de estaciones pluviométricas: la cuenca del río Huancané, ubicada en el Altiplano peruano. En general, la comparación de la precipitación media diaria de la cuenca a partir de las estimaciones de los productos 3B42RT, 3B42V7 e IMERG respecto a la lluvia media diaria de las estaciones (para el periodo Abril 2014 – Diciembre 2015), determina que IMERG representa correctamente los patrones de la precipitación (R2: 0.38) pero no cuantifica adecuadamente la intensidad (BIAS: -32%). Por otro lado, el producto 3B42V7 capta muy bien la intensidad de lluvia en contraste con el 3B42RT que presenta elevadas sobrestimaciones. De igual manera, una evaluación inicial de los productos satelitales sin corregir utilizando el modelo hidrológico agregado GR4J, evidencia que en ausencia de datos observados, el producto 3B42V7 es la mejor opción para la estimación de las descargas. Finalmente, al realizar la corrección del sesgo por el promedio al producto IMERG, los resultados muestran que se mejora las estimaciones de la lluvia (R2: 0.9; BIAS: -10.1%) y en consecuencia, el IMERG corregido es el mejor producto satelital de precipitación para su aplicación al modelamiento hidrológico. Estos resultados preliminares están limitados al análisis de un corto periodo, sin embargo, a medida que se liberan más datos del IMERG, más estudios para explorar su utilidad en aspectos del agua y cambio climático serán necesarios.The current research has the main purpose to assess the capacity of gridded precipitation products of Tropical Rainfall Measuring Mission (TRMM) and Global Precipitation Measurement (GPM) in its application to hydrologic modelling. A quantitative comparison was made among these satellite products with a low dense gauge network over Huancané basin in Peruvian Altiplano. In general, comparisons of 3B42RT, 3B42V7 and IMERG estimates with gauge observations over a period from April 2014 to December 2015 at daily resolution show that IMERG estimates correctly precipitation patterns (R2: 0.38), however it doesn’t quantify properly the rain intensity (BIAS: -32%). On the other hand, the product 3B42V7 captures very well the rain intensity in contrast to the 3B42RT that show high overestimation. An initial hydrologic assessment with GR4J lumped hydrologic model using satellite products without correction indicate that, in lack of gauge observations, 3B42V7 is the best option to simulate daily streamflow. Finally, when performing the mean field bias correction to IMERG, results show that the precipitation estimation is improved (R2: 0.9; BIAS: -10.1%), consequently the IMERG corrected is the best precipitation satellite product to its application in hydrologic modelling. These preliminary results are limited to the short-term analysis, however as more IMERG data is released, more studies to explore its usefulness in water and climate change aspects will be needed.Tesi

Regional parameter estimation of the SWAT model: methodology and application to river basins in the Peruvian Pacific drainage

This study presents a methodology for the regional parameters estimation of the SWAT (Soil and Water Assessment Tool) model, with the objective of estimating daily flow series in the Pacific drainage under the context of limited hydrological data availability. This methodology has been designed to obtain the model parameters from a limited number of basins (14) to finally regionalize them to basins without hydrological data based on physical-climatic characteristics. In addition, the bootstrapping method was selected to estimate the uncertainty associated with the parameters set selection in the regionalization process. In general, the regionalized parameters reduce the initial underestimation which is reflected in a better quantification of daily flows, and improve the low flows performance. Furthermore, the results show that the SWAT model correctly represents the water balance and seasonality of the hydrological cycle main components. However, the model does not correctly quantify the high flows rates during wet periods. These findings provide supporting information for studies of water balance and water management on the Peruvian Pacific drainage. The approach and methods developed can be replicated in any other region of Peru

Surface water resources assessment in Peru through SWAT hydrological model

Surface water resources in Peru show high spatio-temporal variability, being the prediction of streamflow at ungauged sites, one of the fundamental challenges today. This research presents a methodology for regional parameter estimation at national scale using SWAT (Soil and Water Assessment Tools) model, with the goal of estimating the streamflow for three hydrographic regions in Peru: the Pacific, Titicaca and Amazonas. Hydrological models were calibrated using observed discharge data which is sparse and poorly distributed over Peru. In this context, we design a regional parameter estimation following the next steps: i) First, a regionalization of 3394 hydrological response units (HRU) in the whole country were built through Ward’s hierarchical cluster criterion, in which 14 calibration regions were defined. ii) A calibration procedure to obtain the best calibration parameters was made with Non-dominated Sorting Genetic Algorithm (NSGA-II) optimization using the Kling-Gupta (KGE) and Nash Sutcliffe Logarithmic (LogNSE) statistics. A total of 31 hydrological stations were selected to calibration and validation procedure with the condition of leaving at least one in each region defined at point i) iii) Using the physical similarity approach, each set of calibrated parameters was averaged in each region to get the regional parameter sets