Understanding the Scale Relationships of Uncertainty Propagation of Satellite Rainfall through a Distributed Hydrologic Model

Abstract

The study presents a data-based numerical experiment performed to understand the scale relationships of the error propagation of satellite rainfall for flood evaluation applications in complex terrain basins. A satellite rainfall error model is devised to generate rainfall ensembles based on two satellite products with different retrieval accuracies and space–time resolutions. The generated ensembles are propagated through a distributed physics-based hydrologic model to simulate the rainfall–runoff processes at different basin scales. The resulted hydrographs are compared against the hydrograph obtained by using high-resolution radar rainfall as the “reference” rainfall input. The error propagation of rainfall to stream runoff is evaluated for a number of basin scales ranging between 100 and 1200 km2. The results from this study show that (i) use of satellite rainfall for flood simulation depends strongly on the scale of application (catchment area) and the satellite product resolution, (ii) different satellite products perform differently in terms of hydrologic error propagation, and (iii) the propagation of error depends on the basin size; for example, this study shows that small watersheds (<400 km2) exhibit a higher ability in dampening the error from rainfall to runoff than larger-sized watersheds, although the actual error increases as drainage area decreases.

Evaluation of global fine-resolution precipitation products and their uncertainty quantification in ensemble discharge simulations

“…The APHRODITE, PERSIANN, and GSMAP products are seldom evaluated in northeast China using basin-scale gauge data (Zhou et al, 2008). Owing to the high heterogeneity of rainfall across a variety of spatiotemporal scales, the uncertainty characteristics of precipitation products are variable (Asadullah et al, 2008;Dinku et al, 2008;Nikolopoulos et al, 2010;Pan et al, 2010). Thus, in northeast China, it is essential to completely evaluate the applicability of these precipitation products.…”

Avaliação de um Modelo Estocástico de Erro Multidimensional Aplicado a Estimativas de Precipitação por Satélite

“…Neste trabalho foi possível avaliar o modelo de propagação de erro SREM2D e concluir que este modelo possui potencial para gerar campos realísticos de precipitação para bacias de grande porte, complementando os estudos de Maggioni et al (2013) e Nikolopoulos et al (2010), aplicados a bacias de pequeno porte.…”

Flood hazard assessment and mapping in semi-arid piedmont areas: a case study in Beni Mellal, Morocco

“…Less testing has been undertaken in smaller catchments (less than 100 km 2 ). Nikolopoulos et al (2010) showed that the error propagation from satellite rainfall estimates to a hydrological model is dependent on the catchment scale: in small-scale applications, product resolution becomes a critical issue. Even though the spatial resolution is relatively coarse compared to the scale of the studied catchments, this open-source dataset provided the most precise available rainfall representation in terms of temporal resolution.…”

“…Satellite and radar-borne rainfall data are increasingly used in regions where gauging networks are insufficient (Hong et al 2007;Nikolopoulos et al 2010). Remotely sensed data may provide spatially distributed rainfall estimates for often inaccessible catchment areas (Nikolopoulos et al 2010) that can prove more effective in capturing the spatial and temporal variability in rainfall than point gauges.…”

“…Remotely sensed data may provide spatially distributed rainfall estimates for often inaccessible catchment areas (Nikolopoulos et al 2010) that can prove more effective in capturing the spatial and temporal variability in rainfall than point gauges. Rainfall data obtained from airborne sources need to be implemented in a rainfall-runoff model in order to simulate a given flood and assess the hazard associated with it.…”