Abstract
A dense rain-gauge network within continental Ecuador was used to evaluate the quality of various products of rainfall data over the Pacific slope and coast of Ecuador (EPSC). A cokriging interpolation method is applied to the rain-gauge data yielding a gridded product at 5-km resolution covering the period 1965–2015. This product is compared with the Global Precipitation Climatology Centre (GPCC) dataset, the Climatic Research Unit–University of East Anglia (CRU) dataset, the Tropical Rainfall Measuring Mission (TRMM/TMPA 3B43 Version 7) dataset and the ERA-Interim Reanalysis. The analysis reveals that TRMM data show the most realistic features. The relative bias index (Rbias) indicates that TRMM data is closer to the observations, mainly over lowlands (mean Rbias of 7%) but have more limitations in reproducing the rainfall variability over the Andes (mean Rbias of −28%). The average RMSE and Rbias of 68.7 and −2.8% of TRMM are comparable with the GPCC (69.8 and 5.7%) and CRU (102.3 and −2.3%) products. This study also focuses on the rainfall inter-annual variability over the study region which experiences floods that have caused high economic losses during extreme El Niño events. Finally, our analysis evaluates the ability of TRMM data to reproduce rainfall events during El Niño years over the study area and the large basins of Esmeraldas and Guayas rivers. The results show that TRMM estimates report reasonable levels of heavy rainfall detection (for the extreme 1998 El Niño event) over the EPSC and specifically towards the center-south of the EPSC (Guayas basin) but present underestimations for the moderate El Niño of 2002–2003 event and the weak 2009–2010 event. Generally, the rainfall seasonal features, quantity and long-term climatology patterns are relatively well estimated by TRMM.
Highlights
Spatio-temporal analysis of rainfall is crucial for water-resource management including water supply, risk management, sustainable agriculture and hydrological infrastructure
The results of the comparison between in situ observations interpolated with cokriging method (COK) and the four rainfall products described in Section 3.2 are presented in Table 2 and Figure 4
Comparison of the gridded observations with the commonly used rainfall datasets from Global Precipitation Climatology Centre (GPCC), Climatic Research Unit–University of East Anglia (CRU), ERA-Interim reanalysis, and the satellite estimates from Tropical Rainfall Measuring Mission (TRMM) 3B43, showed that the satellite-based rainfall product provides the more reliable estimates
Summary
Spatio-temporal analysis of rainfall is crucial for water-resource management including water supply, risk management, sustainable agriculture and hydrological infrastructure. These aspects must be addressed and discussed before promulgating public policies in order to achieve the best climate-adapted development. The Ecuadorian Pacific slope and coast (EPSC) is an area of particular interest due to its physiographic features (surface, altitudinal range and the considerable horizontal distance from the coastal border to the watershed division on the high Andes) because they have a strong impact on the spatial variability of rainfall. The El Niño-Southern Oscillation (ENSO) is commonly identified as the main driver of temporal rainfall variability along the Ecuadorian coastal region and how the influence of this is different on the Andes [5]. The results of a 35-year simulation of rivers’ runoff over the Pacific Slope and coast of South America (PSCSA) showed that 15% of the total
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