Abstract. At present, new technologies are becoming available to extend the coverage of conventional meteorological datasets. An example is the TMPA-3B42R dataset (research -v6). The usefulness of this satellite rainfall product has been investigated in the hydrological modeling of the Vinces River catchment (Ecuadorian lowlands). The initial TMPA-3B42R information exhibited some features of the precipitation spatial pattern (e.g., decreasing southwards and westwards). It showed a remarkable bias compared to the groundbased rainfall values. Several time scales (annual, seasonal, monthly, etc.) were considered for bias correction. High correlations between the TMPA-3B42R and the rain gauge data were still found for the monthly resolution, and accordingly a bias correction at that level was performed. Bias correction factors were calculated, and, adopting a simple procedure, they were spatially distributed to enhance the satellite data. By means of rain gauge hyetographs, the bias-corrected monthly TMPA-3B42R data were disaggregated to daily resolution. These synthetic time series were inserted in a hydrological model to complement the available rain gauge data to assess the model performance. The results were quite comparable with those using only the rain gauge data. Although the model outcomes did not improve remarkably, the contribution of this experimental methodology was that, despite a high bias, the satellite rainfall data could still be corrected for use in rainfall-runoff modeling at catchment and daily level. In absence of rain gauge data, the approach may have the potential to provide useful data at scales larger than the present modeling resolution (e.g., monthly/basin).

No abstract

Agricultural intensification has stimulated the economy in the Guayas River basin in Ecuador, but also affected several ecosystems. The increased use of pesticides poses a serious threat to the freshwater ecosystem, which urgently calls for an improved knowledge about the impact of pesticide practices in this study area. Several studies have shown that models can be appropriate tools to simulate pesticide dynamics in order to obtain this knowledge. This study tested the suitability of the Soil and Water Assessment Tool (SWAT) to simulate the dynamics of two different pesticides in the data scarce Guayas River basin. First, we set up, calibrated and validated the model using the streamflow data. Subsequently, we set up the model for the simulation of the selected pesticides (i.e., pendimethalin and fenpropimorph). While the hydrology was represented soundly by the model considering the data scare conditions, the simulation of the pesticides should be taken with care due to uncertainties behind essential drivers, e.g., application rates. Among the insights obtained from the pesticide simulations are the identification of critical zones for prioritisation, the dominant areas of pesticide sources and the impact of the different land uses. SWAT has been evaluated to be a suitable tool to investigate the impact of pesticide use under data scarcity in the Guayas River basin. The strengths of SWAT are its semi-distributed structure, availability of extensive online documentation, internal pesticide databases and user support while the limitations are high data requirements, time-intensive model development and challenging streamflow calibration. The results can also be helpful to design future water quality monitoring strategies. However, for future studies, we highly recommend extended monitoring of pesticide concentrations and sediment loads. Moreover, to substantially improve the model performance, the availability of better input data is needed such as higher resolution soil maps, more accurate pesticide application rate and actual land management programs. Provided that key suggestions for further improvement are considered, the model is valuable for applications in river ecosystem management of the Guayas River basin.

Abstract. The equatorial Daule and Babahoyo rivers meet and combine into the tidal Guayas River, which flows into the largest estuary on the Pacific coast of South America. The city of Guayaquil, located along the Guayas, is the main port of Ecuador but, at the same time, the planet's fourth most vulnerable city to future flooding due to climate change. Sedimentation, which has increased in recent years, is seen as one of the factors contributing to the risk of flooding. The cause of this sedimentation is the subject of the current research. We used the process-based Delft3D FM model to assess the dominant processes in the river and the effects that past interventions along the river and its estuary have had on the overall sediment budget. Additionally, a simulation including sea level rise was used in order to understand the possible future impact of climate change on the sediment budget. Results indicate an increase in tidal asymmetry due to land reclamation and a decrease in episodic flushing by river floods due to upstream dam construction. These processes have induced an increased import of marine sediment potentially responsible for the observed sedimentation. This is in contrast with the local perception of the problem, which ascribes sedimentation to deforestation in the upper catchment. Only the deposition of silt and clay in connected stagnant water bodies could perhaps be ascribed to upstream deforestation.

No abstract

Duran is a coastal city located in the Guayas Estuary region in which 24% of urban sectors suffers from the effects of chronic flooding. This study seeks to assess the causes of Duran’s vulnerability by considering exposure, population sensitivity and adaptive capacity to establish alternatives to reduce its vulnerability to flooding. An operational framework is proposed based on the vulnerability definition of the Intergovernmental Panel on Climate Change (IPCC) and applying a census-based Index of Vulnerability, a geographic information system and local knowledge of urban development. A Principal Component and equal weighting analysis were applied as well as a spatial clustering to explore the spatial vulnerability across the city. A total of 34% of the city area is mapped as having high and very high vulnerability, mostly occupied by informal settlements (e.g., 288 hectares). Underlying factors were poor quality housing, lack of city services and low adaptive capacity of the community. However, some government housing programs (e.g., El Recreo), with better housing and adaptive capacity were also highly vulnerable. Limited urban planning governance has led to the overloading of storm water and drainage infrastructure which cause chronic flooding. Understanding the underlying causes of vulnerability is critical in order develop integrated strategies that increase city resilience to climate change.

Abstract. The Equatorial Daule and Babahoyo rivers meet and combine into the tidal Guayas River, which flows into the largest estuary on the Pacific coast of South America. The city of Guayaquil, located along the Guayas, is the main port of Ecuador but, at the same time, the planet's fourth most vulnerable city to future flooding due to climate change. Fluvial sedimentation, which has increased in the recent years, is seen as one of the factors contributing to the risk of flooding. The planning and design of effective mitigation measures requires a good understanding of the causes which have led to the current hazards. In this study, the process-based Delft3D FM model was used in order to explain the dominant processes in the river and the effects that past interventions along the river and its estuary have had in the overall sediment budget. Additionally, a simulation including sea level rise was used in order to understand the possible future impact of climate change on the sediment budget. Results indicate that the increased import of marine sediment is the result of the recent increase in tidal asymmetry due to land reclamation and a decrease of episodic flushing by river floods due to upstream dam construction. This is in contrast with the local perception of the problem, which ascribes sedimentation to deforestation in the upper catchment. Only the deposition of silt and clay in connected stagnant water bodies could perhaps be ascribed to upstream deforestation.

Nowadays, new technologies are being used to expand the coverage of conventional meteorological datasets. An example of these is the TRMM data as long as one considers the bias, the type of rainfall and the current coarse spatial resolution. Although in the Guayas River Basin (Ecuadorian lowlands) the radar-based precipitation does not match the magnitude of the ground-based rainfall, at least it records somewhat the spatial pattern. The bias remains more or less steady when the temporal resolution increases from yearly to seasonal and monthly data. By means of an empirical disaggregation method, synthetic daily rainfall time series were generated at the satellite measuring spots. These artificial series were incorporated into an existing hydrological model to complement the available raingauge data to assess the model performance. The results were quite comparable with those using only gauge information. Although the model outcomes did not improve remarkably, the contribution of this approach was based on the fact that given a known bias, the satellite data could still be corrected and may resemble the information provided by the raingauges. Therefore, TRMM may supply valuable information in areas scarcely gauged such as the Andean foothills in the Guayas River Basin