Factors impacting sustainability in rural drinking water: an integrated approach in Paraguay

The research assesses the sustainability of a program intervention in drinking-water supply in 100 rural communities in Paraguay and identifies the main factors and good practices that could correlate with higher levels of sustainability for drinking-water supply systems. The research includes an integrated assessment of the technical systems, the governance of the community-based provider, and the user’s participation. A total of 100 drinking-water systems built between 2006 and 2010 were technically and operationally revised. Surveys were conducted to 100 community-based sanitation boards (SB) and 450 beneficiary households, using systematic random sampling in 30 rural communities. Preliminary results suggest that participation of the users, the institutional capacity of the SB, the external support of a public institution – as SENASA in this case - and the reinforcement of maintenance activities seem to be key aspects to keep sustainability in rural water systems in the medium and long term

Case Study in Jagua Bay at South of Cuba Using a Coupling WRF/CALMET

<p></p><p>Abstract CALMET meteorological model was evaluated during a typical period of dry season in a coastal domain in the Jagua bay at the south of Cuba, for TERRAD parameter. Several resolutions and four different CALMET input datasets were used. The evaluation was focused in terms of model performance of wind and surface temperature issues. As input data, the WRF model results and meteorological measurements of different stations were combined. WRF model surface speed results has been significantly improved by CALMET model. A slightly improvement is obtained with resolution increasing. A high value of TERRAD of 80 km was obtained as the best fit for this parameter that matches with the domain size. The statistical results (both relative and absolute) were calculated on the stations that were not used as input data. Statistical relative values of wind speed were high, due to weak winds over the study period. However, the absolute ones were better. Significant improvement was also observed in wind speed and temperature for relative and absolute statistical values, when more stations as input data were provided.</p><p></p