42 resultados para Early Warning and Nowcasting Approaches for Water Quality in Riverine and Coastal Systems


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The Republic of Haiti struggles to sustainably manage its water resources. Public health is compromised by low levels of water supply, sanitation, and hygiene, and water resources are often contaminated and unsustainably allocated. While poor governance is often blamed for these shortcomings, the laws and institutions regulating water resources in Haiti are poorly understood, especially by the international community. This study brings together and analyzes Haitian water laws, assesses institutional capacities, and provides a case study of water management in northern Haiti in order to provide a more complete picture of the sector. Funded by the Inter-American Development Bank as part of the Water Availability, Quality and Integrated Water Resources Management in Northern Haiti (HA-T1179) Project, this study took place from January-July 2015, with the help of local experts and participating stakeholders. The results indicate that Haiti’s water law framework is highly fragmented, with overlapping mandates and little coordination between ministries at the national level, and ambiguous but unrealistic roles for subnational governments. A capacity assessment of institutions in northern Haiti illustrates that while local stakeholders are engaged, human and financial resources are insufficient to carry out statutory responsibilities. The findings suggest that water resources management planning should engage local governments and community fixtures while supplementing capacities with national or international support.

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Continuous and reliable monitoring of contaminants in drinking water, which adversely affect human health, is the main goal of the Broward County Well Field Protection Program. In this study the individual monitoring station locations were used in a yearly and quarterly spatiotemporal Ordinary Kriging interpolation to create a raster network of contaminant detections. In the final analysis, the raster spatiotemporal nitrate concentration trends were overlaid with a pollution vulnerability index to determine if the concentrations are influenced by a set of independent variables. The pollution vulnerability factors are depth to water, recharge, aquifer media, soil, impact to vadose zone, and conductivity. The creation of the nitrate raster dataset had an average RMS Standardized error close to 1 at 0.98. The greatest frequency of detections and the highest concentrations are found in the months of April, May, June, July, August, and September. An average of 76.4% of the nitrate intersected with cells of the pollution vulnerability index over 100.