Increasing pressures caused by human activities pose a major threat to water availability and quality worldwide. Water resources have been declining in many catchments during recent decades. This study investigated patterns of river water quality status in a peri-urban/rural catchment in Bolivia in relation to land use during a 26 year period. Satellite images were used to determine changes in land use. To assess water quality, data in the dry season from former studies , complemented with newly collected data (2017), were analysed using the National Sanitation Foundation-Water Quality Index method and the Implicit Pollution Index method. The highest rates of relative increase in land use area were observed for forest, urban, and peri-urban areas, whereas relative decreases were observed for water infiltration zones, bare soil, shrubland, and grassland areas. The water quality indices revealed clear water quality deterioration over time, and from catchment headwaters to outlet. Statistical analyses revealed a significant relationship between decreasing water quality and urban expansion. These results demonstrate the need for an effective control programme, preferably based on water quality index approaches as in the present study and including continuous monitoring of runoff water, mitigation of pollution, and water quality restoration, in order to achieve proper water management and quality.
Changes in pollution pressure exerted on the Rocha River in Bolivia from diffuse sources were assessed using potential non-point pollution indexes (PNPI) for 1997 and 2017. PNPI is a simple, low-effort, time- and resource-saving method suitable for data-scarce regions, as it works at catchment level with commonly available geographical data. Land use type (obtained by Landsat imagery classification), runoff (determined by runoff coefficient characterisation) and distance to river network (calculated at perpendicular distance) were each transformed into corresponding indicators to determine their relative importance in generating pollution. Weighted sum, a multi-criteria analysis tool in the GIS environment, was used to combine indicators with weighting values. Different weighting values were assigned to each of the indicators resulting in a set of six equations. The results showed that higher PNPI values corresponded to human settlements with high population density, higher runoff values and shorter distance to river network, while lower PNPI values corresponded to semi-natural land use type, lower runoff coefficient and longer distances to river. PNPI values were positively correlated with measured nitrate and phosphate concentrations at six sub-catchment outlets. The correlation was statistical significant for phosphate in 2017. Maps were produced to identify priority source areas that are more likely to generate pollution, which is important information for future management.
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