Effects of rainfall and land use on nutrient responses in rivers in the Brazilian semiarid region.

This paper investigated whether rainfall promotes dilution or increase in nutrient concentrations and which land use indicators are the main predictors of nutrients in intermittent rivers in a large Brazilian semiarid region. The total phosphorus (TP) and total inorganic nitrogen (TIN) were monitored between 2013 and 2018 at 92 river water quality monitoring sites. The monthly rainfall (Rn) was obtained from 575 rain gauges. Pearson's correlation (R) between Rn and nutrient concentration was performed. The correlation patterns were also analysed based on land use data: urban area (%), agricultural field area (%), demographic density (inhabitants/km2), sewer system coverage (%), and reservoir density (reservoir/km2). Backward stepwise regression was performed to identify predictors of nutrient concentrations. The results revealed a marginal effect of rainfall on nutrients when the effects of urbanisation outweigh all other aspects. However, in regions with greater accumulated rainfall and lower reservoir density, the rainfall was related to a linear increase in nutrient concentrations (R > 0.8). Contrastingly, in the basins with less accumulated rainfall and greater inter-basin hydrological disconnection, there was a linear reduction in nutrient concentration (R < - 0.5). In the backward stepwise regression, sewer system coverage and Rn had the greatest influence for TP, and the urban area was the strongest predictor for TIN. Importantly, our results demonstrated that in semiarid rivers in densely populated regions, there is no single pattern of variability in nutrient concentration, on a wide scale of assessment. Therefore, adaptative and decentralised management can be more effective in improving water quality in these regions.

Influence of hydroclimatic variability on dengue incidence in a tropical dryland area.

Dengue is an endemic disease in more than 100 countries, but there are few studies about the effects of hydroclimatic variability on dengue incidence (DI) in tropical dryland areas. This study investigates the association between hydroclimatic variability and DI (2008-2018) in a large tropical dryland area. The area studied comprehends seven municipalities with populations ranging from 32,879 to 2,545,419 inhabitants. First, the precipitation and temperature impacts on interannual and seasonal DI were investigated. Then, the monthly association between DI and hydroclimatic variables was analyzed using generalized least squares (GLS) regression. The model's capability to reproduce DI given the current hydroclimatic conditions and DI seasonality over the entire time period studied were assessed. No association between the interannual variation of precipitation and DI was found. However, seasonal variation of DI was shaped by precipitation and temperature. February-July was the main dengue season period. A precipitation threshold, usually above 100 mm, triggers the rapid DI rising. Precipitation and minimum air temperature were the main explanatory variables. A two-month-lagged predictor was relevant for modeling, occurring in all regressions, followed by a non-lagged predictor. The climate predictors differed among the regression models, revealing the high spatial DI variability driven by hydroclimatic variability. GLS regressions were able to reproduce the beginning, development, and end of the dengue season, although we found underestimation of DI peaks and overestimation of low DI. These model limitations are not an issue for climate change impact assessment on DI at the municipality scale since historical DI seasonality was well simulated. However, they may not allow seasonal DI forecasting for some municipalities. These findings may help not only public health policies in the studied municipalities but also have the potential to be reproducible for other dryland regions with similar data availability.

Assessment of phosphorus loading dynamics in a tropical reservoir with high seasonal water level changes.

Nutrient accumulation in man-made reservoirs has been documented worldwide. Therefore, quantifying phosphorus loading and understanding its temporal dynamics in reservoirs is mandatory for sustainable water management. In this study, the Vollenweider's complete-mix phosphorus budget model was adapted to account for high water level variations, which are a common feature in tropical reservoirs, and for internal phosphorus loads. First- and zero-order kinetics were adopted to simulate phosphorus settling and release from the sediment layer, respectively, considering variable area of phosphorus release according to the height of the anoxic layer. The modeling approach was applied for a 52-months period to a 31-years-old reservoir located in the semiarid region of Brazil with 7.7 hm3 storage capacity. The simulations were supported by hydrological, meteorological and water quality data, as well as analyses of phosphorus partitioning of the reservoir bed sediment. The external phosphorus load was estimated from a relationship adjusted between inflow and phosphorus concentration, revealing an u-shaped pattern. Sedimentary phosphorus linked to iron and aluminum (PFeAl) increased over time and along the reservoir. Such measurements were used to estimate the internal phosphorus load, i.e., the yield from the bed sediments to the water column. The adaptations proposed to the model's structure improved its capacity to simulate phosphorus concentration in the water column, from "not satisfactory" to "good". We estimate that the internal phosphorus load currently accounts for 44% of the total load. It prevailed during the wet period, when reservoir stratification and hypolimnetic hypoxia were more notable, resulting in higher phosphorus concentration in the water column due to the combined effects of internal and external loadings. However, if the reservoir were 70 years older, the internal load would reach 83% of the total and the reservoir would become a source instead of a sink of phosphorus.