Author
Abstract
Castanhão is the largest non-hydropower dam in Latin America, which was built in 2002 to serve as a multi-use strategic reservoir in the Brazilian semiarid. Although this reservoir reached 96 % of its capacity in 2009, a severe drought from 2012-2016 resulted in extreme variations in water storage (2 - 82 %) and total phosphorus (TP) in the water (1.0 ⋅ 101 - 2.2 ⋅ 102 mg/m³) and sediments (2.0 ⋅ 105 - 1.4 ⋅ 106 mg/m³), leading to massive fish mortalities and abrupt increases in water treatment costs. In this study, complete-mix TP models considering water and sediment compartments and several improvements compared to previous models such as distinct variabilities of water volume and hypoxic area were developed and tested for the entire study period (2008-2022), including floods and droughts. The model incorporating a stronger pattern of hypoxia in the wet period best represented TP dynamics in the reservoir, with acceptable Nash-Sutcliffe efficiency (NSE = 0.46) and percent bias (PBIAS = -8.98 %) for the water, as well as for the sediments (NSE = 0.80 and PBIAS = +0.39 %). Excepting for the output load, all the other TP fluxes decreased from wet to dry periods, following approximately the behavior of inflow and water volume. An average mass balance in the water showed that the TP sources from external load (25.3 %), fish-cage load (16.3 %) and release from anoxic sediments (8.2 %) were approximately equal to the TP sinks from settling (46.8 %) and output load (3.4 %). On the other hand, a mass balance in the sediments revealed that the TP source from settling (78.5 %) was substantially higher than the TP sinks from release (13.8 %) and burial (7.4 %). Model simulations until 2050 suggested a progressive TP increase both in the water and sediments. Moreover, a total load reduction of at least 80 % would be necessary to stabilize TP concentration in both compartments.
Suggested Citation
Lima Neto, Iran Eduardo, 2025.
"Phosphorus dynamics in water and sediments in a large multi-use reservoir under extreme volume variation,"
Ecological Modelling, Elsevier, vol. 510(C).
Handle:
RePEc:eee:ecomod:v:510:y:2025:i:c:s0304380025003023
DOI: 10.1016/j.ecolmodel.2025.111316
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