No abstract

UASB (upflow anaerobic sludge blanket) reactors have been recognized as a viable option for sewage treatment. However, in order to improve the UASB effluent quality, some type of post-treatment must be implemented. The aims of this study were (i) to establish a start-up methodology of a full-scale anaerobic–aerobic system treating sewage, (ii) to evaluate the concentrations of different constituents in the influent and effluent of the anaerobic and aerobic reactors as well as the removal efficiencies in every step of the system, and (iii) to define relevant operative aspects of the anaerobic and aerobic reactors. The Tunja (Colombia) wastewater treatment plant consists of three modules with preliminary treatment followed by UASB reactors with post-treatment of activated sludge. The results of this investigation showed that the effluent system meets the Colombian environmental legislation with average removal efficiency values of BOD (88 +/− 5%), COD (87 +/− 4%), and TSS (94 +/− 5%). The UASB reactor start-up was conducted without an inoculum, requiring a period of 120 days. The evaluation of the combined systems was conducted over 300 days. Moreover, a methodology to operate the system during and after the start-up of the anaerobic reactor was defined. It was demonstrated that the anaerobic effluent can deteriorate the sludge in the aerobic tank. In order to avoid this, important operational aspects must be considered during the operation of the system, such as the implementation of a raw wastewater bypass higher than 15% and monitoring of the anaerobic effluent settleable solid concentration (<0.3 mL/L).

Climate variability, as an element of uncertainty in water management, affects community, sectoral, and individual decision-making. Long-range prediction models are tools that offer the potential for integration and joint analysis with the hydrological, hydrodynamic, and management response of the socioecological systems to which they are linked. The main objective of this article is to present a seasonal climate prediction model, the open-source algorithm SIE-Climate, whose application consists of three phases (exploration, development, and evaluation), and to describe its application to the Lake Sochagota socio-ecological system (Paipa, Boyac a, Colombia). The K-nearest neighbours method is used when defining a target matrix that represents and integrates macro-and micro-climatic phenomena (Oceanic Niño Index, local temperature, and local rainfall) to identify periods of similar climatic behaviour. Considering a 1-year horizon and management purposes the tool is calibrated and validated in periods with and without climatic anomalies (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012)(2013)(2014)(2015)(2016)(2017)(2018), giving reliable adjustment results (RSME:4.86; R 2 : 0.95; PBIAS: −8.89%; EFF: 0.85). SIE-Climate can be adapted to various contexts, variables of interest, and temporal and spatial scales, with an appropriate technological and computational cost for regional water management.