Assessment of Arequipa's Hydrometeorological Monitoring Infrastructure to Support Water Management Decisions. (14th January 2021) - de Lima Moraes, André Geraldo; Bocardo‐Delgado, Edwin; Bowling, Laura C.; Daneshvar, Fariborz; Pinto, José; Watkins, Alec Hale; Cherkauer, Keith Aric
Abstract: Hydrometeorological monitoring of weather, streamflow, and water quality is essential for understanding available water resources, protecting populations from hazard, and identifying changes in environmental conditions over time. To meet such competing goals, monitoring networks require representative parameters, uniform sampling protocols, and stable locations, selected to reliably measure the phenomenon of interest. However, budgets are always limited, and immediate operational needs and short‐term decisions often influence monitoring decisions. Here, the hydrometeorological monitoring systems in Arequipa, Peru, are examined with respect to established criteria for their ability to support these competing goals. The Arequipa Department in Peru has a well‐established, stable, weather monitoring program, although reliance on manual observers results in variable data quality. The lack of observations in high altitude areas limits estimation of water availability, and high temporal resolution, automatic stations are needed to improve flash flood warnings. The streamflow monitoring system is designed to quantify water transfers throughout this heavily managed system. Twenty‐one discharge monitoring stations were identified to serve as Historic Hydrologic Reference Stations, but many were only operational in the 1960s and 1970s and cannot be used to evaluate environmental trends. Twelve stations are identified that should be maintained for establishment of a future reference network. State sponsored water quality monitoring in the Department is fairly new, and a stratified sampling method has been used to maximize sample locations. Uniform sampling in fewer locations along intermediate sized tributaries, at least two times per year, would improve the reliability of the system and allow better detection of change over time.