Abstract
Water use patterns were explored for three small communities that are located in proximity to agricultural fields and rely on their local wells for potable water supply. High-resolution water use data, collected over a four-year period, revealed significant temporal variability. Monthly, daily, and hourly water use patterns were well described by autoregressive moving average (ARMA) models. Model development was supported by unsupervised clustering analysis via self-organizing maps (SOMs) that revealed similarities of water use patterns and confirmed the time-series water use model attributes. The inclusion of ambient temperature and rainfall as model attributes improved ARMA model performance for daily and hourly water use from R2 ~0.86–0.87 to 0.94–0.97 and from R2 ~0.85–0.89 to 0.92–0.98, respectively. Water use predictions for an entire year forward in time was feasible demonstrating ARMA models’ performance of (i) R2 ~0.90–0.94 and average absolute relative error (AARE) of ~2.9–4.9% for daily water use, and (ii) R2 ~0.81–0.95 and AARE ~1.9–3.8% for hourly water use. The study suggests that ARMA modeling should be useful for analysis of temporally variable water use in support of water source management, as well as assessing capacity building for small water systems including water treatment needs and wastewater handling.
Highlights
The freshwater sources such as rivers, lakes, reservoirs, and groundwater are increasingly being utilized worldwide [1,2]
The time-series water use data were initially explored by self-organizing maps (SOM) and pair-wise correlations data were initially explored by self-organizing maps (SOM) and pair-wise (Spearman coefficient)
Self-organizing map (SOM) clustering was used for visual depiction of similarities in water use patterns among the days of the week and months of the year
Summary
The freshwater sources such as rivers, lakes, reservoirs, and groundwater are increasingly being utilized worldwide [1,2]. In California, impaired groundwater contamination and excessive water salinity are severe in communities in agricultural regions [4,5]. San Joaquin Valley, California, relies on groundwater for its drinking water needs. In this region, there are communities whose water supplies are contaminated by high nitrate levels, which is attributed, in part, to intensive agricultural activities [4,5] and impact of septic systems. Small and disadvantaged communities (i.e., with a community median household income of less than 80% of the state annual median household income), who rely on groundwater as their only potable water source, are the most severely impacted
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