Date of Award
Master of Science
Thomas M. Fullerton
Short-term water demand forecasts inform decisions regarding budgeting, rate design, water supply system operations, and effective implementation of conservation policies. This study develops a Linear Transfer Function (LTF) forecasting model for El Paso, Texas, a growing city located in the desert Southwest region of the United States. The model is used to generate monthly-frequency out-of-sample simulations of water demand for periods when actual demand is known. To measure the accuracy of the LTF projections against viable alternatives, a set of benchmark forecasts is also developed. Both descriptive accuracy metrics and formal statistical tests are used to analyze predictive performance. The LTF model outperforms the alternatives in predicting demand per customer but falls a little short in projecting growth in the customer base. Changes in climatic and economic conditions are found to impact consumption per customer more rapidly than changes in water rates.
Received from ProQuest
Ceballos, Alejandro, "Short-Term Forecasting Analysis of Municipal Water Demand in El Paso, Texas" (2015). Open Access Theses & Dissertations. 1012.