几乎所有用于预测水需求的变量都是不确定的:人口和家庭构成、就业和工业增长、客户部门的收入和用水特征、保护目标和绩效，以及天气。准确预测的关键是分离或指定每个变量的影响，以便将随时间变化的变量引起的需水量变化准确地包括在预测中。在正确指定预测模型后，识别固有误差水平并利用其确定潜在需水量的上限和下限，比坚持微调模型以从有限的数据库中提取最后一盎司效率要有效得多。本文的目的是简要讨论需求预测的主要方法，然后集中于衡量保护绩效，并将保护目标纳入长期规划- 进行需求预测。包括10个参考文献、图表。

Virtually all variables used to forecast water demand are uncertain: population and household formation, employment and industrial growth, income and water use characteristics by customer sectors, conservation targets and performances, and weather. The key to accurate forecasting is to isolate or specify the effects of each variable so that changes in water demand that are attributable to changes in the variables over time can be accurately included in the forecasts. After a forecasting model has been properly specified, it is far more efficient to recognize the inherent error level and work with it to identify upper and lower bounds of potential water demand than to persist in fine-tuning the model to extract the last ounce of efficiency from a limited database. The objective of this article is to briefly discuss the major methods of demand forecasting and then concentrate on measuring conservation performance and integrating conservation targets into long-run demand projections. Includes 10 references, figures.