Sustainable management of water ecosystem services requires reliable information to support decision making. We evaluate the performance of the InVEST Seasonal Water Yield Model (SWYM) against water monitoring records in 224 catchments in southern Chile. We run the SWYM in three years (1998, 2007 and 2013) to account for recent land-use change and climatic variations. We computed squared Pearson correlations between SWYM monthly quickflow predictions and streamflow observations and applied a generalized mixed‐effects model to evaluate annual estimations. Results show relatively low monthly correlations with marked latitudinal and temporal variations while annual estimates show a good match between observed and modeled values, especially for values under 1000 mm/year. Better predictions were observed in regions with high rainfall and in dry years while poorer predictions were found in snow dominated and drier regions. Our results improve SWYM performance and contribute to water supply and regulation decision-making, particularly in data scarce regions.

水生态系统服务的可持续管理需要可靠的信息来支持决策。我们根据智利南部224个集水区的水监测记录评估了InVEST季节性水产量模型（SWYM）的性能。我们在三年（1998年，2007年和2013年）中运行SWYM，以应对近期的土地利用变化和气候变化。我们计算了SWYM每月快速流量预测与流量观测值之间的平方Pearson相关性，并应用了广义混合效应模型来评估年度估计。结果显示相对较低的月度相关性，具有明显的纬度和时间变化，而年度估算值则显示出观测值和模型值之间的良好匹配，尤其是对于1000 mm /年以下的值。在高降雨地区和干旱年份观察到更好的预测，而在以雪为主和较干燥的地区则发现较差的预测。我们的结果提高了SWYM的绩效，并有助于供水和监管决策，尤其是在数据稀缺地区。