Seasonal streamflow forecast bias, changes in climate, snowpack, and land cover, and the effects of these changes on relations between basin‐wide snowpack, SNOw TELemetry (SNOTEL) station snowpack, and seasonal streamflow were evaluated in the headwaters of the Rio Grande, Colorado. Results indicate that shifts in the seasonality of precipitation and changing climatology are consistent with periods of overprediction and underprediction in streamflow forecasts. Multiple linear regression of SNOTEL data, postcedent precipitation, and land‐cover changes explained 2%–18% more variability in streamflow prediction than using SNOTEL station data alone. Simulated basin‐wide snowpack from a physically based model had significant negative trends in snow water equivalent (−4.33 mm/yr) and snow‐covered area (−0.05%/yr) during the melt period April–June. Simulated streamflow from a precipitation‐runoff model increased an average 5% when the effects of bark beetle‐induced tree mortality were compared to a baseline simulation with static vegetation. The effects of a 2013 wildfire increased simulated seasonal streamflow an average 35% for 1–4 years postfire. The combined effects of climate and land‐cover changes on snowpack‐streamflow relations highlight the difficulty in seasonal streamflow forecasting, which has important implications for water‐resource management.

中文翻译：

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气候和土地覆盖的变化影响里奥格兰德河源头的季节性流量预报

在里奥格兰德河源头评估了季节性流量预报的偏差，气候，积雪和土地覆盖的变化，以及这些变化对全流域积雪，SNOw TELemetry（SNOTEL）站积雪和季节性流量之间关系的影响，科罗拉多州。结果表明，降水季节变化和气候变化与流量预测中的高估和低估时期相一致。与仅使用SNOTEL站台数据相比，SNOTEL站数据，先验降水和土地覆盖变化的多元线性回归解释了流量预测的可变性要高2％–18％。在4月至6月的融化期间，基于物理模型的模拟全盆积雪在雪水当量（−4.33 mm / yr）和积雪面积（−0.05％/ yr）方面具有明显的负趋势。将树皮甲虫引起的树木死亡率的影响与静态植被的基线模拟进行比较时，降水径流模型的模拟流量平均增加了5％。2013年野火的影响使火灾后1-4年的模拟季节性流量平均增加了35％。气候和土地覆盖变化对积雪-水流关系的综合影响突显了季节性水流预测的困难，这对水资源管理具有重要意义。