Realistic estimates of daily streamflow and water temperature are requiredfor effective management of water resources (e.g. for electricity and drinkingwater production) and freshwater ecosystems. Although hydrological andprocess-based water temperature modelling approaches have been successfullyapplied to small catchments and short time periods, much less work has beendone at large spatial and temporal scales. We present a physically basedmodelling framework for daily river discharge and water temperaturesimulations applicable to large river systems on a global scale. Modelperformance was tested globally at 1/2 × 1/2° spatial resolutionand a daily time step for the period 1971–2000. We made specific evaluationson large river basins situated in different hydro-climatic zones andcharacterized by different anthropogenic impacts. Effects of anthropogenicheat discharges on simulated water temperatures were incorporated by usingglobal gridded thermoelectric water use datasets and representing thermaldischarges as point sources into the heat advection equation. This resultedin a significant increase in the quality of the water temperaturesimulations for thermally polluted basins (Rhine, Meuse, Danube andMississippi). Due to large reservoirs in the Columbia which affectstreamflow and thermal regimes, a reservoir routing model was used. Thisresulted in a significant improvement in the performance of the riverdischarge and water temperature modelling. Overall, realistic estimates wereobtained at daily time step for both river discharge (median normalizedBIAS = 0.3; normalized RMSE = 1.2; r = 0.76) and water temperature (medianBIAS = ?0.3 °C; RMSE = 2.8 °C; r = 0.91) for the entire validation period,with similar performance during warm, dry periods. Simulated watertemperatures are sensitive to headwater temperature, depending on resolutionand flow velocity. A high sensitivity of water temperature to riverdischarge (thermal capacity) was found during warm, dry conditions. Themodelling approach has potential to be used for risk analyses and studyingimpacts of climate change and other anthropogenic effects (e.g. thermalpollution, dams and reservoir regulation) on large rivers.
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机译：为了有效管理水资源（例如电力和饮用水生产）和淡水生态系统，需要对每日流量和水温进行实际估算。尽管基于水文和过程的水温建模方法已成功地应用于小流域和短时期，但在大时空尺度上所做的工作却少得多。我们提出了一个基于物理的建模框架，用于全球范围内适用于大型河流系统的每日河流流量和水温模拟。在1971–2000年期间，以1/2×1/2°的空间分辨率和每天的时间步长对模型性能进行了全球测试。我们对不同水文气候区的大型流域进行了专门的评估，并以不同的人为影响为特征。通过使用全局网格化热电用水数据集，将人为热量排放对模拟水温的影响纳入其中，并将热量排放表示为热对流方程中的点源。这导致热污染盆地（莱茵，默兹，多瑙河和密西西比州）的水温模拟质量大大提高。由于哥伦比亚的大型水库影响流量和热力状况，因此使用了一个水库调度模型。结果大大改善了河流流量和水温模型的性能。总的来说，在每天的时间步长上都获得了河流流量（中位BIAS = 0.3;中位RMSE = 1.2; r = 0.76）和水温（BIAS中位= 0.3°C; RMSE = 2.8°）的真实估计。 C; r = 0.91），在整个验证期间，在温暖，干燥的时期内，性能相似。根据分辨率和流速，模拟水温对源头水温敏感。在温暖，干燥的条件下，发现水温对河水排放（热容量）高度敏感。该建模方法有潜力用于风险分析和研究气候变化对大型河流的影响以及其他人为影响（例如热污染，水坝和水库调度）。
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