Gridded meteorological data products often fall short in accurately capturing the amount of precipitation and its patterns in regions characterized by high elevations and complex topography. However, realistic precipitation data is crucial for high-alpine hydrological modeling. To address these discrepancies, we analyze possible corrections for solid, liquid and total precipitation of the 1 km2 gridded meteorological INCA-product in the high-alpine catchment of the Kölnbrein hydropower reservoir operated by VERBUND Hydro Power GmbH in the Malta Valley in Austria. By leveraging information from a stereo-satellite-derived snow depth map with physically-based snowpack modeling with Alpine3D, we quantitatively adjust and spatially redistribute solid precipitation, complemented by a multiplicative, stepwise correction model for liquid precipitation. We compare and evaluate five approaches using the hydrological COSERO model to our a) baseline simulation with no corrections on INCA in contrast of correcting, b) the amount and distribution of solely solid precipitation, c) the amount of liquid and solid precipitation, d) the amount of liquid and solid precipitation and the spatial distribution of the latter, e) precipitation inversely by the inflow bias, and f) calibrating the precipitation correction factor. In evaluating these strategies to improve the accuracy of reservoir inflow predictions, we found that separately correcting solid and liquid precipitation yielded the best results (c &d), with a substantial increase of up to 65% over the study period (1.10.2015–30.9.2023), while the other correction variants ranged between 42 and 52%. The inflow predictions by COSERO showed an increase in Nash-Sutcliffe Efficiency (NSE) by 17% and in Kling-Gupta Efficiency by 57% and 59% for variants c and d, respectively, along with an almost complete elimination of model bias. The higher KGE values observed for variant d compared to c during spring, summer, and fall suggest that a more realistic snow distribution enhances the simulation of snowmelt-driven runoff dynamics. In contrast, using a global (i.e., spatially homogeneous) and uniform (i.e., not distinguishing between liquid and solid precipitation phase) correction factor, inversely derived from the inflow bias (e), or solely correcting solid precipitation (b), demonstrated less performance, with a KGE increase of 47% and 49%, respectively, compared to 59% for variant d. Conversely, the calibration of the global and uniform correction factor (f) resulted in significant performance metric improvements (17% NSE, 60% KGE and 90% pBias), similar to variant d, however also led to unrealistic simulations of evapotranspiration, sublimation and glacier net runoff. The simulated water balance components – evapotranspiration and sublimation, as well as glacier runoff – in variant d were deemed plausible based on our comparison with additional simulations using Alpine3D, as well as findings from other high-alpine catchments in Austria reported in the literature. Overall, our results underscore the importance of applying a dual correction strategy for both liquid and solid precipitation, particularly when significant deficiencies are present in meteorological datasets, and suggest that such corrections should be supplemented by a comprehensive analysis of the simulated high-alpine water balance components.

中文翻译：

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评估降水校正以增强高山水文建模


网格化气象数据产品通常无法准确捕获高海拔和复杂地形地区的降水量及其模式。然而，真实的降水数据对于高山水文建模至关重要。为了解决这些差异，我们分析了奥地利马耳他谷 VERBUND Hydro Power GmbH 运营的 Kölnbrein 水电站水库高山集水区中 1 km2 网格化气象 INCA 产品的固体、液体和总降水的可能修正。通过利用立体卫星衍生的积雪深度图和基于 Alpine3D 的物理积雪建模，我们对固体降水进行定量调整和空间重新分配，并辅以液体降水的乘法、逐步校正模型。我们将使用水文 COSERO 模型的五种方法与我们的 a） 基线模拟进行比较和评估，没有对 INCA 进行修正，b） 仅固体降水的数量和分布，c） 液体和固体降水的数量，d） 液体和固体降水的数量以及后者的空间分布， e） 降水与流入偏差成反比，以及 f） 校准降水校正因子。在评估这些策略以提高储层流入预测的准确性时，我们发现分别校正固体和液体降水产生了最佳结果 （c & d），在研究期间（2015 年 10 月 1 日至 2023 年 9 月 30 日）大幅增加了 65%，而其他校正变体在 42% 到 52% 之间。 COSERO 的流入预测显示，变体 c 和 d 的 Nash-Sutcliffe 效率 （NSE） 分别提高了 17%，Kling-Gupta 效率分别提高了 57% 和 59%，同时几乎完全消除了模型偏差。与春季、夏季和秋季的 c 相比，变体 d 观察到的 KGE 值更高，这表明更真实的积雪分布增强了对融雪驱动的径流动力学的模拟。相比之下，使用全局（即空间均匀）和均匀（即不区分液体和固体沉淀相）校正因子，与流入偏差 （e） 成反比，或单独校正固体沉淀 （b），表现出较差的性能，KGE 分别增加了 47% 和 49%，而变体 d 为 59%。相反，全局和均匀校正因子 （f） 的校准导致了性能指标的显着改进（17% NSE、60% KGE 和 90% pBias），类似于变体 d，但也导致了对蒸散、升华和冰川净径流的不切实际的模拟。根据我们与使用 Alpine3D 的其他模拟的比较，以及文献中报道的奥地利其他高山集水区的发现，变体 d 中模拟的水平衡成分——蒸散和升华以及冰川径流——被认为是合理的。总体而言，我们的结果强调了对液体和固体降水应用双重校正策略的重要性，特别是当气象数据集中存在重大缺陷时，并建议应通过对模拟的高山水平衡成分的综合分析来补充这种校正。