Başakın Eyyup Ensar, Ekmekcioğlu Ömer, Stoy Paul C, Özger Mehmet
Hydraulics Division, Civil Engineering Department, Istanbul Technical University, Maslak, 34469, Istanbul, Türkiye.
Disaster and Emergency Management Department, Disaster Management Institute, Istanbul Technical University, Maslak, 34469, Istanbul, Türkiye.
MethodsX. 2023 Mar 28;10:102163. doi: 10.1016/j.mex.2023.102163. eCollection 2023.
In this study, stochastic gradient boosting (SGB), a commonly-adopted soft computing method, was used to estimate reference evapotranspiration (ETo) for the Adiyaman region of southeastern Türkiye. The FAO-56-Penman-Monteith method was used to calculate ETo, which we then estimated using SGB with maximum temperature, minimum temperature, relative humidity, wind speed, and solar radiation obtained from a meteorological station.•The calculated ETo time series values were decomposed into sub-series using Singular Spectrum Analysis (SSA) to enhance prediction accuracy.•Each sub-series was trained with the first 70% of observations and tested with the remaining 30% via SGB. Final prediction values were obtained by collecting all series predictions.•Three lag times were taken into account during the predictions, and both short-term and long-term ETo values were estimated using the proposed framework. The results were tested with respect to root mean square error (RMSE) and Nash-Sutcliffe efficiency (NSE) indicators for ensuring whether the model produced statically acceptable outcomes.
在本研究中，随机梯度提升（SGB）这一常用的软计算方法被用于估算土耳其东南部阿迪雅曼地区的参考蒸散量（ETo）。采用FAO-56-彭曼-蒙特斯方法计算ETo，然后我们使用从气象站获取的最高温度、最低温度、相对湿度、风速和太阳辐射，通过随机梯度提升法对其进行估算。
• 使用奇异谱分析（SSA）将计算得到的ETo时间序列值分解为子序列，以提高预测精度。
• 每个子序列用前70%的观测值进行训练，并通过随机梯度提升法用其余3０%的观测值进行测试。通过收集所有序列预测结果获得最终预测值。
• 在预测过程中考虑了三个滞后时间，并使用所提出的框架估算短期和长期的ETo值。针对均方根误差（RMSE）和纳什-萨特克利夫效率（NSE）指标对结果进行了检验，以确保模型产生的结果在统计上是可接受的。
