eWaterCycle-DA

在eWaterCycle平台上运行水文模型数据同化的代码。

安装

将此软件包与您的eWaterCycle安装一起安装

pip install ewatercycle-DA

然后DA将在eWaterCycle中可用

from ewatercycle_DA import DA

文档

文档可以在此处找到

变更日志

变更日志可以在GitHub上的CHANGELOG.md中找到。

快速使用概述

(可能迁移到文档?)

可以用于或不用于同化，这将运行同一模型的10个版本。通过更改setup_kwargs，您可以更改模型运行本身。

不进行同化

HBVForcing = ...

ensemble = DA.Ensemble(N=10)
ensemble.setup()

ensemble.initialize(model_name="HBV",
                   forcing=HBVForcing,
                   setup_kwargs={'parameters':'7.6,0.5,460,3.8,0.19,1.3,0.082,0.0061',
                                 'initial_storage':'0,100,0,5'}
                    )

ref_model = ensemble.ensemble_list[0].model

lst_Q = []
while ref_model.time < ref_model.end_time:
    ensemble.update(assimilate=False)
    lst_Q.append(ensemble.get_value("Q"))

有关运行HBV的说明，请参阅单独的文档

进行同化

...
ref_model = ...
#... same as above just add two more definitions
def H(Z):
    """returns discharge which is the last value on the state vector for HBV"""
    return Z[-1] 

ds_obs_dir = ...
ensemble.initialize_da_method(ensemble_method_name = "PF", 
                              hyper_parameters = {
                                               'like_sigma_weights' : 0.05,
                                               'like_sigma_state_vector' : 0.01,
                                                 },
                              state_vector_variables = "all", 
                              # the next three are keyword arguments but are needed:
                              observation_path = ds_obs_dir,
                              observed_variable_name = "Q",
                              measurement_operator = H, 
                           
                            )
lst_Q = []
while ref_model.time < ref_model.end_time:
    ensemble.update(assimilate=True)
    lst_Q.append(ensemble.get_value("Q"))