diff --git a/rainforest/performance/eval_calculate.py b/rainforest/performance/eval_calculate.py
index 0119f4a..ff736e0 100644
--- a/rainforest/performance/eval_calculate.py
+++ b/rainforest/performance/eval_calculate.py
@@ -56,9 +56,11 @@ def calcScoresStations(precip_ref : pd.DataFrame,
 
     th_ref, th_est = threshold if isinstance(threshold, list) else [threshold] * 2
 
-    perf_scores = pd.DataFrame(columns=['YESref_YESpred','NOref_NOpred','NOref_YESpred','YESref_NOpred',
+    score_names = ['YESref_YESpred','NOref_NOpred','NOref_YESpred','YESref_NOpred',
                                 'RMSE','corr_p','scatter','logBias', 'n_values', 
-                                'n_events_db','sum_ref_db','sum_pred_db'], 
+                                'n_events_db','sum_ref_db','sum_pred_db']
+    score_db_names = ['n_events_db','sum_ref_db','sum_pred_db', 'RMSE','corr_p','scatter','logBias']
+    perf_scores = pd.DataFrame(columns=score_names,
                                 index=precip_ref.columns.unique())
 
     stations = METSTATIONS.copy()
@@ -94,6 +96,7 @@ def calcScoresStations(precip_ref : pd.DataFrame,
                 np.round(10*np.log10(sum_pred_db/sum_ref_db),decimals=4)
         else:
             logging.info('No measurements for station {}'.format(station_id))
+            perf_scores.loc[station_id, ['logBias','RMSE','corr_p','scatter']] = np.nan
             continue
         try:
             scores = det_cont_fct(precip_est[station_id][double_cond.index].to_numpy(dtype=float),
@@ -104,6 +107,7 @@ def calcScoresStations(precip_ref : pd.DataFrame,
             perf_scores.at[station_id, 'scatter']= np.round(scores['scatter'],decimals=4)
         except:
             logging.info('Could not calculate scores for station {}'.format(station_id))
+            perf_scores.loc[station_id, ['RMSE','corr_p','scatter']] = np.nan
 
     return perf_scores
 
diff --git a/rainforest/performance/eval_get_estimates.py b/rainforest/performance/eval_get_estimates.py
index 9e38d13..f0a5ac2 100644
--- a/rainforest/performance/eval_get_estimates.py
+++ b/rainforest/performance/eval_get_estimates.py
@@ -28,7 +28,8 @@
 from ..common.io_data import read_cart
 
 
-def getGaugeObservations(gaugefolder, t0=None, t1=None, slf_stations=False):
+def getGaugeObservations(gaugefolder, t0=None, t1=None, slf_stations=False, 
+                        missing2nan=False):
     """_summary_
 
     Args:
@@ -50,7 +51,9 @@ def getGaugeObservations(gaugefolder, t0=None, t1=None, slf_stations=False):
                         dtype = {'TIMESTAMP':int,  'STATION': str})
 
     gauge_all = gauge_all.compute().drop_duplicates()
-    gauge_all = gauge_all.replace(-9999,np.nan)
+
+    if missing2nan:
+        gauge_all = gauge_all.replace(-9999,np.nan)
 
     # Assure that datetime object is in UTC
     if t0 != None :
@@ -291,7 +294,8 @@ def extractEstimatesFromMaps(self, slf_stations=False, tagg_hourly=True, save_ou
         #-----------------------------------
         logging.info('Get gauge observations')
         gauge_all = getGaugeObservations(gaugefolder=self.gaugefolder, 
-                        t0 = self.tstart, t1= self.tend, slf_stations = False)
+                        t0 = self.tstart, t1= self.tend, slf_stations = False,
+                        missing2nan=False)
         stations = np.unique(gauge_all['STATION'])
 
         # Get all model files
@@ -360,6 +364,8 @@ def extractEstimatesFromMaps(self, slf_stations=False, tagg_hourly=True, save_ou
             col = gauge_all.loc[gauge_all['STATION'] == ss, 'RRE150Z0'].to_frame(name=ss)
             col.set_index(gauge_all.loc[(gauge_all['STATION'] == ss),'TIME'], inplace=True)
             precip_qpe['GAUGE'][ss] = col
+            precip_qpe['GAUGE'][ss].fillna(0, inplace=True)
+            precip_qpe['GAUGE'][ss].loc[precip_qpe['GAUGE'][ss] < 0] = np.nan
 
         for m in list_models:
             precip_qpe[m] = pd.DataFrame(precip_qpe[m], index=tstamps_10min, columns=precip_qpe['GAUGE'].columns)