Index: wflow-py/wflow/wf_netcdfio.py
===================================================================
diff -u -r5cfd4619803c1e781acb3032ea9d4e27f9620c59 -r7b23641f11fe15d03482a58d08d372f62d449618
--- wflow-py/wflow/wf_netcdfio.py	(.../wf_netcdfio.py)	(revision 5cfd4619803c1e781acb3032ea9d4e27f9620c59)
+++ wflow-py/wflow/wf_netcdfio.py	(.../wf_netcdfio.py)	(revision 7b23641f11fe15d03482a58d08d372f62d449618)
@@ -779,30 +779,29 @@
                 )
                 ncindex = pos
 
-        if var in self.alldat:
-            if ncindex == self.lstep:  # Read new block of data in mem
-                logging.debug(
-                    "reading new netcdf data block starting at: " + str(ncindex)
-                )
-                for vars in self.alldat:
-                    if len(vars) == 3:
-                        self.alldat[vars] = self.dataset.variables[vars][
-                            ncindex : ncindex + self.maxsteps
-                        ]
-                    elif len(vars) == 4:
-                        self.alldat[vars] = self.dataset.variables[vars][
-                            ncindex : ncindex + self.maxsteps, 0
-                        ]
+        if self.alldat.has_key(var):
+            # if ncindex == self.lstep:  # Read new block of data in mem
+            #    logging.debug("reading new netcdf data block starting at: " + str(ncindex))
+            #    for vars in self.alldat:
+            #        self.alldat[vars] = self.dataset.variables[vars][ncindex:ncindex + self.maxsteps]
+            #
+            # self.fstep = ncindex
+            # self.lstep = ncindex + self.maxsteps
 
-                self.fstep = ncindex
-                self.lstep = ncindex + self.maxsteps
+            if len(self.alldat[var].dimensions) == 3:
+                np_step = self.alldat[var][
+                    ncindex - self.fstep,
+                    self.latidx.min() : self.latidx.max() + 1,
+                    self.lonidx.min() : self.lonidx.max() + 1,
+                ]
+            if len(self.alldat[var].dimensions) == 4:
+                np_step = self.alldat[var][
+                    ncindex - self.fstep,
+                    0,
+                    self.latidx.min() : self.latidx.max() + 1,
+                    self.lonidx.min() : self.lonidx.max() + 1,
+                ]
 
-            np_step = self.alldat[var][
-                ncindex - self.fstep,
-                self.latidx.min() : self.latidx.max() + 1,
-                self.lonidx.min() : self.lonidx.max() + 1,
-            ]
-
             miss = float(self.dataset.variables[var]._FillValue)
             if self.flip:
                 return numpy2pcr(Scalar, flipud(np_step).copy(), miss), True