diff --git a/kwant/solvers/default.py b/kwant/solvers/default.py
index 56260d720da54fddb0cccb1f5c4b0059c27cd69f..28145700ae50199051845c5292a4c733e3acd511 100644
--- a/kwant/solvers/default.py
+++ b/kwant/solvers/default.py
@@ -9,9 +9,13 @@
 __all__ = ['smatrx', 'ldos', 'wave_function', 'greens_function']
 
 # MUMPS usually works best.  Use SciPy as fallback.
+import warnings
 try:
     from . import mumps as smodule
 except ImportError:
+    warnings.warn("MUMPS is not available, "
+                  "SciPy built-in solver will be used as a fallback. "
+                  "Performance can be very poor in this case.", RuntimeWarning)
     from . import sparse as smodule
 
 hidden_instance = smodule.Solver()
diff --git a/kwant/solvers/sparse.py b/kwant/solvers/sparse.py
index 9510c52962494bbeb51682c28b85f535c9b15985..508c9d665f0757e4b4421c56e24201a3e3cbcae7 100644
--- a/kwant/solvers/sparse.py
+++ b/kwant/solvers/sparse.py
@@ -88,11 +88,9 @@ if uses_umfpack:
         return solve
 else:
     # no UMFPACK found. SuperLU is being used, but usually abysmally slow
-    # (SuperLu is not bad per se, somehow the SciPy version isn't good)
-    warnings.warn("The installed SciPy does not use UMFPACK. Instead, "
-                  "SciPy will use the version of SuperLu it is shipped with. "
-                  "Performance can be very poor in this case.", RuntimeWarning)
-
+    # (SuperLu is not bad per se, somehow the SciPy version isn't good).
+    # Since scipy doesn't include UMFPACK anymore due to software rot,
+    # there is no warning here.
     factorized = linsolve.factorized