diff --git a/core/src/config.jl b/core/src/config.jl
index 1aa849892..0ae043004 100644
--- a/core/src/config.jl
+++ b/core/src/config.jl
@@ -18,8 +18,8 @@ using OrdinaryDiffEqNonlinearSolve: NLNewton
 using OrdinaryDiffEqLowOrderRK: Euler, RK4
 using OrdinaryDiffEqTsit5: Tsit5
 using OrdinaryDiffEqSDIRK: ImplicitEuler, KenCarp4, TRBDF2
-using OrdinaryDiffEqBDF: QNDF
-using OrdinaryDiffEqRosenbrock: Rodas5, Rosenbrock23
+using OrdinaryDiffEqBDF: FBDF, QNDF
+using OrdinaryDiffEqRosenbrock: Rosenbrock23, Rodas4P, Rodas5P
 
 export Config, Solver, Results, Logging, Toml
 export algorithm,
@@ -213,9 +213,11 @@ Map from config string to a supported algorithm type from [OrdinaryDiffEq](https
 Supported algorithms:
 
 - `QNDF`
+- `FBDF`
 - `Rosenbrock23`
 - `TRBDF2`
-- `Rodas5`
+- `Rodas4P`
+- `Rodas5P`
 - `KenCarp4`
 - `Tsit5`
 - `RK4`
@@ -224,9 +226,11 @@ Supported algorithms:
 """
 const algorithms = Dict{String, Type}(
     "QNDF" => QNDF,
+    "FBDF" => FBDF,
     "Rosenbrock23" => Rosenbrock23,
     "TRBDF2" => TRBDF2,
-    "Rodas5" => Rodas5,
+    "Rodas4P" => Rodas4P,
+    "Rodas5P" => Rodas5P,
     "KenCarp4" => KenCarp4,
     "Tsit5" => Tsit5,
     "RK4" => RK4,
diff --git a/core/test/run_models_test.jl b/core/test/run_models_test.jl
index 065df785b..20cc0b492 100644
--- a/core/test/run_models_test.jl
+++ b/core/test/run_models_test.jl
@@ -280,7 +280,7 @@ end
     @test sparse_fdm.integrator.u ≈ sparse_ad.integrator.u atol = 4
     @test dense_fdm.integrator.u ≈ sparse_ad.integrator.u atol = 4
 
-    config = Ribasim.Config(toml_path; solver_algorithm = "Rodas5", solver_autodiff = true)
+    config = Ribasim.Config(toml_path; solver_algorithm = "Rodas5P", solver_autodiff = true)
     time_ad = Ribasim.run(config)
     @test successful_retcode(time_ad)
     @test time_ad.integrator.u ≈ sparse_ad.integrator.u atol = 10
diff --git a/docs/reference/usage.qmd b/docs/reference/usage.qmd
index 354a3afc0..50f1f63cd 100644
--- a/docs/reference/usage.qmd
+++ b/docs/reference/usage.qmd
@@ -21,7 +21,7 @@ If your model does not converge, or your performance is lower than expected, it
 
 The default solver `algorithm = "QNDF"`, which is a multistep method similar to Matlab's `ode15s` [@shampine1997matlab].
 It is an implicit method that supports the default adaptive timestepping.
-The full list of available solvers is: `QNDF`, `Rosenbrock23`, `TRBDF2`, `Rodas5`, `KenCarp4`, `Tsit5`, `RK4`, `ImplicitEuler`, `Euler`.
+The full list of available solvers is: `QNDF`, `FBDF`, `Rosenbrock23`, `Rodas4P`, `Rodas5P`, `TRBDF2`, `KenCarp4`, `Tsit5`, `RK4`, `ImplicitEuler`, `Euler`.
 Information on the solver algorithms can be found on the [ODE solvers page](https://docs.sciml.ai/DiffEqDocs/stable/solvers/ode_solve/).
 
 By default Ribasim uses adaptive timestepping, though not all algorithms support adaptive timestepping.