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Changelog

Source: NEWS.md

nwsrfsr 1.0.4

  • Fix forcing_adj being ignored by load_example() and nwsrfs_run(). The argument was accepted and stored on the returned object, but the model chain always called fa_nwrfc() with the calibrated adjustment parameters, so forcing_adj = FALSE returned the adjusted simulation. Python’s forcing_adj=False changes the NRKW1 simulation by about 6 percent, which is why R and Python disagreed on the same call.
  • forcing_adj now also accepts a character vector naming a subset of “map”, “mat”, “ptps” and “pet”, matching the Python package. fa_nwrfc() and fa_adj_nwrfc() gained a corresponding adjust argument; dry_run = TRUE is unchanged and remains shorthand for adjusting nothing.
  • Add return_inst to load_example(), nwsrfs_run() and uh(), matching Python. With return_inst = FALSE the unit hydrograph returns period average flow, the mean of each timestep and the one after it with the final value carried forward, computed before the shift_sf shift and before Lag-K routing is added. Default TRUE, which is the previous behaviour.
  • Drop the n_clmods bookkeeping row from the pars table carried on an “nwsrfs_run” object, so it matches the Python parameter table row for row. chanloss() now infers the module count from the cl_factor_## rows when that row is absent, and still honours it when present.

nwsrfsr 1.0.3

CRAN release: 2026-07-22

  • Fix a segfault (memory not mapped) reached by the rsnwelev() example on the CRAN gcc build. The example passed zero-length talr/pxtemp vectors to the Fortran routine, which reads them as dimension(n_hrus), causing an out-of-bounds read. rsnwelev() now selects one parameter value per forcing zone and raises a clear R error when elev, talr or pxtemp are missing, and the example supplies the required parameters.
  • Fix uninitialised-memory reads reported by valgrind in the Lag/K routines. pin7/fka7 compared an uninitialised dimension string (setup calls were disabled in the wrapper port) and flag7 read unwritten slots of its scratch array; all three are now initialised. Model output is unchanged.
  • Fix two -Wlto-type-mismatch warnings reported by the CRAN LTO and gcc-ASAN builds. The SNOW-17 /SNUP19/ common block left its first member MFC implicitly typed (INTEGER) in aesc19 while it is REAL elsewhere, and /SNCO19/ carried an extra trailing TAPREV member in zero19 that the other units do not (in this port TAPREV is a subroutine argument, not a common member). Both are now declared consistently. Model output is unchanged.
  • Declare the umemst dummy array as assumed-size (IARRAY(*)) instead of the legacy IARRAY(1), which made a gfortran -fcheck=all build abort with a spurious out-of-bounds error on the first real write. This lets the package run under Fortran runtime bounds checking. Model output is unchanged.
  • Disable floating-point expression contraction so simulation results agree across platforms. Compilers may fuse a*b+c into a single-rounding fused multiply-add, and whether they do varies by compiler version and CPU; in this iterated single-precision model chain the one-ulp differences are amplified by snow model thresholds into visibly different simulations (macOS/arm64 vs Linux/x86-64 differed by up to a few hundred cfs at individual flow peaks over a 43 year run). A new configure script probes the Fortran compiler for -ffp-contract=off and applies it via a generated src/Makevars (Makevars.win sets it directly since Rtools is always gfortran). With contraction off, results agree across macOS, Linux, x86-64 and arm64 to within libm rounding, which totals ~1e-4 mm of runoff over four decades. Model output changes very slightly on platforms that previously contracted.

nwsrfsr 1.0.2

CRAN release: 2026-07-17

  • Fix installation failure under parallel make (make -j) by declaring the missing Fortran module dependencies (sorting.o: types.o and sac_snow.o: utilities.o) in src/Makevars and src/Makevars.win.

nwsrfsr 1.0.0

CRAN release: 2026-07-16

  • Initial CRAN release
  • Low-level Fortran wrappers: sac_snow(), uh(), lagk(), chanloss(), consuse(), fa_nwrfc()
  • High-level orchestration: nwsrfs_run(), load_example(), update_pars()
  • AdjustQ preprocessing: adjustq(), adjustq_load_example()
  • Bundled example data for NRKW1 and SFLN2 stations