| 24 Nov 2025
Basin-scale Evaluation of the Noah-MP Land Surface Model for Runoff and Snow Generation in the Missouri River Basin: Insights and Recommendations for Parameterization Scheme Selection
Abstract. Process-based land surface models, such as the Noah-Multiparameterization (Noah-MP) model, are widelyused for large-scale hydrologic simulations because of their flexibility in selecting multiple parameterization schemes. However, limited guidance on choosing appropriate configurations constrains their reliability in representing runoff and snowmelt dynamics across diverse land-cover and snow conditions. This study evaluates the defaultparameterization scheme and four alternative parameterization schemes in the Noah-MP land surface model, includingRunoff and Groundwater (RUN), Surface Exchange Coefficient for Heat (SFC), Frozen Soil Permeability (INF), and Snow/Soil Temperature Time Scheme (STC), across 50 Hydro-Climate Data Networks (HCDNs) in the MissouriRiver Basin. Model performance was evaluated using USGS streamflow observations and snow water equivalent (SWE) estimates from the University of Arizona dataset for 2014 to 2023. Results showed that the alternative schemes generally improved runoff simulation compared to the default scheme through better representing key hydrologicaland thermodynamic processes. Specifically, the RUN, SFC, INF, and STC experiments improved the Kling–GuptaEfficiency (KGE) by 0.19, 0.37, 0.48, and 0.14, respectively in representative subbasins, through enhancedgroundwater dynamics, reduced evapotranspiration bias, improved rapid runoff response, and more accurate SWE evolution. SWE evaluation further indicates that the STC experiment reduced the mean bias of the April–July runoff- to-maximum SWE ratio by 12–32 % in high-elevation subbasins, reflecting improved representation of snowmeltdriven runoff. These results highlight the importance of basin-specific parameterization schemes within Noah-MP toimprove hydrological prediction and water management across diverse hydroclimatic regions. The findings further indicate optimal parameterization schemes for different climates, land cover, and snow regimes.
This manuscript provides a detailed evaluation and comparison of runoff and snow simulations using different parameterization schemes of the Noah-MP land surface model in the Missouri River Basin. This work holds scientific value for disaster prevention and mitigation in the basin. However, I have several major concerns, detailed below.
Major Comments:
1. Line 150: I find it unreasonable to use the same initial conditions for the alternative parameterization experiments as for the default simulation. This approach likely affects some of the study's conclusions. I recommend performing a separate spin-up for each experiment. If computational resources are a constraint, the period from January 1, 1995, to December 31, 1999, could be used as the model spin-up phase.
2. Section 6.1: The study concludes that the alternative schemes address three specific limitations of the default scheme. I find these conclusions to be overly strong. Previous research suggests that the performance of land surface process schemes is often region-dependent.
3. Section 6.4: I agree with the two limitations identified in this section: first, that the scheme recommendations may not be directly applicable to other regions, and second, that the interactions between different land surface physical processes are not considered. I strongly recommend providing a more in-depth discussion of these points rather than merely noting them in passing.
Minor Comments:
4. In Figure 1, does the land cover map represent the actual dataset used in the simulations? Was the IGBP land cover classification scheme employed?
5. In Figure 4a, the default scheme fails to accurately reproduce the seasonal variation in groundwater storage, whereas it performs well in Figure 4b. Could the authors please attempt to explain this discrepancy?
6. Is "ROS" in the manuscript an abbreviation for "rain-on-snow"? Please clarify.