Volumetric changes induced by soil moisture phase changes can lead to pore system redistribution in freezing and thawing soil, which in turn affects soil strength and stability. The prefreezing water content and the number of freeze–thaw cycles (FTCs) affecting key factors of soil pore changes, and they determine the volumetric change magnitude and frequency during ice–water phase transitions. This study aims to reveal the effect of the prefreezing water content and the number of freeze–thaw cycles on the pore size distribution (PSD) of black soil, meadow soil and chernozem, which account for the largest arable land area in Heilongjiang Province, China. In situ soil samples with different prefreezing water contents were subjected to 1, 2, 3, 5, 10, and 20 FTCs, and then nuclear magnetic resonance (NMR) was used to quantify the PSD. It was shown that the pore sizes of the three soil types spanned multiple orders of magnitude, ranging from 0.001 to 100 μm overall. The inflection point of the cumulative porosity curves of all three soils occurred near 0.1 μm. For black soil and chernozem with high prefreezing water contents, when the number of FTCs reached 10 or 20, the soil self-weight led to thaw settlement, which reduced the difference in the total porosity of the soils with varying moisture contents. The initial FTC exerts the most significant influence on the pore structure. The impact of the prefreezing water content on soil pore structure diminishes as the number of FTCs increases. The plant root residues rendered meadow soil less sensitive to water content differences after the first FTCs but also limited the development of macropores during the late freeze–thaw period. The prefreezing water content alters the distribution of soil moisture before freezing and has a greater influence on the pore distribution of frozen-thawed soils compared to the cumulative effect of multiple FTCs.

In the 1950s and 1970s, China implemented large-scale wasteland reclamation in the Sanjiang Plain in eastern Heilongjiang Province, which expanded the area of cultivated land. Cultivated areas alter the quantity of water resources, provide the ecological requirements of river basins, and promote the ecological health of land use. In this study, the grid-based Sacramento (GSAC) model was adopted to simulate various changes in arable land, grassland, cultivated land, and deciduous coniferous forest. Quantitative analysis of the influence of cultivated land change on runoff and under dry season flow was conducted. The results showed that the GSAC model attains a high certainty coefficient in the process of simulating the daily basin discharge and reproduces the daily basin discharge process well for many years. The annual runoff increased between 5.07 and 64.05% due to the return of farmland to grassland and coniferous forest. The return of farmland to grassland greatly impacted runoff. The slope of the grassland and coniferous forest converted from farmland was negatively correlated with the discharge in the basin outlet section. The lower the gradient threshold in the scenario of returning arable land to forest or grassland, the more arable land will be replaced by grassland or deciduous coniferous forest, which could result in more water production in the watershed. Among the different change scenarios, the average flow rate of cultivated land with a slope larger than 15° was the closest to the ecological water demand of the studied watershed. The land use mode of converting cultivated land with a slope larger than 15° into grassland is expected to promote the ecological health of the watershed.

Physically-based parameter estimations are essential to improve the simulation performance of a hydrologic model and to produce physically reasonable parameters with spatial consistency. This study proposed a parameter derivation strategy to improve the Sacramento Soil Moisture Accounting (SAC-SMA) model simulation performance based on the publicly accessible Harmonized World Soil Database (HWSD). The HWSD soil properties were used to estimate the soil moisture characteristics, and the HWSD soil texture classifications and International Geosphere-Biosphere Programme (IGBP) land cover types were used to identify the Soil Conservation Service (SCS) runoff curve number (CN). After the soil moisture characteristics and CNs were identified, the major parameters of the SAC-SMA model were derived. The simulation results were evaluated using the Nash efficiency coefficient (NSEC), and Free Search (FS) algorithm was used to further adjust and calibrate the parameters. Compared with the simulation accuracy (NSEC = 0.66~0.88) and parameter transferability (NSEC = 0.22~0.83) obtained for the SAC-SMA model using directly calibrated parameters, the HWSD data-derived parameters allowed the SAC-SMA model to achieve a similar simulation accuracy (NSEC = 0.65~0.86) and a better transferability (NSEC = 0.61~0.85).