Abstract
Spring soil moisture (SM) is of great importance for monitoring agricultural drought and waterlogging in farmland areas. While winter snow cover has an important impact on spring SM, relatively little research has examined the correlation between winter snow cover and spring SM in great detail. To understand the effects of snow cover on SM over farmland, the relationship between winter snow cover parameters (maximum snow depth (MSD) and average snow depth (ASD)) and spring SM in Northeast China was examined based on 30 year passive microwave snow depth (SD) and SM remote-sensing products. Linear regression models based on winter snow cover were established to predict spring SM. Moreover, 4 year SD and SM data were applied to validate the performance of the linear regression models. Additionally, the effects of meteorological factors on spring SM also were analyzed using multiparameter linear regression models. Finally, as a specific application, the best-performing model was used to predict the probability of spring drought and waterlogging in farmland in Northeast China. Our results illustrated the positive effects of winter snow cover on spring SM. The average correlation coefficient (R) of winter snow cover and spring SM was above 0.5 (significant at a 95% confidence level) over farmland. The performance of the relationship between snow cover and SM in April was better than that in May. Compared to the multiparameter linear regression models in terms of fitting coefficient, MSD can be used as an important snow parameter to predict spring drought and waterlogging probability in April. Specifically, if the relative SM threshold is 50% when spring drought occurs in April, the prediction probability of the linear regression model concerning snow cover and spring SM can reach 74%. This study improved our understanding of the effects of winter snow cover on spring SM and will be beneficial for further studies on the prediction of spring drought.
Highlights
Soil moisture (SM) is an essential element of the earth’s ecosystem
It was necessary to analyze the spatial pattern of snow depth (SD) and spring SM in order to understand the characteristics of snow cover and SM over farmland in Northeast China
Understanding the relationship between winter snow cover and spring SM at the regional scale is crucial for strengthening the regulation and management of spring SM over farmland
Summary
Soil moisture (SM) is an essential element of the earth’s ecosystem. As an important indicator for monitoring agricultural drought and waterlogging, spring SM especially has significant implications for seed germination and agricultural production [1], and agriculture is significantly vulnerable to associated hazards when spring SM over farmland is abnormal (e.g., exceeding or less than the suitable SM for seed germination). Because of the accumulation of water in the snowpack in winter and its subsequent release during the springtime snowmelt, snow cover is an important source of spring SM and increases spring SM. Spring agricultural water supply in arid or semiarid regions with abundant snow in winter mainly comes from snowmelt runoff [2,3], underscoring the nonnegligible impact of winter snow cover on spring SM. Estimating the contribution of winter snow cover to spring SM is critical for agricultural water resource management. Exploring the relationship between winter snow cover and spring SM can effectively urge policy departments to formulate immediate adaptation and mitigation measures based on winter snow cover in order to reduce agricultural hazards
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