scholarly journals Influence of snow surface processes on soil moisture dynamics and streamflow generation in alpine catchments

2017 ◽  
Author(s):  
Nander Wever ◽  
Francesco Comola ◽  
Mathias Bavay ◽  
Michael Lehning
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Soil Freezing ◽  
Distributed Model ◽  
Stream Network ◽  
Model Framework ◽  
Soil Layers ◽  
Flood Risks ◽  
Moisture State

Abstract. The assessment of flood risks in alpine, snow covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of a catchment to high flows from rainfall and snow melt for the Dischma catchment in East Switzerland. The recently updated soil module of the physics based, multi-layer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity of the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arises from an overestimation of soil freezing and an absence of a ground water description in the model. Both were found to have an influence in the soil moisture measurements. Streamflow simulations performed with a spatially-explicit hydrological model using a travel time distribution approach coupled to Alpine3D provided a closer agreement with observed streamflow at the outlet of the Dischma catchment when including 30 cm of soil layers. Performance decreased when including 2 cm or 60 cm of soil layers. This demonstrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. Runoff coefficients (i.e., ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency and this shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

scholarly journals Simulating the influence of snow surface processes on soil moisture dynamics and streamflow generation in an alpine catchment

2017 ◽  
Vol 21 (8) ◽  
pp. 4053-4071 ◽  
Author(s):  
Nander Wever ◽  
Francesco Comola ◽  
Mathias Bavay ◽  
Michael Lehning
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Soil Water ◽  
Water Flux ◽  
Response Model ◽  
Hydrologic Response ◽  
Model Framework ◽  
Flood Risks ◽  
Soil Water Flux

Abstract. The assessment of flood risks in alpine, snow-covered catchments requires an understanding of the linkage between the snow cover, soil and discharge in the stream network. Here, we apply the comprehensive, distributed model Alpine3D to investigate the role of soil moisture in the predisposition of the Dischma catchment in Switzerland to high flows from rainfall and snowmelt. The recently updated soil module of the physics-based multilayer snow cover model SNOWPACK, which solves the surface energy and mass balance in Alpine3D, is verified against soil moisture measurements at seven sites and various depths inside and in close proximity to the Dischma catchment. Measurements and simulations in such terrain are difficult and consequently, soil moisture was simulated with varying degrees of success. Differences between simulated and measured soil moisture mainly arise from an overestimation of soil freezing and an absence of a groundwater description in the Alpine3D model. Both were found to have an influence in the soil moisture measurements. Using the Alpine3D simulation as the surface scheme for a spatially explicit hydrologic response model using a travel time distribution approach for interflow and baseflow, streamflow simulations were performed for the discharge from the catchment. The streamflow simulations provided a closer agreement with observed streamflow when driving the hydrologic response model with soil water fluxes at 30 cm depth in the Alpine3D model. Performance decreased when using the 2 cm soil water flux, thereby mostly ignoring soil processes. This illustrates that the role of soil moisture is important to take into account when understanding the relationship between both snowpack runoff and rainfall and catchment discharge in high alpine terrain. However, using the soil water flux at 60 cm depth to drive the hydrologic response model also decreased its performance, indicating that an optimal soil depth to include in surface simulations exists and that the runoff dynamics are controlled by only a shallow soil layer. Runoff coefficients (i.e. ratio of rainfall over discharge) based on measurements for high rainfall and snowmelt events were found to be dependent on the simulated initial soil moisture state at the onset of an event, further illustrating the important role of soil moisture for the hydrological processes in the catchment. The runoff coefficients using simulated discharge were found to reproduce this dependency, which shows that the Alpine3D model framework can be successfully applied to assess the predisposition of the catchment to flood risks from both snowmelt and rainfall events.

scholarly journals Geocryological conditions triggering thermokarst processes in Central Yakutia

2020 ◽  
Vol 163 ◽  
pp. 02007
Author(s):  
Nataliia Nesterova ◽  
Olga Makarieva ◽  
Alexander Fedorov ◽  
Andrey Shikhov
Keyword(s):  
Soil Moisture ◽  
Snow Cover ◽  
Snow Water Equivalent ◽  
River Basins ◽  
Soil Freezing ◽  
Abrupt Increase ◽  
Landsat Images ◽  
Thermokarst Lakes ◽  
Central Yakutia ◽  
Snow Water

The use of the Central Yakutia Landsat images revealed an increase in the area of thermokarst lakes by two times for the Suola and Taatta River basins and a quarter times in the Tanda River basin during the period 2000-2019. The abrupt increase in the lakes area is due to shortterm periods of abnormal rising in the active layer temperature, which are caused by high values of snow water equivalent and total annual precipitation. Increased soil moisture and the warming effect of snow cover led to the decrease of the intensity of soil freezing and increase of the temperature of the ground top layer. The combination of these factors triggered the activation of thermokarst processes, which led to a sharp, more than 1.5 times, increase of the thermokarst lakes area in 2007-2008.

Driving role of snow cover on soil moisture and drought development during the growing season in the Czech Republic

2015 ◽  
Vol 36 (11) ◽  
pp. 3741-3758 ◽  
Author(s):  
Vera Potopová ◽  
Constanţa Boroneanţ ◽  
Martin Možný ◽  
Josef Soukup
Keyword(s):  
Soil Moisture ◽  
Czech Republic ◽  
Snow Cover ◽  
Growing Season ◽  
The Czech Republic

scholarly journals Variability in Soil Moisture by Natural and Artificial Snow: A Case Study in Mt. Balwang Area, Gangwon-do, South Korea

2022 ◽  
Vol 9 ◽  
Author(s):  
Yalalt Nyamgerel ◽  
Hyejung Jung ◽  
Dong-Chan Koh ◽  
Kyung-Seok Ko ◽  
Jeonghoon Lee
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
South Korea ◽  
Snow Cover ◽  
Isotopic Analysis ◽  
High Elevation ◽  
Hydrological Processes ◽  
Soil Freezing ◽  
Freezing And Thawing ◽  
Natural Snow

Soil moisture is an important variable for understanding hydrological processes, and the year-round monitoring of soil moisture and temperature reflect the variations induced by snow cover and its melt. Herein, we monitored the soil moisture and temperature in high (two sites) and low (two sites) elevation regions with groundwater sampling near the Mt. Balwang area in Gangwon-do, South Korea from Sep 2020 to May 2021. This study aims to investigate the temporal and spatial variations in soil moisture and temperature due to snow (natural and artificial snow) and its melt. A ski resort has been operating in this area and has been producing artificial snow during winter periods; thus, the spring snowmelt comprises both natural and artificial snow. The effect of soil freezing and thawing, wind conditions, vegetation covers, the timing and intensity of snow cover and snowmelt were differed in the monitoring sites. The high elevation sites 1 and 2 exhibit the relatively longer and consistent snow cover than the low elevation sites. Particularly, site 2 show late (May 8) snow melting even this site is in south slope of the Mt. Balwang. The relatively steady and moist soil layers at sites 1, 2, and 3 during the warm period can be considered as influential points to groundwater recharge. Moreover, the differences between the mean δ18O (−9.89‰) of the artificial snow layers and other samples were low: in the order of surface water (0.04‰) >groundwater (−0.66 and −1.01‰) >natural snow (1.34 and −3.80‰). This indicates that the imprint of artificial snow derived from surface water and with decreasing amount of natural snow around the Mt. Balwang region, the results support the assumption that the potential influence of artificial snowmelt on groundwater quality. This study helps to understand the snow dynamic and its influence on the hydrological processes in this region by combining the hydro-chemical and isotopic analysis.

scholarly journals The Role of Averaging for Improving Sea Surface Salinity Retrieval from the Soil Moisture and Ocean Salinity (SMOS) Satellite and Impact of Auxiliary Data

2007 ◽  
Vol 24 (2) ◽  
pp. 255-269 ◽  
Author(s):  
Sabine Philipps ◽  
Christine Boone ◽  
Estelle Obligis
Keyword(s):  
Soil Moisture ◽  
Sensitivity Study ◽  
Sea Surface ◽  
Sea Surface Salinity ◽  
Global Ocean ◽  
Surface Salinity ◽  
Auxiliary Data ◽  
Additional Information ◽  
Ocean Salinity

Abstract Soil Moisture and Ocean Salinity (SMOS) was chosen as the European Space Agency’s second Earth Explorer Opportunity mission. One of the objectives is to retrieve sea surface salinity (SSS) from measured brightness temperatures (TBs) at L band with a precision of 0.2 practical salinity units (psu) with averages taken over 200 km by 200 km areas and 10 days [as suggested in the requirements of the Global Ocean Data Assimilation Experiment (GODAE)]. The retrieval is performed here by an inverse model and additional information of auxiliary SSS, sea surface temperature (SST), and wind speed (W). A sensitivity study is done to observe the influence of the TBs and auxiliary data on the SSS retrieval. The key role of TB and W accuracy on SSS retrieval is verified. Retrieval is then done over the Atlantic for two cases. In case A, auxiliary data are simulated from two model outputs by adding white noise. The more realistic case B uses independent databases for reference and auxiliary ocean parameters. For these cases, the RMS error of retrieved SSS on pixel scale is around 1 psu (1.2 for case B). Averaging over GODAE scales reduces the SSS error by a factor of 12 (4 for case B). The weaker error reduction in case B is most likely due to the correlation of errors in auxiliary data. This study shows that SSS retrieval will be very sensitive to errors on auxiliary data. Specific efforts should be devoted to improving the quality of auxiliary data.

scholarly journals Variations of deep soil moisture under different vegetation types and influencing factors in a watershed of the Loess Plateau, China

2016 ◽  
Vol 20 (8) ◽  
pp. 3309-3323 ◽  
Author(s):  
Xuening Fang ◽  
Wenwu Zhao ◽  
Lixin Wang ◽  
Qiang Feng ◽  
Jingyi Ding ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Influencing Factors ◽  
Loess Plateau ◽  
Vegetation Restoration ◽  
Native Vegetation ◽  
Watershed Scale ◽  
Vegetation Types ◽  
Deep Soil ◽  
Soil Layers ◽  
Management Measures

Abstract. Soil moisture in deep soil layers is a relatively stable water resource for vegetation growth in the semi-arid Loess Plateau of China. Characterizing the variations in deep soil moisture and its influencing factors at a moderate watershed scale is important to ensure the sustainability of vegetation restoration efforts. In this study, we focus on analyzing the variations and factors that influence the deep soil moisture (DSM) in 80–500 cm soil layers based on a soil moisture survey of the Ansai watershed in Yan'an in Shanxi Province. Our results can be divided into four main findings. (1) At the watershed scale, higher variations in the DSM occurred at 120–140 and 480–500 cm in the vertical direction. At the comparable depths, the variation in the DSM under native vegetation was much lower than that in human-managed vegetation and introduced vegetation. (2) The DSM in native vegetation and human-managed vegetation was significantly higher than that in introduced vegetation, and different degrees of soil desiccation occurred under all the introduced vegetation types. Caragana korshinskii and black locust caused the most serious desiccation. (3) Taking the DSM conditions of native vegetation as a reference, the DSM in this watershed could be divided into three layers: (i) a rainfall transpiration layer (80–220 cm); (ii) a transition layer (220–400 cm); and (iii) a stable layer (400–500 cm). (4) The factors influencing DSM at the watershed scale varied with vegetation types. The main local controls of the DSM variations were the soil particle composition and mean annual rainfall; human agricultural management measures can alter the soil bulk density, which contributes to higher DSM in farmland and apple orchards. The plant growth conditions, planting density, and litter water holding capacity of introduced vegetation showed significant relationships with the DSM. The results of this study are of practical significance for vegetation restoration strategies, especially for the choice of vegetation types, planting zones, and proper human management measures.

scholarly journals Multi-source hydrological soil moisture state estimation using data fusion optimisation

2017 ◽  
Vol 21 (7) ◽  
pp. 3267-3285 ◽  
Author(s):  
Lu Zhuo ◽  
Dawei Han
Keyword(s):  
Soil Moisture ◽  
Data Fusion ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Local Linear Regression ◽  
Data Sources ◽  
Superior Performance ◽  
Flood Prediction ◽  
Time To Build ◽  
Moisture State

Abstract. Reliable estimation of hydrological soil moisture state is of critical importance in operational hydrology to improve the flood prediction and hydrological cycle description. Although there have been a number of soil moisture products, they cannot be directly used in hydrological modelling. This paper attempts for the first time to build a soil moisture product directly applicable to hydrology using multiple data sources retrieved from SAC-SMA (soil moisture), MODIS (land surface temperature), and SMOS (multi-angle brightness temperatures in H–V polarisations). The simple yet effective local linear regression model is applied for the data fusion purpose in the Pontiac catchment. Four schemes according to temporal availabilities of the data sources are developed, which are pre-assessed and best selected by using the well-proven feature selection algorithm gamma test. The hydrological accuracy of the produced soil moisture data is evaluated against the Xinanjiang hydrological model's soil moisture deficit simulation. The result shows that a superior performance is obtained from the scheme with the data inputs from all sources (NSE = 0.912, r = 0.960, RMSE = 0.007 m). Additionally, the final daily-available hydrological soil moisture product significantly increases the Nash–Sutcliffe efficiency by almost 50 % in comparison with the two most popular soil moisture products. The proposed method could be easily applied to other catchments and fields with high confidence. The misconception between the hydrological soil moisture state variable and the real-world soil moisture content, and the potential to build a global routine hydrological soil moisture product are discussed.

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