Neutrons on Rails – trans‐regional monitoring of soil moisture and snow water equivalent

Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1–6 months) comes from knowledge of initial hydrologic conditions (IHCs) and seasonal climate forecast skill (FS). In this study we quantify the contributions of two primary components of IHCs – soil moisture and snow water content – and FS (of precipitation and temperature) to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two model-based experiments using the variable infiltration capacity (VIC) macroscale hydrology model, one based on ensemble streamflow prediction (ESP) and another based on Reverse-ESP (Rev-ESP), both for a 47 yr re-forecast period (1961–2007). We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings) and estimate the ratio of root mean square error (RMSE) of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude) regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year. Based on our findings, we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.

Download Full-text

Improvement of operational airborne gamma radiation snow water equivalent estimates using SMAP soil moisture

Remote Sensing of Environment ◽

10.1016/j.rse.2020.111668 ◽

2020 ◽

Vol 240 ◽

pp. 111668 ◽

Cited By ~ 1

Author(s):

Eunsang Cho ◽

Jennifer M. Jacobs ◽

Ronny Schroeder ◽

Samuel E. Tuttle ◽

Carrie Olheiser

Keyword(s):

Soil Moisture ◽

Gamma Radiation ◽

Snow Water Equivalent ◽

Snow Water

Download Full-text

Geocryological conditions triggering thermokarst processes in Central Yakutia

E3S Web of Conferences ◽

10.1051/e3sconf/202016302007 ◽

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.

Download Full-text

Airborne Snow Water Equivalent And Soil Moisture Measurement Using Natural Terrestrial Gamma Radiation

10.1117/12.935888 ◽

1983 ◽

Cited By ~ 6

Author(s):

Thomas R. Carroll ◽

John C. Schaake, Jr.

Keyword(s):

Soil Moisture ◽

Gamma Radiation ◽

Snow Water Equivalent ◽

Moisture Measurement ◽

Snow Water ◽

Soil Moisture Measurement

Download Full-text

Influence of snow ablation and frozen ground on spring runoff generation in the Mogot Experimental Watershed, southern mountainous taiga of eastern Siberia

Hydrology Research ◽

10.2166/nh.2006.0002 ◽

2006 ◽

Vol 37 (1) ◽

pp. 21-29 ◽

Cited By ~ 19

Author(s):

Kazuyoshi Suzuki ◽

Jumpei Kubota ◽

Tetsuo Ohata ◽

Valery Vuglinsky

Keyword(s):

Soil Moisture ◽

Snow Water Equivalent ◽

Soil Surface ◽

Eastern Siberia ◽

Snowmelt Runoff ◽

Runoff Generation ◽

Frozen Ground ◽

Spring Runoff ◽

Snow Water ◽

The Difference

Snowmelt runoff is one of the most important discharge events in the southern mountainous taiga of eastern Siberia. The present study was conducted in order to understand the interannual variations in snowmelt infiltration into the frozen ground and in snowmelt runoff generation during the snowmelt period in the southern mountainous taiga in eastern Siberia. Analysis of the obtained data revealed the following: (1) snowmelt infiltration into the top 20 cm of frozen ground is important for evaluating snowmelt runoff generation because frozen ground absorbed from 22.9% (WY1983) to 61.5% (WY1981) of the maximum snow water equivalent. The difference in snowmelt infiltration for the two years appears to have been caused by the difference in snowmelt runoff generation; (2) the snowmelt runoff ratio increased with (i) increase in the fall soil moisture just before the soil surface froze and (ii) increase in the maximum snow water equivalent. The above results imply that the parameters governing snowmelt infiltration in the boreal taiga region in eastern Siberia are fall soil moisture and the maximum snow water equivalent, as is the case in the simple model presented by Gray et al.

Download Full-text

regionalization of the potential to increase rainfall-runoff model performance by multi-objective calibration using modis data over Austria

10.5194/egusphere-egu2020-13804 ◽

2020 ◽

Author(s):

Martin Kubáň ◽

Patrik Sleziak ◽

Adam Brziak ◽

Kamila Hlavčová ◽

Ján Szolgay

Keyword(s):

Soil Moisture ◽

Hydrological Model ◽

Snow Water Equivalent ◽

Model Performance ◽

State Variables ◽

Rainfall Runoff ◽

Multi Objective ◽

Snow Water ◽

Rainfall Runoff Model ◽

Runoff Model

A multi-objective calibration of the parameters of conceptual hydrologic models has the potential to improve the consistency of the simulated model states, their representativeness with respect to catchment states and thereby to reduce the uncertainty in the estimation of hydrological model outputs. Observed in-situ or remotely sensed state variables, such as the snow cover distribution, snow depth, snow water equivalent and soil moisture were often considered as additional information in such calibration strategies and subsequently utilized in data assimilation for operational streamflow forecasting. The objective of this paper is to assess the effects of the inclusion of MODIS products characterizing soil moisture and the snow water equivalent in a multi-objective calibration strategy of an HBV type conceptual hydrological model under the highly variable physiographic conditions over the whole territory of Austria.The methodology was tested using the Technical University of Vienna semi-distributed rainfall-runoff model (the TUW model), which was calibrated and validated in 213 Austrian catchments. For calibration we use measured data from the period 2005 to 2014. Subsequently, we simulated discharges, soil moisture and snow water equivalents based on parameters from the multi-objective calibration and compared these with the respective MODIS values. In general, the multi-objective calibration improved model performance when compared to results of model parametrisation calibrated only on discharge time series. Sensitivity analyses indicate that the magnitude of the model efficiency is regionally sensitive to the choice of the additional calibration variables. In the analysis of the results we indicate ranges how and where the runoff, soil moisture and snow water equivalent simulation efficiencies were sensitive to different setups of the multi-objective calibration strategy over the whole territory of Austria. It was attempted to regionalize the potential to increase of the overall model performance and the improvement in the consistency of the simulation of the two-state variables. Such regionalization may serve model users in the selection which remotely sensed variable or their combination is to be preferred in local modelling studies.

Download Full-text

Numerical Simulation of Terrestrial Radiation over a Snow Cover

Journal of Atmospheric and Oceanic Technology ◽

10.1175/jtech-d-14-00100.1 ◽

2015 ◽

Vol 32 (8) ◽

pp. 1478-1485 ◽

Cited By ~ 1

Author(s):

P. Ducharme ◽

A. Houdayer ◽

Y. Choquette ◽

B. Kapfer ◽

J. P. Martin

Keyword(s):

Soil Moisture ◽

Moisture Content ◽

Soil Moisture Content ◽

Snow Water Equivalent ◽

Field Measurements ◽

Radioactive Material ◽

Gamma Detector ◽

Content Type ◽

Basic Assumptions ◽

Snow Water

AbstractThe intensity of terrestrial gamma radiation is a function of a number of parameters: emissivity and spatial distribution of the radioactive material in the soil, snow/water cover above ground, soil moisture content, type, and height above ground of the detector. Thus, the conversion of gamma measurements into reliable information must be based on a solid knowledge of the behavior of the gamma detector under different conditions. Such a detector, using a cylindrical NaI(Tl) crystal, was developed to remotely and automatically provide information on snow water equivalent (SWE) and soil moisture content (M). It became rapidly obvious that the behavior of the detector [gamma monitor (GMON)] over an infinite source could not be exactly reproduced in a laboratory. Therefore, a relatively simple model to simulate the behavior of GMON and to establish the relevant data analysis algorithms was conceived. This paper presents the basic assumptions for developing the model, the resulting algorithms, a comparison with field measurements, and some useful information on how GMON reacts to various field conditions.

Download Full-text

Hydrologic Flowpath Development Varies by Aspect during Spring Snowmelt in Complex Subalpine Terrain

10.5194/tc-2017-12 ◽

2017 ◽

Cited By ~ 2

Author(s):

Ryan W. Webb ◽

Steven R. Fassnacht ◽

Michael N. Gooseff

Keyword(s):

Soil Moisture ◽

Snow Water Equivalent ◽

Surface Soil ◽

Slope Aspect ◽

Surface Soil Moisture ◽

Near Surface ◽

Mountainous Regions ◽

Snow Water ◽

Spring Snowmelt ◽

Preferential Flowpaths

Abstract. In many mountainous regions around the world, snow and soil moisture are key components of the hydrologic cycle. Preferential flowpaths of snowmelt water through snow have been known to occur for years with few studies observing the effect on soil moisture. In this study, statistical analysis of the topographical and hydrological controls on the spatio-temporal variability of snow water equivalent and soil moisture during snowmelt was undertaken at a subalpine forested setting with north, south, and flat aspects as a seasonally persistent snowpack melts. We investigated if preferential flowpaths in snow can be observed and the effect on soil moisture through measurements of snow water equivalent and near surface soil moisture in addition to observing how SWE and near surface soil moisture vary on hillslopes relative to the toes of hillslopes and flat areas. We then compared snowmelt infiltration beyond the near surface soil between flat and sloping terrain during the entire snowmelt season using soil moisture sensor profiles. This study was conducted during varying snowmelt seasons representing above normal, relatively normal, and below normal snow seasons in northern Colorado. Evidence is presented of preferential meltwater flowpaths at the snow-soil interface on the north facing slope with the effects observed in changes in SWE and infiltration into the soil at 20 cm depth; less association is observed in the near surface soil moisture (top 7 cm). We present a conceptualization of the meltwater flowpaths that develop based on slope aspect and soil properties. The resulting flowpaths are shown to increase the snow water equivalent by as much as 170 % at the base of a north facing hillslope. Results from this study show that snow acts as an extension of the vadose zone during spring snowmelt and future hydrologic investigations will benefit from studying the snow and soil together.

Download Full-text

Spatial extent of hydrological drought in the United States: changes and hydro-meteorological drivers

10.5194/egusphere-egu21-374 ◽

2021 ◽

Author(s):

Manuela Irene Brunner ◽

Daniel L. Swain ◽

Eric Gilleland ◽

Andrew W. Wood

Keyword(s):

United States ◽

Soil Moisture ◽

Snow Water Equivalent ◽

Management Strategies ◽

Threshold Level ◽

The United States ◽

Spatial Extent ◽

Variable Threshold ◽

Snow Water ◽

Over Time

Droughts can seriously challenge water management if they have large spatial extents. These extents may change in a warming climate along with changes in underlying hydro-meteorological drivers. Therefore, we ask (1) how streamflow drought spatial extent has changed over the period 1981-2018 in the United States, (2) which physical drivers govern drought spatial extent, and (3) whether/how the importance of these drivers has changed over time. We analyze temporal changes in streamflow drought extents and their drivers using drought events extracted for 671 catchments in the conterminous United States using a variable threshold-level approach. Drought spatial extents are determined as the percentage of catchments affected by drought during a certain month. Then, important drivers are identified by determining the spatial percentage overlap of the area under streamflow drought with precipitation droughts, temperature anomalies, snow-water-equivalent deficits, and soil moisture deficits. Finally, the spatial extent and overlap time series are used in a trend analysis to determine changes in drought spatial extent and to identify changes in the importance of different variables as drivers of drought spatial extent. Our analyses show that (1) drought spatial extents have increased, mainly because of increases in the extent of small droughts; (2) drought extents overall substantially overlap with soil moisture deficits and the relationship of drought to precipitation and temperature varies seasonally; (3) the importance of temperature as a driver of drought extent has increased over time. We therefore conclude that continued global warming may further increase the probability of spatially compounding drought events, which requires adaptation of regional drought management strategies.&#160;

Download Full-text