scholarly journals Influence of lateral subsurface flow and connectivity on soil water storage in land surface modeling

2016 ◽  
Vol 121 (2) ◽  
pp. 704-721 ◽  
Author(s):  
Jonggun Kim ◽  
Binayak P. Mohanty
Keyword(s):  
Soil Water ◽  
Land Surface ◽  
Subsurface Flow ◽  
Water Storage ◽  
Surface Modeling ◽  
Soil Water Storage ◽  
Land Surface Modeling

Vegetation Control in the Long-Term Self-Stabilization of the Liangzhou Oasis of the Upper Shiyang River Watershed of West-Central Gansu, Northwest China

2009 ◽  
Vol 13 (13) ◽  
pp. 1-22 ◽  
Author(s):  
Charles P-A. Bourque ◽  
Quazi K. Hassan
Keyword(s):  
Soil Water ◽  
Land Surface ◽  
Water Storage ◽  
Qilian Mountains ◽  
Soil Water Storage ◽  
River Watershed ◽  
Vegetation Control ◽  
West Central ◽  
The Qilian Mountains

Abstract This paper explores the relationship between vegetation in the Liangzhou Oasis in the Upper Shiyang River watershed (USRW) of west-central Gansu, China, and within-watershed precipitation, soil water storage, and oasis self-support. Oases along the base of the Qilian Mountains receive a significant portion of their water supply (over 90%) from surface and subsurface flow originating from the Qilian Mountains. Investigation of vegetation control on oasis water conditions in the USRW is based on an application of a process model of soil water hydrology. The model is used to simulate long-term soil water content (SWC) in the Liangzhou Oasis as a function of (i) monthly composites of Moderate Resolution Imaging Spectroradiometer (MODIS) images of land surface and mean air temperature, (ii) spatiotemporal calculations of monthly precipitation and relative humidity generated with the assistance of genetic algorithms (GAs), and (iii) a 80-m-resolution digital elevation model (DEM) of the area. Modeled removal of vegetation is shown to affect within-watershed precipitation and soil water storage by reducing the exchange of water vapor from the land surface to the air, increasing the air’s lifting condensation level by promoting drier air conditions, and causing the high-intensity precipitation band in the Qilian Mountains to weaken and to be displaced upward, leading to an overall reduction of water to the Liangzhou Oasis.

Reconstructing Precipitation Events Using Co-located Soil Moisture Information

2021 ◽  
Author(s):  
Nathaniel Parker ◽  
Andres Patrignani
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Land Surface ◽  
Interpolation Method ◽  
Water Storage ◽  
Soil Water Storage ◽  
Monitoring Networks ◽  
Hourly Precipitation ◽  
Precipitation Record ◽  
Precipitation Events

Abstract Complete and accurate precipitation records are important for developing reliable flood warning systems, streamflow forecasts, rainfall-runoff estimates, and numerical land surface predictions. Existing methods for flagging missing precipitation events and filling gaps in the precipitation record typically rely on precipitation from neighboring stations. In this study, we investigated an alternative method for back-calculating precipitation events using changes in rootzone soil water storage. Our hypothesis was that using a different variable (i.e., soil moisture) from the same monitoring station will be more accurate in estimating hourly precipitation than using the same variable (i.e., precipitation) from the nearest neighboring station. Precipitation events were estimated from soil moisture as the sum of hourly changes in profile soil water storage. Hourly precipitation and soil moisture observations were obtained for a mesoscale network in the central U.S. Great Plains from May 2017 to December 2020. The proposed method based on soil moisture had a minimum detectable limit of 7.6 mm (95th percentile of undetected precipitation events) due to canopy and soil interception. The method was outperformed by the nearest neighbor (NN) interpolation method when neighboring stations were at distances of <10 km. However, the proposed method outperformed the NN method in 22 out of 27 stations when nearest stations were at distances >10 km. Using changes in soil water storage resulted effective in flagging and reconstructing actual missing precipitation events caused by pluviometer malfunction, highlighting new opportunities for using readily available in situ soil moisture information for operational quality control in mesoscale environmental monitoring networks.

scholarly journals Regression Models for Soil Water Storage Estimation Using the ESA CCI Satellite Soil Moisture Product: A Case Study in Northeast Portugal

Water ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Tomás de Figueiredo ◽  
Ana Caroline Royer ◽  
Felícia Fonseca ◽  
Fabiana Costa de Araújo Schütz ◽  
Zulimar Hernández
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Regression Models ◽  
Meteorological Data ◽  
Water Storage ◽  
Model Performance ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
The Relationship

The European Space Agency Climate Change Initiative Soil Moisture (ESA CCI SM) product provides soil moisture estimates from radar satellite data with a daily temporal resolution. Despite validation exercises with ground data that have been performed since the product’s launch, SM has not yet been consistently related to soil water storage, which is a key step for its application for prediction purposes. This study aimed to analyse the relationship between soil water storage (S), which was obtained from soil water balance computations with ground meteorological data, and soil moisture, which was obtained from radar data, as affected by soil water storage capacity (Smax). As a case study, a 14-year monthly series of soil water storage, produced via soil water balance computations using ground meteorological data from northeast Portugal and Smax from 25 mm to 150 mm, were matched with the corresponding monthly averaged SM product. Linear (I) and logistic (II) regression models relating S with SM were compared. Model performance (r2 in the 0.8–0.9 range) varied non-monotonically with Smax, with it being the highest at an Smax of 50 mm. The logistic model (II) performed better than the linear model (I) in the lower range of Smax. Improvements in model performance obtained with segregation of the data series in two subsets, representing soil water recharge and depletion phases throughout the year, outlined the hysteresis in the relationship between S and SM.

scholarly journals Energy balance closure on a winter wheat stand: comparing the eddy covariance technique with the soil water balance method

2016 ◽  
Vol 13 (1) ◽  
pp. 63-75 ◽  
Author(s):  
K. Imukova ◽  
J. Ingwersen ◽  
M. Hevart ◽  
T. Streck
Keyword(s):  
Energy Balance ◽  
Water Balance ◽  
Winter Wheat ◽  
Water Content ◽  
Soil Water ◽  
Water Storage ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Water Balance Method ◽  
Closure Method

Abstract. The energy balance of eddy covariance (EC) flux data is typically not closed. The nature of the gap is usually not known, which hampers using EC data to parameterize and test models. In the present study we cross-checked the evapotranspiration data obtained with the EC method (ETEC) against ET rates measured with the soil water balance method (ETWB) at winter wheat stands in southwest Germany. During the growing seasons 2012 and 2013, we continuously measured, in a half-hourly resolution, latent heat (LE) and sensible (H) heat fluxes using the EC technique. Measured fluxes were adjusted with either the Bowen-ratio (BR), H or LE post-closure method. ETWB was estimated based on rainfall, seepage and soil water storage measurements. The soil water storage term was determined at sixteen locations within the footprint of an EC station, by measuring the soil water content down to a soil depth of 1.5 m. In the second year, the volumetric soil water content was additionally continuously measured in 15 min resolution in 10 cm intervals down to 90 cm depth with sixteen capacitance soil moisture sensors. During the 2012 growing season, the H post-closed LE flux data (ETEC =  3.4 ± 0.6 mm day−1) corresponded closest with the result of the WB method (3.3 ± 0.3 mm day−1). ETEC adjusted by the BR (4.1 ± 0.6 mm day−1) or LE (4.9 ± 0.9 mm day−1) post-closure method were higher than the ETWB by 24 and 48 %, respectively. In 2013, ETWB was in best agreement with ETEC adjusted with the H post-closure method during the periods with low amount of rain and seepage. During these periods the BR and LE post-closure methods overestimated ET by about 46 and 70 %, respectively. During a period with high and frequent rainfalls, ETWB was in-between ETEC adjusted by H and BR post-closure methods. We conclude that, at most observation periods on our site, LE is not a major component of the energy balance gap. Our results indicate that the energy balance gap is made up by other energy fluxes and unconsidered or biased energy storage terms.

Sign in / Sign up

Export Citation Format

Share Document