scholarly journals Estimation of soil water storage change from clay shrinkage using satellite radar interferometry

2017 ◽  
Author(s):  
Bram te Brake
Keyword(s):  
Soil Water ◽  
Water Storage ◽  
Radar Interferometry ◽  
Soil Water Storage ◽  
Satellite Radar ◽  
Storage Change

scholarly journals New interpretation of the role of water balance in an extended Budyko hypothesis in arid regions

2015 ◽  
Vol 12 (10) ◽  
pp. 11013-11052 ◽  
Author(s):  
C. Du ◽  
F. Sun ◽  
J. Yu ◽  
X. Liu ◽  
Y. Chen
Keyword(s):  
Steady State ◽  
Water Balance ◽  
Soil Water ◽  
Arid Regions ◽  
Water Storage ◽  
Soil Water Storage ◽  
Unsteady State ◽  
Monthly Water Balance ◽  
Storage Change

Abstract. The Budyko hypothesis (BH) is an effective approach to investigating long-term water balance at large basin scale under steady state. The assumption of steady state prevents applications of the BH to basins, which is unclosed, or with significant variations in soil water storage, i.e., under unsteady state, such as in extremely arid regions. In this study, we choose the Heihe River Basin (HRB) in China, an extremely arid inland basin, as the study area. We firstly use a calibrated and then validated monthly water balance model, i.e., the abcd model to quantitatively determine annual and monthly variations of water balance for the sub-basins and the whole catchment of the HRB and find that the role of soil water storage change and that of inflow from upper sub-basins in monthly water balance are significant. With the recognition of the inflow water from other regions and the soil water storage change as additional possible water sources to evapotranspiration in unclosed basins, we further define the equivalent precipitation (Pe) to include local precipitation, inflow water and soil water storage change as the water supply in the Budyko framework. With the newly defined water supply, the Budyko curve can successfully describe the relationship between the evapotranspiration ratio and the aridity index at both annual and monthly timescales, whilst it fails when only the local precipitation being considered. Adding to that, we develop a new Fu-type Budyko equation with two non-dimensional parameters (ω and λ) based on the deviation of Fu's equation. Over the annual time scale, the new Fu-type Budyko equation developed here has more or less identical performance to Fu's original equation for the sub-basins and the whole catchment. However, over the monthly time scale, due to large seasonality of soil water storage and inflow, the new Fu-type Budyko equation generally performs better than Fu's original equation. The new Fu-type Budyko equation (ω and λ) developed here enables one to apply the BH to interpret regional water balance over extremely dry environments under unsteady state (e.g., unclosed basins or sub-annual timescales).

scholarly journals Water storage change estimation from in situ shrinkage measurements of clay soils

2012 ◽  
Vol 9 (11) ◽  
pp. 13117-13154 ◽  
Author(s):  
B. te Brake ◽  
M. J. van der Ploeg ◽  
G. H. de Rooij
Keyword(s):  
Soil Water ◽  
Water Storage ◽  
Soil Surface ◽  
Surface Elevation ◽  
Measurement Scale ◽  
Soil Water Storage ◽  
Soil Layers ◽  
Shrinkage Curve ◽  
Elevation Changes ◽  
Storage Change

Abstract. Water storage in the unsaturated zone is a major determinant of the hydrological behaviour of the soil, but methods to quantify soil water storage are limited. The objective of this study is to assess the applicability of clay soil surface elevation change measurements to estimate soil water storage changes. We measured moisture contents in soil aggregates by EC-5 sensors, and in volumes comprising multiple aggregates and intra-aggregates spaces by CS616 sensors. In a prolonged drying period, aggregate-scale storage change measurements revealed normal shrinkage for layers ≥ 30 cm depth, indicating volume loss equalled water loss. Shrinkage in a soil volume including multiple aggregates and voids was slightly less than normal, due to soil moisture variations in the profile and delayed drying of deeper soil layers upon lowering of the groundwater level. This resulted in shrinkage curve slopes of 0.89, 0.90 and 0.79 for the layers 0–60, 0–100 and 0–150 cm. Under a dynamic drying and wetting regime, shrinkage curve slopes ranged from 0.29 to 0.69 (EC-5) and 0.27 to 0.51 (CS616). Alternation of shrinkage and incomplete swelling resulted in an underestimation of volume change relatively to water storage change, due to hysteresis between swelling and shrinkage. Since the slope of the shrinkage relation depends on the drying regime, measurement scale and combined effect of different soil layers, shrinkage curves from laboratory tests on clay aggregates require suitable modifications for application to soil profiles. Then, the linear portion of the curve can help soil water storage estimation from soil surface elevation changes. These elevation changes might be measurable over larger extents by remote sensing.

scholarly journals Water storage change estimation from in situ shrinkage measurements of clay soils

2013 ◽  
Vol 17 (5) ◽  
pp. 1933-1949 ◽  
Author(s):  
B. te Brake ◽  
M. J. van der Ploeg ◽  
G. H. de Rooij
Keyword(s):  
Soil Water ◽  
Volume Change ◽  
Water Loss ◽  
Water Storage ◽  
Bulk Soil ◽  
Soil Water Storage ◽  
Dry Period ◽  
Soil Layers ◽  
Storage Change

Abstract. The objective of this study is to assess the applicability of clay soil elevation change measurements to estimate soil water storage changes, using a simplified approach. We measured moisture contents in aggregates by EC-5 sensors, and in multiple aggregate and inter-aggregate spaces (bulk soil) by CS616 sensors. In a long dry period, the assumption of constant isotropic shrinkage proved invalid and a soil moisture dependant geometry factor was applied. The relative overestimation made by assuming constant isotropic shrinkage in the linear (basic) shrinkage phase was 26.4% (17.5 mm) for the actively shrinking layer between 0 and 60 cm. Aggregate-scale water storage and volume change revealed a linear relation for layers ≥ 30 cm depth. The range of basic shrinkage in the bulk soil was limited by delayed drying of deep soil layers, and maximum water loss in the structural shrinkage phase was 40% of total water loss in the 0–60 cm layer, and over 60% in deeper layers. In the dry period, fitted slopes of the ΔV–ΔW relationship ranged from 0.41 to 0.56 (EC-5) and 0.42 to 0.55 (CS616). Under a dynamic drying and wetting regime, slopes ranged from 0.21 to 0.38 (EC-5) and 0.22 to 0.36 (CS616). Alternating shrinkage and incomplete swelling resulted in limited volume change relative to water storage change. The slope of the ΔV–ΔW relationship depended on the drying regime, measurement scale and combined effect of different soil layers. Therefore, solely relying on surface level elevation changes to infer soil water storage changes will lead to large underestimations. Recent and future developments might provide a basis for application of shrinkage relations to field situations, but in situ observations will be required to do so.

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.

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