scholarly journals An Analytical Hydrological Model for the Study of Scaling Issues in Land Surface Modeling

2006 ◽  
Vol 10 (20) ◽  
pp. 1-24 ◽  
Author(s):  
Diandong Ren ◽  
Ann Henderson-Sellers
Keyword(s):  
Soil Moisture ◽  
Steady State ◽  
Analytical Model ◽  
Hydrological Model ◽  
Clay Soil ◽  
Initial Conditions ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Initial Soil Moisture ◽  
Initial Soil

Abstract Besides the atmospheric forcing such as solar radiation input and precipitation, the heterogeneity of the surface cover also plays an important role, especially in the distribution characteristics of the latent heat flux (LE). In this study, scaling issues are discussed based on an analytical hydrological model that describes the transpiration and diffusion processes of soil water. The solution of this analytical model is composed of a transient part that depends primarily on initial conditions and a steady part that depends on the boundary conditions. To know how sensitive the different averaging approaches are to the initial conditions, three initial profiles are chosen that cover the prevailing soil moisture regimes. After analyzing its solution, the study shows that 1) upon reaching the steady state, directly taking an average of soil properties will cause systematic overestimation in the calculation of area-averaged LE. For an initially very dry condition, averaging of a sandy soil and a clay soil can cause a percentage error as large as 40%. 2) For vegetation growing on sandy soils, a direct averaging of the transpiration rate results in persistent overestimation of LE. For vegetation growing on clay soil, however, even after reaching the steady state, averaging of two water extraction weights can be either an overestimation or an underestimation, depending on which two vegetation types are involved. 3) During the interim stage of drying down, averaging of the soil/vegetation properties can lead to either an overestimation or an underestimation, depending on the evolving stage of the soil moisture profile. 4) The initial soil moisture condition matters during the transient stage of drying down. Different initial soil moisture conditions yield different scenarios of underestimation and overestimation patterns and a differing severity of errors. The simplicity of the analytical model and the heuristic initial soil profiles make the generalization easier than using sophisticated numerical models and make the causality mechanism clearer for physical interpretations.

scholarly journals Critical Role of Soil Moisture Memory in Predicting the 2012 Central United States Flash Drought

2021 ◽  
Vol 9 ◽  
Author(s):  
Miaoling Liang ◽  
Xing Yuan
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Critical Role ◽  
Summer Drought ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Central United States

The unprecedented 2012 summer drought over the central United States was characterized by rapid intensification and severe impact and was known as a flash drought. Since then, flash drought has raised a wide concern, with considerable progresses on the definition, detection of anthropogenic footprints, and assessment of ecological impact. However, physical mechanisms related to the flash drought predictability remain unclear. Here, we show that the severity of the 2012 flash drought will be heavily underestimated without realistic initial soil moisture condition. The global Weather Research and Forecasting (GWRF) model was employed during the summers of 1979–2012, driven by observed sea surface temperature but without lateral boundary controls, which is similar to two-tier global seasonal prediction. The 2012 United States drought pattern was roughly captured by the GWRF ensemble global simulations, although with obvious underestimation of the severity. To further diagnose the role of soil moisture memory, dry and wet simulations that decrease and increase initial soil moisture by 10% were conducted. While the dry case does not significantly differ from the control case, the wet case totally missed the drought over the Central and Southern Great Plains by changing the anticyclonic circulation anomaly to a cyclonic anomaly and simulating a northward anomaly of meridional wind that brought anomalous moisture from the Gulf of Mexico and finally resulted in a failure to predict the drought. This study highlights the importance of soil moisture memory in predicting flash drought that often occurred without strong oceanic signal.

Predictability of Seasonal Streamflow and Soil Moisture in National Water Model and a Humid Alabama–Coosa–Tallapoosa River Basin

2020 ◽  
Vol 21 (7) ◽  
pp. 1447-1467 ◽  
Author(s):  
Yanan Duan ◽  
Sanjiv Kumar
Keyword(s):  
Soil Moisture ◽  
Water Model ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Streamflow Forecast ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Seasonal Streamflow ◽  
Soil Moisture Variability ◽  
National Water

AbstractThis study investigates the potential predictability of streamflow and soil moisture in the Alabama–Coosa–Tallapoosa (ACT) river basin in the southeastern United States. The study employs the state-of-the-art National Water Model (NWM) and compares the effects of initial soil moisture condition with those of seasonal climate anomalies on streamflow and soil moisture forecast skills. We have designed and implemented seasonal streamflow forecast ensemble experiments following the methodology suggested by Dirmeyer et al. The study also compares the soil moisture variability in the NWM with in situ measurements and remote sensing data from the Soil Moisture Active and Passive (SMAP) satellite. The NWM skillfully simulates the observed streamflow in the ACT basin. The soil moisture variability is 46% smaller in the NWM compared with the SMAP data, mainly due to a weaker amplitude of the seasonal cycle. This study finds that initial soil moisture condition is a major source of predictability for the seasonal streamflow forecast. The contribution of the initial soil moisture condition is comparable or even higher than that of seasonal climate anomaly effects in dry seasons. In the boreal summer season, the initial soil moisture condition contributes to 65% and 48% improvements in the seasonal streamflow and soil moisture forecast skills, respectively. This study attributes a greater improvement in the streamflow forecast skill to the lag effects between the soil moisture and streamflow anomalies. The results of this study can inform the development and improvement of the operational streamflow forecasting system.

Effects of Initial Soil Moisture on Rainfall Generation and Subsequent Hydrologic Response during the North American Monsoon

2009 ◽  
Vol 10 (3) ◽  
pp. 644-664 ◽  
Author(s):  
Enrique R. Vivoni ◽  
Kinwai Tai ◽  
David J. Gochis
Keyword(s):  
Soil Moisture ◽  
North American ◽  
Initial Conditions ◽  
Hydrologic Model ◽  
North American Monsoon ◽  
Meteorological Model ◽  
Initial Soil Moisture ◽  
The North ◽  
Spatial Coverage ◽  
Initial Soil

Abstract Through the use of a mesoscale meteorological model and distributed hydrologic model, the effects of initial soil moisture on rainfall generation, streamflow, and evapotranspiration during the North American monsoon are examined. A collection of atmospheric fields is simulated by varying initial soil moisture in the meteorological model. Analysis of the simulated rainfall fields shows that the total rainfall, intensity, and spatial coverage increase with higher soil moisture. Hydrologic simulations forced by the meteorological fields are performed using two scenarios: (i) fixed soil moisture initializations obtained via a drainage experiment in the hydrologic model and (ii) adjusted initializations to match conditions in the two models. The scenarios indicate that the runoff ratio increases with higher rainfall, although a change is observed from a linear (fixed initialization) to a nonlinear response (adjusted initialization). Variations in basin response are attributed to controls exerted by rainfall, soil, and vegetation properties for varying initial conditions. Antecedent wetness significantly influences the runoff response through the interplay of different runoff generation mechanisms and also controls the evapotranspiration process. The authors conclude that a regional increase in initial soil moisture promotes rainfall generation, streamflow, and evapotranspiration for this warm-season case study.

scholarly journals The influence of the initial soil moisture content on the degree of water stable aggregation as determined by wet sieving

1959 ◽  
Vol 31 (1) ◽  
pp. 233-239
Author(s):  
Mikko Sillanpää
Keyword(s):  
Soil Moisture ◽  
Moisture Content ◽  
Soil Moisture Content ◽  
Soil Samples ◽  
Moisture Condition ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Pre Treatment ◽  
A Minor ◽  
Wet Sieving

The effect of the soil moisture content (varying from the field-moist to air-dry before re-wetting the muddy clay soil samples for aggregate analysis) on aggregation was studied. Two wetting procedures were used and compared: They were spraying samples with a fine mist and wetting them by immersion; aggregate analyses were made by wet sieving method. The results of the aggregate analyses proved to be practically independent of the initial moisture condition of the soil samples when the samples were wetted slowly with a spray. When wetting the samples by direct immersion the mean weight diameters of aggregates decrease with decreasing initial soil moisture content to values of less than half of those obtained from samples in their original field-moist condition (34.6—36.7 % dry wt.) or of those wetted with a spray. Air-drying seems to be a minor factor affecting the destruction of aggregates but the destruction effect of the sample pre-treatment may be very harmful if immersion wetting is used. This, however, can be eliminated almost completely if wetting with a fine mist is used.

Large Scale Basins With Small to Negligible Slopes

2000 ◽  
Vol 31 (1) ◽  
pp. 27-40 ◽  
Author(s):  
Luis Silveira
Keyword(s):  
Soil Moisture ◽  
Large Scale ◽  
Hydrological Model ◽  
Transport Processes ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Soil Moisture Storage ◽  
High Soil Moisture ◽  
Rio Negro ◽  
Moisture Storage

Large basins with small to negligible slopes are seldom considered in the hydrological literature. An example of such basins is the Río Negro catchment in Uruguay. The first of this two-paper series showed the following special features: a) the existence of strongly developed horizontal layers and an essentially impervious B-horizon, b) significantly high soil moisture storage in terms of normally expected rainfall during a storm and c) the importance of vertical water transport processes to establish the soil moisture condition prior to a storm and its role concerning basin runoff response. These observations and hypotheses were taken into account by the lumped conceptual hydrological model called Hidro-Urfing through the percolation function and the basin runoff response function. This second paper shows its application to the Laguna I basin, a sub-basin of the Río Negro catchment with a surface area of 13,945 km2, and its ability to model the major storm hydrographs without any subdivision into smaller sub-basins. Modelling of low flows requires disaggregation of spatial-scale issues. A hydrological model of the entire Río Negro catchment did not previously exist.

Initial soil moisture retrievals from the METOP-A Advanced Scatterometer (ASCAT)

2007 ◽  
Vol 34 (20) ◽  
Author(s):  
Zoltan Bartalis ◽  
Wolfgang Wagner ◽  
Vahid Naeimi ◽  
Stefan Hasenauer ◽  
Klaus Scipal ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Initial Soil Moisture ◽  
Initial Soil

Exploring the potential of soil moisture reanalysis data for improving the identification of regional landslide triggering thresholds

2021 ◽  
Author(s):  
Nunziarita Palazzolo ◽  
David J. Peres ◽  
Enrico Creaco ◽  
Antonino Cancelliere
Keyword(s):  
Soil Moisture ◽  
Rainfall Event ◽  
Rainfall Thresholds ◽  
Rainfall Duration ◽  
Soil Moisture Data ◽  
Initial Soil Moisture ◽  
Initial Soil ◽  
Different Depths ◽  
Moisture Conditions ◽  
Landslide Triggering

<p>Landslide triggering thresholds provide the rainfall conditions that are likely to trigger landslides, therefore their derivation is key for prediction purposes. Different variables can be considered for the identification of thresholds, which commonly are in the form of a power-law relationship linking rainfall event duration and intensity or cumulated event rainfall. The assessment of such rainfall thresholds generally neglects initial soil moisture conditions at each rainfall event, which are indeed a predisposing factor that can be crucial for the proper definition of the triggering scenario. Thus, more studies are needed to understand whether and the extent to which the integration of the initial soil moisture conditions with rainfall thresholds could improve the conventional precipitation-based approach. Although soil moisture data availability has hindered such type of studies, yet now this information is increasingly becoming available at the large scale, for instance as an output of meteorological reanalysis initiatives. In particular, in this study, we focus on the use of the ERA5-Land reanalysis soil moisture dataset. Climate reanalysis combines past observations with models in order to generate consistent time series and the ERA5-Land data actually provides the volume of water in soil layer at different depths and at global scale. Era5-Land project is, indeed, a global dataset at 9 km horizontal resolution in which atmospheric data are at an hourly scale from 1981 to present. Volumetric soil water data are available at four depths ranging from the surface level to 289 cm, namely 0-7 cm, 7-28 cm, 28-100 cm, and 100-289 cm. After collecting the rainfall and soil moisture data at the desired spatio-temporal resolution, together with the target data discriminating landslide and no-landslide events, we develop automatic triggering/non-triggering classifiers and test their performances via confusion matrix statistics. In particular, we compare the performances associated with the following set of precursors: a) event rainfall duration and depth (traditional approach), b) initial soil moisture at several soil depths, and c) event rainfall duration and depth and initial soil moisture at different depths. The approach is applied to the Oltrepò Pavese region (northern Italy), for which the historical observed landslides have been provided by the IFFI project (Italian landslides inventory). Results show that soil moisture may allow an improvement in the performances of the classifier, but that the quality of the landslide inventory is crucial.</p>

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