scholarly journals A stochastic approach for the description of the water balance dynamics in a river basin

2008 ◽  
Vol 5 (2) ◽  
pp. 723-748 ◽  
Author(s):  
S. Manfreda ◽  
M. Fiorentino
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
River Basin ◽  
Stochastic Approach ◽  
Soil Water Balance ◽  
Water Storage Capacity ◽  
Spatial Redistribution ◽  
Homogeneous Soil ◽  
Balance Dynamics

Abstract. The present paper introduces an analytical approach for the description of the soil water balance dynamics over a schematic river basin. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance. This equation can be solved assuming known the spatial distribution of the soil moisture over the basin transforming the two dimensional problem in a one dimensional one. This assumption is particularly true in the case of humid and semihumid environments, where spatial redistribution of soil moisture becomes dominant producing a well defined pattern. The model allowed to derive the probability density function of the saturated portion of a basin and of its relative saturation. This theory is based on the assumption that the water storage capacity varies across the basin following a parabolic distribution and the basin has homogeneous soil texture and vegetation cover. The methodology outlined the role played by the basin shape in the soil water balance dynamics.

scholarly journals A stochastic approach for the description of the water balance dynamics in a river basin

2008 ◽  
Vol 12 (5) ◽  
pp. 1189-1200 ◽  
Author(s):  
S. Manfreda ◽  
M. Fiorentino
Keyword(s):  
Water Balance ◽  
Probability Density ◽  
Soil Water ◽  
Storage Capacity ◽  
Water Storage ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Water Storage Capacity ◽  
Soil Water Storage Capacity ◽  
Balance Dynamics

Abstract. The present paper introduces an analytical approach for the description of the soil water balance dynamics over a schematic river basin. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance. This equation can be solved assuming known the spatial distribution of the soil moisture over the basin transforming the two-dimensional problem in space in a one dimensional one. This assumption is particularly true in the case of humid and semihumid environments, where spatial redistribution becomes dominant producing a well defined soil moisture pattern. The model allowed to derive the probability density function of the saturated portion of a basin and of its relative saturation. This theory is based on the assumption that the soil water storage capacity varies across the basin following a parabolic distribution and the basin has homogeneous soil texture and vegetation cover. The methodology outlined the role played by the soil water storage capacity distribution of the basin on soil water balance. In particular, the resulting probability density functions of the relative basin saturation were found to be strongly controlled by the maximum water storage capacity of the basin, while the probability density functions of the relative saturated portion of the basin are strongly influenced by the spatial heterogeneity of the soil water storage capacity. Moreover, the saturated areas reach their maximum variability when the mean rainfall rate is almost equal to the soil water loss coefficient given by the sum of the maximum rate of evapotranspiration and leakage loss in the soil water balance. The model was tested using the results of a continuous numerical simulation performed with a semi-distributed model in order to validate the proposed theoretical distributions.

scholarly journals Runoff generation dynamics within a humid river basin

2008 ◽  
Vol 8 (6) ◽  
pp. 1349-1357 ◽  
Author(s):  
S. Manfreda
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
River Basin ◽  
Parameters Estimation ◽  
Soil Water Balance ◽  
Soil Water Storage ◽  
Runoff Generation ◽  
Water Storage Capacity ◽  
Soil Water Storage Capacity ◽  
Runoff Production

Abstract. The present paper introduces an analytical approach for the description of the soil water balance and runoff production within a schematic river basin. The model is based on a stochastic differential equation where the rainfall is interpreted as an additive noise in the soil water balance and is assumed uniform over the basin, the basin heterogeneity is characterized by a parabolic distribution of the soil water storage capacity and the runoff production occurs for saturation excess. The model allowed to derive the probability density function of the produced surface runoff highlighting the role played by climate and physical characteristics of a basin on runoff dynamics. Finally, the model have been tested over a humid basin of Southern Italy proposing also a strategy for the parameters estimation.

Soil water balance dynamics under plastic mulching in dryland rainfed agroecosystem across the Loess Plateau

2021 ◽  
Vol 312 ◽  
pp. 107354 ◽  
Author(s):  
Ai-Tian Ren ◽  
Rui Zhou ◽  
Fei Mo ◽  
Shu-Tong Liu ◽  
Ji-Yuan Li ◽  
...  
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Loess Plateau ◽  
Soil Water Balance ◽  
The Loess Plateau ◽  
Plastic Mulching ◽  
Balance Dynamics

scholarly journals Probabilistic inference of ecohydrological parameters using observations from point to satellite scales

2018 ◽  
Vol 22 (6) ◽  
pp. 3229-3243 ◽  
Author(s):  
Maoya Bassiouni ◽  
Chad W. Higgins ◽  
Christopher J. Still ◽  
Stephen P. Good
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Dry Season ◽  
Soil Water Balance ◽  
Rainfall Pattern ◽  
Site Specific ◽  
Soil Moisture Dynamics ◽  
Soil Saturation ◽  
Moisture Dynamics

Abstract. Vegetation controls on soil moisture dynamics are challenging to measure and translate into scale- and site-specific ecohydrological parameters for simple soil water balance models. We hypothesize that empirical probability density functions (pdfs) of relative soil moisture or soil saturation encode sufficient information to determine these ecohydrological parameters. Further, these parameters can be estimated through inverse modeling of the analytical equation for soil saturation pdfs, derived from the commonly used stochastic soil water balance framework. We developed a generalizable Bayesian inference framework to estimate ecohydrological parameters consistent with empirical soil saturation pdfs derived from observations at point, footprint, and satellite scales. We applied the inference method to four sites with different land cover and climate assuming (i) an annual rainfall pattern and (ii) a wet season rainfall pattern with a dry season of negligible rainfall. The Nash–Sutcliffe efficiencies of the analytical model's fit to soil observations ranged from 0.89 to 0.99. The coefficient of variation of posterior parameter distributions ranged from < 1 to 15 %. The parameter identifiability was not significantly improved in the more complex seasonal model; however, small differences in parameter values indicate that the annual model may have absorbed dry season dynamics. Parameter estimates were most constrained for scales and locations at which soil water dynamics are more sensitive to the fitted ecohydrological parameters of interest. In these cases, model inversion converged more slowly but ultimately provided better goodness of fit and lower uncertainty. Results were robust using as few as 100 daily observations randomly sampled from the full records, demonstrating the advantage of analyzing soil saturation pdfs instead of time series to estimate ecohydrological parameters from sparse records. Our work combines modeling and empirical approaches in ecohydrology and provides a simple framework to obtain scale- and site-specific analytical descriptions of soil moisture dynamics consistent with soil moisture observations.

scholarly journals Evaluation of DSSAT soil-water balance module under cropped and bare soil conditions

2003 ◽  
Vol 46 (4) ◽  
pp. 489-498 ◽  
Author(s):  
Rogério Teixeira de Faria ◽  
Walter Truman Bowen
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Water Flux ◽  
Soil Water Potential ◽  
Bare Soil ◽  
Root Water Uptake ◽  
Soil Water Balance ◽  
Soil Conditions ◽  
Soil Water Flux

The performance of the soil water balance module (SWBM) in the models of DSSAT v3.5 was evaluated against soil moisture data measured in bare soil and dry bean plots, in Paraná, southern Brazil. Under bare soil, the SWBM showed a low performance to simulate soil moisture profiles due to inadequacies of the method used to calculate unsaturated soil water flux. Improved estimates were achieved by modifying the SWBM with the use of Darcy's equation to simulate soil water flux as a function of soil water potential gradient between consecutive soil layers. When used to simulate water balance for the bean crop, the modified SWBM improved soil moisture estimation but underpredicted crop yield. Root water uptake data indicated that assumptions on the original method limited plant water extraction for the soil in the study area. This was corrected by replacing empirical coefficients with measured values of soil hydraulic conductivity at different depths.

scholarly journals Soil water balance correction due to light rainfall, dew and fog in Ebro river basin (Spain)

2016 ◽  
Vol 170 ◽  
pp. 61-67 ◽  
Author(s):  
R. Moratiel ◽  
A. Martínez-Cob ◽  
A.M. Tarquis ◽  
R.L. Snyder
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
River Basin ◽  
Soil Water Balance ◽  
Ebro River ◽  
Balance Correction

Soil water balance and evapotranspiration of irrigated cotton

1967 ◽  
Vol 69 (1) ◽  
pp. 95-101 ◽  
Author(s):  
W. R. Stern
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Balance Equation ◽  
Dry Season ◽  
Soil Water Balance ◽  
Wet Season ◽  
Water Balance Equation ◽  
Soil Moisture Storage ◽  
Moisture Storage

In a series of five irrigated cotton sowings (T2, T7, T9, T11, T14) evapotranspiration (Et) was determined for the period between October 1961 and October 1962 by observing frequently the changes in soil moisture storage, calculating through drainage, and solving for evapotranspiration in the water balance equation. Thus a water balance was obtained for each sowing extending over the entire crop.The average evapotranspiration in wet season sowings was of the order of 6·5 mm day−1 and in dry season sowings of the order of 4·5 mm day−1. The highest evapotranspiration values ranged between 10 and 12 mm day−1 in T2, T7 and T9 and between 7 and 9·5 mm day−1 in T11 and T14.

scholarly journals Ecohydrologic controls on vegetation density and evapotranspiration partitioning across the climatic gradients of the central United States

2008 ◽  
Vol 5 (2) ◽  
pp. 649-700 ◽  
Author(s):  
J. P. Kochendorfer ◽  
J. A. Ramírez
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Water Balance ◽  
Soil Water ◽  
Water Use ◽  
Soil Surface ◽  
Soil Water Balance ◽  
Vegetation Density ◽  
Study Region ◽  
Central United States

Abstract. The soil-water balance and plant water use are investigated over a domain encompassing the central United States using the Statistical-Dynamical Ecohydrology Model (SDEM). The seasonality in the model and its use of the two-component Shuttleworth-Wallace canopy model allow for application of an ecological optimality hypothesis in which vegetation density, in the form of peak green leaf area index (LAI), is maximized, within upper and lower bounds, such that, in a typical season, soil moisture in the latter half of the growing season just reaches the point at which water stress is experienced. Another key feature of the SDEM is that it partitions evapotranspiration into transpiration, evaporation from canopy interception, and evaporation from the soil surface. That partitioning is significant for the soil-water balance because the dynamics of the three processes are very different. The partitioning and the model-determined peak in green LAI are validated based on observations in the literature, as well as through the calculation of water-use efficiencies with modeled transpiration and large-scale estimates of grassland productivity. Modeled-determined LAI are seen to be at least as accurate as the unaltered satellite-based observations on which they are based. Surprising little dependence on climate and vegetation type is found for the percentage of total evapotranspiration that is soil evaporation, with most of the variation across the study region attributable to soil texture and the resultant differences in vegetation density. While empirical evidence suggests that soil evaporation in the forested regions of the most humid part of the study region is somewhat overestimated, model results are in excellent agreement with observations from croplands and grasslands. The implication of model results for water-limited vegetation is that the higher (lower) soil moisture content in wetter (drier) climates is more-or-less completely offset by the greater (lesser) amount of energy available at the soil surface. This contrasts with other modeling studies which show a strong dependence of evapotranspiration partitioning on climate.

Groundwater recharge estimates combining soil isotope profiles and classical soil water monitoring techniques

2021 ◽  
Author(s):  
Nina Krüger ◽  
Christoph Külls ◽  
Marcel Kock
Keyword(s):  
Soil Moisture ◽  
Water Balance ◽  
Groundwater Recharge ◽  
Soil Water ◽  
Soil Profile ◽  
Tunable Diode Laser ◽  
Soil Water Balance ◽  
Advection Dispersion ◽  
Flow Processes ◽  
Percolation Rate

&lt;p&gt;To improve knowledge of hydrological and hydrogeological flow processes and their dependency on climate conditions it is becoming increasingly important to integrate sensors technology, independent observation methods, and new modeling techniques. Established isotope methods are usually regarded as a supplement and extension to classical hydrological investigation methods but are rarely included in soil water balance models. However, the combination could close knowledge gaps and thus lead to more precise and realistic predictions and therefore to better water management. Within the Wasserpfad project, a project of the Department of Civil Engineering at the TH L&amp;#252;beck, soil moisture has been measured since May 2018. SMT100 soil moisture sensors from TRUEBNER GmbH are used at depths of 20, 40, 60, and 80 cm. Next to the station a 2m deep soil profile was taken in 2020, to estimate groundwater recharge using stable isotope equilibration methods and cryogenic extraction combined with soil water balance modeling. Vertical profiles of stable isotopes have been determined with a 10-cm resolution and measured with Tunable Diode Laser spectrometry. Percolation through the soil profile has been estimated based on the convolution of a seasonal input function using advection-dispersion transport models. Percolation rate estimate based on environmental isotope profiles results in 230 mm per year. Fitting of the advection-dispersion equation using a sinusoidal isotope input fitted to available time series provides an estimate of 255 mm per year. This difference is due to the dispersion effect on the isotope minima and maxima. The result of modeling the soil moisture data with a soil water balance model integrating the Richards equation for water transport and Penmen-Monteith based calculation of actual evaporation is used to verify the percolation rates. The analysis of soil moisture and isotope data by modeling provides a direct and efficient way to estimate the percolation rate. The combination of isotope methods with classical hydrological measuring techniques offers the possibility to verify results, to calibrate models, or to investigate the limits of isotope methods. Thus, flow processes can be predicted more reliably in the future.&lt;/p&gt;

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