scholarly journals Evaluating the Drought Code Using In Situ Drying Timelags of Feathermoss Duff in Interior Alaska

Fire ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 25
Author(s):  
Eric Miller ◽  
Brenda Wilmore
Keyword(s):  
Water Balance ◽  
Evaporation Rate ◽  
Storage Capacity ◽  
Water Storage ◽  
Water Balance Model ◽  
Balance Model ◽  
Potential Evaporation ◽  
Water Storage Capacity ◽  
Interior Alaska

The Drought Code (DC) is a moisture code of the Canadian Forest Fire Weather Index System underlain by a hydrological water balance model in which drying occurs in a negative exponential pattern with a relatively long timelag. The model derives from measurements from an evaporimeter and no soil parameters are specified, leaving its physical nature uncertain. One way to approximate the attributes of a “DC equivalent soil” is to compare its drying timelag with measurements of known soils. In situ measurements of timelag were made over the course of a fire season in a black spruce-feathermoss forest floor underlain by permafrost in Interior Alaska, USA. On a seasonally averaged basis, timelag was 28 d. The corresponding timelag of the DC water balance model was 60 d. Water storage capacity in a whole duff column 200 mm deep was 31 mm. Using these figures and a relationship between timelag, water storage capacity, and the potential evaporation rate, a “DC equivalent soil” was determined to be capable of storing 66 mm of water. This amount of water would require a soil 366 mm deep, suggesting a revision of the way fire managers in Alaska regard the correspondence between soil and the moisture codes of the FWI. Nearly half of the soil depth would be mineral rather than organic. Much of the soil water necessary to maintain a 60 d timelag characteristic of a “DC equivalent soil” is frozen until after the solstice. Unavailability of frozen water, coupled with a June peak in the potential evaporation rate, appears to shorten in situ timelags early in the season.

scholarly journals Testing an optimality-based model of rooting zone water storage capacity in temperate forests

2018 ◽  
Vol 22 (7) ◽  
pp. 4097-4124 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Heike Lischke ◽  
Massimiliano Zappa
Keyword(s):  
Water Balance ◽  
Storage Capacity ◽  
Water Storage ◽  
Water Balance Model ◽  
Balance Model ◽  
Rooting Depth ◽  
Water Storage Capacity ◽  
Rooting Zone ◽  
Local Water ◽  
Zone Water

Abstract. Rooting zone water storage capacity Sr is a crucial parameter for modeling hydrology, ecosystem gas exchange and vegetation dynamics. Despite its importance, this parameter is still poorly constrained and subject to high uncertainty. We tested the analytical, optimality-based model of effective rooting depth proposed by Guswa (2008, 2010) with regard to its applicability for parameterizing Sr in temperate forests. The model assumes that plants dimension their rooting systems to maximize net carbon gain. Results from this model were compared against values obtained by calibrating a local water balance model against latent heat flux and soil moisture observations from 15 eddy covariance sites. Then, the effect of optimality-based Sr estimates on the performance of local water balance predictions was assessed during model validation. The agreement between calibrated and optimality-based Sr varied greatly across climates and forest types. At a majority of cold and temperate sites, the Sr estimates were similar for both methods, and the water balance model performed equally well when parameterized with calibrated and with optimality-based Sr. At spruce-dominated sites, optimality-based Sr were much larger than calibrated values. However, this did not affect the performance of the water balance model. On the other hand, at the Mediterranean sites considered in this study, optimality-based Sr were consistently much smaller than calibrated values. The same was the case at pine-dominated sites on sandy soils. Accordingly, performance of the water balance model was much worse at these sites when optimality-based Sr were used. This rooting depth parameterization might be used in dynamic (eco)hydrological models under cold and temperate conditions, either to estimate Sr without calibration or as a model component. This could greatly increase the reliability of transient climate-impact assessment studies. On the other hand, the results from this study do not warrant the application of this model to Mediterranean climates or on very coarse soils. While the cause of these mismatches cannot be determined with certainty, it is possible that trees under these conditions follow rooting strategies that differ from the carbon budget optimization assumed by the model.

scholarly journals Diagnosis toward predicting mean annual runoff in ungauged basins

2021 ◽  
Vol 25 (2) ◽  
pp. 945-956
Author(s):  
Yuan Gao ◽  
Lili Yao ◽  
Ni-Bin Chang ◽  
Dingbao Wang
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Storage Capacity ◽  
Water Storage ◽  
Annual Runoff ◽  
Balance Model ◽  
Soil Water Storage ◽  
Ungauged Basins ◽  
Water Storage Capacity ◽  
Soil Water Storage Capacity

Abstract. Prediction of mean annual runoff is of great interest but still poses a challenge in ungauged basins. The present work diagnoses the prediction in mean annual runoff affected by the uncertainty in estimated distribution of soil water storage capacity. Based on a distribution function, a water balance model for estimating mean annual runoff is developed, in which the effects of climate variability and the distribution of soil water storage capacity are explicitly represented. As such, the two parameters in the model have explicit physical meanings, and relationships between the parameters and controlling factors on mean annual runoff are established. The estimated parameters from the existing data of watershed characteristics are applied to 35 watersheds. The results showed that the model could capture 88.2 % of the actual mean annual runoff on average across the study watersheds, indicating that the proposed new water balance model is promising for estimating mean annual runoff in ungauged watersheds. The underestimation of mean annual runoff is mainly caused by the underestimation of the area percentage of low soil water storage capacity due to neglecting the effect of land surface and bedrock topography. Higher spatial variability of soil water storage capacity estimated through the height above the nearest drainage (HAND) and topographic wetness index (TWI) indicated that topography plays a crucial role in determining the actual soil water storage capacity. The performance of mean annual runoff prediction in ungauged basins can be improved by employing better estimation of soil water storage capacity including the effects of soil, topography, and bedrock. It leads to better diagnosis of the data requirement for predicting mean annual runoff in ungauged basins based on a newly developed process-based model finally.

scholarly journals A Daily Water Balance Model Based on the Distribution Function Unifying Probability Distributed Model and the SCS Curve Number Method

Water ◽  
2022 ◽  
Vol 14 (2) ◽  
pp. 143
Author(s):  
Marwan Kheimi ◽  
Shokry M. Abdelaziz
Keyword(s):  
Distribution Function ◽  
Water Balance ◽  
Soil Water ◽  
Storage Tank ◽  
Water Storage ◽  
Curve Number ◽  
Water Balance Model ◽  
Balance Model ◽  
Soil Water Storage ◽  
Daily Water

A new daily water balance model is developed and tested in this paper. The new model has a similar model structure to the existing probability distributed rainfall runoff models (PDM), such as HyMOD. However, the model utilizes a new distribution function for soil water storage capacity, which leads to the SCS (Soil Conservation Service) curve number (CN) method when the initial soil water storage is set to zero. Therefore, the developed model is a unification of the PDM and CN methods and is called the PDM–CN model in this paper. Besides runoff modeling, the calculation of daily evaporation in the model is also dependent on the distribution function, since the spatial variability of soil water storage affects the catchment-scale evaporation. The generated runoff is partitioned into direct runoff and groundwater recharge, which are then routed through quick and slow storage tanks, respectively. Total discharge is the summation of quick flow from the quick storage tank and base flow from the slow storage tank. The new model with 5 parameters is applied to 92 catchments for simulating daily streamflow and evaporation and compared with AWMB, SACRAMENTO, and SIMHYD models. The performance of the model is slightly better than HyMOD but is not better compared with the 14-parameter model (SACRAMENTO) in the calibration, and does not perform as well in the validation period as the 7-parameter model (SIMHYD) in some areas, based on the NSE values. The linkage between the PDM–CN model and long-term water balance model is also presented, and a two-parameter mean annual water balance equation is derived from the proposed PDM–CN model.

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.

A performance assessment method for SAR satellite-derived surface soil moisture data using a soil-water balance model, meteorological observations, and soil pedotransfer functions.

2020 ◽  
Author(s):  
John Beale ◽  
Toby Waine ◽  
Ronald Corstanje ◽  
Jonathan Evans
Keyword(s):  
Regression Analysis ◽  
Soil Moisture ◽  
Water Balance ◽  
Surface Soil ◽  
Cosmic Ray ◽  
Water Balance Model ◽  
Balance Model ◽  
Model Parameters ◽  
Surface Soil Moisture

<p>The validation of surface soil moisture products derived from SAR satellites data is challenged by the difficulty of reliably measuring in-situ soil moisture at shallow soil depths of a few centimetres, consistent with the penetration depth of the microwave beam. Our analysis shows that the apparent accuracy of the remote sensing products is underestimated by comparison with inconsistent probe data or measurements at greater soil depths. Our alternative approach uses in-situ meteorological measurements to determine rainfall and potential evapotranspiration, to be used with soil hydrological properties as inputs to a water balance model to estimate surface soil moisture independently of the satellite data. In-situ soil moisture measurements are used to validate and refine the model parameters. The choice of appropriate soil hydrological parameters with which to convert remotely sensed surface soil moisture indices to volumetric moisture content is shown to have a significant impact on the bias and offset in the regression analysis. To illustrate this, Copernicus SSM data is analysed by this method for a number of COSMOS-UK soil moisture monitoring sites, showing a significant improvement in the coefficient of determination, bias and offset over regression analysis using in-situ measurements from soil moisture probes or the cosmic ray soil moisture sensor itself. This will benefit users of such products in agriculture, for example, in determining actual soil moisture deficit.</p>

scholarly journals Diagnosis toward predicting mean annual runoff in ungauged basins

2020 ◽  
Author(s):  
Yuan Gao ◽  
Lili Yao ◽  
Ni-Bin Chang ◽  
Dingbao Wang
Keyword(s):  
Soil Water ◽  
Storage Capacity ◽  
Water Storage ◽  
Annual Runoff ◽  
Balance Model ◽  
Soil Water Storage ◽  
Ungauged Basins ◽  
Water Storage Capacity ◽  
Soil Water Storage Capacity ◽  
Soil Storage Capacity

Abstract. The present work diagnoses the prediction in mean annual runoff affected by the uncertainty in estimated distribution of soil water storage capacity. Based on a distribution function, a water balance model for estimating mean annual runoff is developed, in which the effects of climate variability and the distribution of soil water storage capacity are explicitly represented. As such, the two parameters in the model have explicit physical meanings, and relationships between the parameters and controlling factors on mean annual runoff are established. The estimated parameters from the existing data of watershed characteristics are applied to 35 watersheds. The results showed that the model could capture 88.2 % of the actual runoff on average, indicating that the proposed new water balance model is promising for estimating mean annual runoff in ungauged watersheds. The underestimation of runoff is mainly caused by the underestimation of the spatial heterogeneity of soil storage capacity due to neglecting the effect of land surface and bedrock topography. A higher spatial variability of soil storage capacity estimated through the Height Above the Nearest Drainage (HAND) indicated that topography plays a crucial role in determining the actual soil water storage capacity. The performance of mean annual runoff prediction in ungauged basins can be improved by employing better estimation of soil water storage capacity including the effects of soil, topography and bedrock. The purpose of this study is to diagnose the data requirement for predicting mean annual runoff in ungauged basins based on a newly developed process-based model.

scholarly journals Comparison of real evapotranspiration measured by weighing lysimeters with simulations based on the Penman formula and a crop growth model

2013 ◽  
Vol 61 (2) ◽  
pp. 161-172 ◽  
Author(s):  
Martin Wegehenkel ◽  
Horst H. Gerke
Keyword(s):  
Water Balance ◽  
Soil Water ◽  
Growth Model ◽  
Temporal Dynamics ◽  
Water Storage ◽  
Water Balance Model ◽  
Soil Water Balance ◽  
Balance Model ◽  
Soil Water Storage ◽  
Silty Clay

Abstract Although the quantification of real evapotranspiration (ETr) is a prerequisite for an appropriate estimation of the water balance, precision and uncertainty of such a quantification are often unknown. In our study, we tested a combined growth and soil water balance model for analysing the temporal dynamics of ETr. Simulated ETr, soil water storage and drainage rates were compared with those measured by 8 grass-covered weighable lysimeters for a 3-year period (January 1, 1996 to December 31, 1998). For the simulations, a soil water balance model based on the Darcy-equation and a physiological-based growth model for grass cover for the calculation of root water uptake were used. Four lysimeters represented undisturbed sandy soil monoliths and the other four were undisturbed silty-clay soil monoliths. The simulated ETr-rates underestimated the higher ETr-rates observed in the summer periods. For some periods in early and late summer, the results were indicative for oasis effects with lysimeter-measured ETr-rates higher than corresponding calculated rates of potential grass reference evapotranspiration. Despite discrepancies between simulated and observed lysimeter drainage, the simulation quality for ETr and soil water storage was sufficient in terms of the Nash-Sutcliffe index, the modelling efficiency index, and the root mean squared error. The use of a physiological-based growth model improved the ETr estimations significantly.

The more hydrologic info the less uncertainties in monthly runoff prediction: The case study of a semi-arid Mediterranean island

2020 ◽  
Author(s):  
Enrica Perra ◽  
Salvatore Urru ◽  
Roberto Deidda ◽  
Francesco Viola
Keyword(s):  
Water Balance ◽  
Water Storage ◽  
Hydrologic Model ◽  
Water Balance Model ◽  
Balance Model ◽  
Small Scale ◽  
Test Case ◽  
Additional Information ◽  
Grace Data ◽  
Regional Water

<p>Since the Gravity Recovery and Climate Experiment (GRACE) launch in 2002, a global dataset of Earth’s total water storage (TWS) measures is available, providing additional and useful information for global and regional hydrologic models. In this study we demonstrate how this data can be easily integrated with a simple two-parameter regional water balance model also at the small scale (i.e. area < 50’000 km<sup>2</sup>). In particular, we show how the inclusion of additional information reduces the predictive uncertainty of the hydrologic model. As test case, the island of Sardinia (Italy) located in the Mediterranean Sea, with an area of about 24000 Km<sup>2</sup>, is chosen. The water balance model simulates at monthly scale surface and subsurface runoff, actual evapotranspiration fluxes, and terrestrial (surface and ground) water storage of the island during the period 2002–2017. The results show that GRACE data constitutes a reliable dataset for the hydrologic modeling also at the small scale and their integration into the proposed regional water balance model reduces the uncertainties in reconstructing long-term variations of the TWS.</p>

Sign in / Sign up

Export Citation Format

Share Document