scholarly journals Exploring the role of soil storage capacity for explaining deviations from the Budyko curve using a simple water balance model

2021 ◽  
Author(s):  
Jan Bondy ◽  
Jan Wienhöfer ◽  
Laurent Pfister ◽  
Erwin Zehe

Abstract. The Budyko curve is a widely used framework for predicting the steady-state water balance –solely based on the hydro-climatic setting of river basins. While this framework has been tested and verified across a wide range of climates and settings around the globe, numerous catchments have been reported to considerably deviate from the predicted behavior. Here, we hypothesize that storage capacity and field capacity of the root zone are important controls of the water limitation of evapotranspiration and thus deviations of the mean annual water balance from the Budyko curve. For testing our hypothesis, we selected 16 catchments of different climatic settings and varied the corresponding parameters of a simple water balance model that was previously calibrated against long-term data and investigated the corresponding variations of the simulated water balance in the Budyko space. We found that total soil storage capacity –by controlling water availability and limitation of evapotranspiration– explains deviations of the evaporation ratio (EVR) from the Budyko curve. Similarly, however to a lesser extent, the evaporation ratio showed sensitivity to alterations of the field capacity. In most cases, the parameter variations generated evaporation ratios enveloping the Budyko curve. The distinct soil storage volumes that matched the Budyko curve clustered at a normalized storage capacity equivalent to 5–15 % of mean annual precipitation. The second, capillarity-related soil parameter clustered at around 0.6–0.8, which is in line with its hydropedological interpretation. A simultaneous variation of both parameters provided additional insights into the interrelation of both parameters and their joint control on offsets from the Budyko curve. Here we found three different sensitivity patterns and we conclude the study with a reflection relating these offsets to the concept of catchment coevolution. The results of this study could also be useful to facilitate evaluation of the water balance in data-scarce regions, as they help constrain parameterizations for hydrological models a priori using the Budyko curve as a predictor.

Fire ◽  
2020 ◽  
Vol 3 (2) ◽  
pp. 25
Author(s):  
Eric Miller ◽  
Brenda Wilmore

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.


2018 ◽  
Vol 22 (7) ◽  
pp. 4097-4124 ◽  
Author(s):  
Matthias J. R. Speich ◽  
Heike Lischke ◽  
Massimiliano Zappa

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.


2011 ◽  
Vol 25 (25) ◽  
pp. 3858-3865 ◽  
Author(s):  
T. J. Smith ◽  
J. P. McNamara ◽  
A. N. Flores ◽  
M. M. Gribb ◽  
P. S. Aishlin ◽  
...  

2014 ◽  
Vol 519 ◽  
pp. 1848-1858 ◽  
Author(s):  
Francisco Pellicer-Martínez ◽  
José Miguel Martínez-Paz

2019 ◽  
Vol 35 (9) ◽  
pp. 954-975
Author(s):  
Olutoyin Adeola Fashae ◽  
Rotimi Oluseyi Obateru ◽  
Adeyemi Oludapo Olusola

2015 ◽  
Vol 19 (9) ◽  
pp. 3829-3844 ◽  
Author(s):  
J. Hoogeveen ◽  
J.-M. Faurès ◽  
L. Peiser ◽  
J. Burke ◽  
N. van de Giesen

Abstract. GlobWat is a freely distributed, global soil water balance model that is used by the Food and Agriculture Organization (FAO) to assess water use in irrigated agriculture, the main factor behind scarcity of freshwater in an increasing number of regions. The model is based on spatially distributed high-resolution data sets that are consistent at global level and calibrated against values for internal renewable water resources, as published in AQUASTAT, the FAO's global information system on water and agriculture. Validation of the model is done against mean annual river basin outflows. The water balance is calculated in two steps: first a "vertical" water balance is calculated that includes evaporation from in situ rainfall ("green" water) and incremental evaporation from irrigated crops. In a second stage, a "horizontal" water balance is calculated to determine discharges from river (sub-)basins, taking into account incremental evaporation from irrigation, open water and wetlands ("blue" water). The paper describes the methodology, input and output data, calibration and validation of the model. The model results are finally compared with other global water balance models to assess levels of accuracy and validity.


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