scholarly journals Controls on root zone storage capacity in boreal regions

2018 ◽  
Author(s):  
Tanja de Boer-Euser ◽  
Leo-Juhani Meriö ◽  
Hannu Marttila
Keyword(s):  
Land Cover ◽  
Storage Capacity ◽  
Snow Water Equivalent ◽  
Root Zone ◽  
New Method ◽  
Mean Annual Temperature ◽  
Climate Variables ◽  
Potential Evaporation ◽  
Changing Climate ◽  
Vegetation Characteristics

Abstract. The root zone storage capacity (Sr) of the vegetation is an important parameter for the hydrological behaviour of a catchment. Often this Sr is derived from soil and vegetation data, but a new method uses climate data to estimate Sr under the assumption that vegetation adapts its root zone capacity to overcome dry periods. This method also enables to account for the temporal variability of Sr in case of changing climate or land cover. This study applies the new method in 64 catchments in Finland to investigate the controls on Sr in boreal regions. The relations were assessed between climate derived Sr-values and detailed vegetation characteristics (leaf cover, tree length, root biomass), climate variables (precipitation-potential evaporation rate, mean annual temperature, max snow water equivalent, snow-off date) and land cover types. The results show that especially the phase difference between snow-off date and onset of potential evaporation has a large influence on the derived Sr; results even indicate that (non-)coincidence of snow melt and potential evaporation can cause a division between catchments with a high and a low Sr-value. From this study, it can be concluded that the climate derived root zone storage capacity leads to plausible results in boreal areas and that besides from climate variables, catchment vegetation characteristics can also be directly linked to the derived Sr-values. As the climate derived Sr enables incorporating climatic and vegetation conditions in a hydrological parameter, it could be beneficial to assess the effects of changing climate and environmental conditions in boreal regions.

scholarly journals Understanding variability in root zone storage capacity in boreal regions

2019 ◽  
Vol 23 (1) ◽  
pp. 125-138 ◽  
Author(s):  
Tanja de Boer-Euser ◽  
Leo-Juhani Meriö ◽  
Hannu Marttila
Keyword(s):  
Storage Capacity ◽  
Snow Water Equivalent ◽  
Root Zone ◽  
New Method ◽  
Mean Annual Temperature ◽  
Climate Variables ◽  
Potential Evaporation ◽  
Climate Data ◽  
Tree Length ◽  
Vegetation Characteristics

Abstract. The root zone storage capacity (Sr) of vegetation is an important parameter in the hydrological behaviour of a catchment. Traditionally, Sr is derived from soil and vegetation data. However, more recently a new method has been developed that uses climate data to estimate Sr based on the assumption that vegetation adapts its root zone storage capacity to overcome dry periods. This method also enables one to take into account temporal variability of derived Sr values resulting from changes in climate or land cover. The current study applies this new method in 64 catchments in Finland to investigate the reasons for variability in Sr in boreal regions. Relations were assessed between climate-derived Sr values and climate variables (precipitation-potential evaporation rate, mean annual temperature, max snow water equivalent, snow-off date), detailed vegetation characteristics (leaf cover, tree length, root biomass), and vegetation types. The results show that in particular the phase difference between snow-off date and onset of potential evaporation has a large influence on the derived Sr values. Further to this it is found that (non-)coincidence of snow melt and potential evaporation could cause a division between catchments with a high and a low Sr value. It is concluded that the climate-derived root zone storage capacity leads to plausible Sr values in boreal areas and that, apart from climate variables, catchment vegetation characteristics can also be directly linked to the derived Sr values. As the climate-derived Sr enables incorporating climatic and vegetation conditions in a hydrological parameter, it could be beneficial to assess the effects of changing climate and environmental conditions in boreal regions.

Changes in root zone storage capacity and their effects on river discharge and gross primary production

2020 ◽  
Author(s):  
Rodolfo Nóbrega ◽  
David Sandoval ◽  
Colin Prentice
Keyword(s):  
Land Cover ◽  
Primary Production ◽  
Mass Balance ◽  
Land Cover Change ◽  
Storage Capacity ◽  
Root Zone ◽  
Gross Primary Production ◽  
Terrestrial Ecosystem ◽  
Ecosystem Models ◽  
Stress Functions

<p>Root zone storage capacity (R<sub>z</sub>) is a parameter widely used in terrestrial ecosystem models that estimate the amount of soil moisture available for transpiration. However, R<sub>z</sub> is subject to large uncertainty, due to the lack of data on the distribution of soil properties and the depth of plant roots that actively take up water. Our study makes use of a mass-balance approach to investigate R<sub>z</sub> in different ecosystems, and changes in water fluxes caused by land-cover change. The method needs no land-cover or soil information, and uses precipitation (P) and evapotranspiration (ET) time series to estimate the seasonal water deficit. To account for some of the uncertainty in ET, we use different methods for ET estimation, including methods based on satellite estimates, and modelling approaches that back-calculate ET from other ecosystem fluxes. We show that reduced ET due to land-cover change reduces R<sub>z</sub>, which in turn increases baseflow in regions with a strong rainfall seasonality. This finding allows us to analyse the trade-off between gross primary production and hydrological fluxes at river basin scales. We also consider some ideas on how to use mass-balance R<sub>z</sub> in water-stress functions as incorporated in existing terrestrial ecosystem models.</p>

RAT (Robustness Assessment Test): a straightforward evaluation of hydrological model robustness to a changing climate

2021 ◽  
Author(s):  
Vazken Andréassian ◽  
Léonard Santos ◽  
Torben Sonnenborg ◽  
Alban de Lavenne ◽  
Göran Lindström ◽  
...  
Keyword(s):  
Climate Change ◽  
Hydrological Model ◽  
Hydrological Models ◽  
Climate Variables ◽  
Data Set ◽  
Hydrological Characteristics ◽  
Changing Climate ◽  
Split Sample ◽  
Sample Test ◽  
Model Robustness

<p>Hydrological models are increasingly used under evolving climatic conditions. They should thus be evaluated regarding their temporal transferability (application in different time periods) and extrapolation capacity (application beyond the range of known past conditions). In theory, parameters of hydrological models are independent of climate. In practice, however, many published studies based on the Split-Sample Test (Klemeš, 1986), have shown that model performances decrease systematically when it is used out of its calibration period. The RAT test proposed here aims at evaluating model robustness to a changing climate by assessing potential undesirable dependencies of hydrological model performances to climate variables. The test compares, over a long data period, the annual value of several climate variables (temperature, precipitation and aridity index) and the bias of the model over each year. If a significant relation exists between the climatic variable and the bias, the model is not considered to be robust to climate change on the catchment. The test has been compared to the Generalized Split-Sample Test (Coron et al., 2012) and showed similar results.</p><p>Here, we report on a large scale application of the test for three hydrological models with different level of complexity (GR6J, HYPE, MIKE-SHE) on a data set of 352 catchments in Denmark, France and Sweden. The results show that the test behaves differently given the evaluated variable (be temperature, precipitation or aridity) and the hydrological characteristics of each catchment. They also show that, although of different level of complexity, the robustness of the three models is similar on the overall data set. However, they are not robust on the same catchments and, then, are not sensitive to the same hydrological characteristics. This example highlights the applicability of the RAT test regardless of the model set-up and calibration procedure and its ability to provide a first evaluation of the model robustness to climate change.</p><p> </p><p><strong>References</strong></p><p>Coron, L., V. Andréassian, C. Perrin, J. Lerat, J. Vaze, M. Bourqui, and F. Hendrickx, 2012. Crash testing hydrological models in contrasted climate conditions: An experiment on 216 Australian catchments, Water Resour. Res., 48, W05552, doi:10.1029/2011WR011721</p><p>Klemeš, V., 1986. Operational testing of hydrological simulation models, Hydrol. Sci. J., 31, 13–24, doi:10.1080/02626668609491024</p><p> </p>

Measuring and monitoring land cover, land use, and vegetation characteristics

2010 ◽  
Author(s):  
Ned Horning ◽  
Julie A. Robinson ◽  
Eleanor J. Sterling ◽  
Woody Turner ◽  
Sacha Spector
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Deciduous Forest ◽  
Land Cover Classification ◽  
Remotely Sensed ◽  
Land Cover Mapping ◽  
Remotely Sensed Data ◽  
Soil P ◽  
Vegetation Characteristics ◽  
Classification Project

In terrestrial biomes, ecologists and conservation biologists commonly need to understand vegetation characteristics such as structure, primary productivity, and spatial distribution and extent. Fortunately, there are a number of airborne and satellite sensors capable of providing data from which you can derive this information. We will begin this chapter with a discussion on mapping land cover and land use. This is followed by text on monitoring changes in land cover and concludes with a section on vegetation characteristics and how we can measure these using remotely sensed data. We provide a detailed example to illustrate the process of creating a land cover map from remotely sensed data to make management decisions for a protected area. This section provides an overview of land cover classification using remotely sensed data. We will describe different options for conducting land cover classification, including types of imagery, methods and algorithms, and classification schemes. Land cover mapping is not as difficult as it may appear, but you will need to make several decisions, choices, and compromises regarding image selection and analysis methods. Although it is beyond the scope of this chapter to provide details for all situations, after reading it you will be able to better assess your own needs and requirements. You will also learn the steps to carry out a land cover classification project while gaining an appreciation for the image classification process. That said, if you lack experience with land cover mapping, it always wise to seek appropriate training and, if possible, collaborate with someone who has land cover mapping experience (Section 2.3). Although the terms “land cover” and “land use” are sometimes used interchangeably they are different in important ways. Simply put, land cover is what covers the surface of the Earth and land use describes how people use the land (or water). Examples of land cover classes are: water, snow, grassland, deciduous forest, or bare soil.

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.

Effects of geographical and climatic factors on cystic echinococcosis in south-western Iran

2020 ◽  
Vol 94 ◽  
Author(s):  
A. Jamshidi ◽  
A. Haniloo ◽  
A. Fazaeli ◽  
M.A. Ghatee
Keyword(s):  
Land Cover ◽  
Cystic Echinococcosis ◽  
Geographical Information Systems ◽  
Climatic Factors ◽  
Weather Conditions ◽  
Climatic Conditions ◽  
Geographical Information ◽  
Annual Rainfall ◽  
Mean Annual Temperature ◽  
Western Iran

Abstract Cystic echinococcosis (CE) is caused by the larval form of Echinococcus granulosus that can cause serious health and economic problems in the endemic foci. CE is globally distributed in various climatic conditions from circumpolar to tropical latitudes. Iran is an important endemic area with a spectrum of weather conditions. The aim of this study was to determine the effects of geo-climatic factors on the distribution of livestock CE in south-western Iran (SWI) in 2016 to 2018. Data of livestock CE were retrieved from veterinary organizations of four provinces of SWI. The geo-climatic factors, including mean annual temperature (MAT), minimum MAT (MinMAT), maximum MAT (MaxMAT), mean annual rainfall (MAR), elevation, mean annual evaporation (MAE), sunny hours, wind speed, mean annual humidity (MAH), slope, frost days and land cover, were analysed using geographical information systems (GIS) approaches. The statistical analysis showed that MAR, frost days, elevation, slope and semi-condensed forest land cover were positively and MAE, MAT, MaxMAT, MinMAT and salt and salinity land cover were negatively correlated with CE occurrence. MAE was shown to be a predictive factor in the stepwise linear logistic regression model. In short, the current GIS-based study found that areas with lower evaporation were the main CE risk zones, though those with lower temperature and higher rainfall, altitude and slope, especially where covered with or in close proximity of semi-condensed forest, should be prioritized for consideration by health professionals and veterinarians for conducting control programmes in SWI.

Vulnerability of megapodes (Megapodiidae, Aves) to climate change and related threats

2018 ◽  
Vol 45 (4) ◽  
pp. 396-406 ◽  
Author(s):  
PAUL M. RADLEY ◽  
ROBERT A. DAVIS ◽  
RENÉ W.R.J. DEKKER ◽  
SHAUN W. MOLLOY ◽  
DAVID BLAKE ◽  
...  
Keyword(s):  
Climate Change ◽  
Gene Flow ◽  
Life Histories ◽  
Population Level ◽  
Genetic Connectivity ◽  
Future Research ◽  
Mean Annual Temperature ◽  
Climate Variables ◽  
Microbial Decomposition ◽  
Anthropogenic Habitat

SUMMARYAspects of species life histories may increase their susceptibility to climate change. Owing to their exclusive reliance on environmental sources of heat for incubation, megapodes may be especially vulnerable. We employed a trait-based vulnerability assessment to weigh their exposure to projected climate variables of increasing temperatures, fluctuating rainfall and sea level rise and their biological sensitivity and capacity to adapt. While all 21 species were predicted to experience at least a 2 °C increase in mean annual temperature, 12 to experience a moderate or greater fluctuation in rainfall and 16 to experience rising seas, the most vulnerable megapodes are intrinsically rare and range restricted. Species that employ microbial decomposition for incubation may have an adaptive advantage over those that do not and may be more resilient to climate change. The moderate microclimate necessary for mound incubation, however, may in some areas be threatened by anthropogenic habitat loss exacerbated by warmer and seasonally drier conditions. As with many avian species, little is known about the capacity of megapodes to adapt to a changing climate. We therefore recommend that future research efforts investigate megapode fecundity, gene flow and genetic connectivity at the population level to better determine their adaptive capacity.

An assessment of impacts of land-cover changes on root-zone soil moisture

2015 ◽  
Vol 36 (24) ◽  
pp. 6116-6134 ◽  
Author(s):  
Jifu Yin ◽  
Youfei Zheng ◽  
Xiwu Zhan ◽  
Christopher R. Hain ◽  
Qingfei Zhai ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Cover ◽  
Root Zone ◽  
Land Cover Changes
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