scholarly journals Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties

2019 ◽  
Vol 23 (9) ◽  
pp. 3553-3570 ◽  
Author(s):  
John C. Hammond ◽  
Adrian A. Harpold ◽  
Sydney Weiss ◽  
Stephanie K. Kampf
Keyword(s):  
Soil Properties ◽  
Soil Depth ◽  
Annual Runoff ◽  
Deep Drainage ◽  
Deep Soil ◽  
Climate Type ◽  
Event Scale ◽  
Antecedent Moisture ◽  
Physically Based ◽  
Dry Climates

Abstract. Streamflow generation and deep groundwater recharge may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. We developed model experiments using observed climate from mountain regions and artificial climate inputs that convert all precipitation to rain, and then evaluated how climate variability affects partitioning in soils with different hydraulic properties and depths. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. Annual runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer timescales. Soil texture modifies daily wetting and drying patterns but has limited effect on annual water budget partitioning, whereas increases in soil depth lead to lower runoff and greater deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates, whereas the effects of snowpack decline on deep drainage are less consistent. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and highlight the importance of developing strategies to plan for changes in water budgets in areas most at risk for shifts from snow to rain.

scholarly journals Partitioning snowmelt and rainfall in the critical zone: effects of climate type and soil properties

2019 ◽  
Author(s):  
John C. Hammond ◽  
Adrian A. Harpold ◽  
Sydney Weiss ◽  
Stephanie K. Kampf
Keyword(s):  
Soil Properties ◽  
Sierra Nevada ◽  
Soil Texture ◽  
Root Zone ◽  
Soil Depth ◽  
Deep Drainage ◽  
Event Scale ◽  
Streamflow Generation ◽  
Dry Climates ◽  
Annual Scale

Abstract. Streamflow generation and deep groundwater recharge in high elevation and high latitude locations may be vulnerable to loss of snow, making it important to quantify how snowmelt is partitioned between soil storage, deep drainage, evapotranspiration, and runoff. Based on previous findings, we hypothesize that snowmelt produces greater streamflow and deep drainage than rainfall and that this effect is greatest in dry climates. To test this hypothesis we examine how snowmelt and rainfall partitioning vary with climate and soil properties using a physically based variably saturated subsurface flow model, HYDRUS-1D. To represent climate variability we use historical inputs from five SNOTEL sites in each of three mountain regions with humid to semiarid climates: Northern Cascades, Sierra Nevada, and Uinta. Each input scenario is run with three soil profiles of varying hydraulic conductivity, soil texture, and bulk density. We also create artificial input scenarios to test how the concentration of input in time, conversion of snow to rain input, and soil profile depth affect partitioning of input into deep drainage and runoff. Results indicate that event-scale runoff is higher for snowmelt than for rainfall due to higher antecedent moisture and input rates in both wet and dry climates. At the annual scale, surface runoff also increases with snowmelt fraction, whereas deep drainage is not correlated with snowmelt fraction. Deep drainage is less affected by changes from snowmelt to rainfall because it is controlled by deep soil moisture changes over longer time scales. However, extreme scenarios with input highly concentrated in time, such as during melt of a deep snowpack, yield greater deep drainage below the root zone than intermittent input. Soil texture modifies daily wetting and drying patterns but has limited effect on annual scale partitioning of rain and snowmelt, whereas increases in soil depth decrease runoff and increase deep drainage. Overall these results indicate that runoff may be substantially reduced with seasonal snowpack decline in all climates. These mechanisms help explain recent observations of streamflow sensitivity to changing snowpack and emphasize the need to develop strategies to mitigate impacts of reduced streamflow generation in places most at risk for shifts from snow to rain.

scholarly journals Comparison of Drivers of Soil Microbial Communities Developed in Karst Ecosystems with Shallow and Deep Soil Depths

Agronomy ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 173
Author(s):  
Huiling Guan ◽  
Jiangwen Fan ◽  
Haiyan Zhang ◽  
Warwick Harris
Keyword(s):  
Microbial Community ◽  
Microbial Communities ◽  
Soil Depth ◽  
Phospholipid Fatty Acid ◽  
Soil Microbial Communities ◽  
Deep Soil ◽  
Soil System ◽  
Soil Microbial ◽  
Total Soil ◽  
Karst Ecosystems

Soil erosion is prevalent in karst areas, but few studies have compared the differences in the drivers for soil microbial communities among karst ecosystems with different soil depths, and most studies have focused on the local scale. To fill this research gap, we investigated the upper 20 cm soil layers of 10 shallow–soil depth (shallow–SDC, total soil depth less than 100 cm) and 11 deep–soil depth communities (deep–SDC, total soil depth more than 100 cm), covering a broad range of vegetation types, soils, and climates. The microbial community characteristics of both the shallow–SDC and deep–SDC soils were tested by phospholipid fatty acid (PLFAs) analysis, and the key drivers of the microbial communities were illustrated by forward selection and variance partitioning analysis. Our findings demonstrated that more abundant soil nutrients supported higher fungal PLFA in shallow–SDC than in deep–SDC (p < 0.05). Furthermore, stronger correlation between the microbial community and the plant–soil system was found in shallow–SDC: the pure plant effect explained the 43.2% of variance in microbial biomass and 57.8% of the variance in the ratio of Gram–positive bacteria to Gram–negative bacteria (G+/G−), and the ratio of fungi to total bacteria (F/B); the pure soil effect accounted for 68.6% variance in the microbial diversity. The ratio of microbial PLFA cyclopropyl to precursors (Cy/Pr) and the ratio of saturated PLFA to monounsaturated PLFA (S/M) as indicators of microbial stress were controlled by pH, but high pH was not conducive to microorganisms in this area. Meanwhile, Cy/Pr in all communities was >0.1, indicating that microorganisms were under environmental stress. Therefore, the further ecological restoration of degraded karst communities is needed to improve their microbial communities.

scholarly journals Earthworms as an Ecological Indicator of Soil Recovery after Mechanized Logging Operations in Mixed Beech Forests

Forests ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Hadi Sohrabi ◽  
Meghdad Jourgholami ◽  
Mohammad Jafari ◽  
Farzam Tavankar ◽  
Rachele Venanzi ◽  
...  
Keyword(s):  
Soil Properties ◽  
Soil Depth ◽  
Biological Properties ◽  
Economic Benefits ◽  
Ecological Indicator ◽  
Traffic Intensity ◽  
Soil Biological Properties ◽  
Density And Biomass ◽  
Soil Recovery ◽  
The Impact

Soil damage caused by logging operations conducted to obtain and maximize economic benefits has been established as having long-term effects on forest soil quality and productivity. However, a comprehensive study of the impact of logging operations on earthworms as a criterion for soil recovery has never been conducted in the Hyrcanian forests of Iran. The aim of this study was to determine the changes in soil biological properties (earthworm density and biomass) and its recovery process under the influence of traffic intensity, slope and soil depth in various intervals according to age after logging operations. Soil properties were compared among abandoned skid trails with different ages (i.e., 3, 10, 20, and 25 years) and an undisturbed area. The results showed that earthworm density and biomass in the high traffic intensity and slope class of 20–30% at the 10–20 cm depth of the soil had the lowest value compared to the other treatments. Twenty-five years after the logging operations, the earthworm density at soil depth of 0–10 and 10–20 cm was 28.4% (0.48 ind. m−2) and 38.6% (0.35 ind. m−2), which were less than those of the undisturbed area, respectively. Meanwhile, the earthworm biomass at a soil depth of 0–10 and 10–20 cm was 30.5% (2.05 mg m−2) and 40.5% (1.54 mg m−2) less than the values of the undisturbed area, respectively. The earthworm density and biomass were positively correlated with total porosity, organic carbon and nitrogen content, while negatively correlated with soil bulk density and C/N ratio. According to the results, 25 years after logging operations, the earthworm density and biomass on the skid trails were recovered, but they were significantly different with the undisturbed area. Therefore, full recovery of soil biological properties (i.e., earthworm density and biomass) takes more than 25 years. The conclusions of our study reveal that the effects of logging operations on soil properties are of great significance, and our understanding of the mechanism of soil change and recovery demand that harvesting operations be extensively and properly implemented.

The effects of replaced topsoil of different depths on the vegetation and soil properties of reclaimed coal mine spoils in an alpine mining area

2019 ◽  
Vol 65 (3-4) ◽  
pp. 92-105
Author(s):  
Xinguang Yang ◽  
Xilai Li ◽  
Mingming Shi ◽  
Liqun Jin ◽  
Huafang Sun
Keyword(s):  
Plant Growth ◽  
Soil Properties ◽  
Coal Mine ◽  
Growth Parameters ◽  
Soil Depth ◽  
Mining Area ◽  
Vegetation Coverage ◽  
Mine Spoils ◽  
Plant Soil ◽  
Different Depths

Replacement of topsoil to an appropriate depth is one of the key methods for ecological restoration. The objective of this study was to investigate the effects of topsoil replacement depth on vegetation and soil properties, and to identify the optimum soil depth for reclamation of coal mine spoils in a cold alpine mining area. We sowed 3 herbaceous species after coal mine spoil heaps were treated with topsoil to 3 depths (0, 20‒25, 40‒45 cm). The variations in vegetation community structure, plant growth, soil properties were measured at different replaced topsoil depths. The correlations between plant and soil properties were analyzed statistically. The results showed species richness, diversity and evenness were not significantly different among different depths of topsoil (P > 0.05). Vegetation coverage, density, height and aboveground biomass increased significantly (P < 0.05) with increasing topsoil depth. Soil properties did not change significantly with increasing topsoil depth (P > 0.05), but soil organic matter was significantly higher at 40‒45 cm topsoil depth than at other two depths (P < 0.05). All soil properties, with the exception of total potassium, were positively correlated with the plant growth parameters. The 40‒45 cm topsoil depth of replacement should be considered as effective method in reclaiming coal mine spoils. The use of both topsoil replacement to a depth of 40‒45 cm and sowing of suitable herbaceous seeds is found to be an effective restoration strategy. Additionally, fertilization might be used as a substitute for artificial topsoil replacement to improve soil quality and speed up revegetation process by the positive plant-soil interactions.

scholarly journals The influence of C<sub>3</sub> and C<sub>4</sub> vegetation on soil organic matter dynamics in contrasting semi-natural tropical ecosystems

2015 ◽  
Vol 12 (16) ◽  
pp. 5041-5059 ◽  
Author(s):  
G. Saiz ◽  
M. Bird ◽  
C. Wurster ◽  
C. A. Quesada ◽  
P. Ascough ◽  
...  
Keyword(s):  
Organic Matter ◽  
Soil Organic Matter ◽  
Soil Depth ◽  
Spatial Scales ◽  
Abiotic Factors ◽  
Carbon Isotopic Composition ◽  
Precipitation Gradient ◽  
Deep Soil ◽  
Tropical Ecosystems ◽  
Carbon Isotopic

Abstract. Variations in the carbon isotopic composition of soil organic matter (SOM) in bulk and fractionated samples were used to assess the influence of C3 and C4 vegetation on SOM dynamics in semi-natural tropical ecosystems sampled along a precipitation gradient in West Africa. Differential patterns in SOM dynamics in C3/C4 mixed ecosystems occurred at various spatial scales. Relative changes in C / N ratios between two contrasting SOM fractions were used to evaluate potential site-scale differences in SOM dynamics between C3- and C4-dominated locations. These differences were strongly controlled by soil texture across the precipitation gradient, with a function driven by bulk δ13C and sand content explaining 0.63 of the observed variability. The variation of δ13C with soil depth indicated a greater accumulation of C3-derived carbon with increasing precipitation, with this trend also being strongly dependant on soil characteristics. The influence of vegetation thickening on SOM dynamics was also assessed in two adjacent, but structurally contrasting, transitional ecosystems occurring on comparable soils to minimise the confounding effects posed by climatic and edaphic factors. Radiocarbon analyses of sand-size aggregates yielded relatively short mean residence times (τ) even in deep soil layers, while the most stable SOM fraction associated with silt and clay exhibited shorter τ in the savanna woodland than in the neighbouring forest stand. These results, together with the vertical variation observed in δ13C values, strongly suggest that both ecosystems are undergoing a rapid transition towards denser closed canopy formations. However, vegetation thickening varied in intensity at each site and exerted contrasting effects on SOM dynamics. This study shows that the interdependence between biotic and abiotic factors ultimately determine whether SOM dynamics of C3- and C4-derived vegetation are at variance in ecosystems where both vegetation types coexist. The results highlight the far-reaching implications that vegetation thickening may have for the stability of deep SOM.

Influence of conservation tillage practices on soil properties and crop yields for maize and wheat cultivation in Beijing, China

Soil Research ◽  
2009 ◽  
Vol 47 (4) ◽  
pp. 362 ◽  
Author(s):  
Xirui Zhang ◽  
Hongwen Li ◽  
Jin He ◽  
Qingjie Wang ◽  
Mohammad H. Golabi
Keyword(s):  
Soil Properties ◽  
Crop Yields ◽  
Conservation Tillage ◽  
Soil Depth ◽  
Chemical Properties ◽  
Conventional Tillage ◽  
Production Costs ◽  
Long Term Effects ◽  
Available N ◽  
Beijing Area

Conservation tillage is becoming increasingly attractive to farmers because it involves lower production costs than does conventional tillage. The long-term effects of sub-soiling tillage (ST), no tillage (NT), and conventional tillage (CT) on soil properties and crop yields were investigated over an 8-year period (2000–07). The study was conducted in a 2-crop-a-year region (Daxing) and a 1-crop-a-year region (Changping) of the Beijing area in China. At 0–0.30 m soil depth, water stability of macro-aggregates (>0.25 mm) was much greater for ST (22.1%) and NT (12.0%) than for CT in Daxing, and the improvements in Changping were 18.9% and 9.5%, respectively. ST and NT significantly (P < 0.05) improved aeration porosity by 14.5% and 10.6%, respectively, at Daxing and by 17.0% and 8.6% at Changping compared with CT treatment. Soil bulk density after 8 years was 0.8–1.5% lower in ST and NT treatments than in CT at both sites. Soil organic matter and available N and P followed the same order ST ≈ NT > CT at both sites. Consequently, crop yields in ST and NT plots were higher than in CT plots due to improved soil physical and chemical properties. Within the conservation tillage treatments, despite similar economic benefit, the effects on crop yields for ST were better than for NT. Mean (2000–07) crop yields for ST were 0.2% and 1.5% higher than for NT at Daxing and Changping, respectively. We therefore conclude that ST is the most suitable conservation tillage practice for annual 2-crop-a-year and 1-crop-a-year regions in the Beijing area.

scholarly journals Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models

2017 ◽  
Author(s):  
Madlene Nussbaum ◽  
Lorenz Walthert ◽  
Marielle Fraefel ◽  
Lucie Greiner ◽  
Andreas Papritz
Keyword(s):  
High Resolution ◽  
Soil Properties ◽  
Agricultural Land ◽  
Model Building ◽  
Soil Depth ◽  
Environmental Data ◽  
Gradient Boosting ◽  
Validation Data ◽  
Large Sets ◽  
Skill Scores

Abstract. High-resolution maps of soil properties are a prerequisite for assessing soil threats and soil functions and to foster sustainable use of soil resources. For many regions in the world precise maps of soil properties are missing, but often sparsely sampled and discontinuous (legacy) soil data are available. Soil property data (response) can then be related by digital soil mapping (DSM) to spatially exhaustive environmental data that describe soil forming factors (covariates) to create spatially continuous maps. With air- and spaceborne remote sensing data and multi-scale terrain analysis large sets of covariates have become common. Building parsimonious models, amenable to pedological interpretation, is then a challenging task. We propose a new boosted geoadditive modelling framework (geoGAM) for DSM. A geoGAM models smooth nonlinear relations between responses and single covariates and combines these model terms additively. Residual spatial autocorrelation is captured by a smooth function of spatial coordinates and nonstationary effects are included by interactions between covariates and smooth spatial functions. The core of fully automated model building for geoGAM is componentwise gradient boosting. We illustrate the application of the geoGAM framework by using soil data from the Canton of Zurich, Switzerland. We modelled effective cation exchange capacity (ECEC) in forest topsoils as continuous response. For agricultural land we predicted the presence of waterlogged horizons in given soil depth layers as binary and drainage classes as ordinal responses. For the latter we used proportional odds geoGAM taking the ordering of the response properly into account. Fitted geoGAM contained only few covariates (7 to 17) selected from large sets (333 covariates for forests, 498 for agricultural land). Model sparsity allowed covariate interpretation by partial effects plots. Prediction intervals were computed by model-based bootstrapping for ECEC. Predictive performance of the fitted geoGAM, tested with independent validation data and specific skill scores (SS) for continuous, binary and ordinal responses, compared well with other studies that modelled similar soil properties. SS of 0.23 up to 0.53 (with SS = 1 for perfect predictions and SS = 0 for zero explained variance) were achieved depending on response and type of score. geoGAM combines efficient model building from large sets of covariates with ease of effect interpretation and therefore likely raises the acceptance of DSM products by end-users.

REDUCTION OF SECONDARY TILLAGE IN MOULDBOARD-PLOUGHED SYSTEMS FOR SILAGE CORN AND SPRING CEREALS IN MEDIUM-TEXTURED SOILS

1990 ◽  
Vol 70 (1) ◽  
pp. 1-9 ◽  
Author(s):  
M. R. CARTER ◽  
R. P. WHITE ◽  
R. G. ANDREW
Keyword(s):  
Soil Properties ◽  
Crop Yield ◽  
Prince Edward Island ◽  
Crop Production ◽  
Sandy Loam ◽  
Soil Depth ◽  
Nutrient Content ◽  
Slight Reduction ◽  
Hordeum Vulgare L ◽  
Spring Cereals

Minimum tillage for soils that require regular cultivation consists of reducing the degree of secondary tillage and number of passes over the field. This study was conducted to determine whether one-pass mouldboard-ploughed systems were suitable for production of silage corn (Zea mays L.) and spring cereals (Hordeum vulgare L., Triticum aestivum L.) on loam to sandy loam soils (Humo-Ferric Podzol and Gray Luvisol) in the perhumid soil climate of Prince Edward Island. The effects of reduction in secondary tillage were gauged by characterizing crop yield and nutrient content, soil properties and structure, and relative economics. Plant growth, crop yield, and nutrient content were similar in all the mouldboard-ploughed systems. Soil chemical properties were not affected by reduction in secondary tillage, but the one-pass plough system did result in a macro-aggregate distribution with a greater proportion of large soil aggregates (9.5–16 mm) and a slight reduction in soil strength over the 10- to 25-cm soil depth. Macroporosity and soil density in the top 8 cm of soil were similar between tillage systems. Reducing both the degree of secondary tillage and number of tillage operations decreased both estimated cultivation costs and time of tillage per hectare by 26 and 39%, respectively. One-pass mouldboard-ploughed systems appear suitable for annual crop production on medium-textured soils under the soil environment of Prince Edward Island. Key words: One-pass tillage, soil properties, crop growth

Global Changes of Köppen-Trewartha Climate Zones Derived from RegCM CORDEX-CORE Simulations

2020 ◽  
Author(s):  
Michal Belda ◽  
Tomáš Halenka
Keyword(s):  
Climate Models ◽  
Added Value ◽  
Temperate Climate ◽  
Global Changes ◽  
Vegetation Zone ◽  
Climate Type ◽  
Temperature And Precipitation ◽  
Driving Model ◽  
Dry Climates ◽  
The Individual

&lt;p&gt;&lt;span&gt;The analysis of climate patterns can be performed for each climatic variable separately or the data can be aggregated using e.g. a kind of climate classification. The advantage of such method, in our case K&amp;#246;ppen-Trewartha classification, is putting together the most important variables, i.e. temperature and precipitation, considering not only annual means, but through monthly values the annual cycle as well. These classifications usually correspond to vegetation distribution in the sense that each climate type is dominated by one vegetation zone or eco-region. Climate classifications represent a convenient tool for the assessment and validation of climate models and for the analysis of simulated future climate changes.&lt;/span&gt;&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;&lt;span&gt;The results of RegCM driven by selected CMIP5 simulations (mostly HadGEM, MPI and NorESM) produced within the CORDEX-CORE experiment over nine CORDEX domains are analysed. Validation based on ERA-Interim driven runs compared to CRU database (E-OBS for higher resolution in Europe) shows reasonable agreement in the Northern hemisphere with a tendency towards wetter and colder climate types in North America. Worse representation in Southern hemisphere is observed, mainly in Australia (lack of desert type). Through the analysis of the control experiments together with the performance of driving GCMs we can assess the sources of the biases in present conditions as well as the added value, which comes mainly from better representation of topography in higher resolution and thus appearance of mountaineous tundra type, as well as better representation of coastal regions and thus separating maritime subtypes. Finally, for two scenarios RCP8.5 and RCP2.6 we show the projections of the individual types&amp;#8216; area changes, mainly decline of boreal and polar types, their shift to the higher latitudes and altitudes, increase of temperate, subtropical and dry climates. Magnitude, &lt;/span&gt;&lt;span&gt;and in some cases (temperate climate) even the sign&lt;/span&gt;&lt;span&gt; of change is largely dependent on the region and driving model.&lt;/span&gt;&lt;/p&gt;

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