scholarly journals Analysing the effect of land use and vegetation cover on soil infiltration in three contrasting environments in northeast Spain

2017 ◽  
Vol 43 (1) ◽  
pp. 141 ◽  
Author(s):  
D. Regüés ◽  
D. Badía ◽  
M.T. Echeverría ◽  
M. Gispert ◽  
N. Lana-Renault ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Vegetation Cover ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Joint Analysis ◽  
Soil Infiltration ◽  
Ebro Valley ◽  
Double Ring ◽  
Wide Range

This study presents a joint analysis of the information from 195 field infiltration experiments, using double ring devices. The experiments were carried out in 20 contrasting types of land use, distributed across three geographic contexts (coast of NE Catalonia, low mountains in the central Ebro Valley and mid-height mountains from the southern range of the Central Pyrenees). The objective of this research was to determine the most important factors explaining infiltration variability: land use, type of vegetation cover, soil and bedrock characteristics, soil moisture and altitude. Data analysis was performed by comparing variables using statistical methods: bivariate lineal correlation, ANOVA and Bonferroni multiple comparison tests. Results show that infiltration variability is the most important factor and mainly linked to land use, followed by vegetation type. In contrast, soil moisture did not show any relation with infiltration. The interpretation of these results suggests that the characteristics of the study areas are more decisive than temporal variations of soil water content, although humidity can influence land use to a greater or lesser degree. The validity of the results obtained in this study is supported by the wide range of land use and land cover analysed, located in areas with different geographical and geological characteristics.

scholarly journals An evapotranspiration model self-calibrated from remotely sensed surface soil moisture, land surface temperature and vegetation cover fraction: application to disaggregated SMOS and MODIS data

2019 ◽  
Author(s):  
Bouchra Ait Hssaine ◽  
Olivier Merlin ◽  
Jamal Ezzahar ◽  
Nitu Ojha ◽  
Salah Er-raki ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Energy Balance ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Vegetation Cover ◽  
Land Surface ◽  
Surface Soil ◽  
Surface Soil Moisture ◽  
Wide Range ◽  
The Mean

Abstract. Thermal-based two-source energy balance modeling is very useful for estimating the land evapotranspiration (ET) at a wide range of spatial and temporal scales. However, the land surface temperature (LST) is not sufficient for constraining simultaneously both soil and vegetation flux components in such a way that assumptions (on either the soil or the vegetation fluxes) are commonly required. To avoid such assumptions, a new energy balance model (TSEB-SM) was recently developed in Ait Hssaine et al. (2018a) to integrate the microwave-derived near-surface soil moisture (SM), in addition to the thermal-derived LST and vegetation cover fraction (fc). Whereas, TSEB-SM has been recently tested using in-situ measurements, the objective of this paper is to evaluate the performance of TSEB-SM in real-life using 1 km resolution MODIS (Moderate resolution imaging spectroradiometer) LST and fc data and the 1 km resolution SM data disaggregated from SMOS (Soil Moisture and Ocean Salinity) observations by using DisPATCh. The approach is applied during a four-year period (2014–2018) over a rainfed wheat field in the Tensift basin, central Morocco, during a four-year period (2014–2018). The field was seeded for the 2014–2015 (S1), 2016–2017 (S2) and 2017–2018 (S3) agricultural season, while it was not ploughed (remained as bare soil) during the 2015–2016 (B1) agricultural season. The mean retrieved values of (arss, brss) calculated for the entire study period using satellite data are (7.32, 4.58). The daily calibrated αPT ranges between 0 and 1.38 for both S1 and S2. Its temporal variability is mainly attributed to the rainfall distribution along the agricultural season. For S3, the daily retrieved αPT remains at a mostly constant value (∼ 0.7) throughout the study period, because of the lack of clear sky disaggregated SM and LST observations during this season. Compared to eddy covariance measurements, TSEB driven only by LST and fc data significantly overestimates latent heat fluxes for the four seasons. The overall mean bias values are 119, 94, 128 and 181 W/m2 for S1, S2, S3 and B1 respectively. In contrast, these errors are much reduced when using TSEB-SM (SM and LST combined data) with the mean bias values estimated as 39, 4, 7 and 62 W/m2 for S1, S2, S3 and B1 respectively.

scholarly journals The effect of land uses to change on infiltration capacity and surface runoff at latung sub watershed, Padang City Indonesia

2021 ◽  
Vol 331 ◽  
pp. 08002
Author(s):  
Rusli HAR ◽  
Aprisal ◽  
Werry Darta Taifur ◽  
Teguh Haria Aditia Putra
Keyword(s):  
Land Use ◽  
Surface Runoff ◽  
Land Use Changes ◽  
Curve Number ◽  
Soil Infiltration ◽  
Infiltration Capacity ◽  
Rainwater Infiltration ◽  
Double Ring ◽  
Hydrology Modeling ◽  
Runoff Discharge

Changes in land use in the Air Dingin watershed (DAS) area in Padang City, Indonesia, lead to a decrease in rainwater infiltration volume to the ground. Some land use in the Latung sub-watershed decrease in infiltration capacity with an increase in surface runoff. This research aims to determine the effect of land-use changes on infiltration capacity and surface runoff. Purposive sampling method was used in this research. The infiltration capacity was measured directly in the field using a double-ring infiltrometer, and the data was processed using the Horton model. The obtained capacity was quantitatively classified using infiltration zoning. Meanwhile, the Hydrologic Engineering Center - Hydrology Modeling System with the Synthetic Unit Hydrograph- Soil Conservation Service -Curve Number method was used to analyze the runoff discharge. The results showed that from the 13 measurement points carried out, the infiltration capacity ranges from 0.082 - 0.70 cm/minute or an average of 0.398 cm/minute, while the rainwater volume is approximately 150,000 m3/hour/km2. Therefore, the soil infiltration capacity in the Latung sub-watershed is in zone VI-B or very low. This condition had an impact on changes in runoff discharge in this area, from 87.84 m3/second in 2010 to 112.8 m3/second in 2020 or a nail of 22.13%. Based on the results, it is concluded that changes in the land led to low soil infiltration capacity, thereby leading to an increase in surface runoff.

Infiltration Characteristics of Soil Moisture in Liangping County

2014 ◽  
Vol 641-642 ◽  
pp. 183-186
Author(s):  
Shu Yan ◽  
Juan Gao ◽  
Zhong Yuan Zhang ◽  
Feng Lin Zuo ◽  
Wei Hua Zhang
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Infiltration Rate ◽  
Water Shortage ◽  
Water Infiltration ◽  
Soil Infiltration ◽  
Infiltration Model ◽  
Double Ring ◽  
Soil Water Infiltration ◽  
Relationship Of

In order to relieve water shortage, many countries develop water-saving industries and increase water use rate of irrigation. The research on soil water infiltration has important effect on infiltration and runoff, as well as for irrigation. The study carried out in Liangping district of Chongqing by using double ring infiltration method and exploring the reasonable infiltration model in the study area. The relationship of initial soil moisture and irrigation coefficient was studied as well. The results showed that: the Kostiakov empirical formula could simulate the process of soil water infiltration properly. The soil infiltration rate of Liangping is 0.0320cm/min in the selected location.

scholarly journals P-model v1.0: an optimality-based light use efficiency model for simulating ecosystem gross primary production

2020 ◽  
Vol 13 (3) ◽  
pp. 1545-1581 ◽  
Author(s):  
Benjamin D. Stocker ◽  
Han Wang ◽  
Nicholas G. Smith ◽  
Sandy P. Harrison ◽  
Trevor F. Keenan ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Quantum Yield ◽  
Primary Production ◽  
Vegetation Type ◽  
Meteorological Data ◽  
Gross Primary Production ◽  
Satellite Monitoring ◽  
Light Use Efficiency ◽  
Wide Range ◽  
Use Efficiency

Abstract. Terrestrial photosynthesis is the basis for vegetation growth and drives the land carbon cycle. Accurately simulating gross primary production (GPP, ecosystem-level apparent photosynthesis) is key for satellite monitoring and Earth system model predictions under climate change. While robust models exist for describing leaf-level photosynthesis, predictions diverge due to uncertain photosynthetic traits and parameters which vary on multiple spatial and temporal scales. Here, we describe and evaluate a GPP (photosynthesis per unit ground area) model, the P-model, that combines the Farquhar–von Caemmerer–Berry model for C3 photosynthesis with an optimality principle for the carbon assimilation–transpiration trade-off, and predicts a multi-day average light use efficiency (LUE) for any climate and C3 vegetation type. The model builds on the theory developed in Prentice et al. (2014) and Wang et al. (2017a) and is extended to include low temperature effects on the intrinsic quantum yield and an empirical soil moisture stress factor. The model is forced with site-level data of the fraction of absorbed photosynthetically active radiation (fAPAR) and meteorological data and is evaluated against GPP estimates from a globally distributed network of ecosystem flux measurements. Although the P-model requires relatively few inputs, the R2 for predicted versus observed GPP based on the full model setup is 0.75 (8 d mean, 126 sites) – similar to comparable satellite-data-driven GPP models but without predefined vegetation-type-specific parameters. The R2 is reduced to 0.70 when not accounting for the reduction in quantum yield at low temperatures and effects of low soil moisture on LUE. The R2 for the P-model-predicted LUE is 0.32 (means by site) and 0.48 (means by vegetation type). Applying this model for global-scale simulations yields a total global GPP of 106–122 Pg C yr−1 (mean of 2001–2011), depending on the fAPAR forcing data. The P-model provides a simple but powerful method for predicting – rather than prescribing – light use efficiency and simulating terrestrial photosynthesis across a wide range of conditions. The model is available as an R package (rpmodel).

scholarly journals Analysis of soil moisture condition under different land uses in the arid region of Horqin sandy land, northern China

Solid Earth ◽  
2015 ◽  
Vol 6 (4) ◽  
pp. 1157-1167 ◽  
Author(s):  
C. Y. Niu ◽  
A. Musa ◽  
Y. Liu
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Soil Water ◽  
Soil Layer ◽  
Temporal Variations ◽  
Land Uses ◽  
Deep Soil ◽  
Moisture Condition ◽  
Soil Moisture Condition ◽  
Land Use Types

Abstract. Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff and evapotranspiration, which is important to crop growth and vegetation restoration in semiarid environments, such as Horqin sandy land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil to infiltration under different land use types in semiarid area. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of 2 years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy soils. The higher soil moisture content among different land uses was exhibited by the grassland, followed by cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water at the surface, in the root zone and at the deep soil layer indicated statistical differences for different types of land cover. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in the deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80–120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

scholarly journals Dissolved organic carbon mobilized from organic horizons of mature and harvested black spruce plots in a mesic boreal region

2019 ◽  
Author(s):  
Keri Bowering ◽  
Kate A. Edwards ◽  
Xinbiao Zhu ◽  
Susan E. Ziegler
Keyword(s):  
Soil Moisture ◽  
Organic Carbon ◽  
Dissolved Organic Carbon ◽  
Soil Temperature ◽  
Soil Water ◽  
Temporal Variations ◽  
Forest Harvesting ◽  
Water Fluxes ◽  
Wide Range ◽  
Doc Flux

Abstract. Boreal forests are subject to a wide range of temporally and spatially variable environmental conditions driven by seasonal and regional climate variations, in addition to disturbances such as forest harvesting and climate change. Among the various ecological mechanisms affected by disturbance, is the transport rate of dissolved organic carbon (DOC) from surface soil organic (O) horizons to deeper mineral SOC pools and the adjacent aquatic systems. Here, we examine the transport of DOC from surface O horizons across a boreal forest landscape using passive pan lysimeters in order to identify controls and hot moments of DOC mobilization from this key C source. To do so, we specifically addressed (1) how DOC fluxes from O horizons vary on a weekly to seasonal basis in both forest and harvested plots, and (2) how soil temperature, soil moisture and water inputs relate to DOC fluxes in these plots over time. The total annual DOC flux from O horizons was greater in the warmer harvested plots than in the forest plots (54 g C m−2 vs 38 g C m−2 respectively; p = 0.008), despite smaller aboveground C inputs and smaller SOC stocks in the harvested plots. Water input, measured as rain, throughfall and/or snowmelt depending on season, was positively correlated to temporal variations in soil water and DOC fluxes. Soil temperature was positively correlated to temporal variations of DOC concentration ([DOC]) of soil water and negatively correlated with water fluxes, but no relationship existed between soil temperature and DOC fluxes. Soil moisture was negatively correlated to temporal variations in [DOC] in the harvested plots only. The relationship between water input to soil and DOC fluxes was seasonally dependent in both plot types. In summer, a water limitation on DOC flux existed where weekly periods of no flux alternated with periods of large fluxes, suggesting that increased water fluxes over this period would result in proportional increases in DOC fluxes. In contrast, a flushing of O horizons occurred during increasing water inputs and decreasing soil temperatures in autumn, prior to snowpack development. Soils of both plot types remained snow-covered all winter, which protected soils from frost and limited winter soil water fluxes. The largest water input and soil water fluxes occurred during spring snowmelt, but did not result in the largest fluxes of DOC, suggesting a production limitation on DOC fluxes over both the wet autumn and snowmelt periods. While future increases in annual precipitation could lead to increased DOC fluxes, the response may be dependent on the intra-annual distribution of this increase. Increased water input during the already wet autumn, for instance, may not lead to increased fluxes if the DOC pool is not replenished. Potential reductions in snow cover, however, leading to a reduction in soil insulation and increased occurrence of soil frost in addition to increases in winter-time water fluxes, could be an important mechanism of increased DOC production and fluxes from O horizons in winter.

scholarly journals Soil greenhouse gas emissions under different land-use types in savanna ecosystems of Kenya

2020 ◽  
Vol 17 (8) ◽  
pp. 2149-2167 ◽  
Author(s):  
Sheila Wachiye ◽  
Lutz Merbold ◽  
Timo Vesala ◽  
Janne Rinne ◽  
Matti Räsänen ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Co2 Emissions ◽  
Vegetation Cover ◽  
Ghg Emissions ◽  
N2o Emissions ◽  
Grazing Land ◽  
Soil C ◽  
Land Use Types ◽  
Soil Co2 Emissions

Abstract. Field measurement data on greenhouse gas (GHG) emissions are still scarce for many land-use types in Africa, causing a high level of uncertainty in GHG budgets. To address this gap, we present in situ measurements of carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) emissions from the lowlands of southern Kenya. We conducted eight chamber measurement campaigns on gas exchange from four dominant land-use types (LUTs) comprising (1) cropland, (2) bushland, (3) grazing land, and (4) conservation land between 29 November 2017 and 3 November 2018, accounting for regional seasonality (wet and dry seasons and transitions periods). Mean CO2 emissions for the whole observation period were the highest by a significant margin (p value < 0.05) in the conservation land (75±6 mg CO2-C m−2 h−1) compared to the three other sites, which ranged from 45±4 mg CO2-C m−2 h−1 (bushland) to 50±5 mg CO2-C m−2 h−1 (grazing land). Furthermore, CO2 emissions varied between seasons, with significantly higher emissions in the wet season than the dry season. Mean N2O emissions were highest in cropland (2.7±0.6 µg N2O-N m−2 h−1) and lowest in bushland (1.2±0.4  µg N2O-N m−2 h−1) but did not vary with season. In fact, N2O emissions were very low both in the wet and dry seasons, with slightly elevated values during the early days of the wet seasons in all LUTs. On the other hand, CH4 emissions did not show any significant differences across LUTs and seasons. Most CH4 fluxes were below the limit of detection (LOD, ±0.03 mg CH4-C m−2 h−1). We attributed the difference in soil CO2 emissions between the four sites to soil C content, which differed between the sites and was highest in the conservation land. In addition, CO2 and N2O emissions positively correlated with soil moisture, thus an increase in soil moisture led to an increase in emissions. Furthermore, vegetation cover explained the seasonal variation in soil CO2 emissions as depicted by a strong positive correlation between the normalized difference vegetation index (NDVI) and CO2 emissions, most likely because, with more green (active) vegetation cover, higher CO2 emissions occur due to enhanced root respiration compared to drier periods. Soil temperature did not show a clear correlation with either CO2 or N2O emissions, which is likely due to the low variability in soil temperature between seasons and sites. Based on our results, soil C, active vegetation cover, and soil moisture are key drivers of soil GHG emissions in all the tested LUTs in southern Kenya. Our results are within the range of previous GHG flux measurements from soils from various LUTs in other parts of Kenya and contribute to more accurate baseline GHG emission estimates from Africa, which are key to reducing uncertainties in global GHG budgets as well as for informing policymakers when discussing low-emission development strategies.

Multiple Effects of Topographic Factors on Spatio-temporal Variations of Vegetation Patterns in the Three Parallel Rivers Region, Southeast Tibet

2021 ◽  
Author(s):  
Chunya Wang ◽  
Jinniu Wang ◽  
Niyati Naudiyal ◽  
Ning Wu ◽  
Xia Cui ◽  
...  
Keyword(s):  
River Basin ◽  
Vegetation Cover ◽  
Vegetation Index ◽  
Vegetation Type ◽  
Temporal Variations ◽  
Vegetation Patterns ◽  
Jinsha River ◽  
Modis Ndvi ◽  
Topographic Factors ◽  
Significant Difference

Topographic factors are recognized as one of the key factors influencing vegetation distribution patterns, and studying the interactions between them can contribute to enhancing our understanding of future vegetation dynamics. We used the Moderate-resolution Imaging Spectroradiometer Normalized Differential Vegetation Index (MODIS NDVI) image dataset (2000-2019), combined with Digital Elevation Model (DEM), and vegetation type data for trend analysis, and explored NDVI variation and its relationship with topographic factors through an integrated geographically-weighted model in the Three Parallel Rivers Region (TPRR) of southeastern Tibetan plateau in the past 20 years. Our results indicated that there was no significant increase of NDVI in the entire basin between 2000-2019, except for the Lancang River basin. In the year 2004, abrupt changes in NDVI were observed across the whole basin and each sub-basin. During 2000-2019, the mean NDVI value of the whole basin increased initially and then decreased with the increasing elevation. However, it changed marginally with changes in slope and aspect. We observed a distinct spatial heterogeneity in vegetation patterns with elevation, with vegetation in the southern regions showing higher NDVI than the north as a whole. Most of the vegetation cover was concentrated in the slope range of 8~35&deg;, with no significant difference in distribution except flat-land. Furthermore, from 2000 to 2019, the vegetation cover in the TPRR showed an improving trend with the changes of various topographic factors, with the largest improvement area (36.10%) in the slightly improved category. The improved region was mainly distributed in the source area of the Jinsha River basin and the southern part of the whole basin. Geographically weighted regression (GWR) analysis showed that elevation was negatively correlated with NDVI trends in most areas, especially in the middle reaches of Nujiang River basin and Jinsha River basin, where the influence of slope and aspect on NDVI change was considerably much smaller than elevation.

scholarly journals Analysis of soil moisture condition under different land uses in arid region of Horqin Sandy Land, northern China

2015 ◽  
Vol 7 (3) ◽  
pp. 1979-2009 ◽  
Author(s):  
C. Niu ◽  
A. Musa ◽  
Y. Liu
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Soil Water ◽  
Soil Layer ◽  
Temporal Variations ◽  
Land Uses ◽  
Sandy Land ◽  
Deep Soil ◽  
Moisture Condition ◽  
Soil Moisture Condition

Abstract. Land use plays an important role in controlling spatial and temporal variations of soil moisture by influencing infiltration rates, runoff, and evapotranspiration, which is substantive meaning to crop growth and vegetation restoration in semiarid environments, such as the Horqin Sandy Land in north China. However, few studies have been conducted comparing differences of dynamics of soil water conditions and the responses of soil water to precipitation infiltration under different land use types in this semiarid region. Five different land use types were selected to analyze soil moisture variations in relation to land use patterns during the growing season of two years. Results showed that soil moisture condition was affected by different land uses in semi-arid sandy land. The order of soil moisture (from high to low) among different land uses was grassland, cropland, poplar land, inter-dunes and shrub land. The temporal variations of soil moisture in different land uses were not always consistent with the rainfall due to the dry sequence. Moreover, soil water in surface, root zone and deep soil layer indicated statistical difference for different land covers. Meanwhile, temporal variations of soil moisture profile changed with precipitation. However, in deep soil layer, there was a clear lag in response to precipitation. In addition, seasonal variations of profile soil moisture were classified into two types: increasing and waving types. And the stable soil water layer was at 80–120 cm. Furthermore, the infiltration depth exhibited a positive correlation with precipitation under all land uses. This study provided an insight into the implications for land and agricultural water management in this area.

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