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 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.

scholarly journals A signature-based approach to quantify soil moisture dynamics under contrasting land-uses

2021 ◽  
Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan
Keyword(s):  
Land Use ◽  
Time Series ◽  
Soil Moisture ◽  
Shallow Groundwater ◽  
Storm Event ◽  
Land Uses ◽  
Soil Moisture Dynamics ◽  
Land Use Types ◽  
Event Based ◽  
Moisture Dynamics

Soil moisture signatures provide a promising solution to overcome the difficulty of evaluating soil moisture dynamics in hydrologic models. Soil moisture signatures are metrics that represent catchment dynamics extracted from time series of data and enable process-based model evaluations. To date, soil moisture signatures have been tested only under limited land-use types. In this study, we explore soil moisture signatures’ ability to discriminate different dynamics among contrasting land-uses. We applied a set of nine soil moisture signatures to datasets from six in-situ soil moisture networks worldwide. The dataset covers a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, housing areas, grazed areas, and cropland areas. These signatures characterize soil moisture dynamics at three temporal scales: event, seasonal, and time-series scales. Statistical and visual assessment of extracted signatures showed that (1) storm event-based signatures can distinguish different dynamics for most land-uses, (2) season-based signatures are useful to distinguish different dynamics for some types of land-uses (forested vs. deforested area, greenspace vs. housing area, and deep vs. shallow groundwater area), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (forested vs. deforested area, deep vs. shallow groundwater area, non-wetland vs. wetland area, and ungrazed vs. grazed area). We compared signature-based process interpretations against literature knowledge: event-based and time series-based signatures were generally matched well with previous process understandings from literature, but season-based signatures did not. This study demonstrates the best practices of extracting soil moisture signatures under various land-use and climate environments and applying signatures for model evaluations.

Elucidating soil moisture dynamics in agricultural landscapes under varying weather patterns

2021 ◽  
Author(s):  
Veronica Fritz ◽  
Thakshajini Thaasan ◽  
Andrew Williams ◽  
Ranjith Udawatta ◽  
Sidath Mendis ◽  
...  
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Soil Water ◽  
Water Cycle ◽  
Water Storage ◽  
Soil Water Storage ◽  
Storm Events ◽  
Weather Patterns ◽  
Land Use Types ◽  
Moisture Dynamics

<p>Changing weather patterns and anthropogenic land use change significantly alter the terrestrial water cycle. A key variable that modulates the water cycle on the land surface is soil moisture and its variability in time and space. Hydrological models are used to simulate key components of the water cycle including infiltration, soil storage and uptake by plants. However, uncertainties remain in accurately representing soil moisture dynamics in models. Here, with the aid of several sensors installed at a 30-ha experimental research facility, we attempt to quantify differences in soil water storage across multiple land use types – cropped area, mosaic of turf grass and native plants, and an unkept weeded area as control land use. We will also discuss the accuracy of sensors to correctly measure soil water storage. Our study was conducted at an agricultural experimental station in Columbia, Missouri, USA. We use a variety of instruments to measure weather, evapotranspiration, and soil water. We used boundary layer scintillometers to measure near-surface turbulence, sensors to continuously track soil moisture and temperature, as well as weather stations for precipitation, air temperature, solar radiation and wind speed.  Changes in volumetric water content and soil temperature are measured at 5-minute intervals at 10-, 20-, and 40-cm soil depths to compare soil water storage among the three land use types. We also took soil samples before and after several storm events to calibrate the sensor readings at three sites. We, then, analyzed several storm events over a period of five months and compared the actual soil moisture and soil temperature dynamics at finer time intervals. With additional measurements of weather and boundary layer turbulence, we hope to reveal the landscape and weather control on soil moisture distribution across multiple land uses, and their subsequent impact on plant water uptake. Our preliminary results indicate that continuously disturbed agricultural lands depletes soil moisture at faster rates, which may present challenges in maintaining land productivity in the long term.</p>

Unveiling the relationship between land use types and the temporal signals of crime: An empirical decomposition approach

2021 ◽  
pp. 239980832110333
Author(s):  
Chris Brunsdon ◽  
Jonathan Corcoran
Keyword(s):  
Land Use ◽  
Temporal Variations ◽  
Daily Activities ◽  
Land Use Type ◽  
Land Uses ◽  
Temporal Dimension ◽  
Decomposition Approach ◽  
Crime Type ◽  
Land Use Types ◽  
The Relationship

Whilst some land uses are highly criminogenic, others remain largely free of crime. This patterning is a reflection of the types and timing of daily activities that take place in a given land use and the opportunities that this presents for crime. While the criminology literature has developed a rigorous understanding of geographic component of crime, relatively less emphasis has been placed on the temporal dimension. Here, we address this through applying a technique to examine micro-temporal variations in crime at places. This technique adopts a factor approach to model hourly counts of crime across seven land use types (commercial, residential, parkland, agricultural, medical/hospital, industrial and education) to unveil the number and distribution of crime signals across a 24-hour period along with how these signals mix across each land use type. Results reveal clear and distinct differences between crime type and land use, highlighting the diurnal nature of crime patterns and speak to the literature on risky places and risky times. The utility of our approach lies in its capacity to delineate common temporal rhythms and how these rhythms are shared across different land use types.

scholarly journals A Coupled Model for Simulating Water and Heat Transfer in Soil-Plant-Atmosphere Continuum with Crop Growth

Water ◽  
2018 ◽  
Vol 11 (1) ◽  
pp. 47 ◽  
Author(s):  
Weicai Yang ◽  
Xiaomin Mao ◽  
Jian Yang ◽  
Mengmeng Ji ◽  
Adebayo J. Adeloye
Keyword(s):  
Heat Transfer ◽  
Soil Moisture ◽  
Winter Wheat ◽  
Soil Water ◽  
Coupled Model ◽  
Crop Growth ◽  
Soil Water Storage ◽  
Area Index ◽  
Moisture Condition ◽  
Soil Moisture Condition

Crop growth is influenced by the energy partition and water–heat transfer in the soil and canopy, while crop growth affects the land surface energy distribution and soil water-heat dynamics. In order to simulate the above processes and their interactions, a new model, named CropSPAC, was developed considering both the growth of winter wheat and the water–heat transfer in Soil-Plant-Atmosphere Continuum (SPAC). In CropSPAC, the crop module depicts the dynamic changes of leaf area index (LAI), crop height, and the root distribution and outputs them to the SPAC module, while the latter outputs soil moisture conditions for the crop module. CropSPAC was calibrated and validated by field experiment of winter wheat in Yongledian, Beijing, with five levels of irrigation treatments, namely W0 (0 mm), W1 (60 mm), W2 (110 mm), W3 (170 mm), and W4 (230 mm). Results show that CropSPAC could predict the soil water and temperature distribution, and winter wheat growth with acceptable accuracy. For example, for the 0–1 m soil water storage, the R2 for W0, W1, W2, W3, and W4 is 0.90, 0.88, 0.90, 0.91, and 0.79, and the root mean square error (RMSE) is 17.24 mm, 27.65 mm, 20.47 mm, 22.35 mm, and 12.88 mm, respectively. For soil temperature along the soil profile, the R2 ranges between 0.96 and 0.98, and the RMSE between 1.22 °C and 1.94 °C. For LAI, the R2 varied from 0.76 to 0.96, and the RMSE from 0.52 to 0.67. We further compared the simulation results by CropSPAC and its two detached modules, i.e., crop and the SPAC modules. Results demonstrate that the coupled model could better reflect the interactions between crop growth and soil moisture condition, more suitable to be used under deficit irrigation conditions.

scholarly journals Sloping land use affects the complexity of soil moisture and temperature changes in the loess hilly region of China

PLoS ONE ◽  
2022 ◽  
Vol 17 (1) ◽  
pp. e0262445
Author(s):  
Chao Zhang ◽  
Min Tang ◽  
Xiaodong Gao ◽  
Qiang Ling ◽  
Pute Wu
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Soil Temperature ◽  
Soil Depth ◽  
Soil Layer ◽  
Temperature Changes ◽  
Growing Seasons ◽  
Land Use Types ◽  
Hilly Region ◽  
Sloping Land

Various land use types have been implemented by the government in the loess hilly region of China to facilitate sustainable land use. Understanding the variability in soil moisture and temperature under various sloping land use types can aid the ecological restoration and sustainable utilization of sloping land resources. The objective of this study was to use approximate entropy (ApEn) to reveal the variations in soil moisture and temperature under different land use types, because ApEn only requires a short data series to obtain robust estimates, with a strong anti-interference ability. An experiment was conducted with four typical land use scenarios (i.e., soybean sloping field, maize terraced field, jujube orchard, and grassland) over two consecutive plant growing seasons (2014 and 2015), and the time series of soil moisture and temperature within different soil depth layers of each land use type were measured in both seasons. The results showed that the changing amplitude, degree of variation, and active layer of soil moisture in the 0–160 cm soil depth layer, as well as the changing amplitude and degree of variation of soil temperature in the 0–100 cm soil layer increased in the jujube orchard over the two growing seasons. The changing amplitude, degree of variation, and active layer of soil moisture all decreased in the maize terraced field, as did the changing amplitude and degree of variation of soil temperature. The ApEn of the soil moisture series was the lowest in the 0–160 cm soil layer in the maize terraced field, and the ApEn of the soil temperature series was the highest in the 0–100 cm layer in the jujube orchard in the two growing seasons. Finally, the jujube orchard soil moisture and temperature change process were more variable, whereas the changes in the maize terraced field were more stable, with a stable soil moisture and temperature. This work highlights the usefulness of ApEn for revealing soil moisture and temperature changes and to guide the management and development of sloping fields.

scholarly journals Divergent water sources of three dominant plant species following precipitation events in enclosed and mowing grassland steppes

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7737
Author(s):  
Tiejun Bao ◽  
Yunnuan Zheng ◽  
Ze Zhang ◽  
Heyang Sun ◽  
Ran Chao ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Soil Water ◽  
Plant Species ◽  
Water Use ◽  
Soil Layer ◽  
Deep Soil ◽  
Soil Layers ◽  
Typical Steppe ◽  
Dominant Plant Species ◽  
Precipitation Events

Understanding of the dynamic patterns of plant water use in a changing environment is one of foci in plant ecology, and can provide basis for the development of best practice in restoration and protection of ecosystem. We studied the water use sources of three coexisting dominant plant species Leymus chinensis, Stipa grandis and Cleistogenes squarrosa growing in both enclosed and mowing grassland in a typical steppe. The oxygen stable isotope ratios (δ18O) of soil water and stem water of these three species were determined, along with soil moisture, before and after precipitation events. The results showed that (1) mowing had no significant effect on the soil moisture and its δ18O, whereas precipitation significantly changed the soil moisture though no significant effect detected on its δ18O. (2) C. squarrosa took up water majorly from top soil layer due to its shaollow root system; L. chinensis took up relative more water from deep soil layer, and S. grandis took up water from the middle to deep soil layers. (3) L. chinensis and S. grandis in mowing grassland tended to take up more water from the upper soil layers following precipitation events, but showed no sensitive change in water source from soil profile following the precipitation in the enclosed grassland, indicating a more sensitive change of soil water sources for the two species in mowing than enclosed grassland. The differences in root morphology and precipitation distribution may partly explain the differences in their water uptake from different soil layers. Our results have important theoretical values for understanding the water competition among plants in fluctuating environment and under different land use in the typical steppe.

scholarly journals A signature-based approach to quantify soil moisture dynamics under contrasting land-uses

2021 ◽  
Author(s):  
Ryoko Araki ◽  
Flora Branger ◽  
Inge Wiekenkamp ◽  
Hilary McMillan
Keyword(s):  
Land Use ◽  
Soil Moisture ◽  
Urban Areas ◽  
Shallow Groundwater ◽  
Land Uses ◽  
Catchment Scale ◽  
Soil Moisture Dynamics ◽  
Land Use Types ◽  
Event Based ◽  
Moisture Dynamics

Soil moisture signatures provide a promising solution to overcome the difficulty of evaluating soil moisture dynamics in hydrologic models. Soil moisture signatures are metrics that quantify the dynamic aspects of soil moisture timeseries and enable process-based model evaluations. To date, soil moisture signatures have been tested only under limited land-use types. In this study, we explore soil moisture signatures’ ability to discriminate different dynamics among contrasting land-uses. We applied a set of nine soil moisture signatures to datasets from six in-situ soil moisture networks worldwide. The dataset covered a range of land-use types, including forested and deforested areas, shallow groundwater areas, wetlands, urban areas, grazed areas, and cropland areas. Our set of signatures characterized soil moisture dynamics at three temporal scales: event, season, and a complete timeseries. Statistical assessment of extracted signatures showed that (1) event-based signatures can distinguish different dynamics for all the land-uses, (2) season-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, and cropped vs. grazed vs. grassland contrasts), (3) timeseries-based signatures can distinguish different dynamics for some types of land-uses (deforested vs. forested, urban vs. greenspace, shallow vs. deep groundwater, wetland vs. non-wetland, and cropped vs. grazed vs. grassland contrasts). Further, we compared signature-based process interpretations against literature knowledge; event-based and timeseries-based signatures generally matched well with previous process understandings from literature, but season-based signatures did not. This study will be a useful guideline for understanding how catchment-scale soil moisture dynamics in various land-uses can be described using a standardized set of hydrologically relevant metrics.

scholarly journals Multilayer Soil Moisture Mapping at a Regional Scale from Multisource Data via a Machine Learning Method

2019 ◽  
Vol 11 (3) ◽  
pp. 284 ◽  
Author(s):  
Linglin Zeng ◽  
Shun Hu ◽  
Daxiang Xiang ◽  
Xiang Zhang ◽  
Deren Li ◽  
...  
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Regional Scale ◽  
Remotely Sensed ◽  
Temporal Variations ◽  
Training Data ◽  
Estimation Accuracy ◽  
Learning Approaches ◽  
Remotely Sensed Data ◽  
Deep Soil

Soil moisture mapping at a regional scale is commonplace since these data are required in many applications, such as hydrological and agricultural analyses. The use of remotely sensed data for the estimation of deep soil moisture at a regional scale has received far less emphasis. The objective of this study was to map the 500-m, 8-day average and daily soil moisture at different soil depths in Oklahoma from remotely sensed and ground-measured data using the random forest (RF) method, which is one of the machine-learning approaches. In order to investigate the estimation accuracy of the RF method at both a spatial and a temporal scale, two independent soil moisture estimation experiments were conducted using data from 2010 to 2014: a year-to-year experiment (with a root mean square error (RMSE) ranging from 0.038 to 0.050 m3/m3) and a station-to-station experiment (with an RMSE ranging from 0.044 to 0.057 m3/m3). Then, the data requirements, importance factors, and spatial and temporal variations in estimation accuracy were discussed based on the results using the training data selected by iterated random sampling. The highly accurate estimations of both the surface and the deep soil moisture for the study area reveal the potential of RF methods when mapping soil moisture at a regional scale, especially when considering the high heterogeneity of land-cover types and topography in the study area.

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