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.

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.

Modelling the Hydrologic Regime of Arid Inland Wetlands: Non-linear Relationship Between Root-uptakes of Water and Underground Water Table

2021 ◽  
Author(s):  
Lin Li ◽  
Hu Liu ◽  
Yang Yu ◽  
Wenzhi Zhao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Soil Moisture ◽  
Water Table ◽  
Land Use Changes ◽  
Northwestern China ◽  
Wetland Ecosystem ◽  
Soil Moisture Dynamics ◽  
Inland Wetlands ◽  
Moisture Dynamics

<p><strong>Abstract: </strong>Wetlands remaining in the arid inland river landscapes of northwestern China suffer degradation and their resilience and ability to continue functioning under hydrologic and land use changes resulting from climate change may be significantly inhibited. Information on the desert-oasis wetlands, however, is sparse and knowledge of how ecological functioning and resilience may change under climate change and water-resource management is still lacking. Research in oasis wetland areas of the Northwestern China identified linkages between subsurface flow, plant transpiration, and water levels. In this study, we present an ecohydrological analysis of the energy and water balance in the wetland ecosystem. A process-based stochastic soil moisture model developed for groundwater-dependent ecosystems was employed to modelling the interactions between rainfall, water table fluctuations, soil moisture dynamics, and vegetation, and to investigate the ecohydrology of arid inland wetlands system. Field measured groundwater levels, vertical soil moisture profiles, soil water potentials, and root biomass allocation and transpiration of pioneer species in the wetlands were used to calibrate and validate the stochastic model. The parameterized model was then running to simulate the probability distributions of soil moisture and root water uptake, and quantitative descript the vegetation–water table–soil moisture interplay in the hypothesized scenarios of future. Our analysis suggested the increasing rates of water extraction and regulation of hydrologic processes, coupled with destruction of natural vegetation, and climate change, are jeopardizing the future persistence of wetlands and the ecological and socio-economic functions they support. To understand how climate change will impact on the ecohydrological functioning of wetlands, both hydrological and land use changes need to be considered in future works.</p><p><strong>Keywords: </strong>Wetland ecosystem, groundwater, soil moisture dynamics, water balances, Heihe River Basin</p>

Performance analysis of regional landslide early warning based on soil moisture simulations

2020 ◽  
Author(s):  
Adrian Wicki ◽  
Manfred Stähli
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Performance Analysis ◽  
Early Warning ◽  
Soil Profile ◽  
Forecast Skill ◽  
Soil Moisture Dynamics ◽  
Landslide Early Warning ◽  
Moisture Dynamics

<p>In mountainous regions, rainfall-triggered landslides pose a serious risk to people and infrastructure, particularly due to the short time interval between activation and failure and their widespread occurrence. Landslide early warning systems (LEWS) have demonstrated to be a valuable tool to inform decision makers about the imminent landslide danger and to move people or goods at risk to safety. While most operational LEWS are based on empirically derived rainfall exceedance thresholds, recent studies have demonstrated an improvement of the forecast quality after the inclusion of in-situ soil moisture measurements.</p><p>The use of in-situ soil moisture sensors bears specific limitations, such as the sensitivity to local conditions, the disturbance of the soil profile during installation, and potential data quality issues and inhomogeneity of long-term measurements. Further, the installation and operation of monitoring networks is laborious and costly. In this respect, making use of modelled soil moisture could efficiently increase information density, and it would further allow to forecast soil moisture dynamics. On the other hand, numerical simulations are restricted by assumptions and simplifications related to the soil hydraulic properties and the water transfer in the soil profile. Ultimately, the question arises how reliable and representative landslide early warnings based on soil moisture simulations are compared to warnings based on measurements.</p><p>To answer this, we applied a state-of-the-art one-dimensional heat and mass transfer model (CoupModel, Jansson 2012) to generate time series of soil water content at 35 sites in Switzerland. The same sites and time period (2008-2018) were used in a previous study to compare the temporal variability of in-situ measured soil moisture to the regional landslide activity (currently under review in <em>Landslides</em>). The same statistical framework for soil moisture dynamics analysis, landslide probability modelling and landslide early warning performance analysis was applied to the modelled and the measured soil moisture time series. This allowed to directly compare the forecast skill of modelling-based with measurements-based landslide early warning.</p><p>In this contribution, we will highlight three steps of model applications: First, a straight-forward simulation to all 35 sites without site-specific calibration and using reference soil layering only, to assess the forecast skill as if no prior measurements were available. Second, a model simulation after calibration at each site using the existing soil moisture time series and information on the soil texture to assess the benefit of a thorough calibration process on the forecast skill. Finally, an application of the model to additional sites in Switzerland where no soil moisture measurements are available to assess the effect of increasing the soil moisture information density on the overall forecast skill.</p>

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>

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 Event and seasonal hydrologic connectivity patterns in an agricultural headwater catchment

2020 ◽  
Author(s):  
Lovrenc Pavlin ◽  
Borbála Széles ◽  
Peter Strauss ◽  
Alfred Paul Blaschke ◽  
Günter Blöschl
Keyword(s):  
Soil Moisture ◽  
Shallow Groundwater ◽  
Groundwater Table ◽  
Peak Time ◽  
Spatial And Temporal Patterns ◽  
Topographic Wetness Index ◽  
Event Scale ◽  
Soil Moisture Dynamics ◽  
Moisture Dynamics ◽  
Headwater Catchment

Abstract. Connectivity of the hillslope and the stream is a non stationary and non linear phenomenon dependent on many controls. The objective of this study is to identify these controls by examining the spatial and temporal patterns of the similarity between shallow groundwater and soil moisture dynamics and streamflow dynamics in the Hydrological Open Air Laboratory (HOAL), a small (66 ha) agricultural headwater catchment in Lower Austria. We investigate the responses to 53 precipitation events and the seasonal dynamics of streamflow, groundwater and soil moisture over two years. The similarity, in terms of Spearman correlation coefficient, hysteresis index and peak-to-peak time, of groundwater to streamflow shows a clear spatial organisation, which is best correlated to topographic position index, topographic wetness index and depth to the groundwater table. The similarity is greatest in the riparian zone and diminishes further away from the stream where the groundwater table is deeper. Soil moisture dynamics show high similarity to streamflow but no clear spatial pattern. This is reflected in a low correlation of the similarity to site-characteristics, however, the similarity increases with increasing catchment wetness and rainfall duration. Groundwater connectivity to the stream on the seasonal scale is higher than that on the event scale indicating that groundwater contributes more to the baseflow than to event runoff.

scholarly journals On the use of AMSU-based products for the description of soil water content at basin scale

2011 ◽  
Vol 15 (9) ◽  
pp. 2839-2852 ◽  
Author(s):  
S. Manfreda ◽  
T. Lacava ◽  
B. Onorati ◽  
N. Pergola ◽  
M. Di Leo ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Water Content ◽  
Soil Water ◽  
Soil Water Content ◽  
Land Surface ◽  
Skin Surface ◽  
Soil Moisture Dynamics ◽  
Basin Scale ◽  
Moisture Dynamics

Abstract. Characterizing the dynamics of soil moisture fields is a key issue in hydrology, offering a strategy to improve our understanding of complex climate-soil-vegetation interactions. Besides in-situ measurements and hydrological models, soil moisture dynamics can be inferred by analyzing data acquired by sensors on board of airborne and/or satellite platforms. In this work, we investigated the use of the National Oceanic and Atmospheric Administration – Advanced Microwave Sounding Unit-A (NOAA-AMSU-A) radiometer for the remote characterization of soil water content. To this aim, a field measurement campaign, lasted about three months (3 March 2010–18 May 2010), was carried out using a portable time-domain reflectometer (TDR) to get soil water content measures over five different locations within an experimental basin of 32.5 km2, located in the South of Italy. In detail, soil moisture measurements were carried out systematically at the times of satellite overpasses, over two square areas of 400 m2, a triangular area of 200 m2 and two transects of 60 and 170 m, respectively. Each monitored site is characterized by different land covers and soil textures, to account for spatial heterogeneity of land surface. Afterwards, a more extensive comparison (i.e. analyzing a 5 yr data time series) was made using soil moisture simulated by a hydrological model. Measured and modeled soil moisture data were compared with two AMSU-based indices: the Surface Wetness Index (SWI) and the Soil Wetness Variation Index (SWVI). Both time series of indices have been filtered by means of an exponential filter to account for the fact that microwave sensors only provide information at the skin surface. This allowed to understand the ability of each satellite-based index to account for soil moisture dynamics and to understand its performances under different conditions. As a general remark, the comparison shows a higher ability of the filtered SWI to describe the general trend of soil moisture, while the SWVI can capture soil moisture variations with a precision that increases at the higher values of SWVI.

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