scholarly journals Comparison of soil moisture indices and field measurements in hilly agricultural lands of SW Hungary

2021 ◽  
Vol 15 (1) ◽  
pp. 50-57
Author(s):  
Gábor Nagy ◽  
Dénes Lóczy ◽  
Szabolcs Czigány ◽  
Mauro Hrvatin ◽  
Rok Ciglič
Keyword(s):  
Soil Moisture ◽  
Vadose Zone ◽  
Surface Runoff ◽  
Agricultural Land ◽  
Field Measurements ◽  
Land Use Types ◽  
Remote Sensing Techniques ◽  
Moisture Conditions ◽  
Agricultural Areas ◽  
Moisture Dynamics

The retention of surface runoff and the preservation of soil moisture are among the most important water-related ecosystem services. In addition to field monitoring, advanced remote sensing techniques have been devised to reveal soil moisture dynamics on agricultural land. In our study we compare two soil moisture indices, TWI and SAVI, in three agricultural areas with different land use types. The SAVI has been found suitable to point out spatial variation on the moisture conditions of the vadose zone.

scholarly journals Multitemporal Soil Moisture Retrieval over Bare Agricultural Areas by Means of Alpha Model with Multisensor SAR Data

2018 ◽  
Vol 2018 ◽  
pp. 1-17 ◽  
Author(s):  
Xiang Zhang ◽  
Xinming Tang ◽  
Xiaoming Gao ◽  
Hui Zhao
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Root Mean Square Error ◽  
Field Measurements ◽  
Mean Square ◽  
Approximation Model ◽  
Unknown Parameters ◽  
Sar Data ◽  
Agricultural Areas ◽  
Moisture Estimation

The objective of this research is to optimize the Alpha approximation model for soil moisture retrieval using multitemporal SAR data. The Alpha model requires prior knowledge of soil moisture range to constrain soil moisture estimation. The solution of the Alpha model is an undetermined problem due to the fact that the number of observation equations is less than the number of unknown parameters. This research primarily focused on the optimization of Alpha model by employing multisensor and multitemporal SAR data. The disadvantage of the Alpha model can be eliminated by the combination of multisensor SAR data. The optimized Alpha model was evaluated on the basis of a comprehensive campaign for soil moisture retrieval, which acquired multisensor time series SAR data and coincident field measurements. The agreement between the estimated and measured soil moisture was within a root mean square error of 0.08 cm3/cm3 for both methods. The optimized Alpha model shows an obvious improvement for soil moisture retrieval. The results demonstrated that multisensor and multitemporal SAR data are favorable for time series soil moisture retrieval over bare agricultural areas.

scholarly journals Hydraulic Shortcuts Increase the Connectivity of Arable Land Areas to Surface Waters

2020 ◽  
Author(s):  
Urs Schönenberger ◽  
Christian Stamm
Keyword(s):  
Surface Waters ◽  
Surface Runoff ◽  
Agricultural Land ◽  
Arable Land ◽  
National Level ◽  
Aerial Images ◽  
Major Pathway ◽  
Pesticide Transport ◽  
Storm Drainage ◽  
Agricultural Areas

Abstract. Surface runoff represents a major pathway for pesticide transport from agricultural areas to surface waters. The influence of man-made structures (e.g. roads, hedges, ditches) on surface runoff connectivity has been shown in various studies. In Switzerland, so-called hydraulic shortcuts (e.g. inlets and maintenance manholes of road or field storm drainage systems) have been shown to influence surface runoff connectivity and related pesticide transport. Their occurrence, and their influence on surface runoff and pesticide connectivity have however not been studied systematically. To address that deficit, we randomly selected 20 study areas (average size = 3.5 km2) throughout the Swiss plateau, representing arable cropping systems. We assessed shortcut occurrence in these study areas using three mapping methods: field mapping, drainage plans, and high-resolution aerial images. Surface runoff connectivity in the study areas was analysed using a 2 × 2 m digital elevation model and a multiple-flow algorithm. Parameter uncertainty affecting this analysis was addressed by a Monte Carlo simulation. With our approach, agricultural areas were divided into areas that are either directly connected to surface waters, indirectly (i.e. via hydraulic shortcuts), or not connected at all. Finally, the results of this connectivity analysis were scaled up to the national level using a regression model based on topographic descriptors. Inlets of the road storm drainage system were identified as the main shortcuts. On average, we found 0.84 inlets and a total of 2.0 manholes per hectare of agricultural land. In the study catchments between 43 and 74 % of the agricultural area is connected to surface waters via hydraulic shortcuts. On the national level, this fraction is similar (54 %). These numbers suggest that transport through hydraulic shortcuts is an important pesticide flow path in a landscape where many engineered structures exist to drain excess water from fields and roads. However, this transport process is currently not considered in Swiss pesticide legislation and authorisation. Therefore, current regulations may fall short to address the full extent of the pesticide problem. Overall, the findings highlight the relevance of better understanding the connectivity between fields and receiving waters and the underlying factors and physical structures in the landscape.

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>

scholarly journals A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals

2009 ◽  
Vol 13 (1) ◽  
pp. 1-16 ◽  
Author(s):  
W. T. Crow ◽  
D. Ryu
Keyword(s):  
Soil Moisture ◽  
Data Assimilation ◽  
Surface Runoff ◽  
Surface Soil ◽  
Remotely Sensed ◽  
Hydrologic Model ◽  
Surface Soil Moisture ◽  
Antecedent Soil Moisture ◽  
Runoff Prediction ◽  
Moisture Conditions

Abstract. A number of recent studies have focused on enhancing runoff prediction via the assimilation of remotely-sensed surface soil moisture retrievals into a hydrologic model. The majority of these approaches have viewed the problem from purely a state or parameter estimation perspective in which remotely-sensed soil moisture estimates are assimilated to improve the characterization of pre-storm soil moisture conditions in a hydrologic model, and consequently, its simulation of runoff response to subsequent rainfall. However, recent work has demonstrated that soil moisture retrievals can also be used to filter errors present in satellite-based rainfall accumulation products. This result implies that soil moisture retrievals have potential benefit for characterizing both antecedent moisture conditions (required to estimate sub-surface flow intensities and subsequent surface runoff efficiencies) and storm-scale rainfall totals (required to estimate the total surface runoff volume). In response, this work presents a new sequential data assimilation system that exploits remotely-sensed surface soil moisture retrievals to simultaneously improve estimates of both pre-storm soil moisture conditions and storm-scale rainfall accumulations. Preliminary testing of the system, via a synthetic twin data assimilation experiment based on the Sacramento hydrologic model and data collected from the Model Parameterization Experiment, suggests that the new approach is more efficient at improving stream flow predictions than data assimilation techniques focusing solely on the constraint of antecedent soil moisture conditions.

scholarly journals Interplays between State and Flux Hydrological Variables across Vadose Zones: A Numerical Investigation

Water ◽  
2019 ◽  
Vol 11 (6) ◽  
pp. 1295 ◽  
Author(s):  
Wang ◽  
Wang ◽  
Zhang
Keyword(s):  
Soil Moisture ◽  
Vadose Zone ◽  
Hydraulic Properties ◽  
Climatic Conditions ◽  
Zone Model ◽  
Residual Soil ◽  
Soil Hydraulic Properties ◽  
Soil Hydraulic ◽  
Moisture Conditions ◽  
Hydrological Variables

Knowledge of both state (e.g., soil moisture) and flux (e.g., actual evapotranspiration (ETa) and groundwater recharge (GR)) hydrological variables across vadose zones is critical for understanding ecohydrological and land-surface processes. In this study, a one-dimensional process-based vadose zone model with generated soil hydraulic parameters was utilized to simulate soil moisture, ETa, and GR. Daily hydrometeorological data were obtained from different climate zones to drive the vadose zone model. On the basis of the field phenomenon of soil moisture temporal stability, reasonable soil moisture spatiotemporal structures were reproduced from the model. The modeling results further showed that the dependence of ETa and GR on soil hydraulic properties varied considerably with climatic conditions. In particular, the controls of soil hydraulic properties on ETa and GR greatly weakened at the site with an arid climate. In contrast, the distribution of mean relative difference (MRD) of soil moisture was still significantly correlated with soil hydraulic properties (most notably residual soil moisture content) under arid climatic conditions. As such, the correlations of MRD with ETa and GR differed across different climate regimes. In addition, the simulation results revealed that samples with average moisture conditions did not necessarily produce average values of ETa and GR (and vice versa), especially under wet climatic conditions. The loose connection between average state and flux hydrological variables across vadose zones is partly because of the high non-linearity of subsurface processes, which leads to the complex interactions of soil moisture, ETa, and GR with soil hydraulic properties. This study underscores the importance of using soil moisture information from multiple sites for inferring areal average values of ETa and GR, even with the knowledge of representative sites that can be used to monitor areal average moisture conditions.

scholarly journals Evaluation of the infiltration capacity of soil in a winter wheat stand during the growing season 2010

2011 ◽  
Vol 59 (6) ◽  
pp. 225-234
Author(s):  
Tomáš Mašíček ◽  
František Toman ◽  
Martina Vičanová ◽  
Věra Hubačíková
Keyword(s):  
Soil Moisture ◽  
Winter Wheat ◽  
Field Measurements ◽  
Growing Season ◽  
Specific Weight ◽  
Infiltration Capacity ◽  
Undisturbed Soil ◽  
Volume Weight ◽  
Basin Irrigation ◽  
Moisture Conditions

The aim of the presented paper was to map the course of infiltration during the growing season of 2010 in a winter wheat stand on a selected locality in the Sazomín cadastral area on the basis of selected hydro-physical properties of soil (specific weight, reduced volume weight, actual soil moisture, absorptivity, retention water capacity, porosity, capillary, semi-capillary and non-capillary pores and aeration) evaluated from the analyses of undisturbed soil samples. In order to assess the infiltration capacity of soil at the U Jasana locality in the season April–October, four surveys were realized always with three measurements within each of the surveys. The measurement of infiltration took place in the form of basin irrigation. To evaluate field measurements of infiltration empirical relations were used, namely Kostiakov equations. The highest cumulative infiltration and speed of infiltration were noted in June at the high actual soil moisture and closed stand. In case of October measurement, effects of agro-technical operations became evident on the slightly lower infiltration capacity of soil as compared to June measurements at nearly identical moisture conditions. The lowest infiltration capacity of soil reaching the same level, namely in spite of different moisture conditions and the stand character (July – full-grown stand, August – stubble-field) was found in July and August.

scholarly journals Impacts of forest cover on surface runoff quality in small catchments

BioResources ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. 7830-7845
Author(s):  
Marek Trenčiansky ◽  
Martina Šterbová ◽  
Jozef Výbošťok ◽  
Martin Lieskovský
Keyword(s):  
Surface Runoff ◽  
Forest Cover ◽  
Agricultural Landscape ◽  
Agricultural Land ◽  
Global Climate ◽  
Chemical Compositions ◽  
Absorption Area ◽  
Agricultural Land Management ◽  
Agricultural Areas ◽  
Runoff Quality

Forest cover influences not only the amount of surface runoff, but also its quality. The concentrations of chemicals in surface runoff differ between forest catchments and non-forest catchments (agricultural areas). The authors investigated the chemical compositions of surface runoff in two small neighboring catchments (forest, non-forest), by analyzing and summarizing data over a period of 26 years from 1986 to 2012. During this period, the stock and absorption area of forest stands increased, air quality improved, the agricultural landscape was partly regenerated, and global climate change became apparent. The authors observed differences in surface runoff between forest- and non-forest catchments. However, these differences were not mainly caused by the influence of the forest cover, but by changes in agricultural land management. Since 2006, agricultural land has been managed without the use of artificial fertilizers, which reduced the contents of pollutants in surface runoff from the non-forest catchment. The existence of the forest as such excludes or noticeably eliminates the use of fertilizers and chemical substances that affect water quality.

scholarly journals Improved curve number selection for runoff prediction

1998 ◽  
Vol 25 (4) ◽  
pp. 728-734 ◽  
Author(s):  
J Perrone ◽  
C A Madramootoo
Keyword(s):  
Soil Moisture ◽  
Surface Runoff ◽  
Peak Flow ◽  
Curve Number ◽  
Precipitation Index ◽  
Scs Curve Number ◽  
Antecedent Moisture ◽  
Antecedent Precipitation ◽  
Moisture Conditions ◽  
Antecedent Precipitation Index

The three antecedent moisture conditions used in the SCS (Soil Conservation Service) curve number method of surface runoff volume prediction have been shown to be inapplicable in humid regions such as the Ottawa - St. Lawrence Lowlands. The antecedent precipitation index is an alternative indicator of soil moisture. Using a hydrologic database, calibration curves were developed to correlate antecedent precipitation index to the SCS curve number. Curve numbers were then input to the AGNPS hydrologic model. When compared to the three antecedent moisture conditions in the SCS curve number method, use of antecedent precipitation index as a soil moisture indicator considerably improved surface runoff volume simulations. However, peak flow was generally overpredicted by the AGNPS model.Key words: AGNPS, antecedent moisture, curve number, peak flow, surface runoff, hydrologic modeling, precipitation.

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