Relevance and controls of preferential flow at the landscape scale

Abstract. The spatial and temporal controls of preferential flow (PF) during infiltration are still not fully understood. Soil moisture sensor networks give the possibility to measure infiltration response in high temporal and spatial resolution. Therefore, we used a large-scale sensor network with 135 soil moisture profiles distributed across a complex catchment. The experimental design covers three major geological regions (Slate, Marl, Sandstone) and two land covers (forest, grassland) in Luxembourg. We analyzed the responses of up to 353 rainfall events for every of the 135 soil moisture profiles. Non-sequential responses within the soil moisture depth-profiles were taken as an indication of PF. For sequential responses wetting front velocities were determined from the observations and compared with predictions by capillary flow. A measured wetting front velocity higher than the capillary prediction was also taken as a proxy for PF. We observed the highest fraction of non-sequential response (NSR) in forests on clay-rich soils (Slate, Marl). Furthermore, these two landscape units showed an increase of NSR with lower initial soil water content and higher maximum rainfall intensity. Wetting front velocities ranged from 6 cm day−1 to 80 640 cm day−1 with a median of 113 cm day−1 across all events and landscape units. The soils in the Marl geology had the highest flow velocities, independent of land cover, especially between 30 and 50 cm depth where the clay content increased. For Marl the median water content change was highest for the deepest soil moisture sensor (50 cm), whereas the other two geologies (Slate, Sandstone) showed a decrease of soil moisture change with depth. This confirms that clay content and vegetation strongly influence infiltration and reinforce preferential flow. Capillary-based soil water flow modelling was unable to predict the observed patterns. This demonstrates the danger of treating especially clay soils in the vadose zone as a low-conductivity layer, as the development of soil structure can dominate over the effect of low-conductive texture.

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Soil Moisture Sensor-based Automated Soil Water Content Cycle Classification with a Hybrid Symbolic Aggregate Approximation Algorithm

IEEE Internet of Things Journal ◽

10.1109/jiot.2021.3068379 ◽

2021 ◽

pp. 1-1

Author(s):

Zhongju Wang ◽

Long Wang ◽

Chao Huang ◽

Zijun Zhang ◽

Xiong Luo

Keyword(s):

Soil Moisture ◽

Approximation Algorithm ◽

Water Content ◽

Soil Water ◽

Soil Water Content ◽

Moisture Sensor ◽

Soil Moisture Sensor ◽

Symbolic Aggregate Approximation

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RANCANG BANGUN SISTEM PENYIRAMAN TANAMAN SAYUR BERBASIS ARDUINO DENGAN SENSOR KELEMBABAN TANAH

Jurnal Ilmiah Mahasiswa Kendali dan Listrik ◽

10.33365/jimel.v1i1.186 ◽

2020 ◽

Vol 1 (1) ◽

pp. 23-32

Author(s):

Sampurna Dadi Riskiono ◽

Roy Harry Syidiq Pamungkas ◽

Yudha Arya

Keyword(s):

Soil Moisture ◽

Water Content ◽

Manual Work ◽

Tomato Plants ◽

Moisture Sensor ◽

Final Project ◽

Soil Moisture Sensor ◽

Turn On ◽

System Components ◽

Arduino Uno

Development at this time is increasing, people expect a tool or technology that can help human work, so technology becomes a necessity for humans. This final task is made a device that can do the job of watering tomato plants automatically. This tool aims to replace the manual work becomes automatic. The benefit of this tool is that it can facilitate the work of humans in watering chili plants. This tool uses a soil moisture sensor which acts as a soil moisture detector and sends an order to Arduino Uno to turn on the relay driver so that the wiper motor can splash water according to the needs of the soil automatically. The making of this final project is done by designing, making and implementing system components which include Arduino uno as a controller, driver relay to blow on and off the wiper motor, LCD (Linquit Cristal Display) to display the percentage value of water content

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Spatio-temporal relevance and controls of preferential flow at the landscape scale

Hydrology and Earth System Sciences ◽

10.5194/hess-23-4869-2019 ◽

2019 ◽

Vol 23 (11) ◽

pp. 4869-4889 ◽

Cited By ~ 7

Author(s):

Dominic Demand ◽

Theresa Blume ◽

Markus Weiler

Keyword(s):

Soil Moisture ◽

Land Cover ◽

Preferential Flow ◽

Rainfall Intensity ◽

Capillary Flow ◽

Strong Dependence ◽

Clay Content ◽

Maximum Rainfall ◽

Land Covers ◽

Moisture Profiles

Abstract. The spatial and temporal controls of preferential flow (PF) during infiltration are still not fully understood. As soil moisture sensor networks allow us to capture infiltration responses in high temporal and spatial resolution, our study is based on a large-scale sensor network with 135 soil moisture profiles distributed across a complex catchment. The experimental design covers three major geological regions (slate, marl, sandstone) and two land covers (forest, grassland) in Luxembourg. We analyzed the responses of up to 353 rainfall events for each of the 135 soil moisture profiles. Non-sequential responses (NSRs) within the soil moisture depth profiles were taken as one indication of bypass flow. For sequential responses maximum porewater velocities (vmax⁡) were determined from the observations and compared with velocity estimates of capillary flow. A measured vmax⁡ higher than the capillary prediction was taken as a further indication of PF. While PF was identified as a common process during infiltration, it was also temporally and spatially highly variable. We found a strong dependence of PF on the initial soil water content and the maximum rainfall intensity. Whereas a high rainfall intensity increased PF (NSR, vmax⁡) as expected, most geologies and land covers showed the highest PF under dry initial conditions. Hence, we identified a strong seasonality of both NSR and vmax⁡ dependent on land cover, revealing a lower occurrence of PF during spring and increased occurrence during summer and early autumn, probably due to water repellency. We observed the highest fraction of NSR in forests on clay-rich soils (slate, marl). vmax⁡ ranged from 6 to 80 640 cm d−1 with a median of 120 cm d−1 across all events and soil moisture profiles. The soils in the marl geology had the highest flow velocities, independent of land cover, especially between 30 and 50 cm depth, where the clay content increased. This demonstrates the danger of treating especially clay soils in the vadose zone as a low-conductive substrate, as the development of soil structure can dominate over the matrix property of the texture alone. This confirms that clay content and land cover strongly influence infiltration and reinforce PF, but seasonal dynamics and flow initiation also have an important impact on PF.

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Within-Field Variability in Granular Matrix Sensor Data and its Implications for Irrigation Scheduling

Applied Engineering in Agriculture ◽

10.13031/aea.13918 ◽

2020 ◽

Vol 36 (4) ◽

pp. 437-449

Author(s):

Tsz Him Lo ◽

H C Pringle ◽

Daran R Rudnick ◽

Geng Bai ◽

L Jason Krutz ◽

...

Keyword(s):

Soil Moisture ◽

Soil Water ◽

Irrigation Scheduling ◽

Sensor Data ◽

Moisture Sensor ◽

Soil Moisture Sensor ◽

Soil Water Tension ◽

Granular Matrix ◽

Water Tension ◽

Field Variability

Highlights Within-field variability was larger for individual depths than for the profile average across multiple depths. Distributions of the profile average were approximately normal, with increasing variances as the soil was drying. Probability theory was applied to quantify the effect of sensor set number on irrigation scheduling. The benefit of additional sensors sets may decrease for longer irrigation cycles and for more heterogeneous fields. Abstract. Even when located within the same field, multiple units of the same soil moisture sensor rarely report identical values. Such within-field variability in soil moisture sensor data is caused by natural and manmade spatial heterogeneity and by inconsistencies in sensor construction and installation. To better describe this variability, daily soil water tension values from 14 to 23 sets of granular matrix sensors during the middle part of four soybean site-years in the Mississippi Delta were analyzed. The soil water tension data were found to follow approximately normal distributions, to exhibit moderately high temporal rank stability, and to show strong positive correlation between mean and variance. Based on these observations and the existing literature, a probabilistic conceptual framework was proposed for interpreting within-field variability in granular matrix sensor data. This framework was then applied to investigate the impact of sensor set number (i.e., number of replicates) and irrigation triggering threshold on the scheduling of single-day and multi-day irrigation cycles. If a producer’s primary goal of irrigation scheduling is to keep soil water adequate in a particular fraction of land on average, the potential benefit from increasing sensor set number may be smaller than traditionally expected. Improvement, expansion, and validation of this probabilistic framework are welcomed for developing a practical and robust approach to selecting the sensor set number and the irrigation triggering threshold for diverse soil moisture sensor types in diverse contexts. Keywords: Irrigation scheduling, Probability, Sensors, Soil moisture, Soil water tension, Variability, Watermark.

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PROTOTIPE APLIKASI PENYIRAMAN TANAMAN MENGGUNAKAN SENSOR KELEMBABAN TANAH BERBASIS MICRO CONTOLLER ATMEGA 328

Journal CERITA ◽

10.33050/cerita.v5i1.235 ◽

2019 ◽

Vol 5 (1) ◽

pp. 97-106

Author(s):

Rudi Budi Agung ◽

Muhammad Nur ◽

Didi Sukayadi

Keyword(s):

Soil Moisture ◽

Growth And Development ◽

Large Scale ◽

Simple Method ◽

Moisture Sensor ◽

Sensor Development ◽

Soil Moisture Sensor ◽

Application Systems ◽

Harvesting Systems ◽

Working Principle

The Indonesian country which is famous for its tropical climate has now experienced a shift in two seasons (dry season and rainy season). This has an impact on cropping and harvesting systems among farmers. In large scale this is very influential considering that farmers in Indonesia are stilldependent on rainfall which results in soil moisture. Some types of plants that are very dependent on soil moisture will greatly require rainfall or water for growth and development. Through this research, researchers tried to make a prototype application for watering plants using ATMEGA328 microcontroller based soil moisture sensor. Development of application systems using the prototype method as a simple method which is the first step and can be developed again for large scale. The working principle of this prototype is simply that when soil moisture reaches a certainthreshold (above 56%) then the system will work by activating the watering system, if it is below 56% the system does not work or in other words soil moisture is considered sufficient for certain plant needs.

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