scholarly journals Soil Moisture Sensor Network Design for Hydrological Applications

2020 ◽  
Author(s):  
Lu Zhuo ◽  
Qiang Dai ◽  
Binru Zhao ◽  
Dawei Han
Keyword(s):  
Soil Moisture ◽  
Network Design ◽  
Wrf Model ◽  
Principal Component ◽  
Optimal Number ◽  
In Situ Observation ◽  
Catchment Scale ◽  
Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Vital State

Abstract. Soil moisture plays an important role in the partitioning of rainfall into evapotranspiration, infiltration and runoff, hence a vital state variable in the hydrological modelling. However, due to the heterogeneity of soil moisture in space most existing in-situ observation networks rarely provide sufficient coverage to capture the catchment-scale soil moisture variations. Clearly, there is a need to develop a systematic approach for soil moisture network design, so that with the minimal number of sensors the catchment spatial soil moisture information could be captured accurately. In this study, a simple and low-data requirement method is proposed. It is based on the Principal Component Analysis (PCA) and Elbow curve for the determination of the optimal number of soil moisture sensors; and K-means Cluster Analysis (CA) and a selection of statistical criteria for the identification of the sensor placements. Furthermore, the long-term (10-year) soil moisture datasets estimated through the advanced Weather Research and Forecasting (WRF) model are used as the network design inputs. In the case of the Emilia Romagna catchment, the results show the proposed network is very efficient in estimating the catchment-scale soil moisture (i.e., with NSE and r at 0.995 and 0.999, respectively for the areal mean estimation; and 0.973 and 0.990, respectively for the areal standard deviation estimation). To retain 90 % variance, a total of 50 sensors in a 22,124 km2 catchment is needed, which in comparison with the original number of WRF grids (828 grids), the designed network requires significantly fewer sensors. However, refinements and investigations are needed to further improve the design scheme which are also discussed in the paper.

Soil Moisture Network Design using Advanced Numerical Weather Prediction modelling and Data Mining technology for Hydrological applications

2020 ◽  
Author(s):  
Lu Zhuo ◽  
Qiang Dai ◽  
Dawei Han
Keyword(s):  
Soil Moisture ◽  
Network Design ◽  
Weather Prediction ◽  
Wrf Model ◽  
Principal Component ◽  
Optimal Number ◽  
In Situ Observation ◽  
Catchment Scale ◽  
Soil Moisture Sensors ◽  
Vital State

<p>Soil moisture plays an important role in the partitioning of rainfall into evapotranspiration, infiltration and runoff, hence a vital state variable in the hydrological modelling. However, due to the heterogeneity of soil moisture in space most existing in-situ observation networks rarely provide sufficient coverage to capture the catchment-scale soil moisture variations. Clearly, there is a need to develop a systematic approach for soil moisture network design, so that with the minimal number of sensors the catchment spatial soil moisture information could be captured accurately. In this study, a simple and low-data requirement method is proposed. It is based on the Principal Component Analysis (PCA) and Elbow curve for the determination of the optimal number of soil moisture sensors; and K-means Cluster Analysis (CA) and a selection of statistical criteria for the identification of the sensor placements. Furthermore, the long-term (10-year) soil moisture datasets estimated through the advanced Weather Research and Forecasting (WRF) model are used as the network design inputs. In the case of the Emilia Romagna catchment, the results show the proposed network is very efficient in estimating the catchment-scale soil moisture (i.e., with NSE and r at 0.995 and 0.999, respectively for the areal mean estimation; and 0.973 and 0.990, respectively for the areal standard deviation estimation). To retain 90% variance, a total of 50 sensors in a 22,124 km<sup>2</sup> catchment is needed, which in comparison with the original number of WRF grids (828 grids), the designed network requires significantly fewer sensors. However, refinements and investigations are needed to further improve the design scheme which are also discussed in the paper.</p>

scholarly journals Soil moisture sensor network design for hydrological applications

2020 ◽  
Vol 24 (5) ◽  
pp. 2577-2591
Author(s):  
Lu Zhuo ◽  
Qiang Dai ◽  
Binru Zhao ◽  
Dawei Han
Keyword(s):  
Soil Moisture ◽  
Network Design ◽  
Surface Soil ◽  
Wrf Model ◽  
Principal Component ◽  
In Situ Observation ◽  
Surface Soil Moisture ◽  
Catchment Scale ◽  
Moisture Sensor ◽  
Vital State

Abstract. Soil moisture plays an important role in the partitioning of rainfall into evapotranspiration, infiltration, and runoff, hence a vital state variable in hydrological modelling. However, due to the heterogeneity of soil moisture in space, most existing in situ observation networks rarely provide sufficient coverage to capture the catchment-scale soil moisture variations. Clearly, there is a need to develop a systematic approach for soil moisture network design, so that with the minimal number of sensors the catchment spatial soil moisture information could be captured accurately. In this study, a simple and low-data requirement method is proposed. It is based on principal component analysis (PCA) for the investigation of the network redundancy degree and K-means cluster analysis (CA) and a selection of statistical criteria for the determination of the optimal sensor number and placements. Furthermore, the long-term (10-year) 5 km surface soil moisture datasets estimated through the advanced Weather Research and Forecasting (WRF) model are used as the network design inputs. In the case of the Emilia-Romagna catchment, the results show the proposed network is very efficient in estimating the catchment-scale surface soil moisture (i.e. with NSE and r at 0.995 and 0.999, respectively, for the areal mean estimation; and 0.973 and 0.990, respectively, for the areal standard deviation estimation). To retain 90 % variance, a total of 50 sensors in a 22 124 km2 catchment is needed, and in comparison with the original number of WRF grids (828 grids), the designed network requires significantly fewer sensors. However, refinements and investigations are needed to further improve the design scheme, which are also discussed in the paper.

scholarly journals Design a Monitoring and Control in Irrigation Systems using Arduino Wemos with the Internet of Things

2021 ◽  
Vol 1 (1) ◽  
pp. 53-64
Author(s):  
Lukman Medriavin Silalahi ◽  
Setiyo Budiyanto ◽  
Freddy Artadima Silaban ◽  
Arif Rahman Hakim
Keyword(s):  
Soil Moisture ◽  
Water Level ◽  
Irrigation System ◽  
Ground Level ◽  
Prototype System ◽  
Monitoring And Control ◽  
Moisture Sensor ◽  
Turn On ◽  
Soil Moisture Sensors ◽  
Level Sensor

Irrigation door is a big issue for farmers. The factor that became a hot issue at the irrigation gate was the irresponsible attitude of the irrigation staff regarding the schedule of opening/closing the irrigation door so that it caused the rice fields to becoming dry or submerged. In this research, an automatic prototype system for irrigation system will be designed based on integrating several sensors, including water level sensors, soil moisture sensors, acidity sensors. This sensor output will be displayed on Android-based applications. The integration of communication between devices (Arduino Nano, Arduino Wemos and sensors supporting the irrigation system) is the working principle of this prototype. This device will control via an Android-based application to turn on / off the water pump, to open/close the irrigation door, check soil moisture, soil acidity in real time. The pump will automatically turn on based on the water level. This condition will be active if the water level is below 3cm above ground level. The output value will be displayed on the Android-based application screen and LCD screen. Based on the results of testing and analysis of the prototype that has been done in this research, the irrigation door will open automatically when the soil is dry. This condition occurs if the water level is less than 3 cm. The calibrated Output value, including acidity sensor, soil moisture sensor and water level sensor, will be sent to the server every 5 seconds and forwarded to an Android-based application as an output display.

scholarly journals RANCANG BANGUN PENYIRAM TANAMAN OTOMATIS MENGGUNAKAN SESOR KELEMBABAN TANAH BERBASIS ARDUINO

2019 ◽  
Vol 11 (02) ◽  
pp. 76-83
Author(s):  
Armanto Armanto
Keyword(s):  
Soil Moisture ◽  
Rainy Season ◽  
Dry Season ◽  
Food Plants ◽  
Crop Failure ◽  
Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Self Sufficiency ◽  
Information And Communication ◽  
Moisture Conditions

Food self-sufficiency is a government program that is currently being actively promoted, so that Indonesia can be independent in providing food by the end of 2019. Indonesia besides being a maritime country is also an agricultural country with fertile land with 2 seasons, namely the rainy season and the dry season. In the rainy season food plants usually do not need to be watered because they have enough rain water. Whereas in the dry season the plants must be watered regularly in accordance with soil moisture conditions. Farmers usually do not grow food in the dry season for fear that it will not grow well and crop failure. Dependence of farmers with the season causes farmer production to decline and becomes an obstacle in the success of the food self-sufficiency program. To overcome the constraints of the dry season and so that farmers can still plant crops in the dry season, we need an information and communication technology-based agricultural tool product in the form of a programmed chip mircrocontroller so that it can control watering plants automatically based on soil moisture that is detected using domestic soil moisture sensors . This tool will detect whether the soil where the planting is dry so that the tool can control watering automatically when the soil lacks the element of water. So farmers do not need to do watering manually. So that plants can continue to flourish even though it is the dry season. In addition to helping farmers this tool can also be installed on plantations, seedbed nurseries, urban parks, hotels, offices, and in homes that have parks or plants that need regular watering.   Keywords— Soil Moisture Sensor, Microcontroller, Arduino

scholarly journals Soil Moisture Sensor-based Systems are Suitable for Monitoring and Controlling Irrigation of Greenhouse Crops

HortScience ◽  
2018 ◽  
Vol 53 (4) ◽  
pp. 552-559 ◽  
Author(s):  
Scott Henderson ◽  
David Gholami ◽  
Youbin Zheng
Keyword(s):  
Soil Moisture ◽  
Crop Production ◽  
Growth Index ◽  
Dry Weight ◽  
Irrigation Systems ◽  
Crop Species ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Microclimate Variation

Sensor-based feedback control irrigation systems have been increasingly explored for greenhouse applications. However, the relationships between microclimate variation, plant water usage, and growth are not well understood. A series of trials were conducted to investigate the microclimate variations in different greenhouses and whether a soil moisture sensor-based system can be used in monitoring and controlling irrigation in greenhouse crop productions. Ocimum basilicum ‘Genovese Gigante’ basil and Campanula portenschlagiana ‘Get Mee’ bellflowers were monitored using soil moisture sensors for an entire crop cycle at two commercial greenhouses. Significant variations in greenhouse microclimates were observed within the two commercial greenhouses and within an older research greenhouse. Evaporation rates were measured and used as an integrated indicator of greenhouse microclimate conditions. Evaporation rates varied within all three greenhouses and were almost double the lowest rates within one of the greenhouses, suggesting microclimates within a range of greenhouses. Although these microclimate variations caused large variations in the growing substrate water contents of containers within the greenhouses, the growth and quality of the plants were unaffected. For example, no significant correlations were observed between the growth of bellflower plants and the average volumetric water content (VWC), minimum VWC, or maximum VWC of the growing substrate. The change in VWC at each irrigation (ΔVWC), however, was positively correlated with the fresh weight, dry weight, and growth index (GI) of the bellflowers. For basil, no significant correlations were observed between plant growth and ΔVWC. This suggests that sensor-based feedback irrigation systems can be used for greenhouse crop production when considerations are given to factors such as the magnitude of microclimate variation, crop species and its sensitivity to water stress, and growing substrate.

scholarly journals Comparison between Capacitive and Microstructured Optical Fiber Soil Moisture Sensors

2018 ◽  
Vol 8 (9) ◽  
pp. 1499 ◽  
Author(s):  
Aitor Lopez Aldaba ◽  
Diego Lopez-Torres ◽  
Miguel Campo-Bescós ◽  
José López ◽  
David Yerro ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Optical Fiber ◽  
Soil Conditions ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Microstructured Optical Fiber ◽  
Fabry Perot ◽  
Local Measurements ◽  
First Time

Soil moisture content has always been an important parameter to control because it is a deterministic factor for site-specific irrigation, seeding, transplanting, and compaction detection. In this work, a discrete sensor that is based on a SnO2–FP (Fabry-Pérot) cavity is presented and characterized in real soil conditions. As far as authors know, it is the first time that a microstructured optical fiber is used for real soil moisture measurements. Its performance is compared with a commercial capacitive soil moisture sensor in two different soil scenarios for two weeks. The optical sensor shows a great agreement with capacitive sensor’s response and gravimetric measurements, as well as a fast and reversible response; moreover, the interrogation technique allows for several sensors to be potentially multiplexed, which offers the possibility of local measurements instead of volumetric: it constitutes a great tool for real soil moisture monitoring.

Smart Irrigation System for Crop Farmers in Namibia

2021 ◽  
pp. 120-131
Author(s):  
Anton Limbo ◽  
Nalina Suresh ◽  
Set-Sakeus Ndakolute ◽  
Valerianus Hashiyana ◽  
Titus Haiduwa ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Irrigation System ◽  
Water Requirements ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Remote Server ◽  
Arduino Microcontroller ◽  
Water Pumps ◽  
Large Farms

Farmers in Namibia currently operate their irrigation systems manually, and this seems to increase labor and regular attention, especially for large farms. With technological advancements, the use of automated irrigation could allow farmers to manage irrigation based on a certain crops' water requirements. This chapter looks at the design and development of a smart irrigation system using IoT. The conceptual design of the system contains monitoring stations placed across the field, equipped with soil moisture sensors and water pumps to maintain the adequate moisture level in the soil for the particular crop being farmed. The design is implemented using an Arduino microcontroller connected to a soil moisture sensor, a relay to control the water pump, as well as a GSM module to send data to a remote server. The remote server is used to represent data on the level of moisture in the soil to the farmers, based on the readings from the monitoring station.

scholarly journals Performance Evaluation of Soil Moisture Sensors in Coarse- and Fine-Textured Michigan Agricultural Soils

Agriculture ◽  
2020 ◽  
Vol 10 (12) ◽  
pp. 598
Author(s):  
Younsuk Dong ◽  
Steve Miller ◽  
Lyndon Kelley
Keyword(s):  
Soil Moisture ◽  
Laboratory Experiment ◽  
Mean Squared Error ◽  
Water Movement ◽  
Field Conditions ◽  
Mean Bias Error ◽  
Bias Error ◽  
Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Correction Equations

Soil moisture content is a critical parameter in understanding the water movement in soil. A soil moisture sensor is a tool that has been widely used for many years to measure soil moisture levels for their ability to provide nondestructive continuous data from multiple depths. The calibration of the sensor is important in the accuracy of the measurement. The factory-based calibration of the soil moisture sensors is generally developed under limited laboratory conditions, which are not always appropriate for field conditions. Thus, calibration and field validation of the soil moisture sensors for specific soils are needed. The laboratory experiment was conducted to evaluate the performance of factory-based calibrated soil moisture sensors. The performance of the soil moisture sensors was evaluated using Root Mean Squared Error (RMSE), Index of Agreement (IA), and Mean Bias Error (MBE). The result shows that the performance of the factory-based calibrated CS616 and EC5 did not meet all the statistical criteria except the CS616 sensor for sand. The correction equations are developed using the laboratory experiment. The validation of correction equations was evaluated in agricultural farmlands. Overall, the correction equations for CS616 and EC5 improved the accuracy in field conditions.

scholarly journals Data-Driven Calibration of Soil Moisture Sensor Considering Impacts of Temperature: A Case Study on FDR Sensors

Sensors ◽  
2019 ◽  
Vol 19 (20) ◽  
pp. 4381 ◽  
Author(s):  
Chen ◽  
Zhangzhong ◽  
Zheng ◽  
Yu ◽  
Wang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Gaussian Process Regression ◽  
Calibration Method ◽  
Multivariate Adaptive Regression Splines ◽  
Data Driven ◽  
Sensor Reading ◽  
Moisture Sensor ◽  
Soil Moisture Sensor ◽  
Soil Moisture Sensors ◽  
Adaptive Regression

Commercial soil moisture sensors have been widely applied into the measurement of soil moisture content. However, the accuracy of such sensors varies due to the employed techniques and working conditions. In this study, the temperature impact on the soil moisture sensor reading was firstly analyzed. Next, a pioneer study on the data-driven calibration of soil moisture sensor was investigated considering the impacts of temperature. Different data-driven models including the multivariate adaptive regression splines and the Gaussian process regression were applied into the development of the calibration method. To verify the efficacy of the proposed methods, tests on four commercial soil moisture sensors were conducted; these sensors belong to the frequency domain reflection (FDR) type. The numerical results demonstrate that the proposed methods can greatly improve the measurement accuracy for the investigated sensors.

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