Watermark Sensors Research Articles

Simulated soil water distribution patterns and water use of Alfalfa under different subsurface drip irrigation depths

Alfalfa is one of the major perennial forage crops in California, vital for the livestock industry, and provides environmental benefits to the ecosystem in the state. Information on subsurface drip irrigation (SDI) practices on alfalfa is limited particularly in areas related to drip tape spacings and installation depths and their impacts on topsoil profile wetting patterns and alfalfa productivity. The objective of this study was to compare three different depths of drip lines: 15, 30, and 45 cm on topsoil profile wetting patterns and identify the optimum depth for achieving sustainable management practices for alfalfa production under SDI. Crop water requirements were determined using Tule Technologies system. Volumetric soil water contents from twelve cuts were simulated using HYDRUS-2D. Initial volumetric soil water contents from Watermark sensors were used in the model and measured volumetric soil water distributions were used for hydraulic conductivity calibration. Simulated results showed that there was no significant difference between root water uptake (RWU) among the various drip depths. RWU was 171.6, 170.0, and 168.2 cm at drip line depths of 15, 30, and 45 cm, respectively. Applied irrigation water during the study period was 195.1 cm while rainfall was 4.1 cm. A 10% reduction in topsoil volumetric soil water content was observed for drip lines at 30 cm depth as compared with 15 cm depth, while a 20% reduction in topsoil volumetric soil water content was observed for drip lines at 45 cm depth as compared with 15 cm depth. Drip lines at 30 cm depth are likely the optimal for RWU and free drainage; however, drip lines at 45 cm depth may allow growers to provide additional irrigation events (without increasing the topsoil volumetric soil water content) closer to the harvest date, potentially resulting in higher yield and water use efficiency.

Impact of sensor placement in soil water estimation: a real-case study

One important problem in implementing a closed-loop irrigation system is the determination of the optimal locations to install the sensors, both vertically and horizontally, such that improved pressure head estimation can be obtained. In this work, we find the best locations of the sensors in terms of degree of observability in an actual field and investigate whether the optimal sensor placement can significantly improve the pressure head estimation performance in actual applications. We investigate the impact of sensor placement in pressure head estimation for an actual agricultural field in Lethbridge, Alberta, Canada. In an experiment on the studied field, 42 watermark sensors were installed at different depths to collect the soil water tension measurements. A three-dimensional agro-hydrological model with heterogeneous soil parameters of the studied field is set up. The modal degree of observability is applied to the three-dimensional system to determine the optimal sensor locations. The extended Kalman filter (EKF) is chosen as the data assimilation tool to estimate the pressure head of the studied field. Pressure head estimation results for different scenarios are obtained and analyzed to investigate the effects of sensor placement on the performance of pressure head estimation in the actual applications. Estimation results indicate that optimally placed sensors reduce the average root mean square error by about 30% compared to the case the sensor positions are selected randomly.

Calibration of a granular matrix sensor for suction measurements in partially saturated pyroclastic soil

Field monitoring of soil moisture and matrix suction is a useful tool for the implementation of a reliable early warning system against rainfall-induced landslide occurrence. Several test fields have been set up in Campania region (southern Italy), frequently affected by flow-like landslides involving pyroclastic soil cover. In particular, at the Mount Faito test site (Lattari Mountains, southeast of Naples), field matric suctions were measured over two years by conventional jet-fill tensiometers and granular matrix sensors (Watermark, Irrometer®) at different depths. Granular matrix sensor is a resistive device that is more and more spread in agriculture applications and that may also be used for geotechnical purposes thanks to a suitable calibration. In order to gain the calibration curve of the Watermark sensor, two small tip tensiometers (STT) and one High Capacity Tensiometer (HCT) were installed at the same depth of the Watermark sensor in the partially saturated pyroclastic soil sampled at the topsoil of the Mount Faito test site. Tests were carried out in the laboratory by performing drying and wetting phases on undisturbed soil sample. By coupling resistance measurements by Watermark and matrix suction provided by the reference tensiometers, it was possible to derive the non-linear relationship between these two quantities. The soil retention curve was also determined thanks to the installation in the soil sample of a decagon probe previously calibrated in the same pyroclastic soil.

Selection of [formula omitted]-Caputo derivatives’ functional parameters in generalized water transport equation by genetic programming technique

The paper considers the usage of genetic programming technique to select an analytic form of functional parameter of the ψ-Caputo fractional derivative. We study one-dimensional space–time fractional water transport equation with such derivatives with respect to both time and space variables that generalizes the classical Richards equation. Having water head values measured by Watermark sensors as inputs, the statement of parameters identification problem is performed. The forms of functional parameters are represented as trees and found using a genetic programming algorithm. We compare the accuracy of field data description by the model with fixed and variable forms of derivatives’ functional parameters and obtained up to 30% increase in accuracy for the training dataset and up to 15% increase for the testing dataset when the considered method was used to select parameters’ forms.

A Review on Watermarking using Local Binary Pattern

Local binary patterns are best known because of their robust texture-defining capacities and digital watermarking used to prove multimedia content copyright. This work presents an overview of the binary watermark in the image blocks by changing the pixels conveyed by the LBP pattern of the neighborhood. However, different photo blocks can have the same LBP pattern, which in the watermark process can lead to incorrect detection. In other words, without changing your watermark message, one can change the host image deliberately. Moreover, before watermark embedding, there is no encryption procedure, which leads to another potential security problem. In this paper, we examine the identical process of LBP synthesis or reverse LBP and its suitability for the digital watermarking image. The process of LBP synthesis varies by pixel values so that the LBP from these pixels is the required synthesizable value. Due to the LBP synthesis character, the watermark needs to be integrated with only a few pixels of the given block. The results show that rotational, JPEG compression, and scalable attacks are robust with the technique. This LBP synthesis could also be used to justify ownership using watermark sensor data.

Двовимірне математичне моделювання водного режиму ґрунту за краплинного зрошення

Goal. The objective of the study is to develop a method for predicting the dynamics of soil moisture under drip irrigation based on mathematical modeling by the two-dimensional Richards equation stated in terms of pressure. Methods. The results of the study were obtained by the method of mathematical modeling and verified experimentally. To discretize the Richards equation, a locally one-dimensional finite-difference scheme was used. Systems of linear algebraic equations obtained after the discretization were solved by the Thomas algorithm. To determine the hydrophysical functions of the soil and its constants, a complex of laboratory studies was used. Measurement of suction pressure in the soil was carried out using Watermark sensors. Results. Two empirical coefficients, as well as the parameter of the partitioning of evapotranspiration into the evaporation and transpiration components, are proposed to be added to the mathematical model. Their selection minimizes the impact of evapotranspiration assessment errors and the errors of the determination and modeling of water supply on the overall accuracy of the forecast. The selection of these coefficients is proposed to be carried out by a metaheuristic particle swarm optimization algorithm on the base of measurements within one irrigation cycle. The results of the verification of the proposed methodology on the data obtained growing corn in the production conditions under drip irrigation in the South of Ukraine are presented. In Analyzing the data of mathematical modeling, the average accuracy of modeling volumetric moisture content equal to ~1% was obtained and theoretical expectations regarding the process of transpiration and evaporation from the near-surface soil layers were confirmed. Conclusions. The presented results allow with a controlled discretion to predict the state of soil moisture, in particular, moistened zones, along with its availability to plants, and can be used during the design of drip irrigation systems increasing their efficiency.

Numerical simulation of irrigation scheduling using fractional Richards equation

A method of soil moisture content prediction is presented using fractional differential generalization of one-dimensional Richards equation for the purposes of decision support in irrigation. We propose to use water head dynamics data gathered in the beginning of growth season to perform a calibration of the model by the meta-heuristic particle swarm algorithm. Van Genuchten model is used to describe water retention curve. The cases of the known values of its coefficients along with their identification from water head dynamics data are considered. The paper presents the results of model verification for both classical Richards equation and its fractional differential generalization. For the conditions of sprinkling irrigation in the south of Ukraine, we estimate the accuracy of modelling the water head dynamics measured by the Watermark sensors and the accuracy of seasonal irrigation rate assessment. The obtained results show that the use of water transport model that take soil fractality into consideration has no effect on assessing seasonal irrigation rate but gives up to 7% increase in accuracy while predicting the time and rate of next irrigation application.

Scheduling rice irrigation using soil moisture thresholds for furrow irrigation and intermittent flooding

AbstractAlternative methods of rice (Oryza sativa L.) irrigation are gaining increasing popularity across the U.S. Mid‐South, but an allowable soil moisture deficit stress has not been defined. This study was conducted in 2018 and 2019 to determine the soil moisture threshold for furrow‐irrigated rice (FIR) and alternate wetting and drying (AWD) rice production systems to minimize irrigation water use while maximizing grain and milling yield. Soil moisture thresholds of −15, −30, and −45 kPa, as determined by Watermark sensors at a 10‐cm depth in the top third of the field, were compared with conventional flood rice (CFR) on a Calloway silt loam and a Sharkey clay in eastern Arkansas. Soil moisture threshold had no effect on grain or milling yield across irrigation thresholds; however, the bottom third of FIR, where a flood was held, consistently produced higher grain yield (10,652–10,965 kg ha−1) than the top third (9,442–9,722 kg ha−1). Significant differences in irrigation water use efficiency (IWUE) were achieved under AWD and FIR. The IWUE did not differ across AWD irrigation thresholds but was 58.1–103.8% greater than that of CFR. The −15 and −30 kPa FIR thresholds did not improve IWUE, but using a −45 kPa irrigation threshold resulted in a 42.7% greater IWUE than CFR and 66.0% greater than the −15 kPa threshold. Results suggest that using a −45 kPa irrigation threshold at the 10‐cm depth can potentially maintain grain and milling yield while increasing IWUE under AWD and FIR.

Monitoring of Soil Water Content in Maize Rotated with Pigeonpea Fallows in South Africa

Maize production under smallholder systems in South Africa (RSA) depends on rainfall. Incidences of dry spells throughout the growing season have affected maize yields negatively. The study examined water distribution and water use efficiency (WUE) of maize rotated with two-year pigeonpea fallows as compared to continuous maize without fertilizer. A randomized complete block design, replicated three times, was used with four treatments, which included continuous unfertilized maize, natural fallow-maize, pigeonpea + grass-pigeonpea-maize, and two-year pigeonpea fallow-maize. Soil water mark sensors were installed 0.2; 0.5; and 1.2 m on each plot to monitor soil water tension (kPa). Soil samples were analyzed using pressure plates to determine water retention curves which were used to convert soil water tension to volumetric water content. Maize rotated with two-year pigeonpea fallows had higher dry matter yield (11,661 kg ha−1) and WUE (20.78 kg mm−1) than continuous maize (5314 kg ha−1 and 9.48 kg mm−1). In this era of water scarcity and drought incidences caused by climate change, maize rotated with pigeonpea fallows is recommended among smallholder farmers in RSA because of its higher WUE, hence food security will be guaranteed.

Irrigation Scheduling Based on Wireless Sensors Output and Soil-Water Characteristic Curve in Two Soils.

Data-driven irrigation planning can optimize crop yield and reduce adverse impacts on surface and ground water quality. We evaluated an irrigation scheduling strategy based on soil matric potentials recorded by wireless Watermark (WM) sensors installed in sandy loam and clay loam soils and soil-water characteristic curve data. Five wireless WM nodes (IRROmesh) were installed at each location, where each node consisted of three WM sensors that were installed at 15, 30, and 60 cm depths in the crop rows. Soil moisture contents, at field capacity and permanent wilting points, were determined from soil-water characteristic curves and were approximately 23% and 11% for a sandy loam, and 35% and 17% for a clay loam, respectively. The field capacity level which occurs shortly after an irrigation event was considered the upper point of soil moisture content, and the lower point was the maximum soil water depletion level at 50% of plant available water capacity in the root zone, depending on crop type, root depth, growth stage and soil type. The lower thresholds of soil moisture content to trigger an irrigation event were 17% and 26% in the sandy loam and clay loam soils, respectively. The corresponding soil water potential readings from the WM sensors to initiate irrigation events were approximately 60 kPa and 105 kPa for sandy loam, and clay loam soils, respectively. Watermark sensors can be successfully used for irrigation scheduling by simply setting two levels of moisture content using soil-water characteristic curve data. Further, the wireless system can help farmers and irrigators monitor real-time moisture content in the soil root zone of their crops and determine irrigation scheduling remotely without time consuming, manual data logging and frequent visits to the field.

Comparison of Sensor-Based and Weather-Based Irrigation Scheduling

HighlightsSensor-based irrigation scheduling methods (SBISM) were compared with computerized water balance scheduling.Number and time of irrigation events scheduled using the SBISM were often different from those predicted by the computerized method.The highly variable soils at the Missouri site complicated interpretation of the sensor values.Both SBISM and computerized water balance scheduling could be used for irrigation scheduling with close attention to soil texture and effective rainfall or irrigation.Abstract. Sensor-based irrigation scheduling methods (SBISM) measure soil moisture to allow scheduling of irrigation events based on the soil-water status. With rapid development of soil moisture sensors, more producers have become interested in SBISM, but interpretation of the sensor data is often difficult. Computer-based methods attempt to estimate soil water content and the Arkansas Irrigation Scheduler (AIS) is one example of a weather-based irrigation scheduling tool that has been used in the Mid-South for many years. To aid producers and consultants interested in learning more about irrigation scheduling, field studies were conducted for two years in Mississippi and a year in Missouri to compare SBISM with the AIS. Soil moisture sensors (Decagon GS-1, Acclima TDR-315, Watermark 200SS) were installed in multiple locations of a soybean field (Mississippi) and cotton field (Missouri). Soil water contents of the fields were measured hourly at multiple depths during the growing seasons. The AIS was installed on a computer to estimate soil water content and the required data were obtained from nearby weather stations at both locations and manually entered in the program. In Mississippi, numbers and times of the irrigation events triggered by the SBISM were compared with those that would have been scheduled by the AIS. Results showed the number and time of irrigation events scheduled using the SBISM were often different from those predicted by the AIS, especially during the 2018 growing season. The highly variable soils at the Missouri site complicated the interpretation of the sensor values. While all of the sites were within the Tiptonville silt loam map unit, some of the measurements appeared to come from sandier soils. The AIS assumed more water entered the soil than the sensors indicated from both irrigations and rainfalls less than 25 mm. While the irrigation amounts were based on the pivot sprinkler chart, previous testing had confirmed the accuracy of the charts. Furthermore, the difference varied among sites, especially for rainfall large enough to cause runoff. The recommendations based on the Watermark sensors agreed fairly well with the AIS in July after the data from the sandiest site was omitted; however, the later irrigations called for by the AIS were not indicated by the sensors. Both the sensor-based irrigation scheduling method and the AIS could be used as tools for irrigation management in the Mid-South region, but with careful attention to soil texture and the effective portion of rainfall or irrigation. Keywords: Irrigation scheduling, Soil moisture sensor, Soil water content, Water management.

Standardization of Frequency Domain Reflectometry and Watermark Sensors for Soil Moisture Measurement at Field Level

A field experiment with spilt plot design was carried out for standardization of Frequency Domain Reflectometry (FDR) and Watermark sensors in drip irrigated broccoli(Brassica oleracea var. italica). The experiment included three levels of irrigation frequencies: N1 (once every day), N2 (once every 2 days) and N3 (once every 3 days) with three irrigation regimes of 100, 80 and 60 % of crop evapotranspiration (ETc). For evaluating the performance of different soil moisture sensors, the sensors’ readings were taken from the plot on a daily basis and these readings were compared with gravimetric methods (standard). It was observed that the calibration of two sensors (FDR and Watermark) give a similar calibration equation with lowRMSE after field calibration. The value of coefficient of determination (R2) for FDR was observed 0.85, 0.86, 0.89 and 0.86 for 0-15, 15-30, 30-45 and 45-60 cm soil depth whereas, the value of coefficient of determination (R2) for Watermark sensor was observed as 0.76, 0.83, 0.84 and 0.85 for 0-15, 15-30, 30-45 and 45-60 cm soil depth, respectively. The Watermark sensorscurves observed less sensitive at low soil water tension,whereas FDR sensors performed better in wet as well as dry conditions. That field calibrationof soil moisture sensors isa prerequisite to measure soil moisture content in the soil.

Water balance in soil covered by regenerating rainforest in the Paraíba Valley region, São Paulo, Brazil

The objective of this study was to evaluate the water balance in a Red-Yellow Latosol covered by a regenerating rainforest for 30 years in the Una River Basin between April 2016 and March 2017. Field capacity (FC) and permanent wilting-point values (PWP) used to calculate the available water capacity (AWC) in the soil were determined by the soil moisture characteristic curve obtained in pots, which made it possible to determine the soil residual water content (g / g) from the measurement of water tension in 15 Watermark (TM) sensors installed at depths of 40, 60 and 120 cm. Precipitation during the period (1962 mm) was obtained from the automatic weather station located 300 m from the experimental area. Soil surface runoff was obtained from 5 collectors distributed in the experimental area. Precipitation was characterized by a maximum of 454 mm in January 2017 and no rain in July 2016. The actual evapotranspiration was 744 mm. There were 56 runoff events (SR) totaling 60 mm. The average soil water tension remained below 37 kPa in 67% of the studied period, a condition that kept the soil moisture content high. The soil water balance of the tropical forest area, up to 120 cm deep, kept soil water content near its maximum capacity (173 mm) 49% of the time and saturated 51% of the time, so that it generated deep drainage beyond 120 cm deep and 1023 mm deep.

Agricultural drought monitoring based on soil moisture derived from the optical trapezoid model in Mozambique

Soil moisture (SM) at three depths (15, 25, and 30 cm), derived from the optical trapezoidal model (OPTRAM), was used for multiyear, multisite monitoring of agricultural droughts over two agricultural crops (Maize and Soybean) in southern Mozambique. The OPTRAM was implemented using satellite data from Sentinel-2 and was validated against field SM assessed by gravimetric methods and by Watermark Sensors in sandy-soils with very low water holding capacity (0.13 cm3 / cm3). The OPTRAM model estimated the SM at 15 and 25 cm yielding a R2 ≥ 0.79 and RMSE ≤ 0.030 cm3 / cm3. The OPTRAM-derived SM was successfully used as input to compute and map the soil water deficit index, an indicator of agricultural drought. The results indicate that OPTRAM can provide useful information to improve water productivity in cropland under the specific conditions of Mozambique agricultural systems and for early warning systems development.

Numerical HYDRUS 2D simulation of root zone water uptake dynamics by drip irrigated asparagus

Asparagus (Asparagus officinalis L.) is a perennial vegetable grown in the north eastern part of Belgium. Asparagus is grown on sandy soils with low water holding capacity. Asparagus has been reported to be sensitive to drought stress, with reduced stomatal conductivity and assimilation rate at high soil and plant water potential. On the other hand, the root system has been known to be extensive, which should permit water extraction from a large soil volume. In 2015, a field experiment was conducted to gain insight into the dynamics of root zone water uptake by asparagus under three different drip irrigation treatments; a full irrigation treatment at which irrigation was initiated at -60 kPa, a treatment, which received 50% of irrigation water was compared to the full irrigation treatment and a rain-fed treatment. In every irrigation treatment, crop development and gravimetric soil moisture observations were collected in four replications. For each treatment, one plot was equipped with 6 Watermark granular matrix sensors to observe the variation in soil water potential (Ψsoil). In the autumn, the Watermark sensors were removed and root samples collected at the same place to determine the fine root distribution. The acquired root distribution, in combination with in situ observed water retention characteristics and saturated hydraulic conductivity was fed into the HYDRUS 2D model to numerically describe the water extraction pattern of asparagus. With this calculation, the relation between soil water potential and plant water status was identified in each drip irrigation treatment. Although calculated Ψsoil agreed only moderately with observed Ψsoil, the calculation suggested that transpiration declined in rain-fed asparagus, despite its extensive root system.

EFFECTS OF SCHEDULING TECHNIQUES OF WATER APPLICATION FOR DRIP IRRIGATION SYSTEM ON TOMATO YIELD IN ARID REGIO

Irrigation is necessary in order to produce tomato in arid regions such as Saudi Arabia, with limited water supplies. Drip irrigation (DI) is being adopted in these areas to conserve water under economical crop production. Field experiment was carried out to study effects of different irrigation scheduling management strategies on fruit yield, quality of drip-irrigated fresh market tomatoes, water use efficiency and irrigation application efficiency. The experiment included three scheduling methods, which were used to irrigate tomato field: Evapotranspiration (ET) controller, soil moisture sensor (watermark sensor) and control treatment based on weather data. All irrigation-scheduling methods were effective, prescribing different amount of water for a given season. Irrigation amount increased from 841.5 mm (ET controller) to 882.60 mm (watermark sensor) and 1034.33 mm (control treatment), during two seasons. Both WUE and IWUE increased with decrease in irrigation water depth. The maximum average WUE (7.26 kg-m–3) and IWUE (4.66 kg-m– 3) values were for ET controller as average, during the two seasons. In addition, ET controller method conserved up to 7 % and 18% water compared to the watermark sensor and control treatments, respectively. Based on the above results, it is recommended that if the tomatoes are well irrigated based on ET controller, the farmer can get higher tomato yield in areas experiencing severe drought, such as Saudi Arabia.

Development of a Low-Cost Internet-of-Things (IoT) System for Monitoring Soil Water Potential Using Watermark 200SS Sensors

Soil moisture monitoring is one of the methods that farmers can use for irrigation scheduling. Many sensor types and data logging systems have been developed for this purpose over the years, but their widespread adoption in practical irrigation scheduling is still limited due to a variety of factors. Important factors limiting adoption of soil moisture sensing technology by farmers include high cost and difficulties in timely data collection and interpretation. Recent developments in open source microcontrollers (such as Arduino), wireless communication, and Internet-of-Things (IoT) technologies offer opportunities for reducing cost and facilitating timely data collection, visualization, and interpretation for farmers. Therefore, the objective of this study was to develop and test a low-cost IoT system for soil moisture monitoring using Watermark 200SS sensors. The system uses Arduino-based microcontrollers and data from the field sensors (End Nodes) are communicated wirelessly using LoRa radios to a receiver (Coordinator), which connects to the Internet via WiFi and sends the data to an open-source website (ThingSpeak.com) where the data can be visualized and further analyzed using Matlab. The system was successfully tested under field conditions by installing Watermark sensors at four depths in a wheat field. The system described here could contribute to widespread adoption of easy-to-use and affordable moisture sensing technologies among farmers.

A Note on Comparing Rate of Soil Moisture Loss for Conventional and Conservation Tillage Production methods for Peanut (Arachis hypogaea)

ABSTRACT Soil moisture retention is important for peanut production as well as water conservation in irrigated and non-irrigated fields. One way to increase soil moisture retention of the soil is by increasing soil organic matter. Research was conducted to determine if there is a difference in the rate of soil moisture loss in a field operated under a conservation production system (CPS) method and a conventionally tilled (CT) method, and if there was a time difference between needed wetting events. Experiments were conducted on two different fields with Tifton sandy loam soil. Soil moisture was monitored with Watermark sensors installed at 10, 20 and 30 cm depths. Data was analyzed to determine the rate of soil moisture loss when the soil was wet (below 50 kPa) and dry (above 80 kPa). The rate of soil moisture loss was not significant between CPS and CT when the soil was wet; however, there was a difference in the soil moisture loss rate when soils were dry. When dry, the CT soils lost moisture at a rate 2.5 times that of the CPS soils. This increased rate of loss indicates that water would need to be supplied to the CT soils every 1.5 d whereas the CPS soils would need water every 3.9 d. These results indicate that use of CPS increased the water holding capacity of soil, increased time required between wetting events, and can aid in the conservation of water resources in peanut production.

Control of Hydrological Seasonal Variability of Ash-fall Pyroclastic Deposits on Rainfall Triggering Debris Flows in Campania (Southern Italy)

Ash-fall pyroclastic deposits covering Campanian mountain slopes (southern Italy) are very prone to instability under heavy and prolonged rainfall. In such a geo-hazard framework, to understand hydrological dynamics of pyroclastic mantle is a further step toward the assessment of rainfall thresholds and landslide hazard. In this research, the hydrological and stability modelling of representative ash-fall pyroclastic soil mantled slopes of the Sarno Mountains is proposed to assess the role of seasonal hydrological variability of the pyroclastic cover on rainfall triggering debris flows. The approach is based on the numerical modelling, from seasonal to inter-annual timescales, of unsaturated/saturated flows occurring into the pyroclastic mantle upslope of a source area of a debris flow. Modelling results were calibrated by means of field measurements achieved by a monitoring station equipped with tensiometers and Watermark sensors. Among the main results, the recorded pressure head time series showed a dominant unsaturated condition and a very relevant decrease in the summer season, whose effects are not limited to the root zone but extended down to the bedrock interface, about 4 meter deep. This seasonal hydrological regime of the ash-fall pyroclastic mantle was correlated both to the distinctive water retention properties of pyroclastic soils and to the existence of a deciduous forest, which concentrates the evapotranspiration demand during the dry season. Hydrological and stability modeling of the representative slopes allowed the reconstruction of deterministic rainfall thresholds for both dry and wet seasons and the assessment of the significant predisposing role of antecedent hydrological conditions to slope instability during short and heavy rainstorms.

Numerical calculation of soil water potential in an irrigated ‘conference’ pear orchard

Irrigation in Belgian ‘Conference’ pear orchards is often managed by soil water potential (Ψsoil) sensors. The most widespread sensor among fruit growers in Belgium is the Watermark sensor (Irrometer Co., USA). To gain better insight into the use of the Watermark soil sensor for irrigation scheduling in pear orchards the water extraction pattern of the ‘Conference’ pear trees was acquired by a numerical calculation of Ψsoil in three experimental plots. A reasonable accordance between calculated and measured Ψsoil was observed with R2=0.56 and RMSE=13.4kPa over 1320 observations. Furthermore the sensitivity of the numerical calculation to the selected root distribution was shown. The Ψsoil calculation with the root distribution parameterized by site specific fine root length observations gave satisfactory results for all plots, in contrast to Ψsoil calculation based on other root distributions.