Soil Water Content Profiles Research Articles

Capillary rise quantification improves irrigation performance in pear orchards

The shallow water table in Río Negro and Neuquén valley causes a capillary rise (CR) that modifies the water content in soil profile. Therefore, irrigation performance is expected to be affected by the capillary water input into the root zone. The aim of this study was to evaluate the effect of CR on surface irrigation performance during 2020-2021 growing season in a pear orchard. In a Bartlett pear orchard planted in 2003, three irrigation moments were evaluated, and irrigation sheets were calculated to obtain efficiency. Water table level (WTL) was measured monthly in an open aquifer piezometer. CR was calculated with the software UPFLOW. Soil water content was measured with a Frequency Domain Reflectometry (FDR) sensor at: 0.20 m, 0.40 m, and 0.60 m. Water use efficiency (WUE) and water productivity were calculated using pear crop yield and the irrigation sheets applied and the crop water demand, respectively. WTL was shallower in spring than in the rest of the season. The mean depth fluctuated between 0.70-1.20 m during spring, affecting irrigation performance. Data of FDR deepest sensor showed an increase of soil moisture due to CR. Capillary contribution negatively affects irrigation efficiency if it is not included in the water balance. Irrigation schedules can be re-arranged considering soil moisture and CR. In this way, the necessary water sheets could be applied in each crop development stage adjusted to water demand. Improving irrigation performance and WUE enables a sustainable water management strategy in pear production.

Evaluation of subsurface soil water content estimate methods: Maximum entropy vs. exponential filter

Profile soil water content (SWC) is a vital variable in the atmosphere-vegetation-soil system. Although remote sensing currently can provide reliable surface SWC data (∼5 cm depth), acquiring accurate subsurface SWC data from existing reanalysis products remain challenging. In this study, we evaluated two widely used methods in estimating subsurface SWC, namely the exponential filter (ExpF) and the principle of maximum entropy (POME). The evaluation is carried out in two distinct areas on the Tibetan Plateau using ground observations collected from two monitoring networks: the Maqu network area characterized by cold humid climate and grassland and the Shiquanhe network area characterized by cold arid climate and bare ground. The results indicate that POME generally performs better than ExpF in both areas, particularly in deeper soil layers. Specifically, the accuracy of estimated SWC using the ExpF method decreases with depth, while it increases with depth using the POME method. Additionally, both methods achieve commendable performance at a depth of 10 cm in both areas. The deficiency of ExpF is mainly reflected in underestimations for dry cases, which is amplified with increasing depth. Dry cases account for 51 % in the humid area and 68 % in the arid area throughout the study period. Consequently, the ExpF method yields higher root mean square differences (RMSD) by 30 % and 113 % in the humid area at depths of 20 and 40 cm, respectively, compared to the POME method. Similarly, it results in higher RMSD values by 220 % and 200 % in the arid area. As expected, the superior performance of POME in deeper soil layers is primarily attributed to the incorporation of additional bottom and profile mean SWC observations. However, it also potentially introduces uncertainties when integrated with satellite-based data, which inherently contains errors compared to ground observations. To assess the potential of these two methods in large-scale applications combined with satellite-based datasets, this study conducted further evaluation of both methods with required input data derived from the soil moisture active and passive mission (SMAP). The results demonstrate that the performance of both methods in estimating subsurface SWC is acceptable in both humid and arid areas, although some bias is transferred from the input data. They achieve average RMSD values of 0.034 and 0.055 m3/m−3(−|−) in the humid area for the ExpF and POME methods, respectively, and 0.021 and 0.014 m3/m−3(−|−) in the arid area.

Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat.

The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates. However, CGMs require multiple seasonal environmental records, unlike WGP, which makes CGM-WGP less accurate when applied to historical reference populations that lack crucial environmental inputs. Here, we investigated the ability of CGM-WGP to approximate missing environmental variables to improve prediction accuracy. Two environmental variables in a wheat CGM, initial soil water content (InitlSoilWCont) and initial nitrate profile, were sampled from different normal distributions separately or jointly in each iteration within the CGM-WGP algorithm. Our results showed that sampling InitlSoilWCont alone gave the best results and improved the prediction accuracy of grain number by 0.07, yield by 0.06 and protein content by 0.03. When using the sampled InitlSoilWCont values as an input for the traditional CGM, the average narrow-sense heritability of the genotype-specific parameters (GSPs) improved by 0.05, with GNSlope, PreAnthRes, and VernSen showing the greatest improvements. Moreover, the root mean square of errors for grain number and yield was reduced by about 7% for CGM and 31% for CGM-WGP when using the sampled InitlSoilWCont values. Our results demonstrate the advantage of sampling missing environmental variables in CGM-WGP to improve prediction accuracy and increase the size of the reference population by enabling the utilisation of historical data that are missing environmental records.

Mechanistically derived macroscopic root water uptake functions: The α and ω of root water uptake functions

AbstractWater uptake by plant roots is an important component of the soil water balance. Predicting to what extent potential transpiration from the canopy, that is, transpiration demand, can be met by supply of water from the soil through the root system is crucial to simulate the actual transpiration and assess vegetation water stress. In models that simulate the dynamics of vertical soil water content profiles as a function of water fluxes and soil water potential gradients, the root water uptake (RWU) distribution is represented by macroscopic sink terms. We present RWU functions that calculate sink terms based on a mechanistic model of water flow in the soil–root system. Based on soil–root hydraulics, we define α‐supply functions representing the maximal uptake by the root system from a certain soil depth when the root collar water potential equals the wilting point, ω‐supply factors representing the maximal supply from the entire root system, and a critical ωc factor representing the potential transpiration demand. These functions and factors are subsequently used to calculate RWU distributions directly from potential transpiration or demand and the soil water potentials. Unlike currently used approaches, which define α‐stress functions and ω factors representing ratios of actual uptake to uptake demand, the supply‐based formulations can be derived directly from soil and root hydraulic properties and can represent processes like root hydraulic redistribution and hydraulic lift.

Spatial variability and forecast of soil water in the ultra‐deep loess profile across a south–north transect of the Chinese Loess Plateau

AbstractKnowledge of the spatial variability and forecast of soil water in the ultra‐deep (>21 m) loess profile are important for understanding the chemical, physical, and biological processes in the CZ. In this study, we regularly monitor soil water content (SWC) in deep soil profile along regional transect on the Loess Plateau. Descriptive statistical analysis found that the coefficient of variation (CV) of mean SWC in Ansai and Shenmu were 16.036% and 13.606%, respectively, indicating moderate variability. The CV of mean SWC in Yangling, Changwu, and Fuxian were 4.111%, 7.951%, and 6.117%, respectively, showing low variability. Geo‐statistical analysis indicated that mean SWC showed strong spatial dependence. Wavelet analysis showed that the approximative trend of mean SWC in five sampling sites showed an increased trend along depth series. In addition, a good fit line equation (R2 = 0.329) was established by using observed values and ANN‐forecast of three sites (Yangling, Fuxian, and Shenmu). And the RMSE values of five sample sites, respectively, were 1.302, 4.546, 2.662, 6.231, and 4.293. This study fills the gap in research' ultra‐deep (>21 m) soil water changes and forecast, evidence from soil borehole data. At the same time, our research provides valuable information for the vegetation restoration and modelling of deep soil water.

Revegetation impacts on runoff generation processes in a typical loess catchment

AbstractSince 1999, large‐scale ecosystem restoration has been implemented in the Loess Plateau, effectively increasing regional vegetation coverage. Vegetation restoration has significantly elevated the saturated hydraulic conductivity (Ks) of the near‐surface soil layers and increased the vertical heterogeneity of the Ks profile. Many studies have examined the change of runoff due to revegetation, yet the impacts of Ks profile on the soil moisture distribution and runoff generation processes were less explored. In this study, numerical simulations were conducted to investigate how changes in the Ks profile caused by vegetation restoration influenced the hydrological responses at event scale. The numerical simulation results show that the increase of surface Ks caused by vegetation restoration can effectively reduce runoff at event scale. Moreover, the enhancement of vertical heterogeneity of Ks profiles can significantly change the vertical profile of soil water content, prompting more water to percolate into the deep soil layer. When rainfall exceeds a threshold, the accumulation of soil water above the relatively less permeable layer can cause short‐term saturation in shallow soil layers, resulting in a transient perched water table. As a result, after the vegetation restoration in the Loess Plateau, though Horton overland flow is still the main runoff generation mechanism, there is a possibility of the emergence of Dunne overland flow under the high vegetation coverage (e.g., NDVI larger than 0.5). This emergence of new runoff generation mechanism, saturation excess runoff, in the Loess Plateau due to the vegetation restoration could provide scientific guidance for water and sediment movement, soil and water conservation practices, and desertification control in the Loess Plateau.

Fertigation frequency is a useful tool for nitrate management in intensive open-field agriculture

The main source of nitrogen for most cultivated plants is nitrate. Agriculture has overused this nutrient, resulting in serious environmental problems in various parts of the world. The common practice in open intensive horticultural fields with clay-loam soils with a high water retention capacity (e.g., high percentage of clay) is to irrigate two to four times per week. Technically and logistically, this is much easier than one or more irrigation events per day. However, the loss of nutrients and water below the root zone may occur, with the consequent loss of efficiency. In this work, two cultivation cycles in an open-field endive crop were carried out under plastic soil mulching. We compared three fertigation strategies based on different frequencies of fertigation events; low fertigation frequency (LF, two to three fertigation events per week that simulates common farmer practice), medium fertigation frequency (MF, one fertigation event per day), and high fertigation frequency (HF, three fertigation events per day). The three fertigation strategies applied equal water and fertilizers doses per week. The high fertigation frequency increased volumetric water content in the upper soil profile, while the low fertigation frequency in the lower soil profile. The results demonstrated that HF fertigation increases shoot fresh weight (harvest yield) by increasing shoot water content, but did not improve shoot nutrient uptake or nitrogen nutritional status. The important finding, from the environment point of view, is that high and medium fertigation frequencies decreased nitrate concentration in the root influence zone, where it may be prone to leaching due to heavy rain events.

Root phenotyping and root water uptake calculation using soil water contents measured in a winter wheat field

Non-destructive phenotyping of roots and measurement of root water uptake from different soil layers in the field are vital for improving water management and facilitating the development of drought-resistant crop varieties, but difficult because of their opaqueness. As a result, indirect methods using easy-to-measure variables such as soil water content have been used as alternatives. However, the inherent measurement errors could undermine the robustness and reliability of these methods. This paper proposes a new method to bridge this knowledge gap by using soil water content profiles measured at two time points to calculate root uptake and root-length density. It is based on the Richards' equation by treating root uptake from different soil layers between the two time points as random unknown numbers; their distributions are calculated using the Bayesian framework, solved by the Markov Chain Monte Carlo method. We applied the method to 39 winter wheat lines grown in a silt-clay loam field. Soil water content profile measured at the first time point from each plot served as the initial condition, and water content measured at the second time point was the target to match the model for calculating average root water uptake and root-length density between the two time points. The results show that the measured soil water contents fall within the 95% confidence interval of the calculated soil water contents. The inherent soil water measurement errors lead to uncertainties in the calculated root water uptake for all lines, but such uncertainties decrease with soil depth. Although the soil types and agronomic management were the same for all 39 lines, their root water uptake from different soil layers varies considerably, with some lines more capable of using subsoil water than others. Generally, the calculated and measured root-length densities agree well, albeit the degree of the agreement varies with lines. While this paper focuses on methodology and applies the method to one growth stage spanning one month only, the consistent results for all 39 lines indicates the method is robust and can be applied to other crops cultivated in different conditions. Given the growing interest in improving root traits to enhance water use efficiency, the proposed method has important implications as phenotyping roots and understanding their water uptake from different soil layers in the field is a prerequisite to achieve this crucial target.

Tree root-soil interaction: field study of the effect of trees on soil moisture and ground movement in an urban environment

Abstract Aims Little research has been conducted to quantify the atmosphere-plant-soil interaction in urban environments due to a lack of understanding of plant water use characteristics and the limited availability of high-quality field data. This research aims to quantify the drying effect of root systems of two Australian native tree species on soil water dynamics and ground movement using high-quality field measurement data. Methods A long-term field monitoring on soil moisture variation and ground movement close to C. maculata and M. styphelioides, was conducted for up to 45 months in Melbourne, Australia. The water requirement of each tree was monitored using sap flow sensors. Laboratory soil testing was conducted to obtain soil properties and develop profiles of soil suction and water content. The intercorrelation between soil water dynamics and tree soil water use was established. Results Tree roots could no longer extract water from the soil when total soil suction exceeded a wilting point of approximately 1000 kPa. The soil profile differences between the two sites were a significant factor causing substantial differences in tree water consumption. Conclusions At the C. maculata site, tree-induced soil desiccation occurred to a depth of 1.1 m, while at the M. styphelioides site, it extended down to 2.2 m depth. The tree root-soil interaction analysis shows that water uptake of 10.64 kL by tree roots partially contributes to a 5% decline in soil water content and a 270 kPa rise in soil suction, resulting in a continuous soil settlement of 22 mm.

Version 1.2.0 — pyfao56: FAO-56 evapotranspiration in Python

The pyfao56 software package is a Python-based implementation of the standardized evapotranspiration (ET) methodologies described in Irrigation and Drainage paper No. 56 of the Food and Agriculture Organization of the United Nations, commonly known as FAO-56. This update improved pyfao56 by (1) enhancing the “forecast” module which obtains seven-day weather forecasts from the National Weather Service (NWS), (2) incorporating measured soil water content profiles to estimate soil water depletion in the dynamic and maximum root zones, (3) adding visualization tools that plot measured and simulated soil water depletion and ET versus time, (4) updating the format of standard file headers to include timestamps, simulation options, and user defined metadata, and (5) incorporating minor improvements to the functionality of the core pyfao56 modules. These updates arose from efforts to incorporate pyfao56 into a computational workflow for maize irrigation scheduling research at the Limited Irrigation Research Farm (LIRF) in Greeley, Colorado during the 2023 growing season.

Soil water dynamics and biomass production of young rooibos (Aspalathus linearis) plants

Rooibos (Aspalathus linearis) is endemic to certain regions of the Western- and Northern Cape of South Africa, where it is also commercially grown. Being low-rainfall regions, information on the soil water balance of rooibos is essential, but such data is limited. Consequently, the effect of inorganic fertilisation and soil depth on soil water dynamics in a young rooibos plantation at Nardouwsberg, Western Cape were studied. Soil water content of plots planted to unfertilised and fertilised plants as well as that of bare soil were determined over the duration of the 2016/17 season. All treatments were replicated on shallow and deep soils sites and plant growth was determined at the end of the season. At the end of the study, the profile soil water content and evapotranspiration of the bare and planted plots were similar which prove that fallowing (water harvesting) is not an option in the sandy soils of this region. With the exception of the 20−30 cm root zone of the planted plots at the deep site, the water content decreased to levels below the permanent wilting point in the soil profile during summer. It was concluded that rooibos plants could survive through an adapted root system. A further survival method was proposed, involving moisture moved through evaporation from the deeper soil layers into the drying-front in the ~ 10−30 cm soil layer where a condensation-evaporation cycle enables rooibos to harvest small amounts of water. The highest shoot biomass with the longest taproot resulted from the unfertilised treatment on the deep soil thanks to higher soil water content, whereas the shoot and root biomass of the fertilised treatment at both sites were low due to high P soil concentration. This study revealed that unfertilised plants on deeper soils result in higher rooibos production under drought conditions.

A novel approximate solution to slope rainfall infiltration

Slope rainfall infiltration is a critical component of the Earth's hydrologic processes. Although various infiltration models have been proposed to simulate rainfall infiltration, simple and accurate ones are still scarce. This work developed a non-integral infiltration model for sloping surfaces, called modified approximate solutions under constant pressure conditions (MASCP). New expressions were proposed to improve slope infiltration simulation by introducing a developing saturated zone in soil water content (SWC) profile to quantify the role of ponding water during infiltration. The MASCP was then extended to simulate the infiltration with uniform and non-uniform initial SWC distributions under complex rainfall patterns. The model performance was evaluated by comparing with Hydrus-1D and the sloping Green-Ampt model for four distinct textured soils. The results demonstrated that the ponding time and infiltration rate simulated by the MASCP agreed well with those by Hydrus-1D at all given conditions. Besides, the MASCP yielded higher simulation accuracy than the sloping Green-Ampt model, especially for coarse-textured soils, low rainfall intensity, and long rainfall hiatus. In conclusion, the MASCP is a simple and accurate computation tool for slope rainfall infiltration modeling.

Post‐Wildfire Stability of Unsaturated Hillslopes Against Rainfall‐Triggered Landslides

AbstractWildfire records demonstrate worsening patterns coupled with the spread to higher altitudes in several regions, raising the risk of post‐wildfire ground failures. This study investigates the post‐wildfire stability of unsaturated hillslopes against rainfall‐triggered shallow landslides. We developed a new physics‐based analytical framework incorporating wildfire‐induced changes in soil properties and near‐surface processes affecting the hillslope stability. A coupled hydromechanical infiltration model is integrated into an infinite slope stability analysis to simulate temporal changes in the depth profiles of soil water content, pressure head, and the resulting factor of safety (F.S.) of a vegetated slope. We consider the antecedent conditions of soil and vegetation cover, including the recovery phase after the fire, wildfire‐induced alterations in transpiration, and time‐varying infiltration rates. The model is verified against numerical simulations and employed in parametric studies evaluating the effects of wildfire severity and rainfall intensity‐duration. For the cases examined, it was shown that wildfire could reduce the F.S. of slopes by 25%. As a case study, the model successfully captured shallow rainfall‐triggered landslides that occurred in the Las Lomas watershed in California, USA, in 2019, 3 years after the Fish Fire burned the area. The proposed model uses measurable hillslope and wildfire characteristics and can be employed to evaluate the risk of shallow landslides in wildfire‐prone areas.

Field Evaluation of Conventional and Downhole TDR Soil Water Sensors for Irrigation Scheduling in a Clay Loam Soil

Highlights Soil profile water content derived from Acclima TDR-315™ sensors approximated those from NMM measurements. Soil profile water content from Campbell Scientific SoilVUE™10 sensors grossly underestimated those from the NMM. VWC values from SoilVUE10 sensors were consistently less than those reported by the TDR-315 sensors at all depths. These findings do not support SoilVUE10 use for irrigation scheduling in clay loam soils. Abstract. A field study was performed to evaluate the efficacy of two commercially available time domain reflectometry (TDR) soil water sensors for irrigation scheduling in a clay loam soil near Bushland, Texas. SoilVUE10 (Campbell Scientific Inc., Logan, Utah) and TDR-315 (Acclima Inc., Meridian, Idaho) sensors were installed within 30 cm of neutron moisture meter (NMM) access tubes in a research field planted to corn (Zea mays L) in 2020 and irrigated by a center pivot sprinkler system. Irrigation treatments included 50%, 75%, and 100% of evapotranspiration (ET) replacement with two access tubes installed in each plot, totaling six sensor evaluation sites. Semiweekly measurements with a field-calibrated NMM were used to monitor soil water status and schedule irrigation throughout the growing season. Soil profile water content values integrated over the surface to 1.1-m depth range were derived from SoilVUE10 and vertically distributed arrays of Acclima TDR-315 sensors installed at equivalent depths and were compared with those from NMM data. Average profile soil water contents from the TDR-315 sensors trended well with those from the NMM having mean bias difference (MBD) values of -9.8, -3.1, and 8.4 mm for the 50%, 75%, and 100% treatments, respectively. In contrast, soil profile water content values from the SoilVUE10 sensors grossly underestimated those from the NMM for all irrigation treatments with MBD values of -54.4, -70.5, and -89.8 mm for the 50%, 75%, and 100% treatments, respectively. Comparisons of volumetric water content (VWC) at each of the nine depths common to both electromagnetic sensor types revealed that values from the SoilVUE10 sensors were consistently less than TDR-315 values for all irrigation treatments. Underestimation at the near surface (5 and 10 cm depths) was attributed to loss of soil to electrode contact possibly associated with clay shrinkage during periodic drying following irrigation. Although soil to electrode contact can be problematic at greater depths, the explanation for chronic underestimation of VWC was less obvious except to note that underestimation occurred immediately after installation, which indicated poor electrode-soil contact after installation despite use of manufacturer guidelines and tools. Other possible reasons include challenges for accurate estimation of soil permittivity for a measured permittivity that includes the plastic sensor body. Results from this study suggest vertically distributed arrays of TDR-315 sensors can provide profile water content values adequate for monitoring soil water status for irrigation scheduling in a clay loam soil. The chronic underestimation observed for the SoilVUE10 sensors does not support their use for water resources research and irrigation management and could lead to over irrigation. Additionally, the relatively short 1 m length is less than the rooting depth of many regional crops and thus not capable of determining percolation below the root zone. Keywords: Acclima TDR-315, Campbell Scientific SoilVUE, Irrigation scheduling, Neutron moisture meter, Semi-arid, Soil water sensors, Time domain reflectometry, Volumetric water content.

The performance of dry spell-based index to predict agricultural drought

This study was intended to analyze dry spell-based drought index (SDI) performance in predicting agricultural drought. Agricultural drought was estimated using soil moisture deficit index (SMDI) over a monthly time-scale. The deficit in soil moisture was calculated using soil water content in soil profile predicted by SWAT model. The result indicated that SDI has poor performance in predicting agricultural drought index. However, the outcome might be explained by the low temporal resolution of soil moisture data.

Methods for downhole soil water sensor calibration—Complications of bulk density and water content variations

AbstractDownhole soil volumetric water content (VWC) sensors are used in access tubes to assess the soil water content at multiple depths. If sensor readings are spaced closely enough vertically and are accurate enough, then accurate soil profile water content storage and change in storage can be determined over the depth range of readings, leading to accurate estimates of evapotranspiration (ET) if readings extend to well below the root zone. Even if sensing only covers the active root zone, soil water depletion may be determined well enough to inform irrigation scheduling. While sensor accuracy is dependent on many factors, including the sensor's physical principle of operation, soil‐specific calibration is typically required for good accuracy. In soils with multiple horizons (layers) of different texture, bulk density (BD), or chemical composition, horizon‐specific calibrations may be necessary. We describe methods and equipment used for downhole sensor calibration to typical accuracy of <0.01 m3 m−3 with specific reference to calibration of 10 neutron scattering meters in a soil that required three different horizon‐specific calibrations. Our results contrast with the factory calibration, which would result in a 38‐mm error in water stored in a 1.5‐m deep profile of our soil. We describe variability of measured VWC and BD with depth, distance, and water content and the errors that result from using BD to convert mass basis (g g−1) water content data to VWC data, which can be as much as 35 mm (7.26% underestimation) for soil water storage in a 1.5‐m deep profile of our soil.

Experimental analysis of soil moisture response to rainfall in a typical grassland hillslope under different vegetation treatments

The responses of soil moisture to rainfall are of great significance for watershed hydrological modeling. However, few studies have been done to investigate these responds on hillslope in a typical semi-arid grassland region. This study used high temporal resolution soil moisture data to explore the soil moisture dynamics, response conditions and its controls of 0–40 cm soil profile in the upslope (14°), midslope (9°), and downslope (4°) of a typical grassland inland river basin under bare ground (BG), stubble (SG), and natural grassland (CK) treatments. The results showed that soil water content and water storage increased in the downslope direction, and all showed as BG > SG > CK. The dry and wet changes in fast-changing layer (5 cm) and active layer (10 cm) were rapid, while soil moisture below 20 cm was relatively stable and fluctuated only in heavy or continuous rainfalls. The soil moisture response process varied greatly under different rainfall, rainfall intensity and antecedent soil moisture conditions, which explained 41.1% of the total difference. The rainfall replenishment threshold and the required initial soil profile water content of soil moisture response in 5 cm, 10 cm and 20 cm soil layers were 5.8 mm, 8.0 mm, 11.4 mm and 8.7 vol%, 9.4 vol%, 10.8 vol%, respectively. Soil properties, vegetation characteristics and topography could explain 38.8%, 14.5% and 5.6% of the soil moisture variation on the hillslope. In addition, under the comprehensive influence of environmental factors, changes in soil moisture of the upslope were significantly affected by soil sand content, the differences in the midslope were mainly due to soil clay content and belowground biomass, whereas the vegetation characteristics were the main factors in the downslope. This study can contribute to the further understanding of slope-scale ecohydrological processes and hydrological simulation of semi-arid grassland watersheds.

Estimation of bell pepper evapotranspiration using two-source energy balance model based on high-resolution thermal and visible imagery from unmanned aerial vehicles

Crop evapotranspiration (ET) is a crucial component of energy and water budgets. The accurate determination of ET is vital for agricultural water management. Several satellite-based ET models have been developed to map ET at the field to regional scales. The spatial resolution of the satellite observations, particularly thermal-infrared imagery, is insufficient to estimate ET for small (<1 ha) agricultural fields. With unmanned aerial vehicle (UAV) technology advancement, high spatial and temporal images can be acquired with UAVs to monitor ET for small fields or even at a canopy scale. The aim of this study was the evaluation of the two-source energy balance (TSEB) model to estimate daily and seasonal crop (bell pepper) ET (ETTSEB) using high-resolution visible and thermal UAV imagery. Also, the impact of using different pixel resolutions (40, 50, 60, and 70 cm) with TSEB is compared with ET values derived using a soil water budget approach (ETSWD) with a profile soil water content. The results of this study showed that there is a high correlation between ETTSEB and ETSWD values (R2 = 0.73 for daily, R2 = 0.98 for seasonal). The root mean square error values for daily and seasonal ETTSEB are 0.62 mm day − 1 and 11.46 mm season − 1, respectively. The sensitivity of TSEB output to the spatial resolution indicated that different pixel resolutions do not significantly impact ET estimates. We suggest that the TSEB model has a real potential for agricultural water management applications for small agricultural fields using high-resolution UAV multispectral and thermal images.

Approximate analytical solutions for one-dimensional soil water movement equation with arbitrary initial conditions

Simple analytical solutions of one-dimensional horizontal and vertical soil water movement are of great importance for the soil hydraulic parameters estimation and precision irrigation. We present the approximate analytical solutions for the problem of horizontal absorption and vertical infiltration in soil under arbitrary initial conditions and constant boundary conditions based on the principle of least action and the variational principle. The algebraic functions of soil water content (SWC) profile, cumulative infiltration, infiltration rate and infiltration time about the wetting front distance/depth (WFD) and the parameters of Brooks-Corey model are obtained. Compared with the numerical results simulated by HYDRUS-1D, the algebraic results calculated by approximate analytical solutions have high precision to predict the horizontal and vertical soil water infiltration based on the known WFD. Contrary to the linear relationship in horizontal absorption with uniform initial conditions, the relationships between cumulative infiltration and WFD, infiltration rate and reciprocal of WFD, square of WFD and infiltration time are nonlinear for the arbitrary heterogeneous initial conditions. However, the initial conditions have little effect on the relationship between infiltration rate and WFD when the initial SWCs are lower than 0.6 θs. Based on the nonlinear relationships of infiltration rate and WFD in vertical infiltration, the WFD and time of the stable infiltration are obtained.

Redesign of dryland apple orchards by intercropping the bioenergy crop canola (Brassica napus L.): Achieving sustainable intensification

AbstractChina's Loess Plateau (LOP) contains around 22% of all the world's apple trees, mainly on smallholdings run by farmers. However, business‐as‐usual (BAU) intensification has reduced the ecological resilience of orchards. Agroforestry is considered to be an important method of realizing sustainable intensification of agroecosystems. However, the design of practical agroforestry systems in drylands remains poorly researched. We hypothesized that crop density is a key factor in designing dryland apple tree‐based agroforestry systems. We carried out an experiment in apple orchards in the semiarid LOP, where the bioenergy crop canola (Brassica napus L.) was intercropped at low, medium, and high densities with row spacings of 25, 50, and 100 cm, respectively, to study its effects on water, carbon, and production. We found that intercropping of canola at different densities clearly decreased soil water content (SWC) in the top 60 cm soil layer at all sampling locations, reduced midday leaf water potential (Ψm) and leaf water content (LWC), and caused apple trees to produce more fine roots at greater depths. However, intercropping did not affect SWC in soil layers below 60 cm. The SWC profiles, Ψm and LWC, progressively recovered over the mulching period. Introduction of canola also significantly (p &lt; 0.05) increased SOC content in the surface layer, an effect less visible in deeper layers, and increased the quality of apple fruit to varying degrees while not affecting apple yield measurably. Overall, higher intercropping density does not lead to severer water deficit but have better carbon sequestration benefit than lower density, and therefore seems more appropriate in our study site. Our findings provide solid evidence that agroforestry helps achieve sustainable intensification of dryland orchards.