Analysis of AET and yield predictions under surface and buried drip irrigation systems using the Crop Model PILOTE and Hydrus-2D

Innovative irrigation solutions have to face water scarcity problems affecting the Mediterranean countries. Generally, surface (DI) or subsurface drip irrigation systems (SDI) have the ability to increase water productivity (WP). But the question about their possible utilisation for crops such as corn would merit to be analysed using an appropriate economic tool. The latter would be necessary based on the utilisation of a modelling approach to identify the optimal irrigation strategy associating a water amount with a crop yield (Yc). In this perspective, a possible utilisation of the operative 1D crop model PILOTE for simulating actual evapotranspiration (AET) and yield under a 2D soil water transfer process characterizing DI and SDI was analysed. In this study, limited to a loamy soil cultivated with corn, the pertinence of the root water uptake model used in the numerical code Hydrus-2D for AET estimations of actual evapotranspiration (AET) under water stress conditions is discussed throughout the Yc = F(AET) relationship established by PILOTE on the basis of validated simulations. The conclusions of this work are (i): with slight adaptations, PILOTE can provide reliable WP estimations associated to irrigation strategies under DI and SDI, (ii): the current Hydrus-2D version used in this study underestimates AET, compared with PILOTE, in a range varying from 7% under moderate water stress conditions to 14% under severe ones, (iii): A lateral spacing of 1.6 m for the irrigation of corn with a SDI system is an appropriate solution on a loamy soil under a Mediterranean climate.A local Yc = F(AET) relationship associated with a Hydrus-2D version taking into account the compensating root uptake process could result in an interesting tool to help identify the optimal irrigation system design under different soil conditions.     

Water balance and pattern of soil water uptake in a peach orchard

Five-year-old peach trees were irrigated at 50% and 100% of calculated maximum evapotranspiration (MET) in order to determine the influence of water stress on the pattern of water uptake from the soil and on the actual evapotranspiration (AET) of the crop. A simplified water balance method based on the relationship between the drainage component and the soil water content averaged over the soil profile has been used to estimate AET from periodic neutron probe measurements.Maximum water uptake is from the upper 60 cm of soil when trees are well-watered. Decreased soil water content induces a shift in the soil water uptake towards deeper layers, which can be due either to upward fluxes of water or to an increased water uptake by deeper roots.AET in the 50% MET regime is reduced from July to September, compared to the 100% MET regime, partly because of stomatal closure. There is no drainage in the 50% MET treatment from June to September; it is about 1 mm day⁻¹ in the 100% MET regime until the end of August and ceases in September when the soil dries.     

一种五自由度修剪机器人结构设计与分析

为满足多样化景观绿篱修剪造型对修剪机器人工作空间、结构刚度和强度的需求，设计一种用于园林绿植的五自由度修剪机器人结构。首先采用D-H法对机器人进行建模与运动学分析，利用蒙特卡洛法得到机器人的工作空间；然后以球形绿篱为修剪目标，基于机器人有效空间体积比和速度全域性能指标，确定机器人臂架结构主要杆件的尺寸；最后对臂架结构进行有限元静力学和振动模态仿真分析。仿真结果表明：当大臂尺寸为800 mm，小臂尺寸为900 mm，腕臂尺寸为350 mm时，该机器人垂直修剪作业范围为0~2 000 mm，水平修剪作业范围为-1 300~1 300 mm，工作空间可满足园林绿篱的修剪需求；臂架结构的最大等效应力为34.245 MPa，最大变形为1.897 1 mm，刚度和强度均满足技术指标的要求，且其固有频率可有效避开外界频率，避免共振现象。本研究为景观绿篱修剪机器人研制提供机械结构设计方法与方案，具有一定的应用价值。     

Using the dual approach of FAO-56 for partitioning ET into soil and plant components for olive orchards in a semi-arid region

The main goal of this research was to evaluate the potential of the dual approach of FAO-56 for estimating actual crop evapotranspiration (AET) and its components (crop transpiration and soil evaporation) of an olive (Olea europaea L.) orchard in the semi-arid region of Tensift-basin (central of Morocco). Two years (2003 and 2004) of continuous measurements of AET with the eddy-covariance technique were used to test the performance of the model. The results showed that, by using the local values of basal crop coefficients, the approach simulates reasonably well AET over two growing seasons. The Root Mean Square Error (RMSE) between measured and simulated AET values during 2003 and 2004 were respectively about 0.54 and 0.71 mm per day. The basal crop coefficient (K_cb) value obtained for the olive orchard was similar in both seasons with an average of 0.54. This value was lower than that suggested by the FAO-56 (0.62). Similarly, the single approach of FAO-56 has been tested in the previous work (Er-Raki et al., 2008) over the same study site and it has been shown that this approach also simulates correctly AET when using the local crop coefficient and under no stress conditions.Since the dual approach predicts separately soil evaporation and plant transpiration, an attempt was made to compare the simulated components of AET with measurements obtained through a combination of eddy covariance and scaled-up sap flow measurements. The results showed that the model gives an acceptable estimate of plant transpiration and soil evaporation. The associated RMSE of plant transpiration and soil evaporation were 0.59 and 0.73 mm per day, respectively.Additionally, the irrigation efficiency was investigated by comparing the irrigation scheduling design used by the farmer to those recommended by the FAO model. It was found that although the amount of irrigation applied by the farmer (800 mm) during the growing season of olives was twice that recommended one by the FAO model (411 mm), the vegetation suffered from water stress during the summer. Such behaviour can be explained by inadequate distribution of irrigation. Consequently, the FAO model can be considered as a potentially useful tool for planning irrigation schedules on an operational basis.     

FAO-56 methodology for the stress coefficient evaluation under saline environment conditions: Validation on potato and broad bean crops

This study aims at validating the methodology proposed by Allen et al. (1998) to calculate the stress coefficient Ks (ratio between actual and maximal evapotranspiration) under saline environment conditions not affected by soil water shortage. Validation was performed in Mediterranean region (Bari, southern Italy) on two crops: a winter crop (broad bean) and a spring crop (potato) grown in lysimeters, on clay and loam soils, having different levels of salinity. Preliminary observations were carried out to verify that the conditions established by Allen et al. (1998) for applying this Ks calculation methodology were fulfilled.The measured Ks values showed an evolution during the growing cycle. Ks values were close to 1 after emergence, and decreased at the end of the growing cycle. Contrarily, the calculated Ks values showed steady values during the whole crop cycle, being lower than the measured Ks. Only at the end of the crop cycle the calculated Ks values approached those measured. The various causes of differences between measured and calculated values of Ks are analyzed in this study.The observed differences between calculated and measured values of Ks led to an underestimation of calculated actual evapotranspiration (AET), at different stages in the crop growing cycle, by an average of 12%. The analysis of seasonal evapotranspiration as a function of soil salinity allows for a modulation of this mean value. The underestimation was quite negligible (close to 4%), if the average value of ECe during the crop cycle was close or lower than 3 dS m⁻¹. On the contrary, the underestimation in evapotranspiration was close to 20% when the ECe raised up to 6 dS m⁻¹.An underestimation of calculated AET in saline environment conditions, by the methodology proposed by Allen et al. (1998), causes the appearance of an additional water stress, mainly when soil salinity, increases due to the combined effect of soil water shortage and water quality. Different solutions are proposed to improve the calculation of AET in this condition.     

Comparison between mechanistic and functional models for estimating soil water balance: deterministic and stochastic approaches

In many models used to simulate soil-water relationships, representations of the transport mechanisms in the soil-plant-atmosphere continuum, range from mechanistic to functional. The objective of this paper is to compare two functional models, FAO (Doorenbos and Pruitt, 1977) and Ritchie (1985)models, with a mechanistic model (Maraux and Lafolie, 1998) to simulate the soil water balance of maize and sorghum grown in sequence in Nicaragua. In the FAO model, the soil is described as a single reservoir which is characterized by its amount of water varying on a daily time scale, depending on the rain, drainage, and actual evapotranspiration. In the Ritchie model, the soil is regarded as a multilayered soil profile. The maximum evapotranspiration is divided between soil evaporation and plant transpiration, and drainage occurs if the amount of water arriving in the last layer corresponds to a water content greater than the field capacity. The mechanistic model is based on the Richards' equation. Comparison of the three models was first made according to a deterministic approach with parameters coming from the same database. We then considered a stochastic approach for which 800 hydraulic characteristics of the soil were generated, according to the spatial variability observed at the field scale and to the scaling theory applied to similar porous media. A distribution of the stochastic parameters used in the three models was thus derived. Results showed that the order of magnitude of the evapotranspiration was similar for the three models (902, 874, 842 mm cumulative evapotranspiration for a 203 day period for the MM, Ritchie, and FAO models, respectively). Adding a capillary rise mechanism in the functional models improved moderately the soil-water balance. Evapotranspiration and drainage showed moderate sensitivity to spatial variability in soil hydraulic properties (coefficients of variation less than 1.6%), whereas final water storage (after 203 days) showed a greater sensitivity (coefficients of variation from 7.9–15.7%, depending on the model).     

Hydrological impacts of rainwater harvesting (RWH) in a case study catchment: The Arvari River, Rajasthan, India: Part 2. Catchment-scale impacts

A key question in relation to rainwater harvesting (RWH) is whether the technique increases the sustainability of irrigated agriculture. A conceptual water balance model, based on field data from the Arvari River catchment, was developed to study and understand catchment-scale trade-offs of rainwater harvesting (RWH). The model incorporates an effective representation of RWH function and impact, and works on a daily time step. Catchment spatial variability is captured through sub-basins. Within each sub-basin hydrological response units (HRUs) describe the different land use/soil combinations associated with the case study catchment, including irrigated agriculture. Sustainability indices, based on irrigated agriculture water demand, were used to compare conceptual management scenarios. The results show that as RWH area increases, it reaches a limiting capacity from where additional RWH structures do not increase the benefit to groundwater stores, but reduces stream flow. If the irrigation area is increased at the optimal level of RWH, where the sustainability indices were greatest, the resilience of the system actually decreased. Nevertheless RWH in a system increased the overall sustainability of the water resource for irrigated agriculture, compared to a system without RWH. Also RWH provided a slight buffer in the groundwater store when drought occurred. The conceptual analysis highlights the important link between irrigation area and RWH area, and the impact of RWH on the catchment water balance.     

Regional simulation of maize production in tropical savanna fallow systems as affected by fallow availability

Upscaling of crop models from the field scale to the national or global scale is being used as a widespread method to make large-scale assessments of global change impacts on crop yields and agricultural production. In spite of the fact that soil fertility restoration and crop performance in many developing countries with low-input agriculture rely strongly on fallow duration and management, there are only few approaches which take into account the effect of fallowing on crop yields at the regional scale. The objectives of this study were to evaluate the sensitivity of maize yield simulations with the Environmental Policy Integrated Climate (EPIC) model to fallow availability at the field and regional scale and (2) to present a novel approach to derive a model-based estimate of the average fallow availability within a typical catchment of the sub-humid savanna zone of West Africa. Therefore, the EPIC model has been validated at the field scale and then incorporated into a spatial database covering a typical catchment within the sub-humid savanna zone of West Africa with 121 sub-basins. Maize-fallow rotations have been simulated within 2556 quasi-homogenous spatial units and then aggregated to the 10 districts within the catchment assuming three different scenarios of fallow availability: 100% of the bush-grass savanna area is available and used in fallow-crop rotations (FU100), 50% of the bush-grass savanna area is available and used in fallow-crop rotations (FU50) and 25% of the bush-grass savanna area is available and used in fallow-crop rotations (FU25). A new aggregation procedure has been developed which is based on changes in the frequency of fallow-cropland classes within the sub-basins to render the simulation results in the spatial database sensitive to changes in fallow availability. Comparison of the average simulated grain yield with the mean yield over the catchment shows that the simulations overestimate maize yields by 62%, 44% and 15% for scenario FU100, FU50 and FU25, respectively. The best agreement between simulated and observed crop yields at the district scale was found when using the assumption that 25% of the savanna is available as fallow land under the present cropping patterns, which corresponds to a fallow-cropland ratio of 0.9. Comparison with farm surveys shows that the combination of remote sensing and dynamic crop modelling with yield observations provides realistic estimates of effective fallow use at the regional scale.     

遥感技术在水文水资源领域中的应用研究进展

遥感数据具有周期短、信息量大和成本低的特点,为水文水资源研究提供了丰富的数据源。详细介绍了遥感技术在水文水资源领域的主要应用研究进展,包括降水、蒸散发、径流与水文模型、地表特征及参数提取、洪涝灾害监测、水土保持、土壤水分与旱情监测、积雪与融雪、水质监测和地下水等方面,展望了今后应用研究的发展方向。     

Hydrological impact of biofuel production: A case study of the Khlong Phlo Watershed in Thailand

This study evaluates the potential impact of increased biofuel production on the hydrology of a small watershed, Khlong Phlo, in the eastern part of Thailand. The water footprint of biofuel energy was estimated for three crops in order to identify the most water-efficient crop. The Soil and Water Assessment Tool (SWAT) model was used to evaluate the impact of land use change (LUC) caused by the expansion of biofuel crops on the components of water balance and water quality in the studied watershed. Several LUC scenarios consisting of oil palm (biodiesel), cassava and sugarcane (bio-ethanol) expansion were evaluated. The water footprint results indicated that cassava is more water-efficient than the other two crops considered. Simulation results revealed that although oil palm expansion would have negligible alteration in evapotranspiration (0.5 to 1.6%) and water yield (−0.5 to −1.1%), there would be an increased nitrate loading (1.3 to 51.7%) to the surface water. On the contrary, expansion of cassava and sugarcane would decrease evapotranspiration (0.8 to 11.8%) and increase water yield (1.6 to 18.0%), which would lead to increased sediment (10.9 to 91.5%), nitrate (1.9 to 44.5%) and total phosphorus (15.0 to 165.0%) loading to surface water. Based on the results, it can be concluded that land use change for biodiesel production would affect water quality, while both the water balance components and water quality would be affected by the expansion of bio-ethanol crops. Overall, the study indicates that biofuel production would have a negative impact on the water quality of the studied watershed. Further research at large scale (e.g. basin level) and on the economic aspect is recommended, in order to contribute to developing suitable land use and energy policies.     

基于SEBAL模型和Landsat-8遥感数据的农田蒸散发估算

【目的】及时准确地获取农田蒸散发量,为科学管理农田灌溉、精准估算作物产量和预报土壤水分动态、合理开发水资源等提供有效依据。【方法】以广利灌区为研究对象,基于SEBAL模型利用Landsat-8数据对研究区域农田蒸散发进行估算,通过地表参数计算净辐射通量、土壤热通量和感热通量,利用余项法求得潜热通量及瞬时蒸散发。假定24 h内蒸散比不变,由瞬时蒸散发扩展到日蒸散发量,最终求得研究区的日平均蒸散发量,将模型计算结果与彭曼公式进行了对比,同时结合灌区提供数据对计算结果进行了验证。【结果】彭曼公式计算2014年5月6日和2015年9月14日蒸散量与实测结果相差分别为5.2%和9.4%,SEBAL模型估算得到2014年5月6日和2015年9月14日的日蒸散量与灌区提供日蒸散量相差4.5%、6.0%,且冬小麦及夏玉米蒸散发在空间上存在一定的差异性,主要集中在灌区中部区域及西南区域。【结论】SEBAL模型计算结果具有较高的精度,而且方法相对快捷高效。     

冬小麦田棵间蒸发的试验研究

利用大型称重式蒸渗仪和微型蒸渗仪研究了冬小麦生育期间逐日蒸散和蒸发过程 ,分析了蒸发占蒸散的比例及其随叶面积指数和表层土壤含水量的变化关系、灌溉后土壤蒸发的变化过程     

绿色生态空间网络研究进展

绿色生态空间网络是景观生态学的重要研究内容,是耦合景观格局、生态过程与生态功能的重要桥梁,对于提高景观连接性、保护物种多样性、促进生态系统结构与功能的完整性具有重要意义。本文梳理了绿色生态空间网络的研究脉络,从绿色生态空间网络的概念与特征、相关理论与研究方法等方面展开论述,阐述了绿色生态空间网络的相关概念及发展历程,构建、分析与优化中的常见方法与主要特点,以及绿色空间网络研究中的相关理论,列举了绿色生态空间网络的主要应用领域,如城市、水文、防风固沙、水土保持等,并对绿色生态网络的基本改变、研究方法、尺度研究以及和其他空间网络结合等方面进行了展望。     

Comparison of drainage estimation methods in irrigated citrus orchards

Three different methods of measuring drainage were selected and applied to two irrigated citrus orchards for 3 years. The methods were: (1) a simple soil water capacity model, (2) a chloride balance, and (3) the LEACHM model. In the first method, the soil is assumed to have a given water holding capacity, plants cannot extract water from soil below a certain level, and evapotranspiration varies with soil water content in a well-defined pattern. In the second method, drainage in a given period of time is estimated from the chloride input to soil (mainly with the irrigation and rain water), the changes in soil chloride, and the average chloride concentration of soil solution at the depth where drainage is estimated. In the LEACHM model, water transport in soil is assumed to follow Richards equation, and evapotranspiration depends in soil water content, soil hydraulic properties, the evaporative conditions of the air, and root properties and distribution. Two citrus orchards planted with mature trees, under flood irrigation, were used for the comparison of methods. The three methods provided drainage estimates that differed in most cases by less than 13%, although in some particular season and plot, a given method deviated from the other two by up to 56%. The soil water capacity model is appealing because it only needs a few parameters for calibration, and can be easily programmed in a spreadsheet. The main advantage of the chloride balance approach is that it requires neither calibration nor an estimate of evapotranspiration; this latter fact converts the chloride balance into a good alternative method of measuring evapotranspiration. The precision of the drainage estimates by chloride balance is mainly determined by the spatial variability of soil chloride relative to the chloride input to the soil in the measurement period; in most cases, to obtain a reasonable precision, this period should be longer than 1 or 2 months. The LEACHM model requires more data for calibration, but it can provide additional information on water and solute distribution in the soil profile with time.     

农村道路布局设计及其景观生态效应研究

农村道路及其配套设施建设对农业机械化、现代化有显著影响。该文论述了农村道路网络、农村道路设计及其生态景观效应。农村道路网络规划应与农业产业化紧密结合,在满足连通度的同时,尽可能有益于农村居民点的适度集中,减少对耕地斑块的分割和干扰;路面、路基等设计应综合考虑土壤、工程地质和地形地貌等条件,就地取材;对区域尺度景观的干扰,可通过数个村级尺度单元间“通道－阻隔”效应的耦合积聚而消减。农村道路,特别是丘陵区的农村道路建设,要围绕提高农业机械化水平、优化农村道路网和提高工程设计标准来进行,以改善道路生态景观。      

Estimating plant root water uptake using a neural network approach

Water uptake by plant roots is an important process in the hydrological cycle, not only for plant growth but also for the role it plays in shaping microbial community and bringing in physical and biochemical changes to soils. The ability of roots to extract water is determined by combined soil and plant characteristics, and how to model it has been of interest for many years. Most macroscopic models for water uptake operate at soil profile scale under the assumption that the uptake rate depends on root density and soil moisture. Whilst proved appropriate, these models need spatio-temporal root density distributions, which is tedious to measure in situ and prone to uncertainty because of the complexity of root architecture hidden in the opaque soils. As a result, developing alternative methods that do not explicitly need the root density to estimate the root water uptake is practically useful but has not yet been addressed. This paper presents and tests such an approach. The method is based on a neural network model, estimating the water uptake using different types of data that are easy to measure in the field. Sunflower grown in a sandy loam subjected to water stress and salinity was taken as a demonstrating example. The inputs to the neural network model included soil moisture, electrical conductivity of the soil solution, height and diameter of plant shoot, potential evapotranspiration, atmospheric humidity and air temperature. The outputs were the root water uptake rate at different depths in the soil profile. To train and test the model, the root water uptake rate was directly measured based on mass balance and Darcy's law assessed from the measured soil moisture content and soil water matric potential in profiles from the soil surface to a depth of 100 cm. The ‘measured’ root water uptake agreed well with that predicted by the neural network model. The successful performance of the model provides an alternative and more practical way to estimate the root water uptake at field scale.     

Simulation of furrow irrigation practices (SOFIP): a field-scale modelling of water management and crop yield for furrow irrigation

Because of the spatial and temporal variabilities of the advance infiltration process, furrow irrigation investigations should not be limited to a single furrow irrigation event when using a modelling approach. The paper deals with the development and application of simulation of furrow irrigation practices (SOFIP), a model used to analyse furrow irrigation practices that take into account spatial and temporal variabilities of the advance infiltration process. SOFIP can be used to compare alternative furrow irrigation management strategies and find options that mitigate local deep-percolation risks while ensuring a crop yield level that is acceptable to the farmer. The model is comprised of three distinct modelling elements. The first element is RAIEOPT, a hydraulic model that predicts the advance infiltration process. Infiltration prediction in RAIEOPT depends on a soil moisture deficit parameter. PILOTE, a crop model, which is designed to simulate soil water balance and predict yield values, updates the soil moisture parameter. This parameter is an input of a parameter generator (PG), the third model component, which in turn provides RAIEOPT with the data required to simulate irrigation at the scale of an N-furrow set. The study of sources of variability and their impact on irrigation advance, based on field observations, allowed us to build a robust PG. Model applications show that irrigation practices must account for inter-furrow advance variability when optimising furrow irrigation systems. The impact of advance variability on deep percolation and crop yield losses depends on both climatic conditions and irrigation practices.     

Combining remote sensing and in situ soil moisture data for the application and validation of a distributed water balance model (HIDROMORE)

An application of the FAO56 approach to calculate actual evapotranspiration (AET) and soil moisture is reported, implemented by means of the HIDROMORE computerized tool, which performs spatially distributed calculations of hydrological parameters at watershed scale. The paper describes the application and validation of the model over 1 year in an area located in the central sector of the Duero Basin (Spain), where there is a network of 23 stations for continuous measurement of soil moisture (REMEDHUS; Soil Moisture Measurement Stations Network) distributed over an area of around 1300 km². The application integrated a series of Landsat 7 ETM+ images of 2002, from which the NDVI series (Normalized Difference Vegetation Index) and the map of land covers/uses were derived. Validation consisted of the use of the REMEDHUS soil moisture series and their comparison with the series resulting from the application. Two simulations were performed, with soil parameters values at the surface (0-5 cm depth) and at the mean of the profile scale (0-100 cm depth). The behaviour of the simulated soil moisture was described by means of its correlation with the measured soil moisture (determination coefficient, R² = 0.67 for the surface values and 0.81 for the mean profile values), and the Root Mean Square Error (RMSE), resulting in a range of it for the 23 stations between 0.010 and 0.061 cm³ cm⁻³. The application afforded an underestimation of the soil moisture content, which suggests the need for a redefinition of the limits of the plant available water used in the calculation. The results showed that HIDROMORE is an efficient tool for the characterization of hydrological parameters at global scale in the study zone. The combination of the FAO56 methodology and remote sensing techniques was efficient in the spatially distributed simulation of soil moisture.     

Development of a system to produce maps of agricultural profit on a continental scale: An example for Australia

Policy makers in the agricultural sector are confronted with challenges which might drive land use change and ultimately agricultural profitability to a substantial degree. The challenges include questions around climate variability, demographic changes, use of land for bio-fuel production and ensuring an increase in food production. As profitability triggers many agri-business decisions, knowledge about the existing socio-economic landscape and the economic profile of a region as well as potential impacts on profits provides useful contextual information when agricultural policies are designed. Given the upcoming challenges and their associated uncertainties, it is important to ensure that a map of agricultural profit can be reproduced in a scenario and simulation setting which will allow exploring uncertainties around the impacts on agricultural profits as well. There is however currently no flexible system in operation which allows for a consistent update of a map of agricultural profits in Australia or elsewhere. This paper describes a process that has been developed to produce a map of agricultural profit for Australia for the year 2005/2006. The process involves a complex data architecture that accounts for heterogeneous information that is collected by a variety of institutions across different scales. All information can be comfortably queried and query results can be forwarded for immediate processing and subsequent visualisation in a geographic information system (GIS). To facilitate the production of profit maps in the future, the system provides flexibility regarding an update of new economic information but it can also be linked to maps that show an updated distribution of land use. A map of agricultural profit on a large scale and regular updates thereof will help understand profit trends in time and across space. It will help identifying regions that have a lower economic profile and will inform decisions regarding the design of regulatory policies. As these maps are developed using national scale data, we do not recommend using the results at the farm level but we suggest using separate catchment scale profit assessments to calibrate the national scale profit map. The proposed system is well suited to be used in various land use management and economic scenarios and will represent a step forward regarding a scenario impact assessment on agricultural profits. It will also help understand the economic benefit of land use on a large scale.