SimET: An open-source tool for estimating crop evapotranspiration and soil water balance for plants with multiple growth cycles

Accurate estimation of crop evapotranspiration(ETc) and soil water balance, which is vital for optimizing water management strategy in crop production, can be performed by simulation. But existing software has many deficiencies, including complex operation, limited scalability, lack of batch processing, and a single ETc model. Here we present simET, an open-source software package written in the R programming language. Many concepts involved in crop ETc simulation are condensed into functions in the package. It includes three widely used crop ETc models built on these functions: the single-crop coefficient,double-crop coefficient, and Shuttleworth–Wallace models, along with tools for preparing model data and comparing estimates. SimET supports ETc simulation in crops with repeated growth cycles such as alfalfa, a perennial forage crop that is cut multiple times annually.

Quantifying Responses of Winter Wheat Physiological Processes to Soil Water Stress for Use in Growth Simulation Modeling

A deep understanding of crop-water eco-physiological relations is the basis for quantifying plant physiological responses to soil water stress. Pot experiments were conducted to investigate the winter wheat crop-water relations under both drought and waterlogging conditions in two sequential growing seasons from 2000 to 2002, and then the data were used to develop and validate models simulating the responses of winter wheat growth to drought and waterlogging stress. The experiment consisted of four treatments, waterlogging (keep 1 to 2 cm water layer depth above soil surface), control (70%-80% field capacity), light drought (40%-50% field capacity) and severe drought (30%-40% field capacity) with six replicates at five stages in the 2000-2001 growth season. Three soil water content treatments (waterlogging, control and drought) with two replicates were designed in the 2001-2002 growth season. Waterlogging and control treatments are the same as in the 2000-2001 growth season. For the drought treatment, no water was supplied and the soil moisture decreased from field capacity to wilting point. Leaf net photosynthetic rate, transpiration rate, predawn leaf water potential, soil water potential, soil water content and dry matter weight of individual organs were measured. Based on crop-water eco-physiological relations, drought and waterlogging stress factors for winter wheat growth simulation model were put forward. Drought stress factors integrated soil water availability, the sensitivity of different development stages and the difference between physiological processes (such as photosynthesis, transpiration and partitioning). The quantification of waterlogging stress factor considered different crop species, soil water status, waterlogging days and sensitivity at different growth stages. Data sets from the pot experiments revealed favorable performance reliability for the simulation sub-models with the drought and waterlogging stress factors.

Investigation of crop evapotranspiration and irrigation water requirement in the lower Amu Darya River Basin, Central Asia

High water consumption and inefficient irrigation management in the agriculture sector of the middle and lower reaches of the Amu Darya River Basin(ADRB)have significantly influenced the gradual shrinking of the Aral Sea and its ecosystem.In this study,we investigated the crop water consumption in the growing seasons and the irrigation water requirement for different crop types in the lower ADRB during 2004–2017.We applied the FAO Penman–Monteith method to estimate reference evapotranspiration(ET0)based on daily climatic data collected from four meteorological stations.Crop evapotranspiration(ETc)of specific crop types was calculated by the crop coefficient.Then,we analyzed the net irrigation requirement(NIR)based on the effective precipitation with crop water requirements.The results indicated that the lowest monthly ET0 values in the lower ADRB were found in December(18.2 mm)and January(16.0 mm),and the highest monthly ET0 values were found in June and July,with similar values of 211.6 mm.The annual ETc reached to 887.2,1002.1,and 492.0 mm for cotton,rice,and wheat,respectively.The average regional NIR ranged from 514.9 to 715.0 mm in the 10 Irrigation System Management Organizations(UISs)in the study area,while the total required irrigation volume for the whole region ranged from 4.2×109 to 11.6×109 m3 during 2004–2017.The percentages of NIR in SIW(surface irrigation water)ranged from 46.4%to 65.2%during the study period,with the exceptions of the drought years of 2008 and 2011,in which there was a significantly less runoff in the Amu Darya River.This study provides an overview for local water authorities to achieve optimal regional water allocation in the study area.

覆土浅埋滴灌玉米分阶段亏水条件下AquaCrop与Dual Crop Coefficient模型精度对比研究

近年来,西辽河流域地下水超采问题日益突出,改进灌溉技术降低农业用水可有效解决这一问题,但该技术缺乏科学的水分管理方法及适宜的理论模型。基于单阶段及多阶段亏水情形试验,对比同类农田水分模型精度,优选阶段性亏水管理辅助模型。研究设置7个玉米分阶段亏水调控处理,于2018、2019年进行田间小区试验,取得2个同类模型的本地化参数并比较其模拟精度。结果表明,AquaCrop和双作物系数模型可相近表达玉米冠层发育到最大而未开始衰减期间土壤水分的消耗过程,而对快速生长期与后期1m土层贮水量的模拟差异大。AquaCrop模型在土壤贮水量偏低时高估其实测值,其他情形正负偏差分布相对均匀,双作物系数模型多数情形低估其实测值。AquaCrop模型描述玉米各阶段蒸散量因亏水情形而变化能力优于双作物系数模型。AquaCrop模型和双作物系数模型的标准均方根误差平均值在模拟1 m土层贮水量时分别为4.494%~8.443%、6.017%~8.626%,在模拟蒸散量时分别为8.158%~9.510%、5.980%~15.022%。综合来看,AquaCrop模型表现更好,推荐作为适宜西辽河流域覆土浅埋滴灌玉米水分管理模型。研究可为该区域覆土浅埋滴灌种植玉米选出适宜的水分管理模型,理解新技术条件下玉米分阶段亏水调控机制及田间灌溉管理优化提供参考。

Saline Water Irrigation Scheduling Through a Crop-Water-Salinity Production Function and a Soil-Water-Salinity Dynamic Model

Using a crop-water-salinity production function and a soil-water-salinity dynamic model, optimal irrigation scheduling was developed to maximize net return per irrigated area. Plot and field experiments were used to obtain the crop water sensitivity index, the salinity sensitivity index, and other parameters. Using data collected during 35 years to calculate the 10-day mean precipitation and evaporation, the variation in soil salinity concentrations and in the yields of winter wheat and cotton were simulated for 49 irrigation scheduling that were combined from 7 irrigation schemes over 3 irrigation dates and 7 salinity concentrations of saline irrigation water (fresh water and 6 levels of saline water). Comparison of predicted results with irrigation data obtained from a large area of the field showed that the model was valid and reliable. Based on the analysis of the investment cost of the irrigation that employed deep tube wells or shallow tube wells, a saline water irrigation schedule and a corresponding strategy for groundwater development and utilization were proposed. For wheat or cotton, if the salinity concentration was higher than 7.0 g L-1 in groundwater, irrigation was needed with only fresh water; if about 5.0 g L-1, irrigation was required twice with fresh water and once with saline water; and if not higher than 3.0 g L-1, irrigation could be solely with saline water.

基于AquaCrop模型的玉米需水和降水匹配度变化特征研究

雨热同期为我国大部分地区农业生产提供了充足的水热资源,但从需水机理的角度评估作物生长和降水过程匹配度的变化特征还有待深入。基于AquaCrop模型模拟了关中地区1978-2017年夏玉米生育期内需水量、灌溉需水量、有效降水量和产量的变化特征,并在充分考虑玉米不同生育阶段对水分需求程度差异的基础上,分析了作物需水与降水匹配度的变化特征。结果表明:关中地区玉米生育期内累积降雨量变化幅度相对较小,但降水过程明显后移,且更多的以暴雨的形式发生;玉米生育期内需水量和灌溉需水量均呈现明显的增加趋势,增加幅度分别为4.10 mm/10a和13.38 mm/10a,而有效降水量则以-10.28 mm/10a的速率减小;玉米生育期内需水与降水的平均匹配度为58%,且整体以-2.7%/10a的速率下降。上述结果表明关中地区降水模式越来越难以满足夏玉米的水分需求,延迟播种可作为提高作物需水与降水匹配度的应对措施之一。

Stochastic Modelling of Actual Black Gram Evapotranspiration

The study was undertaken to develop and evaluate evapotranspiration model for black gram (Vigna Mungo L.) crop under climatic conditions of Udaipur, India. Pan evaporation data for the duration of twenty three years (1978-2001) and measured black gram evapotranspiration data by electronic lysimeter for duration of kharif season of 2001 were used for analysis. Black gram is an important crop of Udaipur region. No sys-tematic study on modelling of black gram evapotranspiration was conducted in past under above said cli-matic conditions. Therefore, stochastic model was developed for the estimation of daily black gram evapotranspiration using 24 years data. Validation of the developed models was done by the comparison of the estimated values with the measured values. The developed stochastic model for black gram evapotran-spiration was found to predict the daily black gram evapotranspiration very accurately.

AquaCrop作物模型研究和应用进展

AquaCrop是由国际粮农组织(FAO)开发并向全球免费推广的一款新的作物生长模型,自从2009年发布以来,已经受到各国研究者的重视,而国内对该模型的应用尚处于起步阶段。为国内同仁更深入的了解该模型以及在中国的进一步验证和应用该模型提供有用的背景和参考信息,对模型原理、模型计算方案、模型应用现状和存在问题进行介绍和探讨。众多研究结果证明,AquaCrop模型有很好的模拟精度,可以辅助灌溉管理决策等。AquaCrop作为一个新发展的模型,其适应性还有待进一步验证,研究领域也有待进一步拓宽。

膜下滴灌水源矿化度对棉花生长的影响及AquaCrop模拟

利用微咸水灌溉是缓解干旱区灌溉淡水资源短缺的有效途径。为探讨膜下滴灌水源矿化度对棉花植株体内盐分累积、生长及产量的影响,该研究开展了2 a(2020-2021年)测坑试验,共设置6个灌溉水矿化度,分别为1、2、3、4、5和6 g/L,分析了棉花生育期内不同土层盐分累积规律,构建了不同矿化度水源膜下滴灌棉花的AquaCrop作物生长模型。结果表明:1)不同矿化度水源膜下滴灌棉花土壤盐分在40~60 cm土层积累量达到峰值,80~100 cm土层盐分积累较少。不同矿化度水源膜下滴灌棉花2 a末40~60 cm土层盐分分别累积44.29%、42.68%、43.40%、34.92%、35.69%、39.32%。2)灌溉水源矿化度为3~4 g/L时棉花生长指标和产量优于其他处理,且不会造成盐分累积过高,灌溉水源矿化度为4 g/L与1 g/L相比棉花各生长指标和产量受到影响较小,综合考虑棉花适宜灌溉水源为3~4 g/L之间。3)通过构建AquaCrop作物生长模型模拟冠层覆盖度、地上干物质量模拟值与实测值的决定系数大于等于0.812,标准均方根误差不大于24.1,一致性指数不小于0.984,模拟效果较好。棉花产量模拟值与实测值的相对误差RE小于9.28%,可见AquaCrop作物生长模型能较好地模拟不同矿化度水源膜下滴灌棉花生长发育过程,可用于产量预测和农业水资源优化管理。研究结果可为干旱区咸水资源膜下滴灌技术可持续利用提供依据。

不同矿化度水源膜下滴灌棉田土壤水盐动态和作物生长模拟

为构建适用于干旱区膜下滴灌条件的土壤水盐动态分布和棉花生长模型,基于2020—2021年的田间试验,经过对SWAP模型的土壤、土壤水力功能和作物生长等模块进行率定和验证,对灌溉水矿化度为1、2、3、4、5、6 g·L^(-1)时的土壤水盐分布特征、作物生长过程和干物质累积分配进行数值模拟。结果表明:(1)土壤含水率与土壤含盐量的模拟精度以20~100 cm土层较好,0~20 cm土层模拟精度较差,其中土壤含水量的模拟效果优于土壤含盐量;随着灌溉水源矿化度的增加,土壤含水率和含盐量的模拟误差逐渐变小。(2)不同矿化度水源膜下滴灌棉花叶面积指数模拟效果较好(R2=90.72%,RMSE=0.35 cm^(2)·cm^(-2),NRMSE=8.73%,IOA=0.98)。(3)不同矿化度水源膜下滴灌棉花茎干物质累积量模拟效果较好(R2=89.08%,RMSE=6.12 g,NRMSE=23.16%,IOA=0.96)。研究结果表明,SWAP模型可以较好地对不同矿化度水源膜下滴灌的土壤水盐动态分布和棉花生长过程进行模拟。

基于CROPWAT模型的玉米水分盈亏及灌溉制度研究

为研究黑龙江省中部地区玉米生育期内需水量、水分盈亏指数(CWSDI)、干旱等级变化和不同水文年灌溉制度,基于哈尔滨市1955-2014年气象数据、土壤数据和玉米作物参数,利用CROPWAT模型计算玉米生育期内需水量、有效降雨量和灌溉需水量,计算水分盈亏指数并划分干旱等级,采用Mann-Kendall趋势检验分析以上因素变化趋势,针对不同典型水文年制定灌溉制度。结果表明,该地区1955-2014年生育期内玉米需水量以9.41 mm/10 a的速率下降;丰水年、平水年,枯水年和特枯水年需水量分别为407.80、423.80、452.00和485.60 mm;多年平均CWSDI没有明显变化,生育期内每月CWSDI变化较为明显,干旱等级分析表明在玉米生长初期和生长后期较干旱;不同水文年干旱情况不同,除丰水年外,有效降雨量均难以满足玉米生育期内需水量,不同典型水文年应建立不同的灌溉制度。特枯水年、枯水年和平水年的灌水净定额分别为151.30、117.10和39.70 mm。

农业灌溉水资源优化配置研究进展

水资源短缺是制约农业可持续发展的关键因素,因此农业灌溉水资源的优化配置对于保障粮食安全和水安全具有重要意义。该研究基于农业灌溉水资源优化配置的主要类型,对单一作物灌溉优化决策、多作物水土资源优化配置和灌溉渠系水资源优化调度3个方面的研究进展进行了系统综述。同时指出了当前农业灌溉水资源优化配置中存在的主要问题和未来研究方向,研究认为当前的农业灌溉水资源优化配置应在如下4个方面进行完善:1)建立更具生理意义的作物水分-产量-品质模型;2)在气候变化和人类活动的情景下实现农业灌溉水资源的优化配置;3)构建全面考虑水源、渠系、灌区面积、作物配置以及生育阶段的系统性农业灌溉水资源优化配置模型;4)建立以棵间蒸发最小为目标的动态灌溉优化决策模型。研究可为中国的粮食安全和水安全提供理论指导。

气候变化影响下澜湄流域下游水稻生产用水量模拟与分析

农业用水是社会经济用水的主要行业,气候变化对农业用水的影响可能改变区域的水资源供需情势。以澜沧江-湄公河流域下游为研究区,基于ERA5-Land数据集和最新的CMIP6气候预测数据,选用SSP1-2.6、SSP2-4.5、SSP5-8.5三种排放情景,AquaCrop模型将非生产性土壤蒸发和生产性作物蒸腾分离,将水稻生长期内蒸腾总量作为水稻生产用水量,模拟了澜沧江-湄公河流域下游历史和未来时期水稻生产用水量,分析了水稻生产用水量的变化情况及其与温度、降水和CO_(2)浓度之间的相关关系。结果表明:澜沧江-湄公河流域下游水稻生产用水量在空间上表现为北多南少,总体呈现逐年减少趋势,且在SSP5-8.5情景下趋势更加明显。SSP5-8.5情景下的未来远期,澜沧江-湄公河流域下游水稻生产用水量将减少29.7%。与温度和降水相比,水稻生产用水量和CO_(2)浓度之间的相关性最强。SSP5-8.5情景下的未来远期,在泰国的相关系数为-0.875,其余国家各季度下的相关系数均小于-0.9。

基于校正WOFOST模型的枣树生长模拟与水分利用评价

为实现定量化分析温、光和水资源对果树生长的影响,本研究以成龄骏枣树为研究对象,提出了基于校正WOFOST模型的枣树生长和水分运移模拟方法。利用2016和2017年的田间试验观测数据,重点校正WOFOST模型的物候学发育、初始化、绿叶、CO_(2)同化、干物质分配、呼吸作用和水分利用参数。在田间尺度,完成总地上生物量(TAGP)、叶面积指数(LAI)和土壤水分含量的动态模拟和精度验证;在县域尺度,使用55个果园的最大LAI、单产、实际蒸散量(ET_(a))和水分利用效率(WUE)数据评价模型区域尺度的模拟性能。结果表明,在田间尺度,校正模型模拟不同灌溉梯度TAGP的决定系数R^(2)范围为0.92~0.98,归一化均方根误差NRMSE为8.7%~20.5%;模拟LAI的R^(2)范围为0.79~0.97,NRMSE为8.3%~21.1%;模拟土壤水分含量的决定系数R^(2)范围为0.29~0.75,NRMSE为4.1%~6.1%。在县域尺度,两年模拟最大LAI与实测LAI的R^(2)分别为0.64和0.78,NRMSE分别为13.3%和10.7%;模拟单产的R^(2)分别为0.48和0.60,NRMSE分别是12.1%和11.9%;模拟ET_(a)均方根误差分别为36.1 mm(7.9%)和30.8 mm(7.4%);模型也表现了较高的WUE模拟精度(10%<NRMSE<20%),均方根误差RMSE值分别为0.23和0.28 kg/m³。WOFOST模型在田间和县域尺度都取得了较高的枣树生长和水分运移模拟精度,可为土壤、气象、灌溉管理和枣树生长耦合影响的定量化分析提供新思路。

Towards a better understanding of pathways of multiple co-occurring erosion processes on global cropland

Soil erosion is a complex process involving multiple natural and anthropic agents,causing the deterio-ration of multiple components comprising soil health.Here,we provide an estimate of the spatial pat-terns of cropland susceptibility to erosion by sheet and rill,gully,wind,tillage,and root crops harvesting and report the co-occurrence of these processes using a multi-model approach.In addition,to give a global overview of potential future changes,we identify the locations where these multiple concurrent soil erosion processes may be expected to intersect with projected dry/wet climate changes by 2070.Of a modelled 1.48 billion hectares(B ha)of global cropland,our results indicate that 0.56 B ha(-36%of the total area)are highly susceptible(classes 4 and 5)to a single erosion process,0.27 B ha(-18%of the total area)to two processes and 0.02 B ha(1.4%of the total area)to three or more processes.An estimated 0.82 B ha of croplands are susceptible to possible increases in water(0.68 B ha)and wind(0.14 B ha)erosion.We contend that the presented set of estimates represents a basis for enhancing our founda-tional knowledge on the geography of soil erosion at the global scale.The generated insight on multiple erosion processes can be a useful starting point for decision-makers working with ex-post and ex-ante policy evaluation of the UN Sustainable Development Goal 15(Life on Land)activities.Scientifically,this work provides the hitherto most comprehensive assessment of soil erosion risks at the global scale,based on state-of-the-art models.

基于CROPWAT模型的昆明市水稻需水量及灌溉用水量研究

利用昆明市日气象数据、水稻生育期数据和土壤数据,通过CROPWAT模型模拟研究1980—2012年水稻生育期内需水量和灌溉用水量年际变化特征及气象要素对其的影响。结果表明,1980—1999年,水稻需水量和灌溉用水量呈微弱下降趋势(p=0.08,p=0.8);1999―2012年,水稻需水量和灌溉用水量呈上升趋势(p<0.01);近33a平均水稻需水量和灌溉用水量分别为603.6mm和638.8mm。作物需水量与温度、风速和日照时数正相关,与相对湿度负相关;灌溉用水量与降水量负相关,与日照时数正相关。气温、风速、湿度和日照时数的组合可以预测年尺度上作物需水量的变化趋势;降水和日照时数的组合可以预测年尺度上灌溉用水量的变化趋势。

基于熵权TOPSIS模型的温黄平原单季水稻水肥最优调控模式研究

不同的稻田水肥调控方式,将产生不同的经济、资源和环境效益。合理优化的稻田水肥调控方案应基于水稻节水、增产、减污3个方面的指标综合评价所得。以温黄平原单季稻为研究对象,以田间水肥调控为研究载体,建立基于水资源、环境和经济相统一的水稻水肥调控评价指标体系;同时利用熵权TOPSIS多目标决策模型,对浙东温黄平原单季水稻7种水肥调控方案进行优选。结果表明,浙东温黄平原地区"蓄雨薄露灌溉+3次施肥"模式最有利于水稻高产、节水、减污综合效益的发挥。

Sensitivity Analysis of the ALMANAC Model's Input Variables

Crop models often require extensive input data sets to realistically simulate crop growth. Development of such input data sets can be difficult for some model users. The objective of this study was to evaluate the importance of variables in input data sets for crop modeling. Based on published hybrid performance trials in eight Texas counties, we developed standard data sets of 10-year simulations of maize and sorghum for these eight counties with the ALMANAC (Agricultural Land Management Alternatives with Numerical Assessment Criteria) model. The simulation results were close to the measured county yields with relative error only 2.6% for maize, and - 0.6% for sorghum. We then analyzed the sensitivity of grain yield to solar radiation, rainfall, soil depth, soil plant available water, and runoff curve number, comparing simulated yields to those with the original, standard data sets. Runoff curve number changes had the greatest impact on simulated maize and sorghum yields for all the counties. The next most critical input was rainfall, and then solar radiation for both maize and sorghum, especially for the dryland condition. For irrigated sorghum, solar radiation was the second most critical input instead of rainfall. The degree of sensitivity of yield to all variables for maize was larger than for sorghum except for solar radiation. Many models use a USDA curve number approach to represent soil water redistribution, so it will be important to have accurate curve numbers, rainfall, and soil depth to realistically simulate yields.

Evaluation of the Precision Agricultural Landscape Modeling System (PALMS) in the Semiarid Texas Southern High Plains

Accurate models to simulate the soil water balance in semiarid cropping systems are needed to evaluate management practices for soil and water conservation in both irrigated and dryland production systems. The objective of this study was to evaluate the application of the Precision Agricultural Landscape Modeling System (PALMS) model to simulate soil water content throughout the growing season for several years and for three major soil series of the semiarid Texas Southern High Plains (SHP). Accuracy of the model was evaluated by comparing measured and calculated values of soil water content and using root mean squared difference (RMSD), squared bias (SB), squared difference between standard deviations (SDSD), and lack of correlation weighted by the standard deviation (LCS). Different versions of the model were obtained by modifying soil hydraulic properties, including saturated hydraulic conductivity (Ks) and residual (θr) and saturated (θs) soil volumetric water content, which were calculated using Rosetta pedotransfer functions. These modifications were combined with updated routines of the soil water solver in PALMS to account for rapid infiltration into dry soils that often occur in the SHP. Field studies were conducted across a wide range of soil and water conditions in the SHP. Soil water content was measured by neutron attenuation and gravimetrically throughout the growing seasons at each location to compare absolute values and the spatial distribution of soil water with PALMS calculated values. Use of Rosetta calculated soil hydraulic properties improved PALMS soil water calculation from 1% - 13% of measured soil volumetric water content (θv) depending on soil type. Large-scale models such as PALMS have the potential to more realistically represent management effects on soil water availability in agricultural fields. Improvements in PALMS soil water calculations indicated that the model may be useful to assess long-term implications of management practices designed to conserve irrigation water and maximize the profitability of dryland and irrigated cropping systems in the SHP.

考虑地表-土壤-作物水分联合亏缺的综合旱情指数研究

区域干旱发生发展受地表水、土壤水、作物水等多种缺水过程的共同影响,以往基于单一缺水过程构建的干旱指数难以反映实际旱情,综合考虑多种缺水过程构建综合旱情指数,对有效开展区域旱情监测具有重要的意义。基于水文作物耦合模型(VIC-EPIC)模拟数据,通过线性加权集成标准化径流指数(SRI)、土壤含水量距平指数(SMAPI)和作物缺水指数(CWDI),构建了反映地表土壤作物水分联合亏缺的综合旱情指数(CDSI),并采用1981—2020年数据在湘江流域开展了应用研究。结果表明,基于CDSI提取的旱情特征序列与流域内35个县1990—2007年受旱率相关性在0.4~0.8之间,82.9%通过5%显著性水平检验,与反映单一水分亏缺的SRI、SMAPI和CWDI相比,相关性整体上有较大提升。CDSI能够较好地反映区域实际旱情发生发展,可为大范围旱情准确识别和评估提供有效支撑。