Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

Abstract. Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.

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Influence of ecohydrologic feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1577-2012 ◽

2012 ◽

Vol 16 (6) ◽

pp. 1577-1593 ◽

Cited By ~ 16

Author(s):

P. E. V. van Walsum ◽

I. Supit

Keyword(s):

Climate Change ◽

Soil Moisture ◽

Dynamic Models ◽

Static Model ◽

Crop Growth ◽

Climate Scenarios ◽

Hydrologic Modelling ◽

Growth Simulation ◽

Crop Simulation ◽

Crop Growth Simulation

Abstract. Hydrologic climate change modelling is hampered by climate-dependent model parameterizations. To reduce this dependency, we extended the regional hydrologic modelling framework SIMGRO to host a two-way coupling between the soil moisture model MetaSWAP and the crop growth simulation model WOFOST, accounting for ecohydrologic feedbacks in terms of radiation fraction that reaches the soil, crop coefficient, interception fraction of rainfall, interception storage capacity, and root zone depth. Except for the last, these feedbacks are dependent on the leaf area index (LAI). The influence of regional groundwater on crop growth is included via a coupling to MODFLOW. Two versions of the MetaSWAP-WOFOST coupling were set up: one with exogenous vegetation parameters, the "static" model, and one with endogenous crop growth simulation, the "dynamic" model. Parameterization of the static and dynamic models ensured that for the current climate the simulated long-term averages of actual evapotranspiration are the same for both models. Simulations were made for two climate scenarios and two crops: grass and potato. In the dynamic model, higher temperatures in a warm year under the current climate resulted in accelerated crop development, and in the case of potato a shorter growing season, thus partly avoiding the late summer heat. The static model has a higher potential transpiration; depending on the available soil moisture, this translates to a higher actual transpiration. This difference between static and dynamic models is enlarged by climate change in combination with higher CO2 concentrations. Including the dynamic crop simulation gives for potato (and other annual arable land crops) systematically higher effects on the predicted recharge change due to climate change. Crop yields from soils with poor water retention capacities strongly depend on capillary rise if moisture supply from other sources is limited. Thus, including a crop simulation model in an integrated hydrologic simulation provides a valuable addition for hydrologic modelling as well as for crop modelling.

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Trends of weather-related impacts on Austrian crop production under changing climate

10.5194/ems2021-287 ◽

2021 ◽

Author(s):

Sabina Thaler ◽

Josef Eitzinger ◽

Gerhard Kubu

Keyword(s):

Climate Change ◽

Winter Wheat ◽

Crop Production ◽

Crop Yields ◽

Weather Conditions ◽

Crop Growth ◽

Risk Indicators ◽

Climate Scenarios ◽

Crop Water

Weather-related risks can affect crop growth and yield potentials directly (e.g. heat, frost, drought) and indirectly (e.g. through biotic factors such as pests). Due to climate change, severe shifts of cropping risks may occur, where farmers need to adapt effectively and in time to increase the resilience of existing cropping systems. For example, since the early 21st century, Europe has experienced a series of exceptionally dry and warmer than usual weather conditions (2003, 2012, 2013, 2015, 2018) which led to severe droughts with devastating impacts in agriculture on crop yields and pasture productivity.Austria has experienced above-average warming in the period since 1880. While the global average surface temperature has increased by almost 1&#176;C, the warming in Austria during this period was nearly 2&#176;C. Higher temperatures, changing precipitation patterns and more severe and frequent extreme weather events will significantly affect weather-sensitive sectors, especially agriculture. Therefore, the development of sound adaptation and mitigation strategies towards a "climate-intelligent agriculture" is crucial to improve the resilience of agricultural systems to climate change and increased climate variability. Within the project AGROFORECAST a set of weather-related risk indicators and tailored recommendations for optimizing crop management options are developed and tested for various forecast or prediction lead times (short term management: 10 days - 6 months; long term strategic planning: climate scenarios) to better inform farmers of upcoming weather and climate challenges.Here we present trends of various types of long-term weather-related impacts on Austrian crop production under past (1980-2020) and future periods (2035-2065). For that purpose, agro-climatic risk indicators and crop production indicators are determined in selected case study regions with the help of models. We use for the past period Austrian gridded weather data set (INCA) as well as different regionalized climate scenarios of the Austrian Climate Change Projections &#214;KS15. The calculation of the agro-climatic indicators is carried out by the existing AGRICLIM model and the GIS-based ARIS software, which was developed for estimating the impact of adverse weather conditions on crops. The crop growth model AQUACROP is used for analysing soil-crop water balance parameters, crop yields and future crop water demand.Depending on the climatic region, a more or less clear shift in the various agro-climatic indices can be expected towards 2050, e.g. the number of "heat-stress-days" for winter wheat increases significantly in eastern Austria. Furthermore, a decreasing trend in maize yield is simulated, whereas a mean increase in yield of spring barley and winter wheat can be expected under selected scenarios. Other agro-climatic risk indicators analysed include pest algorithms, risks from frost occurrence, overwintering conditions, climatic crop growing conditions, field workability and others, which can add additional impacts on crop yield variability, not considered by crop models.

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Estimation of Stomatal Conductance using Crop Water Stress Index based on the Thermal Image at a Leaf Scale

10.5194/egusphere-egu2020-11926 ◽

2020 ◽

Author(s):

Hoejeong Jeong ◽

Jae-Hyun Ryu ◽

Sang-il Na ◽

Jaeil Cho

Keyword(s):

Water Stress ◽

Stomatal Conductance ◽

Thermal Image ◽

Crop Growth ◽

Leaf Temperature ◽

Stress Index ◽

Crop Water ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Crop Water Stress

&#160; In 1980s, Crop Water Stress Index (CWSI) is suggested to indicate the water stress of crops. CWSI is based on the leaf energy balance, which is closely related to leaf temperature. To calculate CWSI, meteorological factors such as air temperature and vapor pressure deficit should be measured besides leaf temperature. As recent technology has been developed, leaf temperature can be easily observed by thermal camera or infrared thermometer. Stomatal conductance (gs, mmol m-2 s-1) is one of the critical factors to understand crop photosynthesis and water demand. In addition, the behaviors of gs can represent the biotic and abiotic plant stresses. In abnormal condition, such as drought, insects or disease, gs getting lower. The observation of gs will make better to evaluate and predict crop growth and conditions. Therefore, the time series data of gs is useful for the monitoring of crop growth and the quick detection of abnormal crop condition in smart-farming system but there are some limitations to measure gs continuously and easily.&#160; We assume that there is some relationship between CWSI and gs because both has strong relation to leaf temperature. Thus, the aim of this study is to investigate possibility of estimation of gs using CWSI which is derived from thermal image. Through the data collected from literatures, negative correlations between CWSI and gs were revealed. The slope of correlation was changed according to crop types. In addition, as a result of simulation, there is almost linear negative relationship between CWSI and gs, and the slope was determined by maximum stomatal conductance (gs_max). Field measurement in this study was also demonstrated to identify such correlation. Further, various methods to measure CWSI were tested. This relationship will contribute to not only monitoring of crop stress for irrigation scheduling in smart farm system but also estimating evapotranspiration, photosynthesis, and crop yield.

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Water Stress Regime of Irrigated Crops Based on Remote Sensing and Ground-Based Data

Agronomy ◽

10.3390/agronomy11061117 ◽

2021 ◽

Vol 11 (6) ◽

pp. 1117

Author(s):

Anatoly Mikhailovich Zeyliger ◽

Olga Sergeevna Ermolaeva

Keyword(s):

Remote Sensing ◽

Water Stress ◽

Crop Yield ◽

Satellite Monitoring ◽

Agricultural Crop ◽

Crop Water ◽

Stress Regime ◽

Irrigation Water Use ◽

Crop Water Stress ◽

Crop Irrigation

In the past few decades, combinations of remote sensing technologies with ground-based methods have become available for use at the level of irrigated fields. These approaches allow an evaluation of crop water stress dynamics and irrigation water use efficiency. In this study, remotely sensed and ground-based data were used to develop a method of crop water stress assessment and analysis. Input datasets of this method were based on the results of ground-based and satellite monitoring in 2012. Required datasets were collected for 19 irrigated alfalfa crops in the second year of growth at three study sites located in Saratovskoe Zavolzhie (Saratov Oblast, Russia). Collected datasets were applied to calculate the dynamics of daily crop water stress coefficients for all studied crops, thereby characterizing the efficiency of crop irrigation. Accordingly, data on the crop yield of three harvests were used. An analysis of the results revealed a linear relationship between the crop yield of three cuts and the average value of the water stress coefficient. Further application of this method may be directed toward analyzing the effectiveness of irrigation practices and the operational management of agricultural crop irrigation.

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An insight to the performance of crop water stress index for olive trees

Agricultural Water Management ◽

10.1016/j.agwat.2012.12.004 ◽

2013 ◽

Vol 118 ◽

pp. 79-86 ◽

Cited By ~ 47

Author(s):

N. Agam ◽

Y. Cohen ◽

J.A.J. Berni ◽

V. Alchanatis ◽

D. Kool ◽

...

Keyword(s):

Water Stress ◽

Stress Index ◽

Crop Water ◽

Crop Water Stress Index ◽

Water Stress Index ◽

Olive Trees ◽

Crop Water Stress

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Response of four grain legumes to water stress in south-eastern Queensland. IV. Interaction with sowing arrangement

Australian Journal of Agricultural Research ◽

10.1071/ar9830661 ◽

1983 ◽

Vol 34 (6) ◽

pp. 661 ◽

Cited By ~ 2

Author(s):

RJ Lawn

Keyword(s):

Water Stress ◽

Population Density ◽

Water Use ◽

Spatial Arrangement ◽

Crop Growth ◽

Yield Response ◽

Crop Water ◽

Area Index ◽

Crop Water Use ◽

South Eastern

The effect of spatial arrangement and population density on growth, dry matter production, yield and water use of black gram (Vigna mungo cv. Regur), green gram (V. radiata cv. Berken), cowpea (V. unguiculata CPI 28215) and soybean (Glycine rnax CP126671), under irrigated, rain-fed fallowed and rain-fed double-cropped culture was evaluated at Dalby in south-eastern Queensland. Equidistant spacings increased initial rates of leaf area index (LAI) development and crop water use compared with 1-m rows at the same population densities. In the irrigated and rain-fed fallowed treatments, where more water was available for crop growth, both seed yields and total crop water use were higher in the equidistant spacings. However, in the double-cropped treatment, where water availability was limited, there was no yield difference between rows and equidistant spacings, primarily because initially faster growth in the latter was offset by more severe water stress later in the season. Higher population density also increased initial crop growth rate and water use, particularly in the equidistant spacings. However, there was no significant yield response to density, presumably because subsequent competition for light/ water offset initial effects on growth. Although absolute yield differences existed between legume cultivars within cultural treatments, there were no significant differential responses to either spatial arrangement or population density among these four cultivars.

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