scholarly journals Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

2016 ◽  
Author(s):  
M. J. D. Hack-ten Broeke ◽  
J. G. Kroes ◽  
R. P. Bartholomeus ◽  
J. C. van Dam ◽  
A. J. W. de Wit ◽  
...  
Keyword(s):  
The Netherlands ◽  
Crop Yield ◽  
Groundwater Level ◽  
Agricultural Production ◽  
Root Zone ◽  
Crop Growth ◽  
Extreme Weather Events ◽  
Yield Reduction ◽  
Soil Units ◽  
The Impact

Abstract. For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

scholarly journals Quantification of the impact of hydrology on agricultural production as a result of too dry, too wet or too saline conditions

SOIL ◽  
2016 ◽  
Vol 2 (3) ◽  
pp. 391-402 ◽  
Author(s):  
Mirjam J. D. Hack-ten Broeke ◽  
Joop G. Kroes ◽  
Ruud P. Bartholomeus ◽  
Jos C. van Dam ◽  
Allard J. W. de Wit ◽  
...  
Keyword(s):  
The Netherlands ◽  
Crop Yield ◽  
Groundwater Level ◽  
Agricultural Production ◽  
Root Zone ◽  
Crop Growth ◽  
Extreme Weather Events ◽  
Yield Reduction ◽  
Soil Units ◽  
The Impact

Abstract. For calculating the effects of hydrological measures on agricultural production in the Netherlands a new comprehensive and climate proof method is being developed: WaterVision Agriculture (in Dutch: Waterwijzer Landbouw). End users have asked for a method that considers current and future climate, that can quantify the differences between years and also the effects of extreme weather events. Furthermore they would like a method that considers current farm management and that can distinguish three different causes of crop yield reduction: drought, saline conditions or too wet conditions causing oxygen shortage in the root zone. WaterVision Agriculture is based on the hydrological simulation model SWAP and the crop growth model WOFOST. SWAP simulates water transport in the unsaturated zone using meteorological data, boundary conditions (like groundwater level or drainage) and soil parameters. WOFOST simulates crop growth as a function of meteorological conditions and crop parameters. Using the combination of these process-based models we have derived a meta-model, i.e. a set of easily applicable simplified relations for assessing crop growth as a function of soil type and groundwater level. These relations are based on multiple model runs for at least 72 soil units and the possible groundwater regimes in the Netherlands. So far, we parameterized the model for the crops silage maize and grassland. For the assessment, the soil characteristics (soil water retention and hydraulic conductivity) are very important input parameters for all soil layers of these 72 soil units. These 72 soil units cover all soils in the Netherlands. This paper describes (i) the setup and examples of application of the process-based model SWAP-WOFOST, (ii) the development of the simplified relations based on this model and (iii) how WaterVision Agriculture can be used by farmers, regional government, water boards and others to assess crop yield reduction as a function of groundwater characteristics or as a function of the salt concentration in the root zone for the various soil types.

A parametric insurance framework based on remote-sensing observations to mitigate drought impacts through risk financing

2020 ◽  
Author(s):  
Beatrice Monteleone ◽  
Mario Martina ◽  
Brunella Bonaccorso
Keyword(s):  
Remote Sensing ◽  
Crop Yield ◽  
Agricultural Production ◽  
Growth Period ◽  
Crop Growth ◽  
Extreme Weather Events ◽  
Economic Losses ◽  
Drought Risk ◽  
Drought Impacts ◽  
Parametric Programs

<p>Agricultural production is highly sensitive to extreme weather events such as droughts, floods and storms. According to the Food and Agriculture Organization, between 2005 and 2015 natural disasters cost the agricultural sectors of developing country economies a staggering $96 billion in damaged or lost crop and livestock production. Drought was one of the leading culprits. Eighty-three percent of all drought-caused economic losses documented by FAO's study were absorbed by agriculture, with a price tag of $29 billion. Since extreme droughts are expected to increase worldwide both in number and severity, the development of appropriate strategies to reduce and mitigate drought impacts on agricultural production will be essential to enable farmers to quickly recover from the disaster. There is growing interest in insurance as an instrument for managing drought risk in agriculture. Insurance is a self-reliant mitigation measure that increases society's resilience, particularly in the financial sector. There are two main options of crop risk transfer solutions: indemnity-based programs, in which the basis for compensation is the actual loss; and weather index-based (or parametric) programs. Parametric programs are based on variables called indices, often retrieved from remote-sensing observations. Indices should be highly correlated with agricultural losses. A parametric policy for drought pays out if a specific value of the index is achieved in a specific period. Index-based insurance shows various attractive features: the value of the index cannot be influenced by farmers, indemnities are based on observable variables (the indices), on-farm inspections to assess the damages are no more necessary and finally funds to recover from the disaster are provided quickly.</p><p>The aim of this work is the design of a parametric insurance framework against drought to be applied in the Caribbean region as well as in other regions with similar conditions. Initially a new drought index, the Probabilistic Precipitation and Vegetation Index (PPVI) was developed to identify drought. PPVI was computed combining two consolidated drought indices, the Standardized Precipitation Index (SPI) and the Vegetation Health Index (VHI). SPI was calculated from precipitation retrieved from satellite (the Climate Hazard Group Infrared Precipitation dataset was used) and VHI is already a remote-sensing product. Then a framework allowing an objective identification of drought weeks was implemented. The framework was used in combination with PPVI and the model was calibrated in order to reproduce past drought events at specific locations. A relationship between drought and negative crop yield anomalies was established. Significant crop growth periods were taken into consideration: establishment, vegetative, flowering and yield formation. The probability of having a negative crop yield anomaly when a significant growth period was in drought was computed. The sensitivity to drought of each crop growth period was evaluated based on this probability. In the end a loss index to relate drought with yield reduction suffered by farmers was developed. The entire framework was tested in the Dominican Republic and cereals losses (maize and sorghum) were evaluated. Results were promising.</p>

scholarly journals Climate change and agroecosystems: the effect of elevated atmospheric CO2 and temperature on crop growth, development, and yield

2005 ◽  
Vol 35 (3) ◽  
pp. 730-740 ◽  
Author(s):  
Nereu Augusto Streck
Keyword(s):  
Climate Change ◽  
Crop Yield ◽  
Co2 Concentration ◽  
Crop Growth ◽  
Atmospheric Co2 ◽  
C3 Plants ◽  
Elevated Atmospheric Co2 ◽  
Growth Development ◽  
Carbon Dioxide Co2 ◽  
The Impact

The amount of carbon dioxide (CO2) of the Earth´s atmosphere is increasing, which has the potential of increasing greenhouse effect and air temperature in the future. Plants respond to environment CO2 and temperature. Therefore, climate change may affect agriculture. The purpose of this paper was to review the literature about the impact of a possible increase in atmospheric CO2 concentration and temperature on crop growth, development, and yield. Increasing CO2 concentration increases crop yield once the substrate for photosynthesis and the gradient of CO2 concentration between atmosphere and leaf increase. C3 plants will benefit more than C4 plants at elevated CO2. However, if global warming will take place, an increase in temperature may offset the benefits of increasing CO2 on crop yield.

Crop Yield Estimation Using Multi-source Satellite Image Series and Deep Learning

2020 ◽  
Author(s):  
Gohar Ghazaryan ◽  
Sergii Skakun ◽  
Simon König ◽  
Ehsan Eyshi Rezaei ◽  
Stefan Siebert ◽  
...  
Keyword(s):  
Time Series ◽  
Agricultural Production ◽  
Remotely Sensed ◽  
Growth Conditions ◽  
Crop Growth ◽  
County Level ◽  
Yield Estimation ◽  
Field Level ◽  
The Impact ◽  
Level Analysis

<p>Timely monitoring of agricultural production and early yield predictions are essential for food security. Crop growth conditions and yield are related to climate variability and extreme events. Remotely sensed time-series can be used to study the variability in crop growth and agricultural production. However, the choice of remotely sensed data and methods is still an issue, as different datasets have different spatiotemporal characteristics. Thus, our primary goal was to study the impact of applying different remotely sensed time series on yield estimation in U.S. at the county and field scale. Furthermore, the impact of crop growth conditions on yield variability was assessed. For county-level analysis, MODIS-based surface reflectance, Land Surface Temperature, and Evapotranspiration time series were used as input datasets. Whereas field-level analysis was carried out using NASA’s Harmonized Landsat Sentinel-2 (HLS) product. 3D convolutional neural network (CNN) and CNN followed by long-short term memory (LSTM) were used. For county-level analysis, the CNN-LSTM model had the highest accuracy, with a mean percentage error of 10.3% for maize and 9.6% for soybean. This model presented robust results for the year 2012, which is considered a drought year. In the case of field-level analysis, all models achieved accurate results with R<sup>2 </sup>exceeding 0.8 when data from mid growing season were used. The results highlight the potential of yield estimation at different management scales.</p>

scholarly journals RESILIENCE OF AGRICULTURE FARMERS FOR CROP PRODUCTION IN RESPONSES TO CLIMATE CHANGE IMPACT ON SOUTH-EASTERN COAST OF BANGLADESH

2020 ◽  
Vol 4 (1) ◽  
pp. 28-37
Author(s):  
Prabal Barua ◽  
Syed Hafizur Rahman
Keyword(s):  
Climate Change ◽  
Agricultural Production ◽  
Crop Production ◽  
Yield Loss ◽  
Research Work ◽  
Eastern Coast ◽  
Yield Reduction ◽  
Dual Culture ◽  
The Impact ◽  
Adaptation Options

Coastal people of Bangladesh have been experiencing from lower crop productivity and fewer cropping intensity because of different climatic vulnerabilities. The research work was carried out in Banskhali upazila of Chattogram district and Teknaf of Cox’s Bazar district to assess the impact of climate change on crop production process and to suggest suitable coping strategies and adaptation options for advancing the coastal agriculture for increased agricultural production. To attain the objectives of the research, the author were collected randomly 240 sampled respondents using pre-tested interview schedule. Long-term data/information on climate change showed that there is a trend of temperature rise and erratic rainfall. Participants stated that the current climate in the study area behaving differently than in the past on a number of climate risk factors like increased temperature, frequent drought, changes in seasonal rainfall pattern, long dry spells, increase of soil salinity, increase of tidal surges affecting crop production. The study showed that the main reasons of yield reduction (20-40 % yield loss) in T. aman crop are erratic rainfall, increased intensity and frequency of drought, salinity, floods, cyclone, use of local varieties, increased incidences of pests & diseases etc in the context of climate change. Average yield level of HYV Boro is being affected (20-40 % yield loss) by high temperature and salinity and that of T.Aus/Aus crop is being affected (20-40 % yield loss) by tidal surge. Vegetables, pulses and oilseed crops are being affected (40-60 % yield loss) by soil wetness, excessive rainfall and water-logging in the selected areas. Sorjan system of cropping, rice-fish dual culture, utilization of bunds as vegetables/spices production in gher areas, floating bed agriculture and homestead gardening with introduction of salt-tolerant & drought tolerant crop varieties have been identified as potential adaptation options for development of coastal agriculture for increased agricultural production in attaining food security.

scholarly journals Climate risk services for cereal farming

2021 ◽  
Vol 18 ◽  
pp. 21-25
Author(s):  
Anne Gobin ◽  
Nicoletta Addimando ◽  
Christoph Ramshorn ◽  
Karl Gutbrod
Keyword(s):  
Agricultural Production ◽  
Weather Conditions ◽  
Growing Season ◽  
Crop Growth ◽  
Extreme Weather Events ◽  
Phenological Stages ◽  
Arable Crops ◽  
Frost Risk ◽  
Weather Events ◽  
The World

Abstract. Agricultural production is largely determined by weather conditions during the crop growing season. An important aspect of crop yield estimation concerns crop growth development. The occurrence of meteorological events such as frosts, droughts or heat stress during the crop life cycle or during certain phenological stages helps explain yield fluctuations of common arable crops. We developed a methodology and visualisation tool for risk assessment, and tested the workflow for drought and frost risk for winter wheat, winter barley and grain maize in Belgium. The methodology has the potential to be extended to other extreme weather events and their impacts on crop growth in different regions of the world.

scholarly journals Impact of capillary rise and recirculation on crop yields

2017 ◽  
Author(s):  
Joop Kroes ◽  
Iwan Supit ◽  
Jos Van Dam ◽  
Paul Van Walsum ◽  
Martin Mulder
Keyword(s):  
Soil Water ◽  
Crop Yields ◽  
Root Zone ◽  
Capillary Rise ◽  
Shallow Groundwater ◽  
Flow Regimes ◽  
Crop Growth ◽  
Upward Flow ◽  
The Impact ◽  
Percolation Water

Abstract. This paper describes impact analyses of various soil water flow regimes on grass, maize and potato yields in the Dutch delta, with a focus on upward soil water flows capillary rise and recirculation towards the rootzone. Flow regimes are characterised by soil composition and groundwater depth and derived from a national soil database. The intermittent occurrence of upward flow and its influence on crop growth are simulated with the combined SWAP-WOFOST model using various boundary conditions. Case studies and model experiments are used to illustrate impact of upward flow on yield and crop growth. This impact is clearly present in situations with relatively shallow groundwater levels (85 % of the Netherlands), where capillary rise is the main flow source; but also in free-draining situations the impact of upward flow is considerable. In the latter case recirculated percolation water is the flow source. To make this impact explicit we implemented a synthetic modelling option that stops upward flow from reaching the root zone, without inhibiting percolation. Such a hypothetically moisture-stressed situation compared to a natural one in the presence of shallow groundwater shows mean yield reductions for grassland, maize and potatoes of respectively 25, 4 and 15 % or respectively about 3.2, 0.5 and 1.6 ton dry matter per ha. About half of the withheld water behind these yield effects comes from recirculated percolation water as occurs in free drainage conditions and the other half comes from increased upward capillary rise. Soil water and crop growth modelling should consider both capillary rise from groundwater and recirculation of percolation water as this improves the accuracy of yield simulations. This also improves the accuracy of the simulated groundwater recharge: neglecting these processes causes overestimates of 17 % for grassland and 46 % for potatoes, or 70 and 34 mm a−1, respectively.

scholarly journals Impact of Industrial Air Pollution on Agricultural Production

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 639
Author(s):  
Wei Wei ◽  
Zanxin Wang
Keyword(s):  
Air Pollution ◽  
Crop Yield ◽  
Agricultural Production ◽  
Economic Losses ◽  
Absolute Amount ◽  
Corn Yield ◽  
Industrial Air Pollution ◽  
Frontier Analysis ◽  
The Impact ◽  
The Relationship

This paper aimed to study how industrial air pollution impacts crop yield by investigating the relationship between output and changes in factors. A translog production function was estimated in the context of stochastic frontier analysis using data collected from a field survey in the case of corn. The interaction between the factors as well as the impact of industrial air pollution on the relationship between factors was analyzed using numerical simulation, followed by the estimation of economic losses of corn yield in the polluted area. Results show that industrial air pollution causes a decrease in crop yield for two reasons. First, industrial air pollution changes the output elasticities of production factors and reduces its absolute amount. Second, industrial air pollution causes the relationship between labor and capital, labor and chemicals, capital and seeds to change from substitutable to complementary; it also resulted in an opposite result for the relationship between capital and chemicals. The paper presents a new explanation of how industrial air pollution affects agricultural production from an economic perspective.

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