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One of the greatest challenges of the twenty-first century, doubling food production from already depleted resources!
Some quick facts ...
Some quick facts ...
There will be a global food crisis in less than 30 years!
The global food demand is projected to be doubled by 2050 (causes: population growth (30%), dietary shift mainly toward Meat (70%)! (Tilman and Clark , 2015)
We need irrigated agriculture to produce more food!
Irrigated agriculture is at least twice as productive per unit of land as rainfed agriculture! (world bank, water in agriculture)
But then we would have a water crisis!
80–90% of freshwater consumptive uses are devoted to irrigation globally! (Foley, et al., 2009)
Climate change makes the situation even worse!
~70% of the areas that were irrigated in 1995 will require more irrigation water by 2070 (Döll and Siebert, 2002)
Irrigation is expected to increase by (+30 %) in Europe under a high emission scenario (Busschaert, metal., 2022)
The completion for water resources is already intense is projected to worsen in the future, below map shows the ratio of the demand for the water to the available water (water stress) (World resources institute, Aquaduct)
To enforce rule for governing water extraction we first need to monitor farmer's water withdrawal ...
in situ measurements are difficult because:
It is labor-intensive and expensive even for the developing countries
There are illegal water withdrawal from surface and groundwater
Farmers may oppose or lobby against the installation of meters due to concerns about increased future regulation (Foster et al,., 2020)
Percentage of groundwater irrigation wells with an attached flow metering device for each state in the United States (Foster et al,., 2020)
we can use models to estimate the irrigation water use, however, ...
Dancing crop circles, seen by #Sentinel2. Küçükyıldız, Turkey. Images processed in @sentinel_hub (Annamaria Luongo)
Modeling irrigation is really challenging:
Cultivated crops are constantly changing (crop rotation)
Farmers' irrigation decision is not necessarily related to the crop water demand
Most of the models estimate the required irrigation and not the actual irrigation
Crop cycles near #Bakersfield, CA, NDVI seen by #Sentinel2 created @sentinel_hub (Valtzen)
Irrigation studies
AMSR2 satellite soil moisture data is used to quantify irrigation amount.
SM2RAIN is able to capture irrigation pattern consistent with observations.
Nearly zero irrigation amount is estimated at the non-irrigated pixels.
Weekly signal are observed in soil moisture fluctuation at irrigated pixels.
Coarse resolution of microwave data hampers the usage of the model in small parcels.
Plot scale irrigation signal can not be detected using SMAP enhanced 9km product
The irrigation signal is more evident in the SMAP-Sentinel1 soil moisture variation (second moment of SM time series)
Human activity and land management over irrigated cropland can impact VWC and soil moisture retrieval
Using concurrent observations of vegetation water content can significantly improve soil moisture retrieval exclusively over the irrigated croplands
Quantifying the irrigation water use by assimilating SMAP-Sentinel1 1km soil moisture product
Quantifying the irrigation water use by assimilating SMAP-Sentinel1 1km soil moisture product
a particle batch smoother data assimilation approach is used to quantify the irrigation water use by assimilating SMAP-S1 1km soil moisture data with VIC LSM
the VIC model calibrated against SMAP observation during the rainy season to remove the bias between the model and SMAP-S1 SM observations
Synthetic study shows that the model is able to reproduce the SM time series and the irrigation water use accurately
SMAP-S1 observations maintain irrigation signals, but not enough to back out the full amount of irrigation
underestimation of IWU can also be attributed to the low efficiency of irrigation application,
Our Irrigation studies in the social media
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