Factors Constraining Timely Sowing of Wheat as an Adaptation to Climate Change in Eastern India

Newport, Danielle; Lobell, David B.; Srivastava, Amit K.; Rao, Preeti; Umashaanker, Maanya; Malik, R. K.; McDonald, Andrew J.; Jain, Meha

doi:10.1175/wcas-d-19-0122.1

Cited by 21 publications

(19 citation statements)

References 30 publications

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“…There are several reasons our model may perform better through time in the west compared with the east. First, there is more variability in sowing patterns through time in the east; previous studies have shown that wheat planting date in the eastern IGP is sensitive to the timing of monsoon onset, and thus may fluctuate from year to year [24]. Second, it is possible that our accuracies are lower in the eastern IGP partly due to lower data quality.…”

Section: Discussionmentioning

confidence: 94%

“…Studies have also shown that it is possible for classification models to transfer well to other sites and time periods [23], increasing our ability to produce large-scale maps of zero tillage use across space and time. Yet, it is unclear how well classification models, such as random forest, may generalize in smallholder systems given the large heterogeneity in farm management, even across small spatial scales [24,25] and across multiple years [26].…”

Section: Introductionmentioning

confidence: 99%

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Using Sentinel-2 to Track Field-Level Tillage Practices at Regional Scales in Smallholder Systems

et al. 2021

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Zero tillage is an important pathway to sustainable intensification and low-emission agriculture. However, quantifying the extent of zero tillage adoption at the field scale has been challenging, especially in smallholder systems where field sizes are small and there is limited ground data on zero tillage adoption. Remote sensing offers the ability to map tillage practices at large spatio-temporal scales, yet to date no studies have used satellite data to map zero tillage adoption in smallholder agricultural systems. In this study, we use Sentinel-2 satellite data, random forest classifiers, and Google Earth Engine to map tillage practices across India’s main grain producing region, the Indo-Gangetic Plains. We find that tillage practices can be classified with moderate accuracy (an overall accuracy of 75%), particularly in regions with relatively large field sizes and homogenous crop management practices. We find that models that use satellite data from only the first half of the growing season perform as well as models that use data throughout the growing season, allowing for the creation of within-season tillage maps. Finally, we find that our model can generalize well through time in the western IGP, with reductions in accuracy of only 5–10%. Our results highlight the ability of Sentinel-2 satellite data to map tillage practices at scale, even in smallholder systems where field sizes are small and cropping practices are heterogeneous.

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Section: Discussionmentioning

confidence: 94%

Section: Introductionmentioning

confidence: 99%

Using Sentinel-2 to Track Field-Level Tillage Practices at Regional Scales in Smallholder Systems

et al. 2021

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“…Field management across this region is extremely heterogeneous, making it a complex system in which to map tillage practices using one universal algorithm. The sowing dates of wheat vary widely across the study region, ranging from mid-November to early January [ 35 ]. Wheat variety planted and input use, including fertilizer and irrigation, is also highly variable, with significant heterogeneity even across neighboring fields [ 19 , 35 ].…”

Section: Methodsmentioning

confidence: 99%

“…The sowing dates of wheat vary widely across the study region, ranging from mid-November to early January [ 35 ]. Wheat variety planted and input use, including fertilizer and irrigation, is also highly variable, with significant heterogeneity even across neighboring fields [ 19 , 35 ]. Most farmers clear rice residues prior to sowing wheat, though some farmers leave partial residues in field.…”

Section: Methodsmentioning

confidence: 99%

Using Sentinel-1, Sentinel-2, and Planet satellite data to map field-level tillage practices in smallholder systems

et al. 2022

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Remote sensing can be used to map tillage practices at large spatial and temporal scales. However, detecting such management practices in smallholder systems is challenging given that the size of fields is smaller than historical readily-available satellite imagery. In this study we used newer, higher-resolution satellite data from Sentinel-1, Sentinel-2, and Planet to map tillage practices in the Eastern Indo-Gangetic Plains in India. We specifically tested the classification performance of single sensor and multiple sensor random forest models, and the impact of spatial, temporal, or spectral resolution on classification accuracy. We found that when considering a single sensor, the model that used Planet imagery (3 m) had the highest classification accuracy (86.55%) while the model that used Sentinel-1 data (10 m) had the lowest classification accuracy (62.28%). When considering sensor combinations, the model that used data from all three sensors achieved the highest classification accuracy (87.71%), though this model was not statistically different from the Planet only model when considering 95% confidence intervals from bootstrap analyses. We also found that high levels of accuracy could be achieved by only using imagery from the sowing period. Considering the impact of spatial, temporal, and spectral resolution on classification accuracy, we found that improved spatial resolution from Planet contributed the most to improved classification accuracy. Overall, it is possible to use readily-available, high spatial resolution satellite data to map tillage practices of smallholder farms, even in heterogeneous systems with small field sizes.

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“…Number of farmers who sowed wheat after 30th November 2351 100 Source: Authors' calculation using the LDS data Could it be that the farmers in Bihar and EUP do not realize the negative impact of late sowing of wheat on crop yields? In a survey of 256 farmers in the Arrah district of Bihar, Newport et al (2020) found that most farmers realize there are benefits to sowing earlier.…”

Section: Unavailability Of Seed 59mentioning

confidence: 99%

Seeds, water, and markets to increase wheat productivity in Bihar, India

Kishore¹,

Singh²

2021

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Wheat yields are low and variable in the rice-wheat cropping systems in the lower Indo-Gangetic plains (IGP) covering Bihar and Eastern Uttar Pradesh (EUP) in India and the Terai areas of Nepal. Since wheat is the largest crop of the region and the most important source of calories after rice, its productivity plays a big role in ensuring food security and increasing farmers' income. This paper uses data from a recent large primary survey of a representative sample of 7,649 wheat growers from the region to identify four main reasons for the low productivity of wheat: 1) late sowing of the crop due mainly to the late transplantation and harvest of paddy; 2) insufficient irrigation of wheat; 3) persistent use of old seed varieties, and 4) poor incentives for input intensification due to low price realization by farmers. We argue that the high cost of diesel-powered irrigation is a major reason for the late transplantation of paddy and under-irrigation of wheat. A concerted approach that includes a) public investments in the electrification of irrigation and rationalization of electricity subsidies, b) incentives to promote private sector participation in input markets to accelerate the adoption of improved seeds, c) scaling up of institutional innovations (like FPOs) to aggregate marketable surpluses of smallholder farmers, and d) the creation of competitive agricultural markets to ensure better price realization is required to increase wheat yields and farmers' incomes from wheat production.

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Factors Constraining Timely Sowing of Wheat as an Adaptation to Climate Change in Eastern India

Cited by 21 publications

References 30 publications

Using Sentinel-2 to Track Field-Level Tillage Practices at Regional Scales in Smallholder Systems

Using Sentinel-2 to Track Field-Level Tillage Practices at Regional Scales in Smallholder Systems

Using Sentinel-1, Sentinel-2, and Planet satellite data to map field-level tillage practices in smallholder systems

Seeds, water, and markets to increase wheat productivity in Bihar, India

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