Limitations to adjusting growing periods in different agroecological zones of Pakistan

Shah, Hassnain; Siderius, Christian; Hellegers, Petra

doi:10.1016/j.agsy.2021.103184

Cited by 12 publications

(10 citation statements)

References 49 publications

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“…There is still potential to improve regional agricultural water productivity, although the financial feasibility of water conservation measures in a region with low farm-level profitability remains a matter of concern 36 , and the effect on water consumption at the basin scale may remain limited 37 . Given the strong and increasing dependence on meltwater and groundwater at the onset of the kharif season during the pre-monsoon season for rice and cotton in the Indus and rice in the Ganges basin, a change in crop type or shift in sowing date to later in the year can provide potential solutions 38 , in particular when cropping cycles get shorter in a warmer climate. The Hindu Kush, Karakoram and Himalayan mountain ranges have a large untapped hydropower potential 39 , which is rapidly being deployed.…”

Section: Adaptationmentioning

confidence: 99%

South Asian agriculture increasingly dependent on meltwater and groundwater

Lutz

Immerzeel

Siderius³

et al. 2022

Nat. Clim. Chang.

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Section: Adaptationmentioning

confidence: 99%

South Asian agriculture increasingly dependent on meltwater and groundwater

Lutz

Immerzeel

Siderius³

et al. 2022

Nat. Clim. Chang.

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“…Most papers confirm that farmers are aware that the sustainability of their current livelihood and traditional cropping system is under threat due to changing temperature and precipitation patterns (Shah et al 2021), asking for a change in farm practices to design effective adaptation measures (Cullen and Anderson 2017). As a common trend, farmers tend to invest (limited) resources into climate change adaptation measures depending on whether they perceive risk and how they think it will affect their livelihood (Chen and Whalen 2016).…”

Section: Which Adaptation Measures Are Implemented By Farmers?mentioning

confidence: 99%

On farmers’ perceptions of climate change and its nexus with climate data and adaptive capacity. A comprehensive review

Ricart

Castelletti

Gandolfi

2022

Environ. Res. Lett.

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Farmers’ perception of climate change is crucial in adaptation intention and process. However, farmers’ perceptions may not be timely, accurate and systematically consistent with the direction and significance of observational records. Although some research compared farmers’ perceptions and climate data, little attention has been paid to comprehensibly analyse both data sources discrepancies based on empirical studies results. By combining bibliometrics and a systematic review approach, we identify which approaches are used to compare perceived and observed data, how both patterns have been mutually evolved, which factors determine their (in)consistency, and if their accordance and robustness affect farmers’ adaptive capacity. We analyse a portfolio of 147 papers collected from the Scopus library catalogue since 2000. The bibliometric analysis was coupled with an exploratory analysis of 98 papers selected from the original portfolio. The literature is extensive, fast-growing, and spans several disciplines. We identify four consolidated research lines: i) perceived risk and farmers’ adaptive capacity nexus, ii) crop vulnerability due to temperature increase and erratic rainfall patterns, iii) forecasting use and influence in farmers’ decisions, and iv) climate change awareness conditioning farmers’ profiles. Nonetheless, we observe some research gaps: 1) a conceptual mismatch in ‘normal pattern’ or ‘drought’ meaning, 2) poor or limited data from meteorological stations, 3) overlook or oversimplification of local knowledge in describing perception, 4) farmers’ memory weaknesses to keep track of climate alterations, and 5) a geographical dissonance in favour of Global South regions. Our science-metric study also reveals some research questions to be consolidated: Can the perception of extreme events increase climate change awareness? Can greater awareness reduce discrepancy with observed data? How do heuristics and socio-psychological filters influence farmers’ awareness and interpretation of climate data? We suggest putting major efforts into reinforcing these research lines as part of a novel domain-dependent trend to reduce the discrepancy.

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“…Similar analyses have been performed for different crops: for example, Ortiz-Monasterio et al [7] quantified that wheat yield decreases by about 1% for every day of late sowing in Northern India, because of non-optimal climate conditions in the final growing phase. Frequently, the temporal shift of sowing and harvesting dates has been adopted as local adaptation strategy to climate change, e.g., the sorghum production in Italy [8], rice in Sri Lanka [9], soybean in Austria [10], oilseed crops in the U.S. South-West [11]; however, many limitations still constrain the adjustment of growing periods as a reliable strategy to prevent local climate-driven yield losses [12].…”

Section: Introductionmentioning

confidence: 99%

Analysis of Maize Sowing Periods and Cycle Phases Using Sentinel 1&2 Data Synergy

et al. 2022

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The reliability of crop-growth modelling is related to the accuracy of the information used to describe the agricultural growing phases. A proper knowledge of sowing periods has a significant impact on the effectiveness of any analysis based on modeled crop growth. In this work, an estimation of maize actual sowing periods for year 2019 is presented, combining the optical and radar information from Sentinel-1 and Sentinel-2. The crop classification was conducted according to the information provided by local public authorities over an area of 30 km × 30 km, and 1154 maize fields were considered within the analysis. The combined use of NDVI and radar time series enabled a high-resolution assessment of sowing periods and the description of maize emergence through the soil, by detecting changes in the ground surface geometry. A radar-based index was introduced to detect the periods when plants emerge through the soil, and the sowing periods were retrieved considering the thermal energy needed by seeds to germinate and the daily temperatures before the emergence. Results show that 52% of maize hectares were sowed in late April, while about 30% were sowed during the second half of May. Sentinel-1 appears more suitable to describe the late growing phase of maize, since the radar backscattering is sensitive to the dry biomass of plants while the NDVI decreases because of the chromatic change of leaves. This study highlights the potential of synergy between remote sensing sources for agricultural management policies and improving the accuracy of crop-related modelling.

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Limitations to adjusting growing periods in different agroecological zones of Pakistan

Cited by 12 publications

References 49 publications

South Asian agriculture increasingly dependent on meltwater and groundwater

South Asian agriculture increasingly dependent on meltwater and groundwater

On farmers’ perceptions of climate change and its nexus with climate data and adaptive capacity. A comprehensive review

Analysis of Maize Sowing Periods and Cycle Phases Using Sentinel 1&2 Data Synergy

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