Appraisal of Multiple Scenarios for Rice Plant Growth in Punjab Pakistan Through RS/GIS Techniques

Abstract

Rice has become an essential food/crop for 3 billion population of the world. Punjab province in Pakistan is famous for production of high quality rice globally, but economic indicators are low toward rice contribution in regional economy due to various climatic and physical factors. The contribution of rice in Gross Domestic Product (GDP) of Pakistan is only 1.3-1.6% which is very less however, efforts are on the way at governmental level to enhance the productions. In this research, we tried to explore various scenarios to improve the rice yield using satellite imagery in collaboration with real time field observations. These scenarios include 1) the impact assessment of ecological parameters on the rice yield through Carnegie-Ames-Stanford Approach (CASA) model 2) the identification of suitable site for rice cultivation through Multi-Criteria Evaluation (MCE) techniques 3) yield estimation using the rice plant spectral responses and 4) recognition of vulnerable sites under Yellow Stem Borer (YSB) attacks to save the rice crop canopies. Rice cultivation season was calculated using Moderate Resolution Imaging Spectro-radiometer (MODIS) time series datasets which showed that the rice cultivation could be exercised during the months April to November in the study site but the actual rice cultivation starts after May 20 of each year to save the crop from borer’s attacks following the Punjab rice ordinance, 1974. Net Primary Production (NPP) is an important indicator of the supply of food and wood. We used a hierarchy model and real time field observations to estimate NPP using satellite imagery. NPP incorporates various scenarios effecting the rice plant growth including 1) solar radiations 2) ground heat, sensible heat and latent heat fluxes 3) water availability 4) light use efficiency and 5) the net productions. According to NPP model, net radiations received by rice crop canopies were estimated as 27,428 Wm−2 (215.4 Wm−2 as averaged) throughout the rice cultivation period (RCP), including 23,168 Wm−2 (118.3 Wm−2 as averaged) as shortwave and 4260 Wm−2 (34.63 Wm−2as averaged) as longwave radiations. Soil, sensible and latent heat fluxes were approximated as 3324 Wm−2, 16,549 Wm−2, and 7554 Wm−2 respectively. Water stress on rice crops varied between 0.5838 and 0.1218 from the start to the end of the Rice Cultivation Period (RCP). Biomass generation declined from 6.09–1.03 g/m2 in the tillering and ripening stages respectively. We added a soil suitability constant (ħα) into the CASA model to achieve a more precise 2 estimates of yield. The spatial distribution of rice cultivation as per suitability zone was: the total area under investigation was 13657 km2, out of which 931.61 km2 (6.8%) was found to be least suitable, 3316.69 km2 (24.2%) was moderately suitable, 6019.63 km2 (44%) was highly suitable and 3395.28 km2 (24.85%) was not suitable for rice crop cultivation. Results showed that highly suitable area was characterized by a temperature range between 21-32°C, soil pH level between 5.5-7.2, soil type was <78% clay and the soil was imperfectly drained. We compared land suitability map covering the complete land use with rice cultivated area only and found the results as follows: 592 km2 (5.9%) rice cultivation was in least suitable, 4385 km2 (44%) cultivation was in highly suitable, 2210 km2 (23.2%) cultivation was in moderately suitable and 1674 km2 (16.8%) cultivation was in not suitable regions.1674 km2 was not suitable (NS), 592 km2 was less suitable (LS), 2210 km2 was moderately suitable (MS) and 4385 km2 was highly suitable (HS) soil type with ħα ranges of 0.05–0.25, 0.4–0.6, 0.7–0.75 and 0.85–0.95 of the CASA based yield, respectively. We estimated net production as 1.63 million tons, as per 0.46 ton/ha, 1.2 ton/ha 1.9 ton/ha and 2.4 ton/ha from NS, LS, MS and HS soil types, respectively. The results obtained through the improved CASA model, by addition of the constant ħα, are likely to be useful for agronomists by providing more accurate estimates of NPP