Abstract
There is a global realization in all governmental setups of the need to provoke the efficient appraisal of crop water budgeting in order to manage water resources efficiently. This study aims to use the satellite remote sensing techniques to determine the water deficit in the crop rich Lower Bari Doab Canal (LBDC) command area. Crop classification was performed using multi-temporal NDVI profiles of Landsat-8 imagery by distinguishing the crop cycles based on reflectance curves. The reflectance-based crop coefficients (Kc) were derived by linear regression between normalized difference vegetation index (NDVI) cycles of the Moderate Resolution Imaging Spectroradiometer (MODIS) MOD13Q1 and MYD13Q1 products and Food and Agriculture Organization (FAO) defined crop coefficients. A MODIS 250 m NDVI product of the last 10 years (2004-2013) was used to identify the best performing crop cycle using Fourier filter method. The meteorological parameters including rainfall and temperature substantiated the reference evapotranspiration (ET0) calculated using the Hargreaves method. The difference of potential ET and actual ET, derived from the reflectance-based Kc calculated using reference NDVI and current NDVI, generates the water deficit. Results depict the strong correlation between ET, temperature and rainfall, as the regions having maximum temperature resulted in high ET and low rainfall and vice versa. The derived Kc values were observed to be accurate when compared with the crop calendar. Results revealed maximum water deficit at middle stage of the crops, which were observed to be particularly higher at the tail of the canal command. Moreover, results also depicted that kharif (summer) crops suffer higher deficit in comparison to rabi (winter) crops due to higher ET demand caused by higher temperature. Results of the research can be utilized for rational allocation of canal supplies and guiding farmers towards usage of alternate sources to avoid crop water stress.
Highlights
The irrigated agriculture sector is the prime user of freshwater resources around the world and consumes approximately 69% of the freshwater withdrawal [1]
Visualizing the impact of spatial precipitation variations is necessary to rationalize canal water allocation, which is possible by establishing an approach that is capable of providing estimation of the spatiotemporal dissemination of crop water requirements [39]
This study presents a technique for crop water deficit modeling in data poor areas and concluded the following: (i) normalized difference vegetation index (NDVI)-based crop classification revealed that wheat and cotton are the major cultivated crops for rabi and kharif seasons with an area of approximately 60% and 30%, respectively
Summary
The irrigated agriculture sector is the prime user of freshwater resources around the world and consumes approximately 69% of the freshwater withdrawal [1]. Asia has the largest consumption of around 56% of global fresh water for irrigation purposes [2]. The water resources of Pakistan, both groundwater and surface water, have become inadequate to fulfill the growing demands of the irrigation-based agriculture sector [7]. Canal water is not sufficient to solely satisfy the crop water needs as it fulfills only 37.5% of the crop demand in Punjab. The largest irrigation area of Pakistan, is an intensely cultivated region covering an area of about 8.4 million ha [9]. This area observes cultivation throughout the year in two crop seasons namely summer (kharif) and winter (rabi). There is a realization globally of the need to efficiently utilize water resources to avoid crop water stress and increase crop productivity [12]
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