Agriculture of Pakistan relies on the Indus basin, which is facing severe water scarcity conditions. Poor irrigation practices and lack of policy reforms are major threats for water and food security of the country. In this research, alternative water-saving strategies are evaluated through a high spatio-temporal water footprint (WF) assessment (1997–2016) for the Punjab and Sindh provinces, which cover an irrigated area of 17 million hectares in the Indus basin of Pakistan. The SPARE:WATER model is used as a spatial decision support tool to calculate the WF and establish alternative management plans for more sustainable water use. The average water consumption (WFarea) is estimated to 182 km3 yr−1, composed of 75% blue water (irrigation water from surface water and groundwater sources), 17% green water (precipitation) and 8% grey water (water used to remove soil salinity or dilute saline irrigation water). Sugarcane, cotton, and rice are highly water-intensive crops, which consume 57% of the annual water use. However, WFarea can be reduced by up to 35% through optimized cropping patterns of the existing crops with the current irrigation settings and even by up to 50% through the combined implementation of optimal cropping patterns and improved irrigation technologies, i.e., sprinkler and drip irrigation. We recommend that the economic impact of these water-saving strategies should be investigated in future studies to inform stakeholders and policymakers to achieve a more sustainable water policy for Pakistan.

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This study aimed to develop a theoretical framework to identify and evaluate the factors that improve organizational performance as several ways to increase operational performance have been introduced. The survey in this paper comprised 111 respondents who were drawn from various organizations across Pakistan. The deductive approach followed by the quantitative research method was used to test the study hypotheses through IBM SPSS version 22.0 as a statistical tool. Data analysis was performed by evaluating the regression model. The findings demonstrate that all the hypotheses were supported and significantly contributed to organizational performance. Further, this study will help practitioners to identify and shape their businesses for enhanced organizational performance. Future research can be done on the other factors that could influence organizational performance and can be tested using other research techniques.

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