Water Resources Management Strategies for Irrigated Agriculture in the Indus Basin of Pakistan

Muzammil, Muhammad; Zahid, Azlan

doi:10.3390/w12051429

Cited by 42 publications

(44 citation statements)

References 58 publications

(46 reference statements)

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“…Monitoring land use/land cover changes is fundamental for sustainable irrigation water management plans. The authors of [101,102] showed the importance of using the remote sensing techniques in order to detect LCLU changes and their impact on surface water in Nile Delta. Urban sprawl and rapid LCLU changes in the Nile Delta have a negative impact on water irrigation quality by increasing the concentration of contaminants [103,104].…”

Section: Discussionmentioning

confidence: 99%

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Abdel-Fattah

Abd-Elmabod

Aldosari

et al. 2020

Water

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Water scarcity and suitable irrigation water management in arid regions represent tangible challenges for sustainable agriculture. The current study aimed to apply multivariate analysis and to develop a simplified water quality assessment using principal component analysis (PCA) and the agglomerative hierarchical clustering (AHC) technique to assess the water quality of the Bahr Mouise canal in El-Sharkia Governorate, Egypt. The proposed methods depended on the monitored water chemical composition (e.g., pH, water electrical conductivity (ECiw), Ca2+, Mg2+, Na+, K+, HCO3−, Cl−, and SO42−) during 2019. Based on the supervised classification of satellite images (Landsat 8 Operational Land Imager (OLI)), the distinguished land use/land cover types around the Bahr Mouise canal were agriculture, urban, and water bodies, while the dominating land use was agriculture. The water quality of the Bahr Mouise canal was classified into two classes based on the application of the irrigation water quality index (IWQI), while the water quality was classified into three classes using the PCA and AHC methods. Temporal variations in water quality were investigated, where the water qualities in winter, autumn, and spring (January, February, March, April, November, and December) were classified as class I (no restrictions) based on IWQI application, and the water salinity, sodicity, and/or alkalinity did not represent limiting factors for irrigation water quality. On the other hand, in the summer season (May, June, July, August, and October), the irrigation water was classified as class II (low restrictions); therefore, irrigation processes during summer may lead to an increase in the alkalinity hazard. The PCA classifications were compared with the IWQI results; the PCA classifications had similar assessment results during the year, except in September, while the water quality was assigned to class II using the PCA method and class I by applying the IWQI. Furthermore, the normalized difference vegetation index (NDVI) around the Bahr Mouise canal over eight months and climatic data assisted in explaining the fluctuations in water quality during 2019 as a result of changing the crop season and agriculture management. Assessments of water quality help to conserve soil, reduce degradation risk, and support decision makers in order to obtain sustainable agriculture, especially under water irrigation scarcity and the limited agricultural land in such an arid region.

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Section: Discussionmentioning

confidence: 99%

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Abdel-Fattah

Abd-Elmabod

Aldosari

et al. 2020

Water

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“…As an example, even in the water district with the biggest total water abstractions for irrigation (Thessaly), these abstractions represent about 50% of the theoretical annual available water resources [78]. Previous studies highlighted that optimising cropping patterns of the existing crops can result in an improvement of irrigation settings and in significant water savings [9].…”

Section: Discussionmentioning

confidence: 99%

“…Hydrological modelling is a useful tool for the estimation of irrigation water needs at several scales [5,32,41]. As an example, spatial distributed hydrological modelling has supported the estimate of irrigation water needs at the country scale [5] as well as the estimation of the water footprint of crops to establish alternative management plans for more sustainable water use [9]. During the last decades, Remote Sensing (RS) has provided data with excessive spatial resolution, systematic revisit times and synoptic view of the Earth's surface [42].…”

Section: Introductionmentioning

confidence: 99%

A New Model-Based Approach for the Evaluation of the Net Contribution of the European Union Rural Development Program to the Reduction of Water Abstractions in Agriculture

et al. 2020

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Agriculture is an essential driving force in water resources management and has a central role in the European Union’s Rural Development Programme (RDP). In this study, the solution developed addresses countries characterised by relatively small farms, vast spatial and temporal variability and severe data scarcity. The proposed model-based approach is directly relevant to the evaluation of agricultural policies affecting water abstraction based on multisource data. The evaluation process utilises an entirely spatially distributed, continuous hydrological model. The model provides a gridded output of the main hydrological balance components, as well as vegetation water deficit and irrigation water requirements, on a daily temporal step on a country scale. It provides information at the farm level and facilitates the estimation of water abstractions in agriculture, taking into consideration all the pertinent information included in the Integrated Administration and Control System database that is maintained by RDPs in Europe. Remote sensing data also are used to validate crop patterns. The obtained results were analysed to estimate the net effect of the RDP to the reduction of water abstractions in agriculture. This work produces valuable information concerning the evaluation of agricultural policies and the assessment of land use, and climate change adaptation and mitigation strategies.

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“…In Southern Amazonia, Brazil, green and blue WFs of agriculture (crop and pasture) in recent years (2000 and 2014) and future years (2030 and 2050) were modelled to study the impact of agricultural intensifications on crop water use [44]. In the Indus Basin, Pakistan, the WF of 17 million hectares of irrigated croplands in high spatiotemporal resolution was evaluated to support policymakers with a better vision of the national water and food security agenda [45]. In Punjab, Pakistan, blue, green, and grey WFs of cotton from production to textile were estimated to throw light on the WF of the textile industry [46].…”

Section: Introductionmentioning

confidence: 99%

Water Footprint, Blue Water Scarcity, and Economic Water Productivity of Irrigated Crops in Peshawar Basin, Pakistan

Khan

Nouri

Booij

et al. 2021

Water

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Pakistan possesses the fourth largest irrigation network in the world, serving 20.2 million hectares of cultivated land. With an increasing irrigated area, Pakistan is short of freshwater resources and faces severe water scarcity and food security challenges. This is the first comprehensive study on the water footprint (WF) of crop production in Peshawar Basin. WF is defined as the volume of freshwater required to produce goods and services. In this study, we assessed the blue and green water footprints (WFs) and annual blue and green water consumption of major crops (maize, rice, tobacco, wheat, barley, sugarcane, and sugar beet) in Peshawar Basin, Pakistan. The Global Water Footprint Assessment Standard (GWFAS) and AquaCrop model were used to model the daily WF of each crop from 1986 to 2015. In addition, the blue water scarcity, in the context of available surface water, and economic water productivity (EWP) of these crops were assessed. The 30 year average blue and green WFs of major crops revealed that maize had the highest blue and green WFs (7077 and 2744 m3/ton, respectively) and sugarcane had the lowest blue and green WFs (174 and 45 m3/ton, respectively). The average annual consumption of blue water by major crops in the basin was 1.9 billion m3, where 67% was used for sugarcane and maize, covering 48% of the cropland. The average annual consumption of green water was 1.0 billion m3, where 68% was used for wheat and sugarcane, covering 67% of the cropland. The WFs of all crops exceeded the global average. The results showed that annually the basin is supplied with 30 billion m3 of freshwater. Annually, 3 billion m3 of freshwater leaves the basin unutilized. The average annual blue water consumption by major crops is 31% of the total available surface water (6 billion m3) in the basin. Tobacco and sugar beet had the highest blue and green EWP while wheat and maize had the lowest. The findings of this study can help the water management authorities in formulating a comprehensive policy for efficient utilization of available water resources in Peshawar Basin.

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Water Resources Management Strategies for Irrigated Agriculture in the Indus Basin of Pakistan

Cited by 42 publications

References 58 publications

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

Multivariate Analysis for Assessing Irrigation Water Quality: A Case Study of the Bahr Mouise Canal, Eastern Nile Delta

A New Model-Based Approach for the Evaluation of the Net Contribution of the European Union Rural Development Program to the Reduction of Water Abstractions in Agriculture

Water Footprint, Blue Water Scarcity, and Economic Water Productivity of Irrigated Crops in Peshawar Basin, Pakistan

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