Using Regional Virtual Water Trade and Water Footprint Accounting for Optimizing Crop Patterns to Mitigate Water Crises in Dry Regions

Mojtabavi, Seyed Amin; Shokoohi, Alireza; Etedali, Hadi Ramezani; Singh, Vijay P.

doi:10.1002/ird.2170

Cited by 21 publications

(4 citation statements)

References 25 publications

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“…Reduction in precipitation and increasing daily minimum temperature, which could in turn result in lower chances of snowfall in winter, can significantly reduce domestic and agricultural water supplies in spring and summer. Given that nearly 65% of Iran's arable land was equipped with irrigation in 2014–2016 (Food and Agriculture Organization of the United Nations (FAO), ) and considering the already scarce and unstable status of groundwater in most of the plains in the country (Mojtabavi et al, ), this is expected to put more pressure on the country's agriculture.…”

Section: Discussionmentioning

confidence: 99%

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†

Ababaei

2020

Irrigation and Drainage

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Iran's climate‐sensitive agriculture and water resources are vulnerable to climate change and investigation of climatic trends helps in preparing adaptation strategies. Weather stations are sparsely distributed and access to complete weather data is limited. In such situations, gridded global/regional data sets are promising alternatives. Here, monthly time series of seven weather variables (i.e. monthly averages or monthly totals of daily values) were obtained from the Climatic Research Unit TS V4.01 and Global Precipitation Climatology Centre V7 gridded data sets in 675 grid cells covering the country and analysed over the periods 1957–1986 and 1987–2016 at annual, seasonal and monthly scales. Over the two periods and at a national scale, mean temperature has increased by 0.004 (P = 0.717) and 0.04 °C yr−1 (P = 0.000), while the diurnal temperature range has not significantly changed (P > 0.6). Annual total precipitation experienced an insignificant increase (0.81 mm yr−1; P = 0.666) over the first period but declined by 2.12 mm yr−1 (P = 0.041) over the second. Potential evapotranspiration (PET) has increased by 0.32 (P = 0.398) and 1.43 mm yr−1 (P = 0.015), respectively. Since 1987, significant increasing trends in temperature were detected all over the country. While significant increasing trends in annual precipitation were detected in the central regions and south‐west over the first period, decreasing trends prevailed during 1987–2016 in the south, southwest and east with winter being the largest contributor to annual trends. Over the last three decades, annual PET has increased mostly in the north‐west and south‐east while significant increasing trends were detected in 89% of grid cells, except in a few cells in the north‐east. Cloud cover, vapour pressure and frequency of frost days were also analysed. These results are crucial for policy‐makers, researchers and engineers in the country and internationally who usually base their decisions and designs on outdated data sparsely distributed in space. © 2020 John Wiley & Sons, Ltd.

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Section: Discussionmentioning

confidence: 99%

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†

Ababaei

2020

Irrigation and Drainage

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“…More than 144 000 ha of land in this province is dedicated to wheat, as the most important crop in the region, which produces about 315 000 t yr − 1 . Also, maize is responsible for more than 11% of irrigated lands of the province, which results in 1008015 tons per year (Mojtabavi et al, 2018). In this study, both crops, wheat and maize, were investigated, but due to the similarity of the results, only one crop, wheat, was studied.…”

Section: Case Study and Field Datamentioning

confidence: 99%

The probabilistic behavior of AquaCrop parameters: a Monte-Carlo study

Etedali

Adabi

Gorgin

et al. 2022

Stoch Environ Res Risk Assess

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Crop growth models are multi-outputs and can be valuable tools for the quanti cation of crop growth and production. However, these models usually require several input data, which are costly, time-consuming, and sometimes impossible to measure. These input parameters are mostly estimated by calibration and inverse solving. In this study, ve output variables of the AquaCrop model, including soil evaporation, crop transpiration, evapotranspiration, crop biomass at maturity, and grain yield, were investigated to study 47 genotypic input parameters on the output time series of the model for wheat in the Qazvin Synoptic Station. The SAFE toolbox in the Matlab environment was used to study the GSA and uncertainty of inputs and their impact on outputs. Applying the Monte-Carlo-based methods on closed-source models is not as easy as open-source models. The uncertainty in the outputs of the validated AquaCrop model in simulating wheat yield in the Qazvin Synoptic Station over 36 years was analyzed using the Generalized Likelihood Uncertainty Estimation (GLUE) method.The uncertainty in the outputs of the validated AquaCrop model in simulating wheat yield in the Qazvin station over 36 years was analyzed using the GLUE method. Using RMSE<0.9 as the threshold in a 95% con dence level, the best parameter sets included all the observations. Results showed that evaporation and yield are the least reliable outputs of the AquaCrop model that have not been calibrated, while others consider them reliable. After that, the new domain of each output was determined based on the two indexes. Then we modi ed the domain to reduce its size. Finally, the probabilistic behavior of each input on outputs were introduced by the Easy Fit software. The signi cant result of this study is that the probabilistic nature of the input parameter that is calibrated for a particular output variable can differ from other output variables. Also, when we trust a speci c run of the model (calibrated run) as observed data, the uncertainty bounds covering are very high. Finally, we utilized the GLUE to optimize multi-output models by introducing one unique, optimized PDF for each input parameter for all outputs estimated by collecting all accepted output series of all target outputs.

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“…Rehman et al [71] investigated the economic impact of major crops on the GDP of Pakistan and indicated that cotton, wheat, rice, and maize crops have a positive relationship with GDP while sugarcane crops have a negative effect. In another study, Mujtabai et al [72] recognized that stopping the exports of agriculture commodities is not a wise decision for the economic perspective of a country, so net benefits of alternative cropping patterns should be close to the current benefits. Aldaya et al [50] highlighted that 'more crop per drop' investigation should also consider economic aspects to achieve 'more cash per drop' at the same time.…”

Section: Conflicts Of Interestmentioning

confidence: 99%

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

Muzammil

Zahid

2020

Water

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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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Using Regional Virtual Water Trade and Water Footprint Accounting for Optimizing Crop Patterns to Mitigate Water Crises in Dry Regions

Cited by 21 publications

References 25 publications

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†

The probabilistic behavior of AquaCrop parameters: a Monte-Carlo study

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

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Using Regional Virtual Water Trade and Water Footprint Accounting for Optimizing Crop Patterns to Mitigate Water Crises in Dry Regions

Cited by 21 publications

References 25 publications

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS†

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS†

The probabilistic behavior of AquaCrop parameters: a Monte-Carlo study

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

Contact Info

Product

Resources

About

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†

SPATIO‐TEMPORAL VARIATIONS OF SEVEN WEATHER VARIABLES IN IRAN: APPLICATION OF CRU TS AND GPCC DATA SETS^†