The response of crop water productivity to climatic variation in the upper-middle reaches of the Heihe River basin, Northwest China

Niu, Jun; Liu, Qi; Kang, Shaozhong; Zhang, Xiaotao

doi:10.1016/j.jhydrol.2018.06.062

Cited by 38 publications

(14 citation statements)

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“…When the wind speed becomes larger, the water vapor around the stomata of the crop will be blown away, the diffusion resistance inside and outside the blade will be reduced, and the crop transpiration will be enhanced. Therefore, the rise of air temperature and wind speed and the decline of relative humidity to a certain range will increase the water consumption of crops (Niu, Liu, Kang, & Zhang, ; Sun et al, ). Taking the period of 2026–2030 as an example, under the A2 scenario, the temperature and sunshine duration in the study area are higher, and the relative humidity and precipitation are lower, which results in the irrigation water demand under the A2 scenario being higher than that under the B2 scenario.…”

Section: Discussionmentioning

confidence: 99%

Impacts of future climate and agricultural land‐use changes on regional agricultural water use in a large irrigation district of northwest China

Sun

Zhou

et al. 2019

Land Degrad Dev

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Agricultural sectors are facing various environmental threats, such as land degradation and water resource depletion. Agricultural water use and cropping patterns are closely linked to each other, with both related to the regional climate. This study evaluated the impacts of future climate and agricultural land-use changes on agricultural water consumption in the Hetao Irrigation District (HID), China. The results show that owing to an increase in temperature and a decrease in precipitation, the future climate in the research area will become warmer and dryer, which will increase the water demand of crops. Future climate in the HID will lead to a 10.5% increase in total irrigation water demand under a scenario of high greenhouse gas emissions and a 6.9% increase under a scenario of low greenhouse gas emissions. Results of the grey prediction modeling indicate that the amount of water allocated to the agricultural sector will decrease, which will make it difficult to meet crop irrigation demands. The results of the gray model also show that the cropping pattern in the HID will vary over time, and the proportion of the area of cash crops will increase by 5.3% during the next decade. Regional agricultural water use can be reduced by adjusting the cropping pattern under irrigation water limitations. Meanwhile, the saved water can be used for soil desalination in cultivated land in the HID.Consequently, adjusting the cropping pattern is a nature-based solution by which to address climate change and guarantee the sustainable use of regional water and land resources.

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Section: Discussionmentioning

confidence: 99%

Impacts of future climate and agricultural land‐use changes on regional agricultural water use in a large irrigation district of northwest China

Sun

Zhou

et al. 2019

Land Degrad Dev

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“…In a previous study, Niu et al (2018) successfully developed a distributed hydrological model for the uppermiddle Heihe River basin using SWAT. In their study, the study area was divided into 34 sub-basins and 1613 hydrological response units.…”

Section: Study Area and Established Swatmentioning

confidence: 99%

“…In their study, the study area was divided into 34 sub-basins and 1613 hydrological response units. The model parameter values used in the present study were obtained from Niu et al (2018) using the observed evapotranspiration, detrending crop yield data, and the optimization algorithm of the Sequential Uncertainty Fitting Algorithm Version 2 (SUFI-2) (Abbaspour et al 2004).…”

Section: Study Area and Established Swatmentioning

confidence: 99%

“…The Heihe River basin is an important commercial grain base, located in an arid region in northwest China. The runoff generation and crop production for the region were simulated in the study of Niu et al (2018). Li et al (2016) applied AquaCrop model to quantify the impact of climate change on water consumption and water use efficiency of maize and spring wheat for a sub-region.…”

Section: Introductionmentioning

confidence: 99%

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Accessing future crop yield and crop water productivity over the Heihe River basin in northwest China under a changing climate

et al. 2021

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Quantitative evaluation of the response of crop yield and crop water productivity (CWP) to future climate change is important to prevent or mitigate the adverse effects of climate change. This study made such an evaluation for the agricultural land over the Heihe River basin in northwest China. The ability of 31 climate models for simulating the precipitation, maximum temperature, and minimum temperature was evaluated for the studied area, and a multi-model ensemble was employed. Using the previously well-established Soil and Water Assessment Tool (SWAT), crop yield and crop water productivity of four major crops (corn, wheat, barley, and spring canola-Polish) in the Heihe River basin were simulated for three future time periods (2025–2049, 2050–2074, and 2075–2099) under two Representative Concentration Pathways (RCP4.5 and RCP8.5). The results revealed that the impacts of future climate change on crop yield and CWP of wheat, barley, and canola would all be negative, whereas the impact on corn in the eastern part of the middle reaches of the Heihe River basin would be positive. On the whole, climate change under RCP8.5 scenario would be more harmful to crops, while the corn crops in the Minle and Shandan counties have better ability to cope with climate change.

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“…Major land use types are cultivated land, grassland, and barren land, and the main crops include corn and spring wheat. Precipitation in the middle reaches of the HRB is limited, with farmland accounting for about 86.85% of water consumption in the basin [30]. Gray-brown desert soil and gray desert soil are the zonal soil types in the study area [31].…”

Section: Study Areamentioning

confidence: 99%

Mapping of Soil Total Nitrogen Content in the Middle Reaches of the Heihe River Basin in China Using Multi-Source Remote Sensing-Derived Variables

et al. 2019

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Soil total nitrogen (STN) is an important indicator of soil quality and plays a key role in global nitrogen cycling. Accurate prediction of STN content is essential for the sustainable use of soil resources. Synthetic aperture radar (SAR) provides a promising source of data for soil monitoring because of its all-weather, all-day monitoring, but it has rarely been used for STN mapping. In this study, we explored the potential of multi-temporal Sentinel-1 data to predict STN by evaluating and comparing the performance of boosted regression trees (BRTs), random forest (RF), and support vector machine (SVM) models in STN mapping in the middle reaches of the Heihe River Basin in northwestern China. Fifteen predictor variables were used to construct models, including land use/land cover, multi-source remote sensing-derived variables, and topographic and climatic variables. We evaluated the prediction accuracy of the models based on a cross-validation procedure. Results showed that tree-based models (RF and BRT) outperformed SVM. Compared to the model that only used optical data, the addition of multi-temporal Sentinel-1A data using the BRT method improved the root mean square error (RMSE) and the mean absolute error (MAE) by 17.2% and 17.4%, respectively. Furthermore, the combination of all predictor variables using the BRT model had the best predictive performance, explaining 57% of the variation in STN, with the highest R2 (0.57) value and the lowest RMSE (0.24) and MAE (0.18) values. Remote sensing variables were the most important environmental variables for STN mapping, with 59% and 50% relative importance in the RF and BRT models, respectively. Our results show the potential of using multi-temporal Sentinel-1 data to predict STN, broadening the data source for future digital soil mapping. In addition, we propose that the SVM, RF, and BRT models should be calibrated and evaluated to obtain the best results for STN content mapping in similar landscapes.

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The response of crop water productivity to climatic variation in the upper-middle reaches of the Heihe River basin, Northwest China

Cited by 38 publications

References 38 publications

Impacts of future climate and agricultural land‐use changes on regional agricultural water use in a large irrigation district of northwest China

Impacts of future climate and agricultural land‐use changes on regional agricultural water use in a large irrigation district of northwest China

Accessing future crop yield and crop water productivity over the Heihe River basin in northwest China under a changing climate

Mapping of Soil Total Nitrogen Content in the Middle Reaches of the Heihe River Basin in China Using Multi-Source Remote Sensing-Derived Variables

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