Global assessment of the impact of irrigation on land surface temperature

Yang, Qiquan; Huang, Xin; Tang, Qiuhong

doi:10.1016/j.scib.2020.04.005

Cited by 23 publications

(25 citation statements)

References 14 publications

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“…Irrigation is one of the most important anthropogenic land management activities, with strong biogeophysical effects on the land surface and regional climate (DeAngelis et al 2010, Yang et al 2020a). Since the 1950s, to meet the food demands of the rapidly increasing population, the global area equipped for irrigation (AEI) has increased substantially, from 111 Mha in 1950 to 306 Mha in 2005 (Siebert et al 2015).…”

Section: Introductionmentioning

confidence: 99%

“…Irrigation increases soil moisture and adds additional atmospheric water vapor through evapotranspiration, which reduces the Bowen ratio, lowers surface temperature, increases air humidity, and may also influence regional precipitation. The cooling effects of irrigation on near-surface air temperature (T air ) and land surface temperature have been investigated in numerous studies in recent years, using both meteorological observations (Bonfils and Lobell 2007, Yang et al 2020a, 2020b and climate model simulations (Lobell et al 2008, Cook et al 2010, Kang and Eltahir 2019, Thiery et al 2020. Some studies have noted that irrigation can reduce human exposure to heat stress by alleviating extreme T air (Lobell et al 2008, Thiery et al 2020.…”

Section: Introductionmentioning

confidence: 99%

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Irrigated cropland expansion exacerbates the urban moist heat stress in northern India

Guo

Zhou

Satoh

et al. 2022

Environ. Res. Lett.

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Agricultural irrigation has significantly reshaped the land surface energy and water balance. Previous studies have well investigated its cooling effect on air temperature (Tair). However, its effect on increasing air humidity which can intensify the humid heat was often overlooked, particularly over urban areas with high population density, high Tair, and consequently greater exposure to moist heat stress. In this study, using state-of-the-art reanalysis data at a high spatial resolution (~9 km), we evaluated how changes in area equipped for irrigation (AEI) around a city affect urban moist heat stress (UMHS) in more than 1000 cities in China and India. In addition to Tair, wet-bulb temperature (TWB) and wet-bulb globe temperature (TWBG), which consider humidity and are closer to the perceived temperature, were assessed. We found that although AEI expansion lowers urban Tair, irrigation increases TWB and TWBG due to increased air humidity, thereby exacerbating the UMHS. This “warming” effect of irrigation is more evident in northern India where AEI has expanded significantly in recent decades, and is prominent in the pre-monsoon and post-monsoon seasons, when precipitation and air humidity are low. However, this effect is not evident in China due to the lower intensity of AEI expansion and differing climatic conditions. Overall, this study highlights the side-effect of irrigation on regional climate, providing crucial information for better understanding urban heat stress and for future city planning.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Irrigated cropland expansion exacerbates the urban moist heat stress in northern India

Guo

Zhou

Satoh

et al. 2022

Environ. Res. Lett.

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“…For the past few decades, rapid economic development and population growth has brought about notable implications on LC in China (Yao and Zhang, 2001). Meanwhile, China has implemented a series of ecological projects since the 1980s, such as Gain for Green and Red Lines of Cropland (a policy that China's cropland should be no less than 120 million hectares), which have played an important role in LC changes (Lü et al, 2013;Yin and Yin, 2010).…”

Section: Introductionmentioning

confidence: 99%

The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019

Yang

Huang

2021

Earth Syst. Sci. Data

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1,389

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Abstract. Land cover (LC) determines the energy exchange, water and carbon cycle between Earth's spheres. Accurate LC information is a fundamental parameter for the environment and climate studies. Considering that the LC in China has been altered dramatically with the economic development in the past few decades, sequential and fine-scale LC monitoring is in urgent need. However, currently, fine-resolution annual LC dataset produced by the observational images is generally unavailable for China due to the lack of sufficient training samples and computational capabilities. To deal with this issue, we produced the first Landsat-derived annual China land cover dataset (CLCD) on the Google Earth Engine (GEE) platform, which contains 30 m annual LC and its dynamics in China from 1990 to 2019. We first collected the training samples by combining stable samples extracted from China's land-use/cover datasets (CLUDs) and visually interpreted samples from satellite time-series data, Google Earth and Google Maps. Using 335 709 Landsat images on the GEE, several temporal metrics were constructed and fed to the random forest classifier to obtain classification results. We then proposed a post-processing method incorporating spatial–temporal filtering and logical reasoning to further improve the spatial–temporal consistency of CLCD. Finally, the overall accuracy of CLCD reached 79.31 % based on 5463 visually interpreted samples. A further assessment based on 5131 third-party test samples showed that the overall accuracy of CLCD outperforms that of MCD12Q1, ESACCI_LC, FROM_GLC and GlobeLand30. Besides, we intercompared the CLCD with several Landsat-derived thematic products, which exhibited good consistencies with the Global Forest Change, the Global Surface Water, and three impervious surface products. Based on the CLCD, the trends and patterns of China's LC changes during 1985 and 2019 were revealed, such as expansion of impervious surface (+148.71 %) and water (+18.39 %), decrease in cropland (−4.85 %) and grassland (−3.29 %), and increase in forest (+4.34 %). In general, CLCD reflected the rapid urbanization and a series of ecological projects (e.g. Gain for Green) in China and revealed the anthropogenic implications on LC under the condition of climate change, signifying its potential application in the global change research. The CLCD dataset introduced in this article is freely available at https://doi.org/10.5281/zenodo.4417810 (Yang and Huang, 2021).

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Section: Discussionmentioning

confidence: 99%

“…Given that the simulation of default WRF model has warm bias over heavily irrigated area, the cooling effects of irrigation would alleviate the warm bias and improve the performance in simulating temperature. Recently, several studies have used satellite products to evaluate the effect of irrigation on surface climate (e.g., Chen & Dirmeyer, 2019;Kumar et al, 2017;Yang et al, 2020aYang et al, , 2020bZhu et al, 2012). Yang et al (2020a) proposed an irrigation cooling effect detection method to estimate the effect of irrigation on land surface temperature using the MODIS products across China, and they found that irrigation led to about 0-2°C cooling of the daytime temperature over eastern China, which are close to our simulations (0.2-1.0°C cooling of daily mean temperature whereas 0.2-2.0°C cooling of daytime temperature).…”

Section: Discussionmentioning

confidence: 99%

Simulating the Climatic Effects of Irrigation Over China by Using the WRF‐Noah Model System With Mosaic Approach

et al. 2021

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Investigation on the climatic effects of irrigation is of great significance to fully understand the impact of water management on the Earth's environment and hydrological cycle. To comprehensively explore the effects of irrigation across different climatic regions over China, we propose a novel combined irrigation scheme (including dynamic and fixed irrigation schemes) into the Weather Research and Forecasting (WRF)‐Noah‐mosaic model. Two experiments (with and without irrigation) are designed to simulate the impacts of irrigation over China on regional climate. As irrigation increases the latent heat flux but decreases the sensible heat flux and surface temperature, and the magnitudes of corresponding change are highly dependent on the irrigation amounts and irrigation fraction, the evaporative cooling effects significantly reduce the warm bias over extensive irrigation area during crop growing seasons. Meanwhile, irrigation increases soil moisture during both irrigated and non‐irrigated seasons. Compared with the dynamic irrigation scheme, the fixed irrigation scheme results in relatively higher subsurface runoffs due to the continuous infiltration. In addition, the irrigation‐induced changes on precipitation during spring (March–May) are weaker than that during summer (June–August). The opposed effects of irrigation cooling and wetting on generating convective precipitation, and the irrigation‐induced changes in large‐scale circulation jointly give rise to the heterogeneous changes of precipitation. Besides, the subgrid‐scale irrigation scheme can capture the climatic effects of irrigation in some grids where the dominant land use types are not cropland, indicating that in mesoscale simulation, climate model coupled with subgrid‐scale irrigation scheme may improve climate variables trends attribution studies.

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Global assessment of the impact of irrigation on land surface temperature

Cited by 23 publications

References 14 publications

Irrigated cropland expansion exacerbates the urban moist heat stress in northern India

Irrigated cropland expansion exacerbates the urban moist heat stress in northern India

The 30 m annual land cover dataset and its dynamics in China from 1990 to 2019

Simulating the Climatic Effects of Irrigation Over China by Using the WRF‐Noah Model System With Mosaic Approach

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