Evaluation of Evapotranspiration over a Semiarid Region Using Multiresolution Data Sources

Jamshidi, Sajad; Zand‐Parsa, Shahrokh; Pakparvar, M; Niyogi, Dev

doi:10.1175/jhm-d-18-0082.1

Cited by 74 publications

(44 citation statements)

References 60 publications

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“…However, the negative impacts of climate change will be so severe in arid or semiarid areas such as Iran [6]. e agricultural water has been reducing with a steep downward trend in south of the Iran as a result of climate change [7]. Increased temperatures are likely to shorten the crop cycle, thus reducing crop production [8].…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Change on the Growth of Typical Crops in Karst Areas: A Case Study of Guizhou Province

Weng

et al. 2019

Advances in Meteorology

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Climate change has emerged as a significant man-made global environmental challenge marked by rising temperature. The global rising temperature is supposed to alter climatic patterns like floods and droughts, thereby affecting human life supporting system and global food production. In order to clarify the impact of weather events on agricultural production in karst landforms, this study selected the indices of the growth period of crops (start time and duration), growing season precipitation, intense precipitation, number of consecutive rainless days, and number of drought-flood abrupt alternation events to evaluate the variation trend of future weather events and their impact on crop growth in Guizhou Province, China. The results show that (1) the climate is generally getting warmer. From 2019 to 2050, the sowing period of winter wheat and rice tends to be postponed. The duration of maize and rice’s growth period will be shortened, and the life cycle of wheat also emerges as having a decreasing tendency except for those from the southern region. Comparing with the mean value during 1961 to 2018, the average crop cycle length of winter wheat, summer maize, and rice was shortened. The rate of shortening of crop cycle length is faster than the value during 1961 to 2018. (2) In the next 30 years, extreme precipitation concentrates in June and mainly falls in the central and southeast parts of Guizhou Province. In addition, summer is the outbreak period of drought events and drought-flood abrupt alternation events, which has a great impact on crop’s growth. This study can provide references for the planting system, structure, layout, and management of crops in the karst region.

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Section: Introductionmentioning

confidence: 99%

Impact of Climate Change on the Growth of Typical Crops in Karst Areas: A Case Study of Guizhou Province

Weng

et al. 2019

Advances in Meteorology

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“…Hyperspectral sensors typically collect 200 or more contiguous bands [11], enabling the reconstruction of vegetation signatures [12]. Agriculture studies can benefit significantly from hyperspectral imaging analysis for monitoring crop health status [13].…”

Section: Introductionmentioning

confidence: 99%

“…Hyperspectral s typically collect 200 or more contiguous bands [11], enabling the reconstruction of vegetation res [12]. Agriculture studies can benefit significantly from hyperspectral imaging analysis for ring crop health status [13]. yperspectral remote sensing techniques for coastal water analysis have been developed for han three decades [11,14].…”

Section: Introductionmentioning

confidence: 99%

“…Spectral imaging is a data-intensive method that samples image data on the electromagnetic spectrum. The information retrieved through spectral imagery is crucial for a wide range of earth sciences applications, such as for geology [ 1 ], agriculture [ 2 ] and water management aspects [ 3 , 4 ], inland and coastal water monitoring [ 5 ], gas emission retrieval [ 6 ] and fire detection [ 7 ]. When the reflected energy is sensed within multiple wavelength bands (<20), the imaging process is referred to as multispectral (e.g., the Landsat mission).…”

Section: Introductionmentioning

confidence: 99%

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Comparison of PRISMA Data with Model Simulations, Hyperion Reflectance and Field Spectrometer Measurements on ‘Piano delle Concazze’ (Mt. Etna, Italy)

Romaniello

Silvestri

Buongiorno

et al. 2020

Sensors

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In this work, we compare first acquisitions from the ASI-PRISMA (Agenzia Spaziale Italiana-PRecursore IperSpettrale della Missione Applicativa) space mission with model simulations, past data acquired by the Hyperion sensor and field spectrometer measurements. The test site is ‘Piano delle Concazze’ (Mt. Etna, Italy), suitable for calibration purposes due to its homogeneity characteristics. The area measures at about 0.2 km2 and is composed of very homogeneous trachybasalt rich in plagioclase and olivine. Three PRISMA acquisitions, achieved on 31 July and 8 and 17 August 2019, are analyzed. Firstly, spectral profiles of PRISMA top of atmosphere (TOA) radiance are compared with MODerate resolution atmospheric TRANsmission (MODTRAN) simulations. The Pearson correlation coefficient is equal to 0.998 and 0.994 for VNIR (Visible and Near InfraRed) and SWIR (Short-Wave InfraRed) spectral ranges, respectively. PRISMA radiance overestimates values simulated by MODTRAN for all considered days, showing a mean bias of +5.22 and of +0.91 Wm−2sr−1µm−1 for VNIR and SWIR, respectively. The relative mean difference between reflectance values estimated by PRISMA and Hyperion, on the test area, is around +19%, despite the great difference in time acquisition (up to 19 years); PRISMA slightly overestimates Hyperion reflectance with an absolute mean difference of about +0.0083, within the variability of Hyperion acquisitions of ±0.0250 (corresponding to ±2 standard deviation). Finally, FieldSpec measurements also confirm the great quality of PRISMA reflectance estimations. The absolute mean difference results are around +0.0089 (corresponding to a relative error of about +21%). In the study, we investigate only the lower values of reflectance characterizing the test site. A more complete evaluation of PRISMA performances needs to consider other test sites with different optical characteristics.

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“…In recent decades, several studies developed ET models using remote sensing data from advanced very high resolution radiometer (AVHRR) and moderate resolution imaging spectroradiometer (MODIS) satellite images and eddy covariance flux towers to estimate spatially distributed ET over larger regions (Cleugh, Leuning, Mu, & Running, 2007; Ferguson, Sheffield, Wood, & Gao, 2010; Leuning, Zhang, Rajaud, Cleugh, & Tu, 2008; Mu, Zhao, & Running, 2011; Teluguntla, Ryu, George, & Walker, 2013; Vinukollu, Wood, Ferguson, & Fisher, 2011, Zhang et al, 2009). However, many of them reportedly underestimated ET over semi‐arid regions (Jamshidi, Zand‐parsa, Pakparvar, & Niyogi, 2019). Many of these methods depend on leaf area index (LAI) and other empirically derived parameters integrated into the Penman‐Monteith (PM) model.…”

Section: Introductionmentioning

confidence: 99%

Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin, India

Teluguntla

Ryu

George

et al. 2020

Hydrological Processes

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Evapotranspiration (ET) is one of the major water exchange processes between the earth's surface and the atmosphere. ET is a combined process of evaporation from open water bodies, bare soil and plant surfaces, and transpiration from vegetation. Remote sensing-based ET models have been developed to estimate spatially distributed ET over large regions, however, many of them reportedly underestimate ET over semi-arid regions (Jamshidi et al., Journal of Hydrometeorology, 2019, 20, 947-964). In this work, we show that underestimation of ET can occur due to the open water evaporation from flooded rice paddies ignored in the existing ET models. To address the gap in ET estimation, we have developed a novel approach that accounts for the missing ET component over flooded rice paddies. Our method improved ET estimates by a modified Penman-Monteith algorithm that considered the fraction of open water evaporation from flooded rice paddies. Daily ET was calculated using ground based meteorological data and the MODIS satellite data over the Krishna River Basin. Seasonal and annual ET values over the Krishna Basin were compared with two different ET algorithms. ET estimates from these two models were also compared for different crop combinations. Results were validated with flux tower-based measurements from other studies. We have identified a 17 mm/year difference in average annual ET over the Krishna River Basin with this new ET algorithm. This is very critical in basin scale water balance analysis and water productivity studies. K E Y W O R D S evapotranspiration, flooded rice paddy, Krishna River basin, MODIS, remote sensing ET

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Evaluation of Evapotranspiration over a Semiarid Region Using Multiresolution Data Sources

Cited by 74 publications

References 60 publications

Impact of Climate Change on the Growth of Typical Crops in Karst Areas: A Case Study of Guizhou Province

Impact of Climate Change on the Growth of Typical Crops in Karst Areas: A Case Study of Guizhou Province

Comparison of PRISMA Data with Model Simulations, Hyperion Reflectance and Field Spectrometer Measurements on ‘Piano delle Concazze’ (Mt. Etna, Italy)

Impact of flooded rice paddy on remotely sensed evapotranspiration in the Krishna River basin, India

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