The Heihe Integrated Observatory Network: A Basin‐Scale Land Surface Processes Observatory in China

Liu, Shaomin; Li, Xin; Xu, Ziwei; Che, Tao; Xiao, Qing; Ma, Mingguo; Liu, Qinhuo; Jin, Rui; Guo, Jianwen; Wang, Liangxu; Wang, Weizhen; Yuan, Qi; Li, Hongyi; Xu, Tong; Ran, Youhua; Hu, Xiao-Li; Shi, Sheng‐Cai; Zhu, Zhanyuan; Tan, Junlei; Zhang, Yang; Ren, Zhiguo

doi:10.2136/vzj2018.04.0072

Cited by 290 publications

(171 citation statements)

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“…The Heihe River Basin (HRB) is the second-largest inland river basin in China and is known for its heterogeneous landscapes, diverse ecosystems, unique geographical characteristics and climate change over recent decades. The HRB is mainly composed of glaciers, snow cover, frozen ground, alpine meadows, forests, irrigated crops, riparian ecosystems and deserts (distributed along an altitudinal gradient), which makes it an ideal field site for hydrometeorological research and has motivated and initiated the establishment of China's first basin-scale integrated observatory network (Li et al, 2009(Li et al, , 2013(Li et al, , 2017Liu et al, 2018). As a major component of the ecohydrological processes in the arid and semiarid HRB, alpine hydrological processes, es-pecially those related to snow cover and frozen ground in the upper reaches, have marked impacts on runoff in the mountainous regions, which then regulate agricultural development in the middle reaches and the ecosystems of the lower reaches (Li et al, 2018b).…”

Section: Introductionmentioning

confidence: 99%

Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China

Che

Liu

et al. 2019

Earth Syst. Sci. Data

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Abstract. The alpine region is important in riverine and watershed ecosystems as a contributor of freshwater, providing and stimulating specific habitats for biodiversity. In parallel, recent climate change, human activities and other perturbations may disturb hydrological processes and eco-functions, creating the need for next-generation observational and modeling approaches to advance a predictive understanding of such processes in the alpine region. However, several formidable challenges, including the cold and harsh climate, high altitude and complex topography, inhibit complete and consistent data collection where and when it is needed, which hinders the development of remote-sensing technologies and alpine hydrological models. The current study presents a suite of datasets consisting of long-term hydrometeorological, snow cover and frozen-ground data for investigating watershed science and functions from an integrated, distributed and multiscale observation network in the upper reaches of the Heihe River Basin (HRB) in China. Meteorological and hydrological data were monitored from an observation network connecting a group of automatic meteorological stations (AMSs). In addition, to capture snow accumulation and ablation processes, snow cover properties were collected from a snow observation superstation using state-of-the-art techniques and instruments. High-resolution soil physics datasets were also obtained to capture the freeze–thaw processes from a frozen-ground observation superstation. The updated datasets were released to scientists with multidisciplinary backgrounds (i.e., cryospheric science, hydrology and meteorology), and they are expected to serve as a testing platform to provide accurate forcing data and validate and evaluate remote-sensing products and hydrological models for a broader community. The datasets are available from the Cold and Arid Regions Science Data Center at Lanzhou (https://doi.org/10.3972/hiwater.001.2019.db, Li, 2019).

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Section: Introductionmentioning

confidence: 99%

Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China

Che

Liu

et al. 2019

Earth Syst. Sci. Data

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“…In 2015, there were 16 WSN sites providing SM observations over the study periods ( Figure 1a and Table 1). Additionally, the 4 cm SM observations from the A'rou superstation and the A'rou sunny automatic meteorological stations (AMSs) are also used in the study ( Figure 1a and Table 1) [35].…”

Section: In Situ Measurementsmentioning

confidence: 99%

Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures

et al. 2019

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Hydro-agricultural applications often require surface soil moisture (SM) information at high spatial resolutions. In this study, daily spatial patterns of SM at a spatial resolution of 1 km over the Babao River Basin in northwestern China were mapped using a Bayesian-based upscaling algorithm, which upscaled point-scale measurements to the grid-scale (1 km) by retrieving SM information using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived land surface temperature (LST) and topography data (including aspect and elevation data) and in situ measurements from a wireless sensor network (WSN). First, the time series of pixel-scale (1 km) representative SM information was retrieved from in situ measurements of SM, topography data, and LST. Second, Bayesian linear regression was used to calibrate the relationship between the representative SM and the WSN measurements. Last, the calibrated relationship was used to upscale a network of in situ measured SM to map spatially continuous SM at a high resolution.The upscaled SM data were evaluated against ground-based SM measurements with satisfactory accuracy-the overall correlation coefficient (r), slope, and unbiased root mean square difference (ubRMSD) values were 0.82, 0.61, and 0.025 m 3 /m 3 , respectively. Moreover, when accounting for topography, the proposed upscaling algorithm outperformed the algorithm based only on SM derived from LST (r = 0.80, slope = 0.31, and ubRMSD = 0.033 m 3 /m 3 ). Notably, the proposed upscaling algorithm was able to capture the dynamics of SM under extreme dry and wet conditions. In conclusion, the proposed upscaled method can provide accurate high-resolution SM estimates for hydro-agricultural applications.

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“…The "Heihe Watershed Allied Telemetry Experimental Research" (HiWATER) was established in 2012 (Li, Cheng, et al, 2013Liu et al, 2011Liu et al, , 2018Xu, Guo, et al, 2018). The half-hourly sensible heat flux was measured by the LAS instrument.…”

Section: 1029/2019ea000705mentioning

confidence: 99%

“…(Baldocchi et al, 2001;Baldocchi, & Ma, 2011;Evett et al, 2011;Liu et al, 2018;Sellers et al, 1988). (Baldocchi et al, 2001;Baldocchi, & Ma, 2011;Evett et al, 2011;Liu et al, 2018;Sellers et al, 1988).…”

Section: Introductionmentioning

confidence: 99%

“…Flux tower networks have been used to measure turbulent heat fluxes in many projects (e.g., FLUXNET, AmeriFlux, FIFE, BEAREX08, HiWATER, etc.) (Baldocchi et al, 2001;Baldocchi, & Ma, 2011;Evett et al, 2011;Liu et al, 2018;Sellers et al, 1988). However, these measurements are sparse and available only over limited time periods, causing difficulty to characterize the spatiotemporal patterns in the turbulent heat fluxes over large-scale domains (Baldocchi et al, 2001;Serreze et al, 2005;Sun et al, 2005;Xu, Guo, et al, 2018.…”

Section: Introductionmentioning

confidence: 99%

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Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework

Bateni

et al. 2019

Earth and Space Science

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Estimation of turbulent heat fluxes via variational data assimilation (VDA) approaches has been the subject of several studies. The VDA approaches need an adjoint model that is difficult to derive. In this study, remotely sensed land surface temperature (LST) data from the Moderate Resolution Imaging Spectroradiometer (MODIS) are assimilated into the heat diffusion equation within an ensemble Kalman smoother (EnKS) approach to estimate turbulent heat fluxes. The EnKS approach is tested in the Heihe River Basin (HRB) in northwest China. The results show that the EnKS approach can estimate turbulent heat fluxes by assimilating low temporal resolution LST data from MODIS. The findings indicate that the EnKS approach performs fairly well in various hydrological and vegetative conditions. The estimated sensible (H) and latent (LE) heat fluxes are compared with the corresponding observations from large aperture scintillometer systems at three sites (namely, Arou, Daman, and Sidaoqiao) in the HRB. The turbulent heat flux estimates from EnKS agree reasonably well with the observations, and are comparable to those of the VDA approach. The EnKS approach also provides statistical information on the H and LE estimates. It is found that the uncertainties of H and LE estimates are higher over wet and/or densely vegetated areas (grassland and forest) compared to the dry and/or slightly vegetated areas (cropland, shrubland, and barren land).

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The Heihe Integrated Observatory Network: A Basin‐Scale Land Surface Processes Observatory in China

Cited by 290 publications

References 89 publications

Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China

Integrated hydrometeorological, snow and frozen-ground observations in the alpine region of the Heihe River Basin, China

Mapping Soil Moisture at a High Resolution over Mountainous Regions by Integrating In Situ Measurements, Topography Data, and MODIS Land Surface Temperatures

Mapping Regional Turbulent Heat Fluxes via Assimilation of MODIS Land Surface Temperature Data into an Ensemble Kalman Smoother Framework

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