Yijian Zeng

Estimation of human‐induced changes in terrestrial water storage through integration of GRACE satellite detection and hydrological modeling: A case study of the Yangtze River basin

Quantifying the human effects on water resources plays an important role in river basin management. In this study, we proposed a framework, which integrates the Gravity Recovery and Climate Experiment (GRACE) satellite estimation with macroscale hydrological model simulation, for detection and attribution of spatial terrestrial water storage (TWS) changes. In particular, it provides valuable insights for regions where ground-based measurements are inaccessible. Moreover, this framework takes into account the feedback between land and atmosphere and innovatively put forward several suggestions (e.g., study period selection, hydrological model selection based on soil moisture-climate interactions) to minimize the uncertainties brought by the interaction of human water use with terrestrial water fluxes. We demonstrate the use of the proposed framework in the Yangtze River basin of China. Our results show that, during the period 2003–2010, the TWS was continually increasing in the middle and south eastern reaches of the basin, at a mean rate of about 3 cm yr21. This increment in TWS was attributed to anthropogenic modification of the hydrological cycle, rather than natural climate variability. The dominant contributor to the TWS excess was found to be intensive surface water irrigation, which recharged the water table in the middle and south eastern parts of the basin. Water impoundment in the Three Gorges Reservoir (TGR) is found to account for nearly 20% of the human-induced TWS increment in the region where the TGR is located. The proposed framework gives water managers/researchers a useful tool to investigate the spatial human effects on TWS changes. Quantifying the human effects on water resources plays an important role in river basin management. In this study, we proposed a framework, which integrates the Gravity Recovery and Climate Experiment (GRACE) satellite estimation with macroscale hydrological model simulation, for detection and attribution of spatial terrestrial water storage (TWS) changes. In particular, it provides valuable insights for regions where ground-based measurements are inaccessible. Moreover, this framework takes into account the feedback between land and atmosphere and innovatively put forward several suggestions (e.g., study period selection, hydrological model selection based on soil moisture-climate interactions) to minimize the uncertainties brought by the interaction of human water use with terrestrial water fluxes. We demonstrate the use of the proposed framework in the Yangtze River basin of China. Our results show that, during the period 2003–2010, the TWS was continually increasing in the middle and south eastern reaches of the basin, at a mean rate of about 3 cm yr21. This increment in TWS was attributed to anthropogenic modification of the hydrological cycle, rather than natural climate variability. The dominant contributor to the TWS excess was found to be intensive surface water irrigation, which recharged the water table in the middle and south eastern parts of the basin. Water impoundment in the Three Gorges Reservoir (TGR) is found to account for nearly 20% of the human-induced TWS increment in the region where the TGR is located. The proposed framework gives water managers/researchers a useful tool to investigate the spatial human effects on TWS changes.

Assessment of the SMAP Level-4 Surface and Root-Zone Soil Moisture Product Using In Situ Measurements

AbstractThe Soil Moisture Active Passive (SMAP) mission Level-4 Surface and Root-Zone Soil Moisture (L4_SM) data product is generated by assimilating SMAP L-band brightness temperature observations into the NASA Catchment land surface model. The L4_SM product is available from 31 March 2015 to present (within 3 days from real time) and provides 3-hourly, global, 9-km resolution estimates of surface (0–5 cm) and root-zone (0–100 cm) soil moisture and land surface conditions. This study presents an overview of the L4_SM algorithm, validation approach, and product assessment versus in situ measurements. Core validation sites provide spatially averaged surface (root zone) soil moisture measurements for 43 (17) “reference pixels” at 9- and 36-km gridcell scales located in 17 (7) distinct watersheds. Sparse networks provide point-scale measurements of surface (root zone) soil moisture at 406 (311) locations. Core validation site results indicate that the L4_SM product meets its soil moisture accuracy requiremen...

Blending satellite observed, model simulated, and in situ measured soil moisture over Tibetan Plateau

The inter-comparison of different soil moisture (SM) products over the Tibetan Plateau (TP) reveals the inconsistency among different SM products, when compared to in situ measurement. It highlights the need to constrain the model simulated SM with the in situ measured data climatology. In this study, the in situ soil moisture networks, combined with the classification of climate zones over the TP, were used to produce the in situ measured SM climatology at the plateau scale. The generated TP scale in situ SM climatology was then used to scale the model-simulated SM data, which was subsequently used to scale the SM satellite observations. The climatology-scaled satellite and model-simulated SM were then blended objectively, by applying the triple collocation and least squares method. The final blended SM can replicate the SM dynamics across different climatic zones, from sub-humid regions to semi-arid and arid regions over the TP. This demonstrates the need to constrain the model-simulated SM estimates with the in situ measurements before their further applications in scaling climatology of SM satellite products.

First Assessment of Sentinel-1A Data for Surface Soil Moisture Estimations Using a Coupled Water Cloud Model and Advanced Integral Equation Model over the Tibetan Plateau

The spatiotemporal distribution of soil moisture over the Tibetan Plateau is important for understanding the regional water cycle and climate change. In this paper, the surface soil moisture in the northeastern Tibetan Plateau is estimated from time-series VV-polarized Sentinel-1A observations by coupling the water cloud model (WCM) and the advanced integral equation model (AIEM). The vegetation indicator in the WCM is represented by the leaf area index (LAI), which is smoothed and interpolated from Terra Moderate Resolution Imaging Spectroradiometer (MODIS) LAI eight-day products. The AIEM requires accurate roughness parameters, which are parameterized by the effective roughness parameters. The first halves of the Sentinel-1A observations from October 2014 to May 2016 are adopted for the model calibration. The calibration results show that the backscattering coefficient (σ°) simulated from the coupled model are consistent with those of the Sentinel-1A with integrated Pearson’s correlation coefficients R of 0.80 and 0.92 for the ascending and descending data, respectively. The variability of soil moisture is correctly modeled by the coupled model. Based on the calibrated model, the soil moisture is retrieved using a look-up table method. The results show that the trends of the in situ soil moisture are effectively captured by the retrieved soil moisture with an integrated R of 0.60 and 0.82 for the ascending and descending data, respectively. The integrated bias, mean absolute error, and root mean square error are 0.006, 0.048, and 0.073 m3/m3 for the ascending data, and are 0.012, 0.026, and 0.055 m3/m3 for the descending data, respectively. Discussions of the effective roughness parameters and uncertainties in the LAI demonstrate the importance of accurate parameterizations of the surface roughness parameters and vegetation for the soil moisture retrieval. These results demonstrate the capability and reliability of Sentinel-1A data for estimating the soil moisture over the Tibetan Plateau. It is expected that our results can contribute to developing operational methods for soil moisture retrieval using the Sentinel-1A and Sentinel-1B satellites.

Study of Snow Dynamics at Subgrid Scale in Semiarid Environments Combining Terrestrial Photography and Data Assimilation Techniques

AbstractSnow cover simulation is a complex task in mountain regions because of its highly irregular distribution. GIS-based calculations of snowmelt–accumulation models must deal with nonnegligible scale effects below cell size, which may result in unsatisfactory predictions depending on the study scale. Terrestrial photography, whose scales can be adapted to the study problem, is a cost-effective technique, capable of reproducing snow dynamics at subgrid scale. A series of high-frequency images were combined with a mass and energy model to reproduce snow evolution at cell scale (30 m × 30 m) by means of the assimilation of the snow cover fraction observation dataset obtained from terrestrial photography in the Sierra Nevada, southern Spain. The ensemble transform Kalman filter technique is employed. The results show the convenience of adopting a selective depletion curve parameterization depending on the succession of accumulation–melting cycles in the snow season in these highly variable environments. A...

New evidence for the links between the local water cycle and the underground wet sand layer of a mega-dune in the Badain Jaran Desert, China

Scientists and the local government have great concerns about the climate change and water resources in the Badain Jaran Desert of western China. A field study for the local water cycle of a lake-desert system was conducted near the Noertu Lake in the Badain Jaran Desert from 21 June to 26 August 2008. An underground wet sand layer was observed at a depth of 20–50 cm through analysis of datasets collected during the field experiment. Measurements unveiled that the near surface air humidity increased in the nighttime. The sensible and latent heat fluxes were equivalent at a site about 50 m away from the Noertu Lake during the daytime, with mean values of 134.4 and 105.9 W/m2 respectively. The sensible heat flux was dominant at a site about 500 m away from the Noertu Lake, with a mean of 187.7 W/m2, and a mean latent heat flux of only 26.7 W/m2. There were no apparent differences for the land surface energy budget at the two sites during the night time. The latent heat flux was always negative with a mean value of −12.7 W/m2, and the sensible heat flux was either positive or negative with a mean value of 5.10 W/m2. A portion of the local precipitation was evaporated into the air and the top-layer of sand dried quickly after every rainfall event, while another portion seeped deep and was trapped by the underground wet sand layer, and supplied water for surface psammophyte growth. With an increase of air humidity and the occurrence of negative latent heat flux or water vapor condensation around the Noertu Lake during the nighttime, we postulated that the vapor was transported and condensed at the lakeward sand surface, and provided supplemental underground sand pore water. There were links between the local water cycle, underground wet sand layer, psammophyte growth and landscape evolution of the mega-dunes surrounding the lakes in the Badain Jaran Desert of western China.

Reply to comment by Binayak P. Mohanty and Zhenlei Yang on “A simulation analysis of the advective effect on evaporation using a two-phase heat and mass flow model

[1] We thank Mohanty and Yang [2013] (hereafter referred to as MY) for their comment on our paper ‘‘A simulation analysis of the advective effect on evaporation using a two-phase heat and mass flow model’’ [Zeng et al., 2011b]. We appreciate the effort by MY to look critically at our paper. We hope that the responses to their comments will help to clarify the issues they raised and to communicate better our approach and contributions to the reader. By reviewing MY’s comments, it is clear to us that we need to provide further clarification on the details of the key aspects of our paper. As shall be seen in following sections, we disagree with all of their objections. Before we issue the point-to-point rebuttal to the two key points MY raised, we want to clarify the approaches we presented in our paper. In such way, we hope to assist the reader to have a systematic view on the key aspects and make definite conclusions on its merits and validity. [2] The main objective of our paper was to identify the controlling mechanism for the advective effect on soil evaporation. When excluding soil airflow, the advective flux can lead to the underestimation of surface evaporative flux [Zeng et al., 2011a, 2011b]. To identify such mechanism, a systematic approach, including both experimental and numerical ones, should be applied. We implemented an in situ experiment and developed a two-phase heat and mass flow model to serve this purpose. With the calibrated two-phase model, the detailed driving force (e.g., matric potential gradient, soil air pressure gradients, and soil temperature gradients) and conductivity fields can be used to investigate and identify what exactly drives the underestimation error. The comparison in the modeled surface fluxes (e.g., evaporative fluxes) with and without soil airflow can identify the underestimation error. The modeled surface flux is a total flux, which is the summation of thermal and isothermal fluxes, and advective fluxes (e.g., when soil airflow being considered). Therefore, it requires a systematic view to decompose the total flux into different components, based on different driving forces. This is what we discussed at the beginning of section 3.3 in our original paper [Zeng et al., 2011b], from where we have analyzed the direct and indirect controlling mechanisms. [3] Based on the diurnal variation pattern of matric potential gradients above the depth of 50 cm, upward during the day and downward during the night, the original paper targets the isothermal flux as the direct driving factor for the underestimation error (e.g., the upward isothermal flux is higher when considering airflow than that without airflow). The inverse variation pattern of soil temperature and soil air pressure gradients, compared to the matric potential one, precludes their direct influence on the underestimation error. However, soil temperature gradient may have an indirect effect on the error (e.g., the downward thermal flux is lower when considering airflow than that without airflow). To verify the above hypothesis, the original paper compares the gradient and conductivity fields by using a normalized scale index (NSI). It is found that the indirect effect of thermal fluxes on the error is invalid because the downward thermal flux with airflow mechanism is larger than that without airflow. This is in contrast to the hypothesis. On the other hand, the original paper verifies the isothermal flux as the direct driving factor accounting for the underestimation error. The upward isothermal flux with airflow mechanism is indeed larger than that without airflow. [4] From Figure 4 of Zeng et al. [2011b], it is obvious that the advective effect is the most significant on day 2, which is chosen for analyzing the controlling mechanism behind the effect. The most significant effect, on day 2, implies the dominance of isothermal fluxes, which can be inferred by comparing the magnitude of different component fluxes [Zeng et al., 2009b]. From day 2 onward, the thermal fluxes start to dominate. As the soil temperature gradient is downward during daytime, it can be inferred that the dominance of thermal fluxes will minify the advective effect. This is because both fluxes (downward thermal and upward isothermal fluxes) will cancel each other out. This can also be inferred from the diurnal patterns of matric potential and soil temperature gradient in Figure 5 of Zeng et al. [2011b]. [5] The further analysis identifies the isothermal hydraulic conductivity as the key factor accounting for the advective effect since it is increased largely when considering airflow. One of the possible mechanisms for such increase Faculty of Geo-Information Science and Earth Observation, University of Twente, Enschede, Netherlands.

Determination of the Optimal Mounting Depth for Calculating Effective Soil Temperature at L-Band: Maqu Case

Effective soil temperature T e f f is one of the basic parameters in passive microwave remote sensing of soil moisture. At present, dedicated satellite soil moisture monitoring missions use the L-band as the operating frequency. However, T e f f at the L-band is strongly affected by soil moisture and temperature profiles. Recently, a two-layer scheme and a corresponding multilayer form have been developed to accommodate such influences. In this study, the soil moisture/temperature data collected and simulated by the Noah land surface model across the Maqu Network are used to verify the newly developed schemes. There are two key findings. Firstly, the new two-layer scheme is able to assess which site provides relatively higher accuracy when estimating T e f f . It is found that, on average, nearly 20% of the T e f f signal cannot be captured by the Maqu Network, in the currently assumed common installation configuration. This knowledge is important, since the spatial averaged brightness temperature (a function of T e f f ) is used to determine soil moisture. Secondly, the developed method has made it possible to identify that the optimal mounting depths for the observation pair are 5 cm and 20 cm for calculating T e f f at the center station in the Maqu Network. It has been suggested that the newly developed method can provide an objective way to configure an optimal soil moisture/temperature network and improve the representativeness of the existing networks regarding the calculation of T e f f .

An Overview of European Efforts in Generating Climate Data Records

AbstractThe Coordinating Earth Observation Data Validation for Reanalysis for Climate Services project (CORE-CLIMAX) aimed to substantiate how Copernicus observations and products can contribute to climate change analyses. CORE-CLIMAX assessed the European capability to provide climate data records (CDRs) of essential climate variables (ECVs), prepared a structured process to derive CDRs, developed a harmonized approach for validating essential climate variable CDRs, identified the integration of CDRs into the reanalysis chain, and formulated a process to compare the results of different reanalysis techniques. With respect to the Copernicus Climate Change Service (C3S), the systematic application and further development of the CORE-CLIMAX system maturity matrix (SMM) and the spinoff application performance metric (APM) were strongly endorsed to be involved in future implementations of C3S. We concluded that many of the current CDRs are not yet sufficiently mature to be used in reanalysis or applied in cli...

Coupled Dynamics in Soil

General Introduction.- Diurnal Pattern of Coupled Moisture and Heat Transport Process.- Application of Diurnal Soil Water Dynamics in Determining Effective Precipitation.- Two-Phase Mass and Heat Flow Model.- How Airflow Affects Soil Water Dynamics.- Impact of Model Physics on Retrieving Soil Moisture and Soil Temperature.- Concluding Remarks.