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Jianguo Liu and Zhenghui Xie

Abstract

Bayesian model averaging (BMA) probability quantitative precipitation forecast (PQPF) models were established by calibrating their parameters using 1–7-day ensemble forecasts of 24-h accumulated precipitation, and observations from 43 meteorological stations in the Huaihe Basin. Forecasts were provided by four single-center (model) ensemble prediction systems (EPSs) and their multicenter (model) grand ensemble systems, which consider exchangeable members (EGE) in The Observing System Research and Predictability Experiment (THORPEX) Interactive Grand Global Ensemble (TIGGE). The four single-center EPSs were from the China Meteorological Administration (CMA), the European Centre for Medium-Range Weather Forecasts (ECMWF), the National Centers for Environment Prediction (NCEP), and the Met Office (UKMO). Comparisons between the raw ensemble, logistic regression, and BMA for PQPFs suggested that the BMA predictive models performed better than the raw ensemble forecasts and logistic regression. The verification and comparison of five BMA EPSs for PQPFs in the study area showed that the UKMO and ECMWF were a little superior to the NCEP and CMA in general for lead times of 1–7 days for the single-center EPSs. The BMA model for EGE outperformed those for single-center EPSs for all 1–7-day ensemble forecasts, and mostly improved the quality of PQPF. Based on the percentile forecasts from the BMA predictive PDFs for EGE, a heavy-precipitation warning scheme is proposed for the test area.

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Yujin Zeng, Zhenghui Xie, and Jing Zou

Abstract

In this study, a groundwater (GW) extraction scheme was incorporated into the Community Earth System Model, version 1.2.0 (CESM1.2.0), to create a new version called CESM1.2_GW, which was used to investigate hydrologic and climatic responses to anthropogenic GW extraction on a global scale. An ensemble of 41-yr simulations with and without GW extraction (estimated based on local water supply and demand) was conducted and analyzed. The results revealed that GW extraction and water consumption caused drying in deep soil layers but wetting in upper layers, along with a rapidly declining GW table in areas with the most severe GW extraction, including the central United States, the north China plain, and northern India and Pakistan. The atmosphere also responded to GW extraction, with cooling at the 850-hPa level over northern India and Pakistan and a large area in northern China and central Russia. Increased precipitation occurred in the north China plain due to increased evapotranspiration from irrigation. Decreased precipitation occurred in northern India because the Indian monsoon and its transport of water vapor were weaker as a result of cooling induced by GW use. Additionally, the background climate change may complicate the precipitation responses to the GW use. Local terrestrial water storage was shown to be unsustainable at the current high GW extraction rate. Thus, a balance between reduced GW withdrawal and rapid economic development must be achieved in order to maintain a sustainable GW resource, especially in regions where GW is being overexploited.

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Zhenghui Xie, Zhenhua Di, Zhendong Luo, and Qian Ma

Abstract

In this study, a quasi-three-dimensional, variably saturated groundwater flow model was developed by approximately dividing the three-dimensional soil water and groundwater flow into an unsaturated vertical soil water flow and a horizontal groundwater flow to simulate the interactions among soil water, groundwater, and vegetation. The developed model consists of a one-dimensional unsaturated soil water flow model with the water table as the moving boundary using an adaptive grid structure for a vertical soil column formed based on discrete grid cells in a horizontal domain, a two-dimensional groundwater flow model for the horizontal domain, and an interface model connecting the two components for the horizontal grid cells in the domain. Synthetic experiments by the model were conducted to test the sensitivities of the model parameters of river elevation, ground surface hydraulic conductivity, and surface flux, and the results from the experiments showed the robustness of the proposed model under different conditions. Comparison of the simulation by the model and that by a full three-dimensional scheme showed its feasibility and efficiency. A case of stream water conveyance in the lower reaches of the Tarim River was then applied to validate the developed model for simulation of the water table elevations at the Yingsu section. Finally, a numerical experiment by the model for the Tarim River basin was conducted to discuss the groundwater latent flow for large-scale high-relief topography with stream water conveyance. The results show that the model can simulate the water table reasonably well.

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Binghao Jia, Jianguo Liu, Zhenghui Xie, and Chunxiang Shi

Abstract

In this study, a microwave-based multisatellite merged product released from the European Space Agency’s Climate Change Initiative (ESA CCI) and two model-based simulations from the Community Land Model 4.5 (CLM4.5) and Global Land Data Assimilation System (GLDAS) were used to investigate interannual variations and trends of soil moisture in China between 1979 and 2010. They were also evaluated using in situ observations from the nationwide agrometeorological network. These three datasets show consistent drying trends for surface soil moisture in northeastern and central China, as well the eastern portion of Inner Mongolia, and wetting trends in the Tibetan Plateau, which are also identified by in situ observations. Trends in the root-zone soil moisture are in line with those of surface soil moisture seen in the CLM4.5 and GLDAS simulations obtained from most areas in China (78%–88%), except for northwestern China and southwest of the Tibetan Plateau. Moreover, the drying trend intensifies with increasing soil depth. Taking the in situ measurements as reference, it is found that ESA CCI has better accuracy in identifying the significant drying trends while CLM4.5 and GLDAS capture wetting trends better. Compared to temperature, precipitation is the primary factor responsible for these trends, which controls the direction of soil moisture changes, while increasing temperatures can also enhance soil drying during periods of decreased precipitation.

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Zhenghui Xie, Fei Yuan, Qingyun Duan, Jing Zheng, Miaoling Liang, and Feng Chen

Abstract

This paper presents a methodology for regional parameter estimation of the three-layer Variable Infiltration Capacity (VIC-3L) land surface model with the goal of improving the streamflow simulation for river basins in China. This methodology is designed to obtain model parameter estimates from a limited number of calibrated basins and then regionalize them to uncalibrated basins based on climate characteristics and large river basin domains, and ultimately to continental China. Fourteen basins from different climatic zones and large river basins were chosen for model calibration. For each of these basins, seven runoff-related model parameters were calibrated using a systematic manual calibration approach. These calibrated parameters were then transferred within the climate and large river basin zones or climatic zones to the uncalibrated basins. To test the efficiency of the parameter regionalization method, a verification study was conducted on 19 independent river basins in China. Overall, the regionalized parameters, when evaluated against the a priori parameter estimates, were able to reduce the model bias by 0.4%–249.8% and relative root-mean-squared error by 0.2%–119.1% and increase the Nash–Sutcliffe efficiency of the streamflow simulation by 1.9%–31.7% for most of the tested basins. The transferred parameters were then used to perform a hydrological simulation over all of China so as to test the applicability of the regionalized parameters on a continental scale. The continental simulation results agree well with the observations at regional scales, indicating that the tested regionalization method is a promising scheme for parameter estimation for ungauged basins in China.

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Yaling Liu, Dongdong Chen, Soukayna Mouatadid, Xiaoliang Lu, Min Chen, Yu Cheng, Zhenghui Xie, Binghao Jia, Huan Wu, and Pierre Gentine

Soil moisture (SM) links the water and energy cycles over the land-atmosphere interface and largely determines ecosystem functionality, positioning it as an essential player in the Earth system. Despite its importance, accurate estimation of large-scale SM remains a challenge. Here we leverage the strength of neural network (NN) and fidelity of long-term measurements to develop a daily multi-layer cropland SM dataset for China from 1981-2013, implemented for a range of different cropping patterns. The training and testing of the NN for the five soil layers (0-50cm, 10-cm depth each) yield R2 values of 0.65-0.70 and 0.64-0.69, respectively. Our analysis reveals that precipitation and soil properties are the two dominant factors determining SM, but cropping pattern is also crucial. In addition, our simulations of alternative cropping patterns indicate that winter wheat followed by fallow will largely alleviate the SM depletion in most part of China. On the other hand, cropping patterns of fallow in the winter followed by maize/soybean seems further aggravate SM decline in the Huang-Huai-Hai region and Southwestern China, relative to prevalent practices of double cropping. This may be due to their low soil porosity which results in more soil water drainage, as opposed to the case that winter crop roots help maintain SM. This multi-layer cropland SM dataset with granularity of cropping patterns provides an important alternative and is complementary to modelled and satellite-retrieved products.

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