Ecological restoration impact on total terrestrial water storage


Large-scale ecological restoration (ER) has been successful in curbing land degradation and improving ecosystem services. Previous studies have shown that ER changes individual water flux or storage, but its net impact on total water resources remains unknown. Here we quantify ER impact on total terrestrial water storage (TWS) in the Mu Us Sandyland of northern China, a hotspot of ER practices. By integrating multiple satellite observations and government reports, we construct a TWS record that covers both the pre-ER (1982–1998) and the post-ER (2003–2016) periods. We observe a significant TWS depletion (P < 0.0001) after ER, a substantial deviation from the pre-ER condition. This contrasts with a TWS increase simulated by an ecosystem model that excludes human interventions, indicating that ER is the primary cause for the observed water depletion. We estimate that ER has consumed TWS at an average rate of 16.6 ± 5.0 mm yr−1 in the analysed domain, equivalent to a volume of 21 km3 freshwater loss during the post-ER period. This study provides a framework that directly informs the water cost of ER. Our findings show that ER can exert excessive pressure on regional water resources. Sustainable ER strategies require optimizing ecosystem water consumption to balance land restoration and water resource conservation.

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Fig. 1: Conceptual diagram of the potential impact of ER on total TWS.
Fig. 2: Vegetation restoration in our study region.
Fig. 3: TWS trends for the post-ER and pre-ER periods.
Fig. 4: Separation of ER impact.
Fig. 5: Schematic of future TWS trends under different ER strategies in the analysed domain.

Data availability

GRACE TWS are available from NASA JPL ( NDVI from GIMMS-3g are available at NDVI from MODIS are available at Land cover change data are available at Station precipitation data are from the National Meteorological Administration of China ( Gridded precipitation data are from the Climate Research Unit ( and the Tropical Rainfall Measuring Mission ( Runoff data is provided by C. Shi from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China. Yellow River Resource Bulletins are available at Results from the dynamic vegetation model are available from the corresponding author upon request.

Code availability

Computer code used in this study is available from the corresponding author upon reasonable request.


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We thank C. Shi from the Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Science, Beijing, China for providing Wuding river runoff data. We thank Z. He from the Department of Earth System Science, University of California Irvine, for designing Fig. 5. We thank D. N. Wiese at NASA JPL for helpful discussion about potential signal leakage in JPL mascon solution. We thank Z. Wu from the Department of Physical Geography and Ecosystem Science, Lund University and W. Chao from the Sierra Nevada Research Institute, University of California, Merced for helpful discussion about LPJ-GUESS modelling. We acknowledge funding from the NASA Earth and Space Science Fellowship programme and the terrestrial hydrology programme.

Author information




J.Z. initiated the research. M.Z. and G.A. designed the study with I.V. M.Z. conducted the analyses with G.A., J.Z. and I.V. M.Z. and G.A. wrote the manuscript. M.Z., G.A., J.Z. and I.V. edited the manuscript. J.Z., C.L. and Z.L. prepared weather station data.

Corresponding author

Correspondence to Meng Zhao.

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Extended data

Extended Data Fig. 1 GRACE TWS, satellite and gauge precipitation time series.

a, GRACE TWS time series and domain-averaged annual total precipitation from the Climate Research Unit (CRU) and the Tropical Rainfall Measuring Mission (TRMM). b, Gridded precipitation data (TRMM and CRU) with precipitation time series averaged at six weather stations (Fig. 2b in the main text). The correlation coefficients of station vs. CRU and station vs. TRMM are 0.8 and 0.9, respectively.

Extended Data Fig. 2 ET estimates from 1982–2016.

Error bars represent 1-σ errors.

Extended Data Fig. 3 ET-NDVI relationship.

Scatterplot of interannual MODIS NDVI values and GRACE water budget-based ET estimates during 2003–2016. The dashed line represents the best fit regression line.

Extended Data Fig. 4 JPL Mascon solution.

a, The location of JPL mascons (that is #822 and #823) that include Mu Us Sandyland. The land-cover legend is the same as in Fig. 2b in the main text. b, and c, are GRACE TWS time series for the two mascons, respectively. The shaded blue area represents 1σ error of TWS.

Extended Data Fig. 5 Potential signal leakage from the groundwater depletion in North China Plain (NCP) to our study domain.

a, NCP groundwater depletion rate derived from previous research. b, Mascon representation of (a). The two black boxes in (b) represent JPL mascon #822 and #823.

Extended Data Fig. 6 Runoff analysis.

a, Drainage basins in our study region. The green basin is the Ordos endorheic basin. The red basin is the Wuding River drainage basin. Baijiachuan is a hydrological gauge station that measures the total runoff out of the Wuding River basin. The background raster represents the long-term mean annual total precipitation from TRMM during 1998–2018. b, Time series of estimated runoff for our entire study region.

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Zhao, M., A, G., Zhang, J. et al. Ecological restoration impact on total terrestrial water storage. Nat Sustain (2020).

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