scholarly journals Investigating basin-scale water budget dynamics in 18 rivers across Tibetan Plateau through multiple datasets

2017 ◽  
Author(s):  
Wenbin Liu ◽  
Fubao Sun ◽  
Yanzhong Li ◽  
Guoqing Zhang ◽  
Yan-Fang Sang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Water Budget ◽  
Water Resource Management ◽  
Management Practices ◽  
Yellow River ◽  
Aridity Index ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Basin Scale

Abstract. The dynamics of basin-scale water budgets are not well understood nowadays over the Tibetan Plateau (TP) due to the lack of hydro-climatic observations. In this study, we investigate seasonal cycles and trends of water budget components (e.g., precipitation-P, evapotranspiration-ET and runoff-Q) in eighteen TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g., in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations). A water balance-based two-step procedure, which considers the changes in basin-scale water storage at the annual scale, is also adopted to calculate actual ET. The results indicated that precipitation (mainly snowfall from mid-autumn to next spring), which mainly concentrated during June–October (varied among different monsoons-impacted basins), was the major contributor to the runoff in TP basins. Increased P, ET and Q were found in most TP basins during the past 30 years except for the upper Yellow River basin and some sub-basins of Yalong River, which were mainly affected by the weakening East Asian Monsoon. Moreover, the aridity index (PET/P) and runoff coefficient (Q/P) decreased in most basins, which were in agreement with the warming and moistening climate in the Tibetan Plateau. The results obtained demonstrated the usefulness of integrating multi-source datasets to hydrological applications in the data-sparse regions. More generally, such approach might offer helpful insights towards understanding the water and energy budgets and sustainability of water resource management practices of data-sparse regions in a changing environment.

scholarly journals Investigating water budget dynamics in 18 river basins across the Tibetan Plateau through multiple datasets

2018 ◽  
Vol 22 (1) ◽  
pp. 351-371 ◽  
Author(s):  
Wenbin Liu ◽  
Fubao Sun ◽  
Yanzhong Li ◽  
Guoqing Zhang ◽  
Yan-Fang Sang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Budget ◽  
Water Resource Management ◽  
Yellow River ◽  
Aridity Index ◽  
River Basins ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Basin Scale

Abstract. The dynamics of basin-scale water budgets over the Tibetan Plateau (TP) are not well understood nowadays due to the lack of in situ hydro-climatic observations. In this study, we investigate the seasonal cycles and trends of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q) in 18 TP river basins during the period 1982–2011 through the use of multi-source datasets (e.g. in situ observations, satellite retrievals, reanalysis outputs and land surface model simulations). A water balance-based two-step procedure, which considers the changes in basin-scale water storage on the annual scale, is also adopted to calculate actual ET. The results indicated that precipitation (mainly snowfall from mid-autumn to next spring), which are mainly concentrated during June–October (varied among different monsoons-impacted basins), was the major contributor to the runoff in TP basins. The P, ET and Q were found to marginally increase in most TP basins during the past 30 years except for the upper Yellow River basin and some sub-basins of Yalong River, which were mainly affected by the weakening east Asian monsoon. Moreover, the aridity index (PET/P) and runoff coefficient (Q/P) decreased slightly in most basins, which were in agreement with the warming and moistening climate in the Tibetan Plateau. The results obtained demonstrated the usefulness of integrating multi-source datasets to hydrological applications in the data-sparse regions. More generally, such an approach might offer helpful insights into understanding the water and energy budgets and sustainability of water resource management practices of data-sparse regions in a changing environment.

Spatiotemporal characteristics of water budget dynamic in the Yarlung Tsangpo River basin of Tibetan Plateau based on multi-source datasets

2020 ◽  
Author(s):  
Yao Jiang ◽  
Zongxue Xu
Keyword(s):  
Tibetan Plateau ◽  
River Basin ◽  
Water Budget ◽  
Water Resource Management ◽  
The Tibetan Plateau ◽  
Water Budgets ◽  
Climate Conditions ◽  
Basin Scale ◽  
Yarlung Tsangpo ◽  
Yarlung Tsangpo River

<p>Understanding the dynamics of basin-scale water budgets over the Tibetan Plateau (TP) is significant for hydrology and water resource management in the southern and eastern Asia. However, a detailed water balance analysis is limited by the lack of adequate hydro-climatic observations in this region. In this study, we investigate the spatiotemporal variation of water budget components (e.g. precipitation P, evapotranspiration ET and runoff Q etc.) in the Yarlung Tsangpo River basin (YTB) of southeast TP during the period of 1975-2015 through using multi-source datasets (e.g. insitu observation, remote sensing data products, reanalysis outputs and model simulations etc.). The change trend of water budget components and vegetation parameters was analyzed in the YTB on interannual scale. The results indicated that the detailed water budgets are different from upstream to downstream YTB due to different temperature, vegetation cover and evapotranspiration, which are mainly affected by different climate conditions. In the whole basin, precipitation that are mainly during June to October was the major contributor to the runoff. The P and Q were found to show a slight but insignificant decrease in most regions of YTB since the late 1990s, which showed positive relationships with the weakening Indian summer monsoon. While the ET showed an insignificant increase across most of the YTB, especially in the middle basin. The runoff coefficient (Q/P) exhibited an indistinctively decreasing trend which may be, to some extent, due to the overlap effects of ET increase and snow and glacier changes. The obtained results offer insights into understanding the evolution mechanism of hydrological processes in such a data-sparse region under changing environment.</p>

scholarly journals Seasonal cycles and trends of water budget components in 18 river basins across Tibetan Plateau: a multiple datasets perspective

2016 ◽  
Author(s):  
Wenbin Liu ◽  
Fubao Sun ◽  
Yanzhong Li ◽  
Guoqing Zhang ◽  
Yan-Fang Sang ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Water Budget ◽  
Snow Water Equivalent ◽  
Climate Model ◽  
East Asian Monsoon ◽  
Aridity Index ◽  
Western China ◽  
Surface Model ◽  
Seasonal Cycles

Abstract. The insights of water budgets over Tibetan Plateau (TP) are not fully understood so far due to the lack of quantitative observations of the land surface processes. Here, we investigated the seasonal cycles and trends of water budget components in 18 TP basins through the use of multi-source datasets during the period 1982–2011. A two-step bias correction procedure was applied to calculate the basin-wide evapotranspiration (ET) through the water balance considering the influences of glacier and water storage change. The results indicated that precipitation, which mainly concentrated during June–October (varied among different monsoons impacted basins), is the major contributor to the runoff in TP basins. The basin-wide snow water equivalent (SWE) was relatively higher from mid-autumn to spring for most TP basins. The water cycles intensified under a global warming in most basins except for the upper Yellow and Yalong Rivers, which were significantly influenced by the weakening East Asian monsoon. Corresponded to the climate warming and moistening in the TP and western China, the aridity index (PET/P) in most basins decreased. The general hydrological regimes could be inferred from the perspective of multi-source datasets although there are considerable uncertainties from different datasets, which are comparable to some existing studies using the field observations and complex modeling approaches. The results highlighted the usefulness of integrating the multi-source data (e.g., in situ observations, remote sensing products, reanalysis, land surface model simulations and climate model outputs) for hydrological applications in the data-sparse environments and could be benefit for understanding the water and energy budgets, sustainable management of water resources under a warming climate in the harsh and data-sparse Tibetan Plateau.

scholarly journals Influence of thermodynamic soil and vegetation parameterizations on the simulation of soil temperature states and surface fluxes by the Noah LSm over a Tibetan plateau site

2009 ◽  
Vol 6 (1) ◽  
pp. 455-499 ◽  
Author(s):  
R. van der Velde ◽  
Z. Su ◽  
M. Ek ◽  
M. Rodell ◽  
Y. Ma
Keyword(s):  
Thermal Properties ◽  
Tibetan Plateau ◽  
Land Surface ◽  
Land Surface Model ◽  
Soil Heat Flux ◽  
Stomatal Resistance ◽  
Surface Fluxes ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Soil Thermal Properties

Abstract. In this paper, we investigate the ability of the Noah Land Surface model (LSm) to simulate temperature states in the soil profile and surface fluxes measured during a 7-day dry period at a micrometeorological station on the Tibetan Plateau. Adjustments in soil and vegetation parameterizations required to ameliorate the Noah simulation on these two aspects are presented, which include: (1) Differentiating the soil thermal properties of top- and subsoils, (2) Investigation of the different numerical soil discretizations and (3) Calibration of the parameters utilized to describe the transpiration dynamics of the Plateau vegetation. Through the adjustments in the parameterization of the soil thermal properties (STP) simulation of the soil heat transfer is improved, which results in a reduction of Root Mean Squared Differences (RMSD's) by 14%, 18% and 49% between measured and simulated skin, 5-cm and 25-cm soil temperatures, respectively. Further, decreasing the minimum stomatal resistance (Rc, min) and the optimum temperature for transpiration (Topt) of the vegetation parameterization reduces RMSD's between measured and simulated energy balance components by 30%, 20% and 5% for the sensible, latent and soil heat flux, respectively.

Developing the soil texture effects on the surface resistance to bare soil based on MOD16 algorithm to estimate evapotranspiration over the Tibetan Plateau

2020 ◽  
Author(s):  
Ling Yuan ◽  
Yaoming Ma ◽  
Xuelong Chen
Keyword(s):  
Tibetan Plateau ◽  
Soil Texture ◽  
Land Surface ◽  
Bare Soil ◽  
The Other ◽  
Accurate Estimation ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
The Mean ◽  
Modified Algorithm

<p>Evapotranspiration (ET), composed of evaporation (ETs) and transpiration (ETc) and intercept water (ETw), plays an indispensable role in the water cycle and energy balance of land surface processes. A more accurate estimation of ET variations is essential for natural hazard monitoring and water resource management. For the cold, arid, and semi-arid regions of the Tibetan Plateau (TP), previous studies often overlooked the decisive role of soil properties in ETs rates. In this paper, an improved algorithm for ETs in bare soil and an optimized parameter for ETc over meadow based on MOD16 model are proposed for the TP. The nonlinear relationship between surface evaporation resistance (r<sub>s</sub><sup>s</sup>) and soil surface hydration state in different soil texture is redefined by ground-based measurements over the TP. Wind speed and vegetation height were integrated to estimate aerodynamic resistance by Yang et al. (2008). The validated value of the mean potential stomatal conductance per unit leaf area (C<sub>L</sub>) is 0.0038m s<sup>-1</sup>. And the algorithm was then compared with the original MOD16 algorithm and a soil water index–based Priestley-Taylor algorithm (SWI–PT). After examining the performance of the three models at 5 grass flux tower sites in different soil texture over the TP, East Asia, and America, the validation results showed that the half-hour estimates from the improved-MOD16 were closer to observations than those of the other models under the all-weather in each site. The average correlation coefficient(R<sup>2</sup>) of the improved-MOD16 model was 0.83, compared with 0.75 in the original MOD16 model and 0.78 in SWI-PT model. The average values of the root mean square error (RMSE) are 35.77W m<sup>-2</sup>, 79.46 W m<sup>-2</sup>, and 73.88W m<sup>-2</sup> respectively. The average values of the mean bias (MB) are -4.08W m<sup>-2</sup>, -52.36W m<sup>-2</sup>, and -11.74 W m<sup>-2</sup> overall sites, respectively. The performance of these algorithms are better achieved on daily (R<sup>2</sup>=0.81, RMSE=17.22W m<sup>-2</sup>, MB=-4.12W m<sup>-2</sup>; R<sup>2</sup>=0.64, RMSE=56.55W m<sup>-2</sup>, MB=-48.74W m<sup>-2</sup>; R2=0.78, RMSE=22.3W m<sup>-2</sup>, MB=-9.82W m<sup>-2</sup>) and monthly (R2=0.93, RMSE=23.35W m<sup>-2</sup>, MB=-2.8W m<sup>-2</sup>; R2=0.86, RMSE=69.11W m<sup>-2</sup>, MB=-39.5W m<sup>-2</sup>; R2=0.79, RMSE=62.8W m<sup>-2</sup>, MB=-9.7W m<sup>-2</sup>) scales. Overall, the results showed that the newly developed MOD16 model captured ET more accurately than the other two models. The comparisons between the modified algorithm and two mainstream methods suggested that the modified algorithm could produce high accuracy ET over the meadow sites and has great potential for land surface model improvements and remote sensing ET promotion for the ET region.</p>

scholarly journals Recent Changes in the Moisture Source of Precipitation over the Tibetan Plateau

2017 ◽  
Vol 30 (5) ◽  
pp. 1807-1819 ◽  
Author(s):  
Chi Zhang ◽  
Qiuhong Tang ◽  
Deliang Chen
Keyword(s):  
Tibetan Plateau ◽  
Land Surface ◽  
Hydrological Cycle ◽  
Land Surface Model ◽  
Water Vapor Transport ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Precipitation Trend ◽  
Moisture Source ◽  
Moisture Supply

Abstract Evidence has suggested a wetting trend over part of the Tibetan Plateau (TP) in recent decades, although there are large uncertainties in this trend due to sparse observations. Examining the change in the moisture source for precipitation over a region in the TP with the most obvious increasing precipitation trend may help understand the precipitation change. This study applied the modified Water Accounting Model with two atmospheric reanalyses, ground-observed precipitation, and evaporation from a land surface model to investigate the change in moisture source of the precipitation over the targeted region. The study estimated that on average more than 69% and more than 21% of the moisture supply to precipitation over the targeted region came from land and ocean, respectively. The moisture transports from the west of the TP by the westerlies and from the southwest by the Indian summer monsoon likely contributed the most to precipitation over the targeted region. The moisture from inside the region may have contributed about 18% of the total precipitation. Most of the increased moisture supply to the precipitation during 1979–2013 was attributed to the enhanced influx from the southwest and the local moisture supply. The precipitation recycling ratio over the targeted region increased significantly, suggesting an intensified hydrological cycle. Further analysis at monthly scale and with wet–dry-year composites indicates that the increased moisture contribution was mainly from the southwest and the targeted region during May and September. The enhanced water vapor transport from the Indian Ocean during July and September and the intensified local hydrological recycling seem to be the primary reasons behind the recent precipitation increase over the targeted region.

scholarly journals Missing water from the Qiangtang Basin on the Tibetan Plateau

Geology ◽  
2021 ◽  
Author(s):  
Bin Yong ◽  
Chi-Yuen Wang ◽  
Jiansheng Chen ◽  
Jiaqi Chen ◽  
D.A. Barry ◽  
...  
Keyword(s):  
Tibetan Plateau ◽  
Water Cycle ◽  
Yellow River ◽  
Outer Region ◽  
Normal Faults ◽  
The Tibetan Plateau ◽  
Satellite Mission ◽  
Qiangtang Basin ◽  
Basin Scale ◽  
Terrestrial Water

The Qiangtang Basin is a large endorheic basin in the inner part of the Tibetan Plateau, and has been thought to be a dry region in contrast with the surrounding wet outer region that feeds all the major Asian rivers. Combining surface hydrological data with modeling and satellite data from 2002 to 2016 CE, our study reveals that an enormous amount of water, ~54 ± 4 km3, is unaccounted for annually in the Qiangtang Basin. The amount of missing water is comparable to the total annual discharge of the Yellow River. Data from the Gravity Recovery and Climate Experiment (GRACE) satellite mission show little increase of local terrestrial water storage. Thus, the missing water must have flowed out of the basin through underground passages. Interpreting this result in the context of recent seismic and geological studies of Tibet, we suggest that a significant amount of meteoric water in the Qiangtang Basin leaks out by way of groundwater flow through deep normal faults and tensional fractures along the nearly north-south rift valleys that are oriented subnormal to and cross the surficial hydrological divide on the southern margin of the basin. Cross-basin groundwater outflow of such a magnitude defies the traditional view of a basin-scale water cycle and leads to a very different picture from the previous hydrological view of the Qiangtang Basin. This finding calls for major rethinking of the regional water balance.

scholarly journals Evaluating and improving simulations of diurnal variation in land surface temperature with the Community Land Model for the Tibetan Plateau

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11040
Author(s):  
Xiaogang Ma ◽  
Jiming Jin ◽  
Lingjing Zhu ◽  
Jian Liu
Keyword(s):  
Thermal Conductivity ◽  
Tibetan Plateau ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Soil Layer ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Soil Thermal Conductivity ◽  
Community Land Model

This study evaluated and improved the ability of the Community Land Model version 5.0 (CLM5.0) in simulating the diurnal land surface temperature (LST) cycle for the whole Tibetan Plateau (TP) by comparing it with Moderate Resolution Imaging Spectroradiometer satellite observations. During daytime, the model underestimated the LST on sparsely vegetated areas in summer, whereas cold biases occurred over the whole TP in winter. The lower simulated daytime LST resulted from weaker heat transfer resistances and greater soil thermal conductivity in the model, which generated a stronger heat flux transferred to the deep soil. During nighttime, CLM5.0 overestimated LST for the whole TP in both two seasons. These warm biases were mainly due to the greater soil thermal inertia, which is also related to greater soil thermal conductivity and wetter surface soil layer in the model. We employed the sensible heat roughness length scheme from Zeng, Wang & Wang (2012), the recommended soil thermal conductivity scheme from Dai et al. (2019), and the modified soil evaporation resistance parameterization, which was appropriate for the TP soil texture, to improve simulated daytime and nighttime LST, evapotranspiration, and surface (0–10 cm) soil moisture. In addition, the model produced lower daytime LST in winter because of overestimation of the snow cover fraction and an inaccurate atmospheric forcing dataset in the northwestern TP. In summary, this study reveals the reasons for biases when simulating LST variation, improves the simulations of turbulent fluxes and LST, and further shows that satellite-based observations can help enhance the land surface model parameterization and unobservable land surface processes on the TP.

Evaluation of WRF coupled with Noah using an improved albedo parameterization scheme during a severe snow event over the Tibetan Plateau

2020 ◽  
Author(s):  
Lian Liu ◽  
Massimo Menenti ◽  
Yaoming Ma ◽  
Weiqiang Ma
Keyword(s):  
Tibetan Plateau ◽  
Air Temperature ◽  
Land Surface ◽  
Large Impact ◽  
Parameterization Scheme ◽  
Surface Model ◽  
The Tibetan Plateau ◽  
Vegetation Fraction ◽  
Green Vegetation ◽  
Heavy Snow

<p>Snow falls frequently over the Tibetan Plateau, and is a vital component of the widespread cryosphere which has vital feedback to climate change. Snowfall and the subsequent evolution of the snowpack have a large effect on surface energy balance and water cycle. Albedo, the main determinant of net radiation flux, is a major driver of land surface processes. However, the current widely used Noah land surface model does not describe snow albedo correctly, although it keeps snow-related variables i.e. snow cover and age into account. In our study, the impact of an improved albedo parameterization scheme in WRF coupled with Noah was investigated. In the improved albedo scheme, albedo was parameterized as functions of snow depth and age which was developed using remote sensing retrievals of albedo. Numerical experiments were conducted to model a severe snow event in March 2017. The performance of WRF coupled with Noah applying the improved albedo scheme was compared with that of applying the default albedo scheme and with that of WRF coupled with CLM applying CLM’s complex albedo scheme. First, the improved albedo scheme largely reduces the WRF coupled with Noah albedo overestimation in the southeastern Tibetan Plateau, remarkably reducing the large cold bias estimates by 0.7 ℃ air temperature RMSE. Second, the improved albedo scheme gives the highest correlationship between the satellite-derived and the model estimated albedo, contributing to achieve the SWE spatial pattern, heavy snow belt and maximum SWE estimates in eastern Tibetan Plateau. Remarkable underestimation of albedo in WRF coupled with CLM contributes to regional maximum SWE underestimation and failure in heavy snow belt estimates.</p><p>In addition, WRF default land cover and green vegetation fraction were out of date but played a large impact on estimates of air temperature, albedo and SWE. Updated land parameters led to improve the model performance in simulating the severe snow event, by reducing albedo RMSE by 1%-4%. The choice of the algorithm to retrieve green vegetation fraction had a large impact on the accuracy of green vegetation fraction retrievals. It remains open to debate the optimal algorithm to estimate land surface properties in the complex topographic Tibetan Plateau.</p>

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