Spatiotemporal Change of Blue Water and Green Water Resources in the Headwater of Yellow River Basin, China

Green water accounts for two-thirds of precipitation, and the proportion could be even higher in dry years. Conflicts between water supply and demand have gradually become severe in the Hai River Basin (HRB) due to the socioeconomic development. Thus, the exploitation and the utilization of green water have attracted increasing attention. By gathering the related hydrological, meteorological, and geographic data, the spatiotemporal distribution of green water in HRB and the impacts of land use types on green water are analyzed based on the SWAT (Soil and Water Assessment Tool) model in this study. Furthermore, three new indices are proposed for evaluation, including the maximum possible storage of green water (MSGW), the consumed green water (CGW), and the utilizable green water (UGW). The results show that (1) the MSGW is relatively low in plain areas and its spatial distribution is significantly associated with the soil type; (2) according to the evaluation results of CGW and UGW in HRB, a further improvement of utilization efficiency of green water could be achieved; (3) in general, the utilization efficiency of precipitation in farmlands is higher than other land use types, which means that the planting of appropriate plants could be helpful to enhance the utilization efficiency of green water. Our results summarize the spatiotemporal distribution of green water resource and provide a reference for water resources management in other water-short agricultural areas.

Section: Evaluation Methodsmentioning

confidence: 99%

The Assessment of Green Water Based on the SWAT Model: A Case Study in the Hai River Basin, China

Zhu

Xie

Zhao

et al. 2018

“…The overall hydrologic balance is simulated for each HRU, including: the canopy interception of precipitation, partitioning of precipitation, snowmelt water, redistribution of water within the soil profile, evapotranspiration (ET), lateral subsurface flow from the soil profile, and the return flow from shallow aquifers. SWAT has been widely applied in a range of climatic, topographic, soil, and management conditions around the world to investigate a broad range of hydrological and environmental topics [58], including the cases of snow hydrology studies [59][60][61] and the glacial hydrology studies [38,39,44].…”

Section: Description Of Swatmentioning

confidence: 99%

“…Generally, SWAT allows the sub-watershed to be split into a maximum of ten elevation bands, and the temperature and precipitation for each band to be adjusted using t laps and p laps , respectively. A detailed description has been reported in the model documentation [61]. SWAT2005 is used in this study.…”

Section: Description Of Swatmentioning

confidence: 99%

The Spatial and Temporal Contribution of Glacier Runoff to Watershed Discharge in the Yarkant River Basin, Northwest China

Yin

Feng

Liu

et al. 2017

Abstract:In this paper, a glacial module based on an enhanced temperature-index approach was successfully introduced into the Soil and Water Assessment Tool (SWAT) model to simulate the glacier runoff and water balance of a glacierized watershed, the mountainous region of the Yarkant River Basin (YRB) in Karakoram. Calibration and validation of the SWAT model were based on comparisons between the simulated and observed discharge with a monthly temporal resolution from 1961 to 2011 for the Kaqun hydrological station. The results reaffirmed the viability of the approach for simulating glacier runoff, as evidenced by a Nash-Sutcliff Efficiency (NSE) of 0.82-0.86 as well as a percentage bias (PBIAS) of −4.5% to 2.4%, for the calibration and validation periods, respectively. Over the last 50 years, the total discharge and glacier runoff both exhibited increasing trends with 0.031 × 10 9 m 3 ·a −1 and 0.011 × 10 9 m 3 ·a −1 . The annual glacier runoff contribution to the streamflow was between 42.3% and 64.5%, with an average of 51.6%, although the glaciers accounted for only 12.6% of the watershed drainage area in the mountainous YRB. The monthly contribution of the glacier runoff ranged from 11.0% in April to 62.1% in August, and the glacier runoff from June to September accounted for about 86.3% of the annual glacier runoff. Runoff from the mountainous regions above 5000 m a.s.l. accounted for 70.5% of the total discharge, with glacier runoff contributions being approximately 46.4%.

“…Since then, numerous methods have been used to assess blue water and green water resources. With the development of distributed hydrological models, the temporal-spatial variations of blue and green water resources can be estimated by methods which have a clearer physical mechanism [11,[21][22][23]. It has been demonstrated that the soil and water assessment tool (SWAT) model can simulate blue and green water resources and detect the impacts of climate variability on hydrological components [24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Impact of Climate Variability on Blue and Green Water Flows in the Erhai Lake Basin of Southwest China

Yuan

Meng

et al. 2019

The Erhai Lake Basin is a crucial water resource of the Dali prefecture. This research used the soil and water assessment tool (SWAT) and the China Meteorological Assimilation Driving Datasets for the SWAT model (CMADS) to estimate blue and green water flows. Then the spatial and temporal change of blue and green water flows was investigated. With the hypothetical climate change scenarios, the sensitivity of blue and green water flows to precipitation and temperature has also been analyzed. The results showed that: (1) The CMADS reanalysis dataset can capture the observed probability density functions for daily precipitation and temperature. Furthermore, the CMADS performed well in monthly variables simulation with relative bias and absolute bias less than 7% and 0.5 °C for precipitation and temperature, respectively; (2) blue water flow has increased while green water flow has decreased during 2009 to 2016. The spatial distribution of blue water flow was uneven in the Erhai Lake Basin with the blue water flow increased from low altitudes to mountain areas. While the spatial distribution of green water flow was more homogeneous; (3) a 10% increase in precipitation can bring a 20.8% increase in blue water flow with only a 2.5% increase in green water flow at basin scale. When temperature increases by a 1.0 °C, the blue water flow and green water flow changes by −3% and 1.7%, respectively. Blue and green water flows were more sensitive to precipitation in low altitude regions. In contrast, the water flows were more sensitive to temperature in the mountainous area.