Modelling the Impact of Vegetation Change on Hydrological Processes in Bayin River Basin, Northwest China

Waterlogging refers to the damage to plants by water stress due to excess soil water in the crop’s root zone that exceeds the maximum water holding capacity of the field. It is one of the major disasters affecting agricultural production. This study aims to add a crop waterlogging identification module to the coupled SWAT (Soil and Water Assessment Tools)-MODFLOW (Modular Finite Difference Groundwater Flow Model) model and to accurately identify and predict crop waterlogging risk areas under the CMIP6 (Coupled Model Intercomparison Project 6) climate scenarios. The result showed that: (1) The SWAT-MODFLOW model, which coupled with a crop waterlogging identification module, had good simulation results for LAI (Leaf Area Index), ET (Evapotranspiration), spring wheat yield, and groundwater level in the middle and lower reaches of the Bayin River; (2) The precipitation showed an overall increasing trend in the Bayin River watersheds over the next 80 years under the SSP1-2.6, SSP2-4.5 and SSP5-8.5 scenarios. The temperature showed a clear increasing trend over the next 80 years under the SSP2-4.5 and SSP5-8.5 scenarios; (3) Under the SSP1-2.6 scenario, the mountain runoff from the upper reaches of the Bayin River was substantially higher than in other scenarios after 2041. The mountain runoff in the next 80 years will decrease substantially under the SSP2-4.5 scenario. The mountain runoff over the next 80 years showed an initial decrease and then an increasing trend under the SSP5-8.5 scenario; (4) During the historical period, the crop waterlogging risk area was 10.9 km2. In the next 80 years, the maximum crop waterlogging area will occur in 2055 under the SSP1-2.6 scenario. The minimum crop waterlogging area, 9.49 km2, occurred in 2042 under the SSP2-4.5 scenario. The changes in the area at risk of crop waterlogging under each scenario are mainly influenced by the mountain runoff from the upper reaches of the Bayin River.

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Identification and Prediction of Crop Waterlogging Risk Areas under the Impact of Climate Change

Jin

Zhai

et al. 2022

“…The WRB starts in the Niaoshu Mountain, flows through Gansu, Ningxia, Shanxi, and eventually joins the Yellow River at Tongguan. The average annual natural runoff is 10.4 billion m 3 . The average annual precipitation is about 610 mm, the average annual tem-perature ranges from 7.8 to 13.5 • C, and the average annual potential evapotranspiration (PET) varies from 800 to 1200 mm [36].…”

Section: Study Area and Hydrometeorological Datamentioning

confidence: 99%

“…The global hydrologic cycle and distribution of water resources are changing on various scales due to climate change and human interference during the past decades [1][2][3]. The changes in precipitation, temperature, wind speed, humidity, and solar radiation have caused decreases in streamflow in some regions [4,5].…”

Section: Introductionmentioning

confidence: 99%

Base Flow Variation and Attribution Analysis Based on the Budyko Theory in the Weihe River Basin

Liu

Lin

et al. 2022

The composition and change of runoff are closely related to climate change and human activities. To design effective watershed water resources management measures, there is a need for a clear understanding of the impact of climate change and human activities on baseflow and surface runoff. The purpose of this essay is to quantify their impact on the annual total stream flow, surface runoff, and base flow in the Weihe River Basin (WRB) using a two-stage annual precipitation partitioning method, wherein the surface runoff and base flow are separated from the measured total flow by using a one-parameter digital filter method for which the common filter parameter value is 0.925. The stream flow records were split into two periods: 1960–1970 (pre-change period) and 1971–2005 (post-change period) based on the hydrological breakpoints detected. We found that climate change and human activities have different impacts on base flow and surface runoff. We attributed the decrease in surface runoff due to climate change accounting for 76–78%, while we determined that human activities were responsible to the decrease in base flow accounting for 59–73% of the total observed change. We concluded that both climate change and human beings contributed to the hydrologic change through different hydrological processes: climate change dominated the surface runoff change, while human influences controlled the base flow change. To achieve the expected goals of ecological restoration, appropriate measures must be taken by watershed management in the WRB to mitigate the likely impacts of climate change on water hydrology.

“…The results showed that nitrate-nitrogen loads in this region showed a decreasing trend. Xin et al [16] combined the dynamic hydrological response units with a coupled SWAT-MODFLOW, which can reflect actual land cover changes in the basin, to simulate the vegetation change in the Bayin River basin, an arid inland river in China. The results can assist in ensuring revegetation sustainability and rationally allocating water resources in arid areas.…”

Section: Introductionmentioning

confidence: 99%

Study on the Impact of Land-Use Change on Runoff Variation Trend in Luojiang River Basin, China

Wan

Chen

et al. 2021

To reveal the influence process of land use changes on runoff variation trends, this paper takes the Luojiang River of China as the study area, and the Soil and Water Assessment Tool (SWAT) model was constructed to quantitatively analyze the impact of different land uses on runoff formation in the watershed, and used the Cellular Automata-Markov (CA-Markov) model to predict future land use scenarios and runoff change trends. The results show that: (1) the SWAT model can simulate the runoff in the Luojiang River basin; (2) the runoff in the Luojiang River basin has a decreasing trend in recent 10 years, caused by the decrease of rainfall and runoff due to changes in land use; (3) the forecast shows that the land-use changes in the basin will lead to an increase in runoff coefficient in 2025. The increase of the runoff coefficient will bring some adverse effects, and relevant measures should be taken to increase the water storage capacity of urban areas. This study can help plan future management strategies for the study area land coverage and put forward a preventive plan for the possible adverse situation of runoff variation.