Climate change is the main driving force for altering river basin hydrology, and the impact of climate and land cover changes on hydrological components has garnered substantial attention in recent years. This study aimed to assess the effects of climate and land cover changes on the components of the hydrological cycle in the Middle Huai River Basin (MHRB) during the reference period (1991–2020) and two future periods, mid-term (2041–2060) and long-term (2071–2090), under three Shared Socioeconomic Pathway scenarios (SSPs) (SSP126, SSP245, and SSP585). The Soil and Water Assessment Tool (SWAT) model was employed to simulate hydrological cycle components, such as surface runoff (RF), actual (ETa), potential (ETp) evapotranspiration, and total water yield (TWY). The Long Ashton Research Station weather generator (LARS-WG 8.0) was used to downscale climate variables (i.e., precipitation, maximum (Tmax), and minimum (Tmin) temperatures) from global climate models (GCMs) to the site level. The study revealed that climate change is the dominant factor impacting hydrological cycle components in the MHRB compared to land use and land cover (LULC) change during the reference period. Climate change positively contributed to ETa and ETp, whereas it negatively impacted RF and TWY during the reference period. Future projections of climate variables, including precipitation and both maximum (Tmax) and minimum (Tmin) temperatures, are projected to increase across all hydrometeorological stations in both future periods and all three SSPs scenarios. The mean annual precipitation was projected to increase by 13.63% under SSP126, 16.22% under SSP245, and 18.78% under SSP585. The mean annual Tmax and Tmin are projected to increase by 2.18 and 1.58 °C, 2.64 and 2.19 °C, and 3.77 and 3.21 °C under SSP126, SSP245, and SSP585, respectively. The components of the hydrological cycle in the MHRB are projected to increase under future climate scenarios owing to increased precipitation and temperature. However, greater monthly variability was observed, which may pose a risk to agricultural production in this region. For example, decreases in RF and ETa were projected in September and July, respectively, whereas ETp and TWY were expected to increase in all months. With the projected increase in climate variables, the mean annual RF was simulated to increase by 31.32% under SSP126, 37.12% under SSP245, and 45.43% under SSP585, with the most significant increase anticipated in the long-term period (42.92%) compared to that in the mid-term period (33%). Similarly, the mean annual ETa and ETp are projected to increase by 6.73% and 6.74% under SSP126, 7.89% and 8.77% under SSP245, and 9.90% and 13.09% under SSP585, respectively. The analysis of single climate variables revealed that precipitation exerted a more substantial positive influence on RF and ETp than air temperature. Conversely, the combined effect of precipitation and air temperature demonstrated a greater positive impact on ETa than either variable. The combined impact of increased precipitation and air temperature in the river basin resulted in the most significant rise in average seasonal RF during spring (46.76%), followed by winter (42.41%), summer (38.77%), and autumn (17.05%). Additionally, there was an increase in the monthly TWY, ranging from 12.12% to 46.97%.

Modelling the impact of climate and land cover changes on hydrological cycle components: a case of the middle Huai river basin

期刊论文
发表日期：

2025年12月29日

查看全文

Kinde Negessa Disasa,
Haofang Yan,
Guoqing Wang,
Jianyun Zhang,
Chuan Zhang,
Biyu Wang,
Rongxuan Bao

摘要

Climate change is the main driving force for altering river basin hydrology, and the impact of climate and land cover changes on hydrological components has garnered substantial attention in recent years. This study aimed to assess the effects of climate and land cover changes on the components of the hydrological cycle in the Middle Huai River Basin (MHRB) during the reference period (1991–2020) and two future periods, mid-term (2041–2060) and long-term (2071–2090), under three Shared Socioeconomic Pathway scenarios (SSPs) (SSP₁₂₆, SSP₂₄₅, and SSP₅₈₅). The Soil and Water Assessment Tool (SWAT) model was employed to simulate hydrological cycle components, such as surface runoff (RF), actual (ET_a), potential (ET_p) evapotranspiration, and total water yield (TWY). The Long Ashton Research Station weather generator (LARS-WG 8.0) was used to downscale climate variables (i.e., precipitation, maximum (T_max), and minimum (T_min) temperatures) from global climate models (GCMs) to the site level. The study revealed that climate change is the dominant factor impacting hydrological cycle components in the MHRB compared to land use and land cover (LULC) change during the reference period. Climate change positively contributed to ET_a and ET_p, whereas it negatively impacted RF and TWY during the reference period. Future projections of climate variables, including precipitation and both maximum (T_max) and minimum (T_min) temperatures, are projected to increase across all hydrometeorological stations in both future periods and all three SSPs scenarios. The mean annual precipitation was projected to increase by 13.63% under SSP₁₂₆, 16.22% under SSP₂₄₅, and 18.78% under SSP₅₈₅. The mean annual T_max and T_min are projected to increase by 2.18 and 1.58 °C, 2.64 and 2.19 °C, and 3.77 and 3.21 °C under SSP₁₂₆, SSP₂₄₅, and SSP₅₈₅, respectively. The components of the hydrological cycle in the MHRB are projected to increase under future climate scenarios owing to increased precipitation and temperature. However, greater monthly variability was observed, which may pose a risk to agricultural production in this region. For example, decreases in RF and ET_a were projected in September and July, respectively, whereas ET_p and TWY were expected to increase in all months. With the projected increase in climate variables, the mean annual RF was simulated to increase by 31.32% under SSP₁₂₆, 37.12% under SSP₂₄₅, and 45.43% under SSP₅₈₅, with the most significant increase anticipated in the long-term period (42.92%) compared to that in the mid-term period (33%). Similarly, the mean annual ET_a and ET_p are projected to increase by 6.73% and 6.74% under SSP₁₂₆, 7.89% and 8.77% under SSP₂₄₅, and 9.90% and 13.09% under SSP₅₈₅, respectively. The analysis of single climate variables revealed that precipitation exerted a more substantial positive influence on RF and ET_p than air temperature. Conversely, the combined effect of precipitation and air temperature demonstrated a greater positive impact on ET_a than either variable. The combined impact of increased precipitation and air temperature in the river basin resulted in the most significant rise in average seasonal RF during spring (46.76%), followed by winter (42.41%), summer (38.77%), and autumn (17.05%). Additionally, there was an increase in the monthly TWY, ranging from 12.12% to 46.97%.