Search Results (53)

Understanding the drivers of water yield (WY) changes in ecologically sensitive, data-scarce watersheds is crucial for sustainable management, particularly in the context of accelerating forest expansion and urbanization. This study focuses on the upper Yellow River Basin (UYRB), a critical headwater region that supplies 60% of the Yellow River’s flow and is undergoing rapid land use transitions from 1990 to 2100. Using the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) model and the Future Land-Use Simulation (FLUS) model, we quantify historical (1990–2020) and projected (2025–2100) WY dynamics under three SSP scenarios (SSP126, SSP370, and SSP585). InVEST, a spatially explicit ecohydrological model based on the Budyko framework, estimates WY by balancing precipitation and evapotranspiration. The FLUS model combines cellular automata (CA) with an artificial neural network (ANN)-based suitability evaluation and Markov chain-derived transition probabilities to simulate land-use change under multiple scenarios. Results show that WY increased significantly during the historical period (1990–2020), primarily driven by increased precipitation, with climate change accounting for 94% and land-use change for 6% of the total variation in WY. Under future scenarios (SSP126, SSP370, and SSP585), WY is projected to increase to 217 mm, 206 mm, and 201 mm, respectively. Meanwhile, the influence of land-use change is expected to diminish, with its contribution decreasing to 9.1%, 5.7%, and 3.1% under SSP126, SSP370, and SSP585, respectively. This decrease reflects the increasing strength of climate signals (especially extreme precipitation and evaporative demand), which masks the hydrological impacts of land-use transitions. These findings highlight the dominant role of climate change, the scenario-dependent effects of land-use change, and the urgent need for integrated climate–land management strategies in forest-urbanizing watersheds. Full article

The Tumen River Basin (TRB), a critical China border region, has experienced a complex evolution of runoff due to climate change and human activities. This study aims to quantify the main drivers of runoff variations in the TRB based on the Budyko framework to assess the relative contributions of climate change and human activities to runoff fluctuations. Results indicate pronounced warming and increased precipitation in the TRB, while runoff exhibits a declining trend with temporal variability. Runoff decreased during 1956–1980 but increased post 1980. Overall, climate change is the dominant factor driving runoff fluctuations in the TRB. A comparison across different sub-basins shows that the contribution of climate change to runoff variations is higher in the middle and upper reaches of the Tumen River, reaching up to 93.8%. In the lower basin, human activities contribute significantly to runoff variations. Higher forest cover and reservoir construction help maintain the long-term stability of watershed runoff. This study provides a scientific basis and data support for water resources development and ecological protection in the basin. Full article

This study examines runoff variations and their drivers in the Buha and Shaliu Rivers of the Qinghai Lake Basin (1960–2016), a key ecological area in China. Abrupt changes were detected using the Mann–Kendall and cumulative anomaly methods, while the Budyko framework attributed runoff variations to dominant factors. Correlation and grey relational analyses assessed multicollinearity, and a lake water balance model with climate elasticity theory quantified the effects of climate and land surface changes on runoff components and lake levels. Results indicate that the Buha River experienced an abrupt runoff change in 2004, while the Shaliu River exhibited a change beginning in 2003. Based on the trends and abrupt change points of each factor, the study period was divided into four segments: 1960–1993, 1994–2016, 1960–2003, and 2004–2016. The correlation coefficients are significantly different in different periods. The climate elasticity coefficients were as follows: P (precipitation), 1.98; ET₀ (potential evapotranspiration), −0.98; Rn (net radiation), 0.66; T (average temperature), 0.02; U₂ (wind speed at 2 m height), 0.16; RHU (relative umidity), −0.56. The elasticity coefficient of runoff with respect to precipitation is significantly higher than that for other climate variables. Net radiation and relative humidity contribute equally to runoff, while wind speed and temperature have relatively smaller effects. In the Qinghai Lake Basin, runoff is sensitive to precipitation (0.38), potential evapotranspiration (−0.07), and the underlying surface parameter ω (−98.32). Specifically, a 1 mm increase in precipitation raises runoff by 0.38 mm, while a 1 mm rise in potential evapotranspiration reduces it by 0.07 mm. A one-unit increase in ω leads to a significant runoff decrease of 98.32 mm. According to the lake water balance model, climate contributes 88.43% to groundwater runoff, while land surface changes contribute −11.57%. Climate change and land surface changes contribute 93.02% and 6.98%, respectively, to lake water levels. This study quantitatively evaluates the impacts of climate and land surface changes on runoff, providing insights for sustainable hydrological and ecological management in the Qinghai Lake Basin. Full article

Accurately understanding flood evolution and its attribution is crucial for watershed water resource management as well as disaster prevention and mitigation. The source region of the Yellow River (SRYR) has experienced several severe floods over the past few decades, but the driving factor influencing flood volume variation in the SRYR remains unclear. In this study, the Budyko framework was used to quantify the effects of climate change, vegetation growth, and permafrost degradation on flood volume variation in six basins of the SRYR. The results showed that the flood volume decreased before 2000 and increased after 2000, but the average value after 2000 remained lower than that before 2000. Flood volume is most sensitive to changes in precipitation, followed by changes in landscape in all basins. The decrease in flood volume was primarily influenced by changes in active layer thickness in permafrost-dominated basins, while it was mainly controlled by other landscape changes in non-permafrost-dominated basins. Meanwhile, the contributions of changes in potential evapotranspiration and water storage changes to the reduced flood volume were negative in all basins. Furthermore, the impact of vegetation growth on flood volume variation cannot be neglected due to its regulating role in the hydrological cycle. These findings can provide new insights into the evolution mechanism of floods in cryospheric basins and contribute to the development of strategies for flood control, disaster mitigation, and water resource management under a changing climate. Full article

The generalized proportionality hypothesis (GPH) highlights the competitive relationships among hydrological components as precipitation (P) transforms into runoff (Q) and evapotranspiration (E), providing a novel perspective on E partitioning that differs from the traditional physical source-based approach. To achieve sequential partitioning of E into initial (E_i) and continuing (E_c) evapotranspiration under the GPH, a P-Q relationship-based E_i estimation method was proposed for the Model Parameter Estimation Experiment (MOPEX) catchments. On this basis, we analyzed the relationship between the GPH-based E components and the physical source-based ones separated by the Penman-Monteith-Mu algorithm. Additionally, we explored the differences between the calculated and inverse Budyko-WT model parameter (E_i/E) and discussed the implications for the Budyko framework. The results showed the following: (1) A significant linear P-Q relationship (p < 0.05) prevailed in the MOPEX catchments, providing a robust data foundation for E_i estimation. Across the MOPEX catchments, E_i and E_c contributed 73% and 27% of total E, respectively. (2) The combined proportion of evaporation from canopy interception and wet soil averaged about 25%, and it was much lower than that of E_i, indicating that it was difficult to establish a connection between E_i and the physical source-based E components. (3) The potential evapotranspiration (E_P) satisfying the Budyko-WT model was strictly constrained by the GPH, while the inappropriate E_P estimation method largely explained the discrepancy between the calculated and inverse E_i/E. This study deepens the knowledge of the sequential partitioning of E components, uncovers the discrepancies between different E partitioning frameworks, and provides new insights into the characterization of key variables in Budyko models. Full article

The intensification of global climate change and human activities has made drought one of the most severe global challenges, bringing unprecedented challenges to the hydrological and water resource system. Although several studies have been conducted on hydrological droughts, few have examined the response relationship between hydrological droughts and water and energy balance. This study uses multi-year drought detection and the Budyko framework to investigate the impact of climate change and human activities on runoff changes, with a focus on the differences between drought and non-drought conditions. The results indicate that (1) the sensitivity of runoff to precipitation (εPR), potential evapotranspiration (PET) (εPET), and the watershed characteristic parameter n (εn) varies over time, initially increasing and then decreasing, and peaking between 1995 and 2006. Runoff is most sensitive to precipitation (PR) and least sensitive to potential evapotranspiration (PET). (2) The dominant contribution shifted from climate change during 1977–1985 to human activities during 1986–2014. (3) Multi-year drought in the Yellow River Basin (YRB) significantly altered n, εPR, εPET, and εn, changing from (1.50, 2.19, −1.19, −5.66) in non-drought periods to (1.84, 2.57, −1.57, −9.93) in drought periods, with greater absolute values during drought periods. (4) Compared to non-drought periods, the contribution scores of human activities (δh) are significantly higher. The growing contribution of human activities to runoff can exacerbate the occurrence of hydrological droughts. Full article

Actual evapotranspiration (AET) estimation plays a crucial role in watershed management. Hydrological models are commonly used to simulate watershed responses and estimate AET. However, their calibration heavily depends on station-based data, which is often limited in availability and frequently inaccessible, making the process challenging and time-consuming. In this study, the Budyko model framework, which effectively utilizes remote sensing data for hydrological modeling and requires the calibration of only one parameter, is adopted for AET estimation across Ontario, Canada. Four different parameter estimation methods were developed and compared, and an attribution analysis was also conducted to investigate the impacts of climate and vegetation factors on AET changes. Results show that the developed Budyko models performed well, with the best model achieving a Nash-Sutcliffe Efficiency (NSE) value of 0.74 and a Root Mean Square Error (RMSE) value of 55.5 mm/year. The attribution analysis reveals that climate factors have a greater influence on AET changes compared to vegetation factors. This study presents the first Budyko modeling attempt for Canadian watersheds. It demonstrates the applicability and potential of the Budyko framework for future case studies in Canada and other cold regions, providing a new, straightforward, and efficient alternative for AET estimation and hydrological modeling. Full article

This study aimed to assess the hydrological response and resilience of watersheds in a neotropical region to identify regions sensitive to climate variations, enabling the development of adaptive strategies in response to global environmental changes. This study applied Budyko’s framework using Fuh’s hydrological model rewritten by Zhou to estimate hydrological response and Budyko’s metrics (deviation and elasticity) to estimate hydrological resilience to climatic changes in 26 watersheds in southeastern Brazil. The proposed modeling was able to capture the differences among the watersheds, with “m” values ranging from 1.79 to 3.63. It was possible to rank the hydrological resilience from low to high across watersheds using Budyko’s metrics, where the highest values of elasticity were found in watersheds with a higher percentage of forest cover. The sensitive analyses showed that watersheds with higher “m” values are more sensitive to changes in precipitation and potential evapotranspiration. The results also demonstrate that mean elevation and stream density were two key variables that influence the “m” value; these physiographic characteristics may alter the water and energy balance of the watershed affecting the water yield. A relationship between watershed’s hydrological response and resilience was proposed to identify critical areas for the stability of water yield in the watersheds, providing a guide for public policy and suggesting ways to help the management of water resources in watersheds. Full article

Determining the relative roles of climatic versus anthropogenic factors in runoff alterations is important for sustainable water resource utilization and basin management. The Danjiang River watershed is a crucial water resource area of the middle route of the South-to-North Water Transfer Project. In this study, four widely used quantitative methods, including the simple linear regression, the double mass curve, the paired year with similar climate conditions, and an elasticity method based on the Budyko framework were applied to detect the relative contribution of climatic and anthropogenic factors to runoff variation in the Danjiang River watershed. The calculation processes of each method were systematically explained, and their characteristics and applications were summarized. The results showed that runoff decreased significantly (p < 0.05) with an average change rate of −3.88 mm year⁻¹ during the period of 1960–2017, and a significant change year was detected in 1989 (p < 0.05). Generally, consistent estimates could be derived from different methods that human activity was the dominant driving force of significant runoff reduction. Although the impacts of human activity estimated by the paired year with similar climate conditions method varied among paired years, the other three methods demonstrated that human activity accounted for 80.22–92.88% (mean 86.33%) of the total reduction in the annual runoff, whereas climate change only contributed 7.12–19.78% (mean 13.67%). The results of this study provide a good reference for estimating the effects of climate change and human activities on runoff variation via different methods. Full article

In recent years, the runoff of numerous rivers has experienced substantial changes owing to the dual influences of climate change and human activities. This study focuses on the Lixian hydrological station’s controlled basin, located in the upper reaches of the Jialing River in China. The objective is to assess and quantify the impacts of human activities and climate change on runoff variations. This study analyzed runoff variations from 1960 to 2016 and employed the Soil and Water Assessment Tool (SWAT) model, the long short-term memory (LSTM) model, and eight Budyko framework formulations to assess factors influencing runoff. Additionally, it used the patch-generating land use simulation (PLUS) and SWAT models to simulate future runoff scenarios under various conditions. The results indicate the following. (1) The study area has witnessed a significant decline in runoff (p < 0.01), while potential evapotranspiration shows a significant upward trend (p < 0.01). Precipitation displays a nonsignificant decreasing trend (p > 0.1). An abrupt change point in runoff occurred in 1994, dividing the study period into baseline and change periods. (2) The Budyko results reveal that human activities contributed 50% to 60% to runoff changes. According to the SWAT and LSTM models, the contribution rates of human activities are 63.21% and 52.22%, respectively. Human activities are thus identified as the predominant factor in the decline in runoff. (3) Human activities primarily influence runoff through land cover changes. Conservation measures led to a notable increase in forested areas from 1990 to 2010, representing the most significant change among land types. (4) Future land use scenarios suggest that the highest simulated runoff occurs under a comprehensive development scenario, while the lowest is observed under an ecological conservation scenario. Among the 32 future climate scenarios, runoff increases significantly with a 10% increase in precipitation and decreases substantially with a 15% reduction in precipitation. These findings underscore the significant impact of human activities and climate change on runoff variations in the upper reaches of the Jialing River, highlighting the importance of incorporating both factors in water resource management and planning. Full article

This study presents a framework to attribute river runoff variations to the combined effects of reservoir operations, land surface changes, and climate variability. We delineated the data into natural and impacted periods. For the natural period, an integrated Long Short-Term Memory and Random Forest model was developed to accurately simulate both mean and extreme runoff values, outperforming existing models. This model was then used to estimate runoff unaffected by human activities in the impacted period. Our findings indicate stable annual and wet season mean runoff, with a decrease in wet season maximums and an increase in dry season means, while extreme values remained largely unchanged. A Budyko framework incorporating reconstructed runoff revealed that rainfall and land surface changes are the predominant factors influencing runoff variations in wet and dry seasons, respectively, and land surface impacts become more pronounced during the impacted period for both seasons. Human activities dominate dry season runoff variation (93.9%), with climate change at 6.1%, while in the wet season, the split is 64.5% to 35.5%. Climate change and human activities have spontaneously led to reduced runoff during the wet season and increased runoff during the dry season. Only reservoir regulation is found to be linked to human-induced runoff changes, while the effects of land surface changes remain ambiguous. These insights underscore the growing influence of anthropogenic factors on hydrological extremes and quantify the role of reservoirs within the impacts of human activities on runoff. Full article

The hydrological response to climate change and human activities plays a pivotal role in the field of water resource management within a given basin. This study was conducted with a primary focus on the Du River basin, aiming to assess and quantify the impacts of climate change and human activities on changes in runoff patterns. The study utilized the Budyko framework in conjunction with the Soil and Water Assessment Tool (SWAT) model to project future changes in runoff while also employing statistical tests like the Pettitt and Mann–Kendall tests to identify abrupt shifts and monotonic trends in the data. The results shows that (1) The analysis of runoff data spanning from 1960 to 2016 revealed a significant declining trend (p < 0.05) in annual runoff, with an abrupt change point identified in 1994. The multi-year average runoff depth was determined to be 495 mm. (2) According to the Budyko framework, human activities were found to be the dominant driver behind runoff changes, contributing significantly at 74.42%, with precipitation changes contributing 24.81%. (3) The results obtained through the SWAT model simulation indicate that human activities accounted for 61.76% of the observed runoff changes, whereas climate change played a significant but slightly smaller role, contributing 38.24% to these changes. (4) With constant climate conditions considered, the study predicted that runoff will continue to decrease from 2017 to 2030 due to the influence of ongoing and future human activities. However, this downward trend was found to be statistically insignificant (p > 0.1). These findings provide valuable insights into the quantitative contributions of climate change and human activities to runoff changes in the Du River basin. This information is crucial for decision-makers and water resource managers, as it equips them with the necessary knowledge to develop effective and sustainable strategies for water resource management within this basin. Full article

Climate warming globally has a profound effect on the hydrological regime, amplifying evapotranspiration and precipitation and accelerating the processes of snow melt and permafrost thaw. However, in the context of small river basins—those encompassing less than 10,000 km²—the response of the hydrological regime to climate change is intricate and has not yet been thoroughly understood. In this study, the Zhizdra River Basin, a typical small river basin in the eastern European plain with a total drainage area of 6940 km², was selected to investigate the long-term variability of the hydrological regime and its responses to climate warming. Our results show that during the period of 1958–2016, the average runoff in the Zhizdra River Basin was approximately 170 mm, with significant fluctuations but no trend. Sensitivity analysis by the Budyko framework revealed that the runoff was more sensitive to changes in precipitation (P) compared to potential evapotranspiration (E₀), implying that the Zhizdra River Basin is limited by water availability and has a slightly dry trend. A comprehensive analysis based on the seasonality of hydrometeorological data revealed that temperature predominantly affects spring runoff, while P mainly controls autumn runoff. Both factors make significant contributions to winter runoff. In response to climate change, the nonuniformity coefficient (C_v) and concentration ratio (C_n) of runoff have noticeably declined, indicating a more stabilized and evenly distributed runoff within the basin. The insights gleaned from this research illuminate the complex hydrological responses of small river basins to climate change, underlining the intricate interrelation among evapotranspiration, precipitation, and runoff. This understanding is pivotal for efficient water resource management and sustainable development in the era of global warming. Full article

Abrupt runoff reduction in the Wei River Basin (WRB) has attracted extensive attention owing to climate change and human activities. Nevertheless, previous studies have inadequately assessed the respective contributions of climate variability and human activities to runoff change on different spatial scales. Using Mann–Kendall and Pettitt’s methods, this study identified long-term (1970–2018) changes in hydro-meteorological variables. Furthermore, the Budyko-based method was used to quantify the influence of climate change and human activities on runoff change at different spatial scales of the WRB, including the whole WRB, three sub-basins, and sixteen catchments. The results show that a significant decrease trend was identified in runoff at different spatial scales within the WRB. Runoff in almost all catchments showed a significant downward trend. Temperature, potential evapotranspiration, and the parameter n showed significant increases, whereas no significant trend in precipitation was observed. The change in runoff was mainly concentrated in the mid-1990s and early 2000s. Anthropogenic activities produced a larger impact on runoff decrease in the WRB (62.8%), three sub-basins (53.9% to 65.8%), and most catchments (–47.0% to 147.3%) than climate change. Dramatic catchment characteristic changes caused by large-scale human activities were the predominant reason of runoff reduction in the WRB. Our findings provide a comprehensive understanding of the dominate factors causing runoff change and contribute to water resource management and ecosystem health conservation in the WRB. Full article

Drought is a meteorological phenomenon that negatively impacts agricultural production. In recent years, southwest China has frequently experienced agricultural droughts; these have significantly impacted the economy and the ecological environment. Although several studies have been conducted on agricultural droughts, few have examined the factors driving agricultural droughts from the perspective of water and energy balance. This study aimed to address this gap by utilizing the Standardized Soil Moisture Index (SSMI) and the Budyko model to investigate agricultural drought in southwest China. The study identified four areas in Southwest China with a high incidence of agricultural drought from 2000 to 2020. Yunnan and the Sichuan-Chongqing border regions experienced drought in 10% of the months during the study period, while Guangxi and Guizhou had around 8% of months with drought. The droughts in these regions exhibited distinct seasonal characteristics, with Yunnan experiencing significantly higher drought frequency than other periods from January to June, while Guizhou and other areas were prone to severe droughts in summer and autumn. The Budyko model is widely used as the mainstream international framework for studying regional water and energy balance. In this research, the Budyko model was applied to analyze the water and energy balance characteristics in several arid regions of southwest China using drought monitoring data. Results indicate that the water and energy balances in Yunnan and Sichuan-Chongqing are more moisture-constrained, whereas those in Guizhou and Guangxi are relatively stable, suggesting lower susceptibility to extreme droughts. Furthermore, during severe drought periods, evapotranspiration becomes a dominant component of the water cycle, while available water resources such as soil moisture decrease. After comparing the causes of drought and non-drought years, it was found that the average rainfall in southwest China is approximately 30% below normal during drought years, and the temperature is 1–2% higher than normal. These phenomena are most noticeable during the spring and winter months. Additionally, vegetation transpiration is about 10% greater than normal during dry years in Southwest China, and soil evaporation increases by about 5% during the summer and autumn months compared to normal conditions. Full article