Search Results (33)

Anthropogenic activities and climate change have significantly altered runoff generation in the upper Han River basin, posing a challenge to the water supply sustainability for the Middle Route of the South-to-North Water Diversion Project. Land use/cover changes (LUCCs) affect hydrological processes by modifying evapotranspiration, infiltration and soil moisture content. Based on hydro-meteorological data from 1961 to 2023 and LUCC data series from 1985 to 2023, this study aimed to identify the temporal trend in hydro-meteorological variables, to quantify the impacts of underlying land surface and climate factors at different time scales and to clarify the effects of LUCCs and basin greening on the runoff generation process. The results showed that (1) inflow runoff declined at a rate of −1.71 mm/year from 1961 to 2023, with a marked shift around 1985, while potential evapotranspiration increased at a rate of 2.06 mm/year within the same time frame. (2) Annual climate factors accounted for 61.01% of the runoff reduction, while underlying land surface contributed 38.99%. Effective precipitation was the dominant climatic factor during the flood season, whereas potential evapotranspiration had a greater influence during the dry season. (3) From 1985 to 2023, the LUCC changed significantly, mainly manifested by the increasing forest area and decreasing crop land area. The NDVI also showed an upward trend over the years; the actual evapotranspiration increased by 1.163 billion m³ due to the LUCC. This study addresses the climate-driven and human-induced hydrological changes in the Danjiangkou Reservoir and provides an important reference for water resource management. Full article

The estimation of water requirements constitutes a critical prerequisite for delineating water scarcity hotspots and mitigating intersectoral competition, particularly in endorheic basins in arid or semi-arid regions where hydrological closure exacerbates resource allocation conflicts. Under conditions of water scarcity, water supplied locally by precipitation and shallow groundwater bodies should be taken into account to estimate the net water requirements to be met with water conveyed from off-site sources. This concept is embodied in the distinction of blue ET (BET) and green ET (GET). In this study, the Budyko hypothesis (BH) method was optimized to partition the total ET into GET and BET during 2001–2018 in the Heihe River Basin. In this region, a better knowledge of net water requirements is even more important due to water allocation policies which reduced water supply to irrigated lands in the last 15 years. This study proposes a modified BH method based on a new vegetation-specific parameter (${\omega }_v$) which was optimized for different vegetation types using precipitation and actual ET data obtained from remote sensing observations. The results show that the BH method partitioned GET and BET reasonably well, with a percent bias of 23.8% and 37.4% and a root mean square error of 84.8 mm/a and 113.6 mm/a, respectively, when compared with reported data, which are superior to that of the precipitation deficit and soil water balance methods. A sensitivity experiment showed that the BH method exhibits a low sensitivity to uncertainties of input data. The results documented differences in the contribution of GET and BET to total ET across different land cover types in the Heihe River Basin. As expected, rainfed forest and grassland ecosystems are predominantly governed by GET, with 81.3% and 87.2% of total ET, respectively. In contrast, croplands and shrublands are primarily regulated by BET, with contributions of 61.5% and 84.3% to total ET. The improved BH method developed in this study paves the way for further analyses of the net water requirements in arid and semi-arid regions. Full article

Vegetation restoration and farmland irrigation are important environmental factors affecting the water cycle process in basins. Analyzing the impact of vegetation restoration and farmland irrigation on runoff is an international frontier and hot topic in current research, which is crucial for the management and protection of water resources, especially for the ecological protection and high-quality development of basins. Based on the normalized difference vegetation index (NDVI), effective irrigated area (EIA), and meteorology and hydrology data for Wujiang River (WJR), this research aims to quantitatively calculate the influence degree of vegetation recovery, agricultural irrigation, and climatic variability on discharge alteration in WJR. First, Mann–Kendall and Pettitt approaches were used for recognizing the mutation year of streamflow data at Wulong station from 1982 to 2015. Then, a corrective Budyko model was built by constructing multiple linear regression equations for the NDVI, climate factors, EIA, and Budyko parameters. Finally, the corrective Budyko model was adopted to reveal how vegetation restoration, agri-cultural irrigation, and climate variation influence discharge alteration in WJR. The results showed the following: (1) Both runoff depth (R) and rainfall (Pr) exhibited a non-significant de-clining tendency, while potential evapotranspiration (ET0) demonstrated a non-significant in-creasing tendency. The NDVI and EIA both demonstrated a notable upward tendency (p < 0.01). (2) The mutation year of discharge in WJR was 2004. (3) The underlying surface parameters ω have a strong correlation with vegetation, agricultural irrigation, and climate factors. (4) The contribution of rainfall (Pr), potential evapotranspiration (ET0), NDVI, EIA, and human activities to runoff depth in WJR were 57.34%, 24.67%, -11.75%, 11.71%, and 18.02%, respectively. This re-search is helpful for elucidating the effects of ecological construction measures and agricultural irrigation on streamflow in WJR, and offers great scientific significance and practical value for understanding the evolution mechanism of water circulation and for managing regional water resources. Full article

Hydrological processes and the sustainable use of water resources in a river basin are altered by climate change and changes in human variables. This study examined the significant effects of vegetation and hydrological, climatic, and human activity changes on the basin’s biological environment and usage of water resources. The Min River Basin (MRB) in the upper Yangtze River served as the study location. Mann–Kendall and Pettitt mutation test techniques were used to examine the features of runoff changes in the basin. The effects of meteorological and anthropogenic factors on runoff and vegetation changes in the MRB from 1982 to 2020 were quantitatively evaluated using the expanded Budyko equation. Following this, spatial and temporal variations in land use and the NDVI in the basin were studied. The results of the research demonstrated the following: (1) The MRB yearly runoff trended downward and that an abrupt change in runoff happened in 1994. (2) Precipitation (Pr) showed a decreasing tendency from the base period (S1) to the change period (S2), but potential evapotranspiration (ET₀) showed an increasing trend. (3) From 1985 to 2020, the land use area of the MRB changed rapidly, and the construction land and water area increased by 322% and 58.85%, respectively, while the cultivated land area decreased by 11.72%. (4) From S1 to S2, there was a rising trend in both the NDVI and the Budyko parameter n. The contributions of Pr, ET₀, NDVI, and n to the runoff change were 32.41%, 9.43%, 27.51%, and 30.65%, respectively. Full article

Climate change and human activities exert significant impact on the mechanism of runoff generation and confluence. Comprehending the reasons of runoff change is crucial for the sustainable development of water resources. Taking the Upper Shule River as the research area, the M-K test and the moving t test were used to diagnose the runoff mutation time. Furthermore, the slope changing ratio of cumulative quantity method (SCRCQ), climate elasticity method, and Budyko equation were utilized to quantitatively evaluate the impacts and contribution rates of climate change and human activities. The following results were obtained: (1) The Upper Shule River experienced a significant increase in runoff from 1972 to 2021, with 1998 marking the year of abrupt change. (2) The runoff sensitivity showed a downward trend from 1972 to 2021. The main factor affecting the decrease in runoff sensitivity was the characteristic parameters of underlying surface (n), followed by precipitation (P), while the influence of potential evapotranspiration (ET₀) was the weakest. (3) The response of runoff changes to runoff sensitivity and influencing factors were 90.32% and 9.68%, respectively. (4) The results of three attribution methods indicated that climate change was the primary factor causing the alteration of runoff in the Upper Shule River. The research results supplement the hydrological change mechanisms of the Upper Shule River and provide a scientific basis for future water resources management and flood control measures. Full article

Beyond their deterministic predictability limits of ≈10 days and 6 months, the atmosphere and ocean become effectively stochastic. This has led to the development of stochastic models specifically for this macroweather regime. A particularly promising approach is based on the Fractional Energy Balance Equation (FEBE), an update of the classical Budyko–Sellers energy balance approach. The FEBE has scaling symmetries that imply long memories, and these are exploited in the Stochastic Seasonal and Interannual Prediction System (StocSIPS). Whereas classical long-range forecast systems are initial value problems based on spatial information, StocSIPS is a past value problem based on (long) series at each pixel. We show how to combine StocSIPS with a classical coupled GCM system (CanSIPS) into a hybrid system (CanStoc), the skill of which is better than either. We show that for one-month lead times, CanStoc’s skill is particularly enhanced over either CanSIPS or StocSIPS, whereas for 2–3-month lead times, CanSIPS provides little extra skill. As expected, the CanStoc skill is higher over ocean than over land with some seasonal dependence. From the classical point of view, CanStoc could be regarded as a post-processing technique. From the stochastic point of view, CanStoc could be regarded as a way of harnessing extra skill at the submonthly scales in which StocSIPS is not expected to apply. Full article

Investigations into runoff change and its influencing factors hold immense significance for promoting sustainable development, efficient water resource utilization, and the improvement of the ecological environment. To reduce methodological uncertainties, this study employed six attribution analysis methods, including two statistical approaches, a Budyko equation sensitivity coefficient method, and three hydrology models, to differentiate the contributions of climate change and human activities to the runoff change in the Xiliugou basin. The results indicated an abrupt change point in 2006, and the annual runoff series from 1960 to 2020 demonstrated a significant declining trend. All the six methods revealed that human activities were the major influencing factor. The average contribution rate of climate change was noted to be 24.2%, while that of human activities was 75.8% among the six methods used for this study. The prominent human activities in the Xiliugou basin revolve around soil and water conservation measures. The research findings hold great significance for the comprehensive understanding of runoff formation and its response to the changing environment in the Xiliugou basin. Additionally, these results can provide a foundation for decision-making for water resource management and ecological protection. Full article

Vegetation changes have a significant impact on the underlying surface of a watershed and alter hydrological processes. To clarify the synergistic evolution relationship between climate, vegetation, and hydrology, this study aims to reveal how vegetation restoration influences streamflow decline. This study first applied the trend-free pre-whitening Mann–Kendall (TFPW-MK) method to identify variation trends of various elements at Baihe and Shayang hydrologic stations from 1982 to 2015. Secondly, an extended Budyko equation was improved by fitting the linear relationship between annual NDVI and Budyko parameter (ω). Finally, based on the extended Budyko formula, the elastic coefficient method was applied to identify the influence of vegetation changes on runoff changes of the Baihe and Shayang stations from 1982 to 2015. The results displayed that (1) the annual NDVI of Baihe and Shayang hydrologic stations both presented an increasing trend, and streamflow presented an insignificant decrease trend. The mutation year of the annual runoff depth of Baihe and Shayang stations both occurred in 1990. (2) The annual NDVI had a significant and positive linear relationship with ω. (3) The streamflow decline of Baihe and Shayang stations is mainly influenced by precipitation variation and human activities. (4) Vegetation growth had a positive effect on the streamflow decline of Baihe and Shayang stations, with a contribution rate of 14.06% and 17.87%. This effect of vegetation growth on discharge attenuation should be given high priority. Full article

The occurrence of water scarcity and extreme hydrological events is becoming increasingly frequent worldwide. The river runoff process, as an important link in the water cycle of a basin, is an essential content of the study of hydrological processes in the basin. Vegetation is an influencing factor closely related to hydrological processes in a watershed. This article quantitatively analyzes the impact of vegetation restoration and climate variation on runoff in the Luan River Basin from 1982 to 2018. Firstly, trend analysis was conducted on runoff depth, precipitation, the Normalized Vegetation Index (NDVI), and reference evaporation. Then, Mann–Kendall mutation analysis and Pettitt mutation analysis were used to identify the year of runoff mutation. Finally, a Budyko model was constructed to quantitatively analyze the impact of vegetation and climate change on the runoff of the Luan River. The results showed that: (1) The runoff reduction rate of the Luan River was 1.2437 mm/a. The precipitation was increasing at a rate of 0.6977 mm/a. The reference evaporation rate decreased at a rate of 0.0977 mm/a. The annual growth rate of the Budyko parameter (n) was 0.0283. The annual growth rate of NDVI was 0.0022. (2) The coefficient of determination in the functional equation (a = 14.74, b = −3.4105) for NDVI and Budyko parameter (n) was 0.3297 (p < 0.01). (3) The contributions of Pr, ET₀, NDVI, and (n) to reduced flow were −17.49%, 1.46%, 35.25%, and 80.78%, respectively. The increase in vegetation would lead to a decrease in runoff. This study can clarify the impact of vegetation restoration on water resource security in the Luan River Basin. Full article

The Yarlung Zangbo River (YZR) is the largest river on the Qinghai Tibet Plateau, and changes in its meteorology, hydrology and vegetation will have a significant impact on the ecological environment of the basin. In order to deepen our understanding of the relationship of climate–vegetation–hydrological processes in YZR, the purpose of this study is to explore how vegetation growth in the YZR affects its runoff changes. We first identified the abrupt year of discharge in the YZR using a heuristic segmentation algorithm and cumulative anomaly mutation test approach. After that, the functional equation for NDVI and the Budyko parameter (n) was computed. Finally, the NDVI was introduced into the Budyko equation to evaluate the impact of vegetation changes on the streamflow in the YZR. Results showed that: (1) NDVI and discharge in the YZR both presented an increasing trend, and the mutation year of annual runoff in Nuxia station occurred in 1997. (2) n had a significant negative correlation with NDVI in the YZR (p < 0.01). (3) The contributions of Pr, ET₀, NDVI, and n on streamflow change in the S2 period (1998–2015) were 5.26%, 1.14%, 43.04%, and 50.06%. The results of this study can provide scientific guidance and support for the evaluation of the effects of ecological restoration measures, as well as the management and planning of water resources in the YZR. Full article

Since the first climate models in the 1970s, algorithms and computer speeds have increased by a factor of ≈10¹⁷ allowing the simulation of more and more processes at finer and finer resolutions. Yet, the spread of the members of the multi-model ensemble (MME) of the Climate Model Intercomparison Project (CMIP) used in last year’s 6th IPCC Assessment Report was larger than ever: model uncertainty, in the sense of MME uncertainty, has increased. Even if the holy grail is still kilometric scale models, bigger may not be better. Why model structures that live for ≈15 min only to average them over factors of several hundred thousand in order to produce decadal climate projections? In this commentary, I argue that alongside the development of “seamless” (unique) weather-climate models that chase ever smaller—and mostly irrelevant—details, the community should seriously invest in the development of stochastic macroweather models. Such models exploit the statistical laws that are obeyed at scales longer than the lifetimes of planetary scale structures, beyond the deterministic prediction limit (≈10 days). I argue that the conventional General Circulation Models and these new macroweather models are complementary in the same way that statistical mechanics and continuum mechanics are equally valid with the method of choice determined by the application. Candidates for stochastic macroweather models are now emerging, those based on the Fractional Energy Balance Equation (FEBE) are particularly promising. The FEBE is an update and generalization of the classical Budyko–Sellers energy balance models, it respects the symmetries of scaling and energy conservation and it already allows for both state-of-the-art monthly and seasonal, interannual temperature forecasts and multidecadal projections. I demonstrate this with 21st century FEBE climate projections for global mean temperatures. Overall, the projections agree with the CMIP5 and CMIP6 multi-model ensembles and the FEBE parametric uncertainty is about half of the MME structural uncertainty. Without the FEBE, uncertainties are so large that climate policies (mitigation) are largely decoupled from climate consequences (warming) allowing policy makers too much “wiggle room”. The lower FEBE uncertainties will help overcome the current “uncertainty crisis”. Both model types are complementary, a fact demonstrated by showing that CMIP global mean temperatures can be accurately projected using such stochastic macroweather models (validating both approaches). Unsurprisingly, they can therefore be combined to produce an optimum hybrid model in which the two model types are used as copredictors: when combined, the various uncertainties are reduced even further. Full article

Calibrating spatially distributed hydrological models in ungauged mountain basins is complicated due to the paucity of information and the uncertainty in representing the physical characteristics of a drainage area. In this study, an innovative method is proposed that incorporates the Budyko framework and water balance equation derived water yield (WYLD) in the calibration of the Soil and Water Assessment Tool (SWAT) with a monthly temporal resolution. The impact of vegetation dynamics (i.e., vegetation coverage) on Budyko curve shape parameter ω was considered to improve the Budyko calibration. The proposed approach is applied to the upstream Lancang-Mekong River (UL-MR), which is an ungauged mountain basin and among the world’s most important transboundary rivers. We compared the differences in SWAT model results between the different calibration approaches using percent bias (PBIAS), coefficient of determination (R²), and Nash–Sutcliffe efficiency (NSE) coefficient. The results demonstrated that the Budyko calibration approach exhibited a significant improvement against an unfitted priori parameter run (the non-calibration case) though it did not perform as good as fitting of the calibration by the observed streamflow. The NSE value increased by 44.59% (from 0.46 to 0.83), the R² value increased by 2.30% (from 0.87 to 0.89) and the PBIAS value decreased by 55.67% (from 39.7 to 17.6) during the validation period at the drainage outlet (Changdu) station. The outcomes of the analysis confirm the potential of the proposed Budyko calibration approach for runoff predictions in ungauged mountain basins. Full article

Understanding the impact of climate change and human activities on the hydrological cycle of any watershed can provide a scientific basis for regional water resource planning, flood management, and disaster mitigation. An improved three-parameter hydrological model (CM) based on monthly water balance using an exponential equation to depict the distribution of groundwater storage capacity was developed and evaluated. The model uses Asian Precipitation Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) rainfall data as input, with the Zhejiang Province as the case application, and the effects of climate change and human activities on streamflow changes were assessed by separating environmental variables in this study. The results indicate that APHRODITE data has excellent monthly accuracy, with a mean correlation coefficient (CC) of more than 0.96 and an average absolute percentage bias (Pbais) of less than 5%. The three models are relatively close in their ability to simulate high flows, but the CM simulated low flow is better than the other two models. Positive and negative Pbais phenomena occur in the CM model in each catchment, and absolute levels are regulated by 5%. Furthermore, the CM model’s average Nash efficiency coefficient (NSE) is greater than 0.9, indicating that it can correctly fulfill the water balance. The results are more consistent throughout multiple catchments in each watershed using Budyko-based and hydrological model technique to evaluate the influence of climate change and human activities on streamflow. Climate change dominated streamflow variations in 18 of the 21 catchments in Zhejiang Province, whereas human activities dominated the rest. The findings of the study will be used to influence the management, development, and usage of water resources in the watershed. Full article

A new daily water balance model is developed and tested in this paper. The new model has a similar model structure to the existing probability distributed rainfall runoff models (PDM), such as HyMOD. However, the model utilizes a new distribution function for soil water storage capacity, which leads to the SCS (Soil Conservation Service) curve number (CN) method when the initial soil water storage is set to zero. Therefore, the developed model is a unification of the PDM and CN methods and is called the PDM–CN model in this paper. Besides runoff modeling, the calculation of daily evaporation in the model is also dependent on the distribution function, since the spatial variability of soil water storage affects the catchment-scale evaporation. The generated runoff is partitioned into direct runoff and groundwater recharge, which are then routed through quick and slow storage tanks, respectively. Total discharge is the summation of quick flow from the quick storage tank and base flow from the slow storage tank. The new model with 5 parameters is applied to 92 catchments for simulating daily streamflow and evaporation and compared with AWMB, SACRAMENTO, and SIMHYD models. The performance of the model is slightly better than HyMOD but is not better compared with the 14-parameter model (SACRAMENTO) in the calibration, and does not perform as well in the validation period as the 7-parameter model (SIMHYD) in some areas, based on the NSE values. The linkage between the PDM–CN model and long-term water balance model is also presented, and a two-parameter mean annual water balance equation is derived from the proposed PDM–CN model. Full article

The conterminous United States includes national forests and grasslands that provide ecological, social, economic, recreational, and aesthetic services. Future climate change can alter long-term hydroclimatic conditions of national forests and grasslands and lead to negative consequences. This study characterizes shifts in hydroclimatology and basin characteristics of US National Forests (NFs) and National Grasslands (NGs) in response to climate change over the 21st century under the DRY, MIDDLE, and WET climate models with the representative concentration pathway (RCP) 8.5 emission scenario. Climatic projections for three climate models ranging from the driest to wettest conditions were obtained from the Multivariate Adaptive Constructed Analogs (MACA) dataset. Then, the variable infiltration capacity (VIC) model was used to model hydrological responses of the selected future climates. Changes in regional hydroclimatic conditions of NFs and NGs were assessed by the magnitude and direction of movements in the Budyko space. The Fu’s equation was applied to estimate changes in basin characteristics. The results indicate that NFs and NGs are likely to experience larger changes in basin characteristics compared to the average of the United States. In general, across the conterminous US, the NFs in mountainous regions are likely to have larger changes in hydroclimatic variables than NFs with lower elevation and NGs. Comparing Forest Service regions, Pacific Northwest, Intermountain, and Northern regions may have a less arid climate with lower freshwater availability. The Southwestern, Northern, Intermountain, and Rocky Mountain regions are likely to experience higher shifts in their basin characteristics. This study can help environmental scientists, and land and water managers improve future land management plans. Full article