Temporal and Spatial Changes of Runoff Regime in the Yellow River Basin from 1956 to 2017

The Yellow River is one of the major rivers with severe runoff declines in China, but there are significant differences in runoff changes in the upper and lower reaches of the basin and among different tributaries. However, the characteristic of runoff change and its spatial heterogeneity are not well understood in the whole basin. In this paper, 48 hydrological stations located in the mainstream and major tributaries were selected, and the meteorological and runoff data from 1956 to 2017 were collected. The multi-year and intra-year changes in runoff were analyzed, and then the attribution of climate change and human activity to runoff change was quantified by the climate elasticity coefficients. The results showed that: (1) in the past 60 years, the runoff of the Yellow River showed a serious decrease trend of −8.25 mm/10a. Moreover, most tributaries decreased significantly in runoff with a rate of −1.42 mm/10a to −28.99 mm/10a; (2) for the whole basin, the contribution of climate change and human activity to runoff changes was 13% and 87%, respectively. Moreover, the contribution of the two factors varied considerably in different tributaries. Finally, focusing on different runoff regime and socioeconomic characteristics, this study provided corresponding water resources adaptive management suggestions.

Contribution Analysis of the Streamflow Changes in Selected Catchments on the Loess Plateau, China, Using Multiple Budyko-Based Approaches

A better understanding of how streamflow interacts with climate change and human activities would contribute to the efficiency and effectiveness of water resources management. Specifically, quantifying the climate and human contributions has widely been used when attributing streamflow changes. However, only a few previous studies compared the results derived by different methods that are currently available, and even fewer studies have ever had a close look at the uncertainties induced by various estimations of evapotranspiration. This research first examined the streamflow changes for 12 catchments on the Loess Plateau in China during the period of 1961–2018 with Mann–Kendall test and relevant statistical measurements. Then, 8 Budyko-based climate elasticity methods, each with 13 estimations of evapotranspiration, were used to quantifying human and climate contributions to streamflow change in the study area (i.e., 104 pairs of values for human and climate contributions for one catchment). The results showed that significant declining trends could be found in 11 of the 12 catchments studied. In terms of contribution rates, human activity has been shown as the major contributor to the streamflow decrease (60–90%) compared to climate change (10–50%). By comparing the contribution results derived by possible combinations of attribution method and evapotranspiration estimation, the variability due to different Budyko-based methods being used seems to be related to geographical location and climate. Although the spatial pattern of variability due to different estimations of evapotranspiration is not obvious, it is necessary to consider the uncertainties induced when launching contribution analysis over specific regions.

The Role of Climate Change and Human Factors in Affecting Runoff and Hydrological Drought Characteristics of a Watershed

The main objective of the study is to evaluate the roles of climate change and human factors on runoff, baseflow, and hydrological drought characteristics at a watershed scale. The novelty of the study is to assess separately the cascading, indirect, accumulative effects of climate change and human factors on hydrological drought, i.e. runoff and baseflow. This involved analyzing change points to divide the available hydrometeorological data into a baseline and a perturbed period. We applied two hydrological models, SWAT and HBV-light, and two nonparametric climate elasticity of runoff to identify the contribution of climate change and human factors in influencing runoff and baseflow processes. The hydrological models were used to simulate naturalized runoff and baseflow during the perturbed period. The temporal variation in the characteristics of the baseflow regime is expressed as baseflow index. Drought indices, standardized runoff index and standardized baseflow index were used as hydrological drought indicators. A significant change in runoff reduction in the Kamienna watershed began in 1982, suggesting that human factors play a dominant role in influencing runoff. In addition, we found that an increase in baseflow and a decrease in hydrological drought events in the 2010s are a positive long-term effect of human factors such as construction of dams in the watershed. Finally, analyses of changes in land cover dynamics in the watershed over the past four decades using satellite imagery are used to confirm the presence of human interventions.

Climate elasticity of evapotranspiration shifts the water balance of Mediterranean climates during multi-year droughts

Multi-year droughts in Mediterranean climates may shift the water balance, that is, the partitioning rule of precipitation across runoff, evapotranspiration, and sub-surface storage. Mechanisms causing these shifts remain largely unknown and are not well represented in hydrologic models. Focusing on measurements from the headwaters of California's Feather River, we found that also in these mixed rain–snow Mediterranean basins a lower fraction of precipitation was partitioned to runoff during multi-year droughts compared to non-drought years. This shift in the precipitation–runoff relationship was larger in the surface-runoff-dominated than subsurface-flow-dominated headwaters (−39 % vs. −18 % decline of runoff, respectively, for a representative precipitation amount). The predictive skill of the Precipitation Runoff Modeling System (PRMS) hydrologic model in these basins decreased during droughts, with evapotranspiration (ET) being the only water-balance component besides runoff for which the drop in predictive skill during drought vs. non-drought years was statistically significant. In particular, the model underestimated the response time required by ET to adjust to interannual climate variability, which we define as climate elasticity of ET. Differences between simulated and data-driven estimates of ET were well correlated with accompanying data-driven estimates of changes in sub-surface storage (ΔS, r=0.78). This correlation points to shifts in precipitation–runoff relationships being evidence of a hysteretic response of the water budget to climate elasticity of ET during and after multi-year droughts. This hysteresis is caused by carryover storage offsetting precipitation deficit during the initial drought period, followed by vegetation mortality when storage is depleted and subsequent post-drought vegetation expansion. Our results point to a general improvement in hydrologic predictions across drought and recovery cycles by including the climate elasticity of ET and better accounting for actual subsurface water storage in not only soil, but also deeper regolith that stores water accessible to roots. This can be done by explicitly parametrizing carryover storage and feedback mechanisms capturing vegetation response to atmospheric demand for moisture.

Integrated assessment of climate and human contributions to variations in streamflow in the Ten Great Gullies Basin of the Upper Yellow River, China

Climate change and human activity are two linked factors that alter the spatiotemporal distribution of the available water. Assessing the relative contribution of the two factors on runoff changes can help the planners and managers to better formulate strategies and policies regarding regional water resources. In this work, using two typical sub-basins of the Yellow River as the study area, we first detected the trend and the breakpoint in the annual streamflow data with the Pettitt test during the period 1964–2011. Next, a Budyko-based climate elasticity model and a monthly hydrological model were employed as an integrated method to distinguish the relative contributions of climate change and human activities to the long-term changes in runoff. The results showed that a significant decline in the annual runoff occurred in the two sub-basins during the study period, and the abrupt change point in the annual runoff at the two sub-basins both occurred in 1997. The conceptual hydrological model performed well in reproducing monthly runoff time series at the two sub-basins. The Nash-Sutcliffe efficiency (NSE) between observed and simulated runoff during the validation period exceeds 0.83 for the two sub-basins. Climate elasticity method and hydrological model give consistent attribution results: human activities are the major drivers responsible for the decreased annual runoff in the Ten Great Gullies Basin. The relative contributions of climate change and human activities to the changes in the annual runoff were 22–32% and 68–78%, respectively.

Climate elasticity of low-flows: the long-term impact of droughts

<p>The long-term memory of catchments (carried by their hydrogeological characteristics) has a considerable impact on low-flow dynamics. Here, we present an exploratory study on a large French dataset to characterize the climate elasticity of low-flows and understand its long-term dependency. The climate elasticity of catchments is a simple concept (almost model-free) that allows analyzing the linear dependency of streamflow anomalies to climate anomalies (Andréassian et al., 2016). Widely-used for average annual streamflow, we propose to extend this concept to annual minimum monthly flow anomalies (QMNA) in order to characterize the climate dependency of QMNAs. By introducing progressively the linear dependency to the climatic anomalies of previous years, we further characterize the long-term memory of low-flows for the catchments of our set.</p><p><strong>References</strong></p><p>Andréassian, V., Coron, L., Lerat, J., and Le Moine, N. 2016. Climate elasticity of streamflow revisited – an elasticity index based on long-term hydrometeorological records, Hydrol. Earth Syst. Sci., 20, 4503-4524.</p><p> </p>