Propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescales

According to the widely accepted definition of drought, meteorological and hydrological droughts originally develop from rainfall and runoff deficits, respectively. Runoff deficit is mainly derived from rainfall deficit, and the propagation from meteorological drought to hydrological drought is critical for agricultural water management. Nevertheless, the characteristics and dynamics of drought propagation in the spatiotemporal scale remain unresolved. To this end, the characteristics and dynamics of drought propagation in different seasons and their linkages with key forcing factors are evaluated. In this study, meteorological and hydrological droughts are characterized by the Standardized Precipitation Index (SPI) and the Standardized Runoff Index (SRI), respectively. Propagation time is identified by the corresponding timescale of the maximum correlation coefficient between the SPI and the SRI. Then, a 20-year sliding window is adopted to explore the propagation dynamic in various seasons. Furthermore, the multiple linear regression model is established to quantitatively explore the influence of meteorological factors, underlying surface features and teleconnection factors on the propagation time variations. The Wei River Basin, a typical Loess Plateau watershed in China, is selected as a case study. Results indicate the following: (1) the propagation time from meteorological to hydrological drought is shorter in summer (2 months) and autumn (3 months), whereas it is longer in spring (8 months) and winter (13 months). Moreover, the propagation rates exhibit a decreasing trend in warm seasons, which, however, show an increasing trend in cold seasons; (2) a significant slowing propagation in autumn is mainly caused by the decreasing soil moisture and precipitation, whereas the non-significant tendency in summer is generally induced by the offset between insignificant increasing precipitation and significant decreasing soil moisture; (3) the replenishment from streamflow to groundwater in advance prompts the faster propagation from meteorological to hydrological drought in spring and winter and (4) teleconnection factors have strong influences on the propagation in autumn, in which Arctic Oscillation, El Niño-Southern Oscillation and Pacific Decadal Oscillation mainly affect participation, arid index and soil moisture, thereby impacting drought propagation.

Bias Correction, Historical Evaluations and Future Projections of Climate Simulations in the Wei River Basin Using CORDEX-EA

The utilization of Regional Climate Methods (RCMs) to predict future regional climate is an important study under the changing environment. The primary objective of the paper is to correct the temperature and precipitation simulations for the period of 1980-2005 and 2026-2098 in the Wei River Basin (WRB), to evaluate the performance of RCMs for the period of 1980-2005, and further, to analyze the future changes of projected temperature and precipitation during 2026-2098. In this paper, the linear scaling method was used to correct the temperature simulations. Quantile mapping, local intensity scaling method and hybrid method were used to correct the precipitation simulations. The future changes of projected temperature and precipitation for the near-term (2026-2050), mid-term (2051-2075) and far-term (2076-2098), relative to the period of 1980-2005, were investigated under RCP 2.6 and RCP 8.5. Results indicate that: (1) The temperature biases were different spatial distributions, and the precipitation wet biases were detected in the WRB. After correction, HadGEM2-ES driven by RegCM4-4 had the best temperature reproducibility, and NCC-NorESM1-M driven by RegCM4-4 had the best precipitation reproducibility. (2) Under RCP 2.6, the projected annual, winter and spring temperature showed decreasing trends. The temperature was higher than that for the period of 1980-2005 except for the spring temperature decreases in the Beiluo River Basin. Under RCP 8.5, the temperature showed significantly increasing trends. The temperature for the near-term was similar to the period of 1980-2005, while the temperature increased significantly for the mid-term and far-term. (3) Under RCP 2.6, the precipitation had decreasing trends. Under RCP 8.5, precipitation trends were also spatially distributed. The relative deviation of winter precipitation was the largest. Relative to the period of 1980-2005, the light and moderate rain days showed little change for the period of 2026-2098, while the extreme rain days showed significantly increasing trends. (4) The results could be beneficial to the future climate projection, which provide references for the water resources management, the future hydrological process changes and attribution analysis in the WRB.

Clarifying the propagation dynamics from meteorological to hydrological drought induced by climate change and direct human activities

An understanding of the propagation process from meteorological to hydrological drought contributes to accurate prediction hydrological drought. However, the comprehensive influence of direct human activities involved in drought propagation is not well understood. In this study, an identification framework for drought propagation time was constructed to quantify the effects of direct human activities (i.e., reservoir storage, irrigation, industrial, domestic and agricultural water consumption) on drought propagation. Subsequently, the effects of meteorological and underlying surface factors on the drought propagation process were clarified based on random forest method, and the driving effect of teleconnection factors was investigated from top to bottom. The Wei River Basin (WRB), the largest tributary of the Yellow River Basin, was selected as the case study. Results disclosed that the propagation time from meteorological to hydrological drought was short in summer (approximately 2 months) and autumn (approximately 3 months), while long in spring (approximately 3–5 months) and winter (approximately 3–8 months), exhibiting noticeable spatial variability. In a changing environment, the propagation time generally showed a decreasing trend in spring and winter, while increasing propagation time was observed in summer and autumn. The dynamic drought propagation time of each season was all jointly controlled by the different extent variation of meteorological and underlying surface conditions, and the basic flow is all relatively significant throughout the period. Direct human activities had an effect on the seasonal dynamics of drought propagation, especially during the winter of the non-flood season, which alleviated the severity of winter hydrological drought to some extent, thus delaying the transmission of meteorological signals to hydrological systems. Sunspots, the dominant direct teleconnection driving force in the WRB, could indirectly affect the local precipitation and base flow in spring, autumn, and winter and interferes with the drought propagation process. This study sheds new insights into the attribution of drought propagation dynamics in a changing environment.

Time-scale dependent mechanism of atmospheric CO2 concentration drivers of watershed water-energy balance

<p>The elevated atmospheric carbon dioxide concentration (CO<sub>2</sub>), as a key variable linking human activities and climate change, seriously affects the watershed hydrological processes. However, whether and how atmospheric CO<sub>2</sub> influences the watershed water-energy balance dynamics at multiple time scales have not been revealed. Based on long-term hydrometeorological data, the variation of non-stationary parameter n series in the Choudhury's equation in the mainstream of the Wei River Basin (WRB), the Jing River Basin (JRB) and Beiluo River Basin (BLRB), three typical Loess Plateau regions in China, was examined. Subsequently, the Empirical Mode Decomposition method was applied to explore the impact of CO<sub>2</sub> on watershed water-energy balance dynamics at multiple time scales. Results indicate that (1) in the context of warming and drying condition, annual n series in the WRB displays a significantly increasing trend, while that in the JRB and BLRB presents non-significantly decreasing trends; (2) the non-stationary n series was divided into 3-, 7-, 18-, exceeding 18-year time scale oscillations and a trend residual. In the WRB and BLRB, the overall variation of n was dominated by the residual, whereas in the JRB it was dominated by the 7-year time scale oscillation; (3) the relationship between CO<sub>2 </sub>concentration and n series was significant in the WRB except for 3-year time scale. In the JRB, CO<sub>2 </sub>concentration and n series were significantly correlated on the 7- and exceeding 7-year time scales, while in the BLRB, such a significant relationship existed only on the 18- and exceeding 18-year time scales. (4) CO<sub>2</sub>-driven temperature rise and vegetation greening elevated the aridity index and evaporation ratio, thus impacting watershed water-energy balance dynamics. This study provided a deeper explanation for the possible impact of CO<sub>2</sub> concentration on the watershed hydrological processes.</p>

The propagation dynamics and causes of hydrological drought in response to meteorological drought at seasonal timescale

<p>According to widely accepted definition of drought, meteorological and hydrological droughts originally develop from rainfalls and runoffs deficits, respectively. Runoffs deficit is mainly derived from rainfalls deficit. Therefore, hydrological drought is essentially propagated from meteorological drought, which is critical for agricultural water management. Investigation of the propagation from meteorological to hydrological drought is important for drought early warning, preparedness and mitigation. Nevertheless, the characteristics and dynamic of drought propagation in spatiotemporal scale remain unresolved. To this end, the characteristics and dynamic of drought propagation in different seasons and their linkages with key forcing factors are evaluated. In this study, the meteorological drought and hydrological drought are characterized by Standardized Precipitation Index (SPI) and Standardized Runoff Index (SRI), respectively. The propagation time is identified by the corresponding timescale of the maximum correlation coefficient between SPI and SRI. Then, a 20-year sliding window is adopted to explore the propagation dynamic in various seasons. Furthermore, the multiple linear regression model (MLR) is established to quantitatively explore the influence of meteorological factors, underlying surface features and teleconnection factors on the propagation time variations. The Wei River Basin (WRB), which is a typical Loess Plateau watershed in China, is selected as a case study. Results indicate that: (1) the propagation time from meteorological to hydrological drought is shorter in summer (2 months) and autumn (3 months), whilst that is longer in spring (8 months) and winter (13 months). Moreover, the propagation rates exhibit decreasing trend in warm seasons, which however show increasing trend in cold seasons; (2) a significant slowing propagation in autumn is mainly caused by the decreasing soil moisture and precipitation, while the non-significant tendency in summer is generally induced by the offset between insignificant increasing precipitation and significant decreasing soil moisture; (3) the replenishment from streamflow to groundwater in advance prompts the faster propagation from meteorological to hydrological drought in spring and winter; (4) teleconnection factors have strong influences on the propagation in autumn, in which Arctic Oscillation (AO), El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) mainly affect participation, arid index and soil moisture, thereby impacting drought propagation.</p>

Microplastics in surface waters of the Wei River, China

Microplastics are a new type of persistent organic pollutants, usually on the micron scale. In this study, we investigated the abundance, distribution, and other characterization of microplastics in surface waters of the Wei River Basin in the Shandong peninsula. The results showed that the abundance of microplastics in the surface water of Wei River varied from 0.40 to 1.20 items/L, and the average abundance was 0.81 items/L, which was at a moderate pollution level compared with other rivers. It was found that the abundance of microplastics was higher in densely populated areas, and hydrodynamic conditions such as river inflow and seawater scour also affected the abundance of microplastics. Fiber (83.4%) was the dominant type. Colorless (93.6%) was the dominant color type. The particle size (0.06 - 0.5mm) (47.9%) was the main size of microplastics in the Wei River. This study provides data for the further study of microplastics in rivers and provides a warning for the management and prevention of microplastics in freshwater.

Impact of Input Filtering and Architecture Selection Strategies on GRU Runoff Forecasting: A Case Study in the Wei River Basin, Shaanxi, China

A gated recurrent unit (GRU) network, which is a kind of artificial neural network (ANN), has been increasingly applied to runoff forecasting. However, knowledge about the impact of different input data filtering strategies and the implications of different architectures on the GRU runoff forecasting model’s performance is still insufficient. This study has selected the daily rainfall and runoff data from 2007 to 2014 in the Wei River basin in Shaanxi, China, and assessed six different scenarios to explore the patterns of that impact. In the scenarios, four manually-selected rainfall or runoff data combinations and principal component analysis (PCA) denoised input have been considered along with single directional and bi-directional GRU network architectures. The performance has been evaluated from the aspect of robustness to 48 various hypermeter combinations, also, optimized accuracy in one-day-ahead (T + 1) and two-day-ahead (T + 2) forecasting for the overall forecasting process and the flood peak forecasts. The results suggest that the rainfall data can enhance the robustness of the model, especially in T + 2 forecasting. Additionally, it slightly introduces noise and affects the optimized prediction accuracy in T + 1 forecasting, but significantly improves the accuracy in T + 2 forecasting. Though with relevance (R = 0.409~0.763, Grey correlation grade >0.99), the runoff data at the adjacent tributary has an adverse effect on the robustness, but can enhance the accuracy of the flood peak forecasts with a short lead time. The models with PCA denoised input has an equivalent, even better performance on the robustness and accuracy compared with the models with the well manually filtered data; though slightly reduces the time-step robustness, the bi-directional architecture can enhance the prediction accuracy. All the scenarios provide acceptable forecasting results (NSE of 0.927~0.951 for T + 1 forecasting and 0.745~0.836 for T + 2 forecasting) when the hyperparameters have already been optimized. Based on the results, recommendations have been provided for the construction of the GRU runoff forecasting model.

Comparison of Fish, Macroinvertebrates and Diatom Communities in Response to Environmental Variation in the Wei River Basin, China

Land use changes usually lead to the deterioration of freshwater ecosystems and reduced biodiversity. Aquatic organisms are considered valuable indicators for reflecting the conditions of freshwater ecosystems. Understanding the relationship between organisms and land use type, as well as physiochemical conditions, is beneficial for the management, monitoring and restoration of aquatic ecosystems. In this study, fish, macroinvertebrates, and diatoms were investigated at 60 sampling sites in the Wei River basin from October 2012 to April 2013 to determine the relationships between the environment and aquatic organisms. The richness, abundance, Shannon diversity, evenness, Margalef diversity, and Simpson diversity were selected as biological indices for analyzing the correlation between these communities and environmental variables according to Pearson’s coefficient. Canonical correspondence analysis (CCA) was used to analyze the relationship between the biotic communities and environmental variables. The results showed that three diatom indices were weakly correlated with chemical oxygen demand (COD), qualitative Habitat Evaluation Index (QH), and dissolved oxygen (DO). Four macroinvertebrate indices were associated with total phosphorus (TP) while total nitrogen (TN), and agricultural land (AL) had a significant influence on assemblages, suggesting that macroinvertebrates could respond to nutrient levels in the Wei River basin. All land use types had a strong effect on fish indices except AL, indicating that fish would be better used as indicators of spatial changes in the aquatic ecosystem. In conclusion, fish and macroinvertebrates have the potential for use in routine monitoring programs in the Wei River basin.