Shengzhi Huang

Spatio-temporal Changes and Frequency Analysis of Drought in the Wei River Basin, China

This study has investigated the spatio-temporal changes of droughts from 1961 to 2005 in the Wei River Basin. The Standardized Precipitation Index (SPI) was employed to describe the droughts. The trends of SPI value at all the meteorological stations were calculated by using the modified Mann-Kendall (MMK) trend test method, indicating that the western basin has a significantly wet trend, whilst the eastern basin including the Guanzhong Plain has a trend towards drought . Since the historical droughts records were too short to fully investigate drought properties in this basin, a practical nonparametric method was proposed to calculate the joint probability distribution of drought properties, which overcomes the shortcomings of the univariate and parametric frequency analysis. The frequency analysis of drought in the Wei River Basin indicates that the Guanzhong Plain and the surrounding areas of Huanxian meteorological station have a high drought risks, whilst the western and northern basin except the surrounding areas of Huanxian station has a relatively low drought risk.

Cross‐scale intercomparison of climate change impacts simulated by regional and global hydrological models in eleven large river basins

Ideally, the results from models operating at different scales should agree in trend direction and magnitude of impacts under climate change. However, this implies that the sensitivity to climate variability and climate change is comparable for impact models designed for either scale. In this study, we compare hydrological changes simulated by 9 global and 9 regional hydrological models (HM) for 11 large river basins in all continents under reference and scenario conditions. The foci are on model validation runs, sensitivity of annual discharge to climate variability in the reference period, and sensitivity of the long-term average monthly seasonal dynamics to climate change. One major result is that the global models, mostly not calibrated against observations, often show a considerable bias in mean monthly discharge, whereas regional models show a better reproduction of reference conditions. However, the sensitivity of the two HM ensembles to climate variability is in general similar. The simulated climate change impacts in terms of long-term average monthly dynamics evaluated for HM ensemble medians and spreads show that the medians are to a certain extent comparable in some cases, but have distinct differences in other cases, and the spreads related to global models are mostly notably larger. Summarizing, this implies that global HMs are useful tools when looking at large-scale impacts of climate change and variability. Whenever impacts for a specific river basin or region are of interest, e.g. for complex water management applications, the regional-scale models calibrated and validated against observed discharge should be used.

Analysis of temporal and spatial trends of hydro-climatic variables in the Wei River Basin

The Wei River is the largest tributary of the Yellow River in China. The relationship between runoff and precipitation in the Wei River Basin has been changed due to the changing climate and increasingly intensified human activities. In this paper, we determine abrupt changes in hydro-climatic variables and identify the main driving factors for the changes in the Wei River Basin. The nature of the changes is analysed based on data collected at twenty-one weather stations and five hydrological stations in the period of 1960-2010. The sequential Mann-Kendall test analysis is used to capture temporal trends and abrupt changes in the five sub-catchments of the Wei River Basin. A non-parametric trend test at the basin scale for annual data shows a decreasing trend of precipitation and runoff over the past fifty-one years. The temperature exhibits an increase trend in the entire period. The potential evaporation was calculated based on the Penman-Monteith equation, presenting an increasing trend of evaporation since 1990. The stations with a significant decreasing trend in annual runoff mainly are located in the west of the Wei River primarily interfered by human activities. Regression analysis indicates that human activity was possibly the main cause of the decline of runoff after 1970.

Spatio-Temporal Changes in Potential Evaporation Based on Entropy Across the Wei River Basin

The distribution of potential evaporation is highly unstable due to complex human activities and climate changes. Therefore, it is of great significance for further understanding hydrological cycle to estimate potential evaporation distribution. Reasonable regionalization of potential evaporation will help to improve the efficiency of irrigation and increase the ability of drought relief, which is of great importance to irrigation planning and management. Hence, the spatio-temporal changes in potential evaporation distribution at monthly and annual scales are investigated based on the modified Mann-Kendall trend test method and the entropy theory in the Wei River Basin. A nonparametric method as an attractive alternative to empirical and parametric approaches is proposed to calculate the univariate and bivariate probability distribution of potential evaporation. The directional information transfer index (DITI) is employed to estimate the similarity among the meteorological stations, and the k-means cluster analysis is used to classify the meteorological stations into several distribution zones with distinct features. Based on the monthly potential evaporation from 1960 to 2008 at 21 meteorological stations, the basin is ultimately classified into 8 zones with their own distinct spatio-temporal distribution features. In view of the distinct spatio-temporal distribution features, the DITI-based model combined with the nonparametric probability estimation method and the k-means cluster analysis offers a more precise classification of potential evaporation distribution zones.

Identification of abrupt changes of the relationship between rainfall and runoff in the Wei River Basin, China

The relationship between rainfall and runoff in the Wei River Basin, one of the most important relationships in hydrology, possibly changed due to the changing climate and increasingly intensifying human activities. The identification of abrupt changes of the relationship will help to further understand the changing mechanism of runoff generation, being a great stimulus to the development of water resources planning and management. Therefore, a new method based on copulas was employed to detect change points of the relationship. Additionally, a Bayesian copula selection method was employed to choose the most appropriate copula, and the primary conclusions are as follows:(1) the Bayesian copula selection method based on Bayesian analysis is independent of parameter selections and easy to implement; (2) the identified change points can be summarized as the early 1970s, the late 1980s, and the middle 1990s; (3) from climate change perspective, the combined impact of increasing air temperature and initially decreasing then increasing potential evaporation had a certain effect on these change points; from human activities perspective, the underlying causes of these change points of the early 1970s, the late 1980s, and the middle 1990s were the construction of water projects and soil conservation, the growing effective arable land of the late 1980s and the growing utilization of water resources in the middle 1990s, respectively. The dominant factor influencing the relation between precipitation and runoff is the increasingly intensifying human activities, and this relation is increasingly weakening.

Contributions of climate variability and human activities to the variation of runoff in the Wei River Basin, China

ABSTRACT The Wei River Basin is a typical arid and semi-arid area of the Yellow River Basin. Quantitative estimates of the contributions of human activities and climate changes in this region will enhance our understanding of the local hydrological mechanism and provide an effective reference for other arid and semi-arid areas of the world in local water resource planning and management. The heuristic segmentation method was used to detect the inflection points of the annual runoff. The slope change ratio of accumulative quantity (SCRAQ) method was applied to compute the relative contributions of human activities and climate changes to the decreasing runoff in the whole basin and the basin above Linjiacun. For the whole basin, when 1960–1969 is selected as the baseline, the contributions of climate changes and human activities in 1970–1993 are 26.47% and 73.53%, respectively, those in 1993–2005 are 23.33% and 76.67%, respectively. When 1970–1993 is selected as the baseline, the contributions of climate and human impacts in 1994–2005 are 18.88% and 81.12%, respectively. The results imply that human activities are the dominant driving factors of runoff reduction, whose effect is increasingly intensifying. Furthermore, in order to verify the contributions of human activities and climate changes based on the SCRAQ method, an approach based on the Budyko hypothesis was used in this paper. The results indicate that the contributions of human activities and climate changes based on the SCRAQ method are consistent with those based on the sensitivity-based method. Editor Z.W. Kundzewicz; Associate editor D. Yang

Spatial-temporal change in precipitation patterns based on the cloud model across the Wei River Basin, China

It is of significant importance to investigate the spatial-temporal change in precipitation patterns due to its great effects on droughts, floods, soil erosion and water resource management. A complete investigation of precipitation structure and its distribution pattern based on daily precipitation covering 1960–2005 at 21 meteorological stations in the Wei River Basin has been performed. In order to comprehensively and objectively describe the changing pattern of precipitation, the cloud model is employed to quantitatively analyse the average, uniformity and stability of precipitation. Results indicate the following: (1) the occurrence of different precipitation durations exhibits a positive exponential curve with the decrease in precipitation durations, and 1–3-day events are the predominant precipitation events which have an increasing trend; (2) precipitation and its non-uniformity is increasingly reducing, while its stability increases initially then decreases; (3) mean precipitation reduces from southeast to northwest, and the precipitation of the Guanzhong Plain has a low uniformity and stability due to its location and increasingly intensifying human activities. The cloud model provides a new idea and quantitative measure for the evaluation of the uniformity and stability of precipitation.

A Case Study on a Combination NDVI Forecasting Model Based on the Entropy Weight Method

It is critically meaningful to accurately predict NDVI (Normalized Difference Vegetation Index), which helps guide regional ecological remediation and environmental managements. In this study, a combination forecasting model (CFM) was proposed to improve the performance of NDVI predictions in the Yellow River Basin (YRB) based on three individual forecasting models, i.e., the Multiple Linear Regression (MLR), Artificial Neural Network (ANN), and Support Vector Machine (SVM) models. The entropy weight method was employed to determine the weight coefficient for each individual model depending on its predictive performance. Results showed that: (1) ANN exhibits the highest fitting capability among the four forecasting models in the calibration period, whilst its generalization ability becomes weak in the validation period; MLR has a poor performance in both calibration and validation periods; the predicted results of CFM in the calibration period have the highest stability; (2) CFM generally outperforms all individual models in the validation period, and can improve the reliability and stability of predicted results through combining the strengths while reducing the weaknesses of individual models; (3) the performances of all forecasting models are better in dense vegetation areas than in sparse vegetation areas.

The asymmetric impact of global warming on US drought types and distributions in a large ensemble of 97 hydro-climatic simulations

Projection of future drought is often involved large uncertainties from climate models, emission scenarios as well as drought definitions. In this study, we investigate changes in future droughts in the conterminous United States based on 97 1/8 degree hydro-climate model projections. Instead of focusing on a specific drought type, we investigate changes in meteorological, agricultural, and hydrological drought as well as the concurrences. Agricultural and hydrological droughts are projected to become more frequent with increase in global mean temperature, while less meteorological drought is expected. Changes in drought intensity scale linearly with global temperature rises under RCP8.5 scenario, indicating the potential feasibility to derive future drought severity given certain global warming amount under this scenario. Changing pattern of concurrent droughts generally follows that of agricultural and hydrological droughts. Under the 1.5 °C warming target as advocated in recent Paris agreement, several hot spot regions experiencing highest droughts are identified. Extreme droughts show similar patterns but with much larger magnitude than the climatology. This study highlights the distinct response of droughts of various types to global warming and the asymmetric impact of global warming on drought distribution resulting in a much stronger influence on extreme drought than on mean drought.

Spatial-temporal variation of precipitation concentration and structure in the Wei River Basin, China

It is of significant importance to investigate precipitation structure and precipitation concentration due to their great impact on droughts, floods, soil erosion, as well as water resources management. A complete investigation of precipitation structure and its distribution pattern in the Wei River Basin was performed based on recorded daily precipitation data in this study. Two indicators were used: concentration index based on daily precipitation (CID), to assess the distribution of rainy days, and concentration index based on monthly precipitation (CIM), to estimate the seasonality of the precipitation. Besides, the modified Mann–Kendall trend test method was employed to capture the variation trends of CID and CIM. The results indicate that: (1) the 1–3-day events are the predominant precipitation events in terms of the occurrence and fractional contribution; (2) the obvious differences in the CID of various areas are found in the Wei River Basin, and the high CID values mainly concentrate in the northern basin, conversely, the southern basin has a relatively low CID value; (3) high CIM values are primarily in the western and northern basin, reflecting a remarkable seasonality of precipitation in these regions; and (4) all of the stations show a downward trend of CIM, which indicates that the monthly precipitation distribution tends to be more uniform.