Jianxia Chang

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.

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 Hybrid Index for Characterizing Drought Based on a Nonparametric Kernel Estimator

AbstractThis study develops a nonparametric multivariate drought index, namely, the nonparametric multivariate standardized drought index (NMSDI), by considering the variations of both precipitation and streamflow. Building upon previous efforts in constructing nonparametric multivariate drought index, the nonparametric kernel estimator is used to derive the joint distribution of precipitation and streamflow, thus providing additional insights into drought-index development. The proposed NMSDI is applied in the Wei River basin (WRB), on the basis of which the drought-evolution characteristics are investigated. Three main results were found: 1) In general, NMSDI captures drought onset in a way that is similar to that of the standardized precipitation index and captures drought termination and persistence in a way that is similar to that of the standardized streamflow index. The drought events identified by NMSDI match well with historical drought records in the WRB. Performance is also consistent with that...

Spatial–temporal changes in potential evaporation patterns based on the Cloud model and their possible causes

It is of importance to comprehensively investigate the spatial–temporal changes in potential evaporation patterns, which helps guide the long-term water resource allocation and irrigation managements. In this study, the Cloud model was adopted to quantify the average, uniformity, and stability of the annual potential evaporation in the Wei River Basin (WRB), a typical arid and semi-arid region in China, with the purpose of objectively and comprehensively characterizing its changing patterns. The cross wavelet analysis was then applied to explore the correlations between annual potential evaporation and Arctic Oscillation (AO)/El Niño Southern Oscillation (ENSO) with an aim to determine the possible causes of annual potential evaporation variations. Results indicated that: (1) the average of annual potential evaporation in the WRB first declined and then increased, and its stability also showed the same change characteristics, whilst its dispersion degree exhibited a decreasing trend, implying that potential evaporation has a smaller inter-annual variation; (2) the average of annual potential evaporation in the western basin was obviously smaller than that in the other areas, while its uniformity and stability in the Guanzhong plain and the Loess Plateau areas are larger than those in other areas, especially in the western basin where the uniformity and stability are the smallest; (3) both AO and ENSO exhibited strong correlations with annual potential evaporation variations, indicating that both AO and ENSO have played an important role in the annual potential evaporation variations in the WRB.

Bivariate frequency analysis of flood and extreme precipitation under changing environment: case study in catchments of the Loess Plateau, China

Floods have changed in a complex manner, triggered by the changing environment (i.e., intensified human activities and global warming). Hence, for better flood control and mitigation in the future, bivariate frequency analysis of flood and extreme precipitation events is of great necessity to be performed within the context of changing environment. Given this, in this paper, the Pettitt test and wavelet coherence transform analysis are used in combination to identify the period with transformed flood-generating mechanism. Subsequently, the primary and secondary return periods of annual maximum flood (AMF) discharge and extreme precipitation (Pr) during the identified period are derived based on the copula. Meanwhile, the conditional probability of occurring different flood discharge magnitudes under various extreme precipitation scenarios are estimated using the joint dependence structure between AMF and Pr. Moreover, Monte Carlo-based algorithm is performed to evaluate the uncertainties of the above copula-based analyses robustly. Two catchments located on the Loess plateau are selected as study regions, which are Weihe River Basin (WRB) and Jinghe River Basin (JRB). Results indicate that: (1) the 1994–2014 and 1981–2014 are identified as periods with transformed flood-generating mechanism in the WRB and JRB, respectively; (2) the primary and secondary return periods for AMF and Pr are examined. Furthermore, chance of occurring different AMF under varying Pr scenarios also be elucidated according to the joint distribution of AMF and Pr. Despite these, one thing to notice is that the associate uncertainties are considerable, thus greatly challenges measures of future flood mitigation. Results of this study offer technical reference for copula-based frequency analysis under changing environment at regional and global scales.