Zengchao Hao

Review of dependence modeling in hydrology and water resources

Various methods have been developed over the past five decades for dependence modeling of multivariate variables in hydrology and water resources, but there has been no overall review of techniques commonly used in the field. This paper, therefore, introduces several methods focusing on dependence structure modeling, including parametric distribution, entropy, copula, and nonparametric. Recent advances in modeling dependences mainly reside in nonlinear dependence modeling (including extreme dependence) with flexible marginal distributions, and in high-dimension dependence modeling via the vine copula construction with flexible dependence structures. Strengths and limitations of different methods and avenues for future research, such as dependence modeling in a changing climate, are discussed to aid water resource planners and managers in the selection and application of suitable techniques.

Integrating Entropy and Copula Theories for Hydrologic Modeling and Analysis

Entropy is a measure of uncertainty and has been commonly used for various applications, including probability inferences in hydrology. Copula has been widely used for constructing joint distributions to model the dependence structure of multivariate hydrological random variables. Integration of entropy and copula theories provides new insights in hydrologic modeling and analysis, for which the development and application are still in infancy. Two broad branches of integration of the two concepts, entropy copula and copula entropy, are introduced in this study. On the one hand, the entropy theory can be used to derive new families of copulas based on information content matching. On the other hand, the copula entropy provides attractive alternatives in the nonlinear dependence measurement even in higher dimensions. We introduce in this study the integration of entropy and copula theories in the dependence modeling and analysis to illustrate the potential applications in hydrology and water resources.

Refining a Distributed Linear Reservoir Routing Method to Improve Performance of the CREST Model

AbstractAs one of the most important components of hydrologic models, routing module determines model performance to a large degree. In this study, the authors proposed a fully distributed linear r...

Combined impacts of land use and soil property changes on soil erosion in a mollisol area under long-term agricultural development

Soil erosion exhibits special characteristics in the process of agricultural development. Understanding the combined impacts of land use and soil property changes on soil erosion, especially in the area under long-term agricultural cultivations, is vital to watershed agricultural and soil management. This study investigated the temporal-spatial patterns of the soil erosion based on a modified version of Universal Soil Loss Equation (USLE) and conducted a soil erosion contribution analysis. The land use data were interpreted from Landsat series images, and soil properties were obtained from field sampling, laboratory tests and SPAW (Soil-Plant-Atmosphere-Water) model calculations. Over a long period of agricultural development, the average erosion modulus decreased from 187.7tkm-2a-1 in 1979 to 158.4tkm-2a-1 in 2014. The land use types were transformed mainly in the reclamation of paddy fields and the shrinking of wetlands on a large scale. Most of the soils were converted to loam from silty or clay loam and the saturated hydraulic conductivity (Ks) of most soil types decreased by 1.11% to 43.6%. The rapidly increasing area of 49.8km2 of paddy fields together with the moderate decrease of 14.0km2 of forests, as well as Ks values explained 87.4% of the total variance in soil erosion. Although changes in soil physical and water characteristics indicated that soil erosion loads should have become higher, the upsurge in paddy fields played an important role in mitigating soil erosion in this study area. These results demonstrated that land use changes had more significant impacts than soil property changes on soil erosion. This study suggested that rational measures should be taken to extend paddy fields and control the dry land farming. These findings will benefit watershed agricultural targeting and management.

An integrated package for drought monitoring, prediction and analysis to aid drought modeling and assessment

Due to severe drought events and disastrous impacts in recent decades, substantial efforts have been devoted recently to drought monitoring, prediction and risk analysis for aiding drought preparedness plans and mitigation measures. Providing an overview of these aspects of drought research, this study presents an integrated R package and illustrates a wide range of its applications for drought modeling and assessment based on univariate and multivariate drought indices for both operational and research purposes. The package also includes statistical prediction of drought in a probabilistic manner based on multiple drought indicators, which serves as a baseline for drought prediction. The univariate and multivariate drought risk analysis of drought properties and indices is also presented. Finally, potential extensions of this package are also discussed. The package is provided freely to public to aid drought early warning and management. Derivation of univariate and multivariate drought indices based on hydroclimatic variables.Probabilistic drought prediction of multiple drought indices with statistical methods.Joint and conditional risk analysis of multiple drought properties and types.Application of an integrated R package for drought monitoring, prediction and analysis.

A Statistical Method for Categorical Drought Prediction Based on NLDAS-2

AbstractDrought is a slowly varying natural phenomenon and may have wide impacts on a range of sectors. Tremendous efforts have therefore been devoted to drought monitoring and prediction to reduce potential impacts of drought. Reliable drought prediction is critically important to provide information ahead of time for early warning to facilitate drought-preparedness plans. The U.S. Drought Monitor (USDM) is a composite drought product that depicts drought conditions in categorical forms, and it has been widely used to track drought and its impacts for operational and research purposes. The USDM is an assessment of drought condition but does not provide drought prediction information. Given the wide application of USDM, drought prediction in a categorical form similar to that of USDM would be of considerable importance, but it has not been explored thus far. This study proposes a statistical method for categorical drought prediction by integrating the USDM drought category as an initial condition with dro...

Farmland-atmosphere feedbacks amplify decreases in diffuse nitrogen pollution in a freeze-thaw agricultural area under climate warming conditions.

Although climate warming and agricultural land use changes are two of the primary instigators of increased diffuse pollution, they are usually considered separately or additively. This likely lead to poor decisions regarding climate adaptation. Climate warming and farmland responses have synergistic consequences for diffuse nitrogen pollution, which are hypothesized to present different spatio-temporal patterns. In this study, we propose a modeling framework to simulate the synergistic impacts of climate warming and warming-induced farmland shifts on diffuse pollution. Active accumulated temperature response for latitudinal and altitudinal directions was predicted based on a simple agro-climate model under different temperature increments (△T0 is from 0.8°C to 1.4°C at an interval of 0.2°C). Spatial distributions of dryland shift to paddy land were determined by considering accumulated temperature. Different temperature increments and crop distributions were inserted into Soil and Water Assessment Tool model, which quantified the spatio-temporal changes of nitrogen. Warming led to a decrease of the annual total nitrogen loading (2.6%-14.2%) in the low latitudes compared with baseline, which was larger than the decrease (0.8%-6.2%) in the high latitudes. The synergistic impacts amplified the decrease of the loading in the low and high latitudes at the sub-basin scale. Warming led to a decrease of the loading at a rate of 0.35kg/ha/°C, which was lower than the synergistic impacts (3.67kg/ha/°C) at the watershed level. However, warming led to the slight increase of the annual averaged NO3 (LAT) (0.16kg/ha/°C), which was amplified by the synergistic impacts (0.22kg/ha/°C). Expansion of paddy fields led to a decrease in the monthly total nitrogen loading throughout the year, but amplified an increase in the loading in August and September. The decreased response in spatio-temporal nitrogen patterns is substantially amplified by farmland-atmosphere feedbacks associated with farmland shifts in response to warming.

An Overview of Drought Monitoring and Prediction Systems at Regional and Global Scales

AbstractIn past decades, severe drought events have struck different regions around the world, leading to huge losses to a wide array of environmental and societal sectors. Because of wide impacts of drought, it is of critical importance to monitor drought in near–real time and provide early warning. This article provides an overview of the development of drought monitoring and prediction systems (DMAPS) at regional and global scales. After introducing drought indicators, drought monitoring (based on different data sources and tools) is summarized, along with an introduction of statistical and dynamical drought prediction approaches. The current progress of the development and implementation of DMAPS with various indicators at different temporal and/or spatial resolutions, based on the land surface modeling, remote sensing, and seasonal climate forecast, at the regional and global scales is then reviewed. Advances in drought monitoring with multiple data sources and tools and prediction from multimodel en...

Quantitative risk assessment of the effects of drought on extreme temperature in eastern China

Hot extremes may lead to disastrous impacts on human health and agricultural production. Previous studies have revealed the feedback between drought and hot extremes in large regions of eastern China while quantifying the impact of antecedent drought on hot extremes has been limited. This study aims at quantitatively assessing the risk of extreme temperature conditioned on the antecedent drought condition represented by Standardized Precipitation Index (SPI) during summer time in eastern China. A copula based model is proposed to construct the joint probability distribution of extreme temperature and drought based on 6-month SPI (SPI6). Accordingly, the conditional probability distribution is employed to quantify impacts of antecedent dry (and wet) conditions on the exceedance probability of extreme temperature. Results show that the likelihood of extreme temperature exceeding high quantiles is higher given antecedent dry conditions than that given antecedent wet conditions in large regions from southwestern to northeastern China. Specifically, the conditional probability difference of temperature exceeding 80th percentile given SPI6 lower than or equal to -0.5 and SPI6 higher than 0.5 is around 0.2-0.3. The case study of the 2006 summer hot extremes and drought in Sichuan and Chongqing region shows that the conditional return period of extreme temperature conditioned on antecedent drought is around 5-50 years shorter than univariate return period. These results quantify the impact of antecedent drought on subsequent extreme temperature and highlight the important role of antecedent drought in intensifying hot extremes in these regions.

Rainwater characteristics and interaction with atmospheric particle matter transportation analyzed by remote sensing around Beijing

Air pollution in Beijing has attracted much more attentions, and multiple regulations have been enacted since 2013. Based on the close link between the atmospheric particle matter concentration and the deposited load in rainwater, 336 rainwater samplings with seven parameters (pH, NH4+-N, NO3--N, P, S, Cu and Cd) at five-minute intervals in 2013 and 2014 were compared. The field monitoring and the temporal patterns analysis revealed a positive development of air quality. The lesser composition of coal in the energy consumption and the effective control of traffic emission were found. The average Aerosol Optical Depth (AOD) value around the sampling point during the 7 sampling rainfall events in 2014 was 2.855, which was higher than that in 2013 (1.807). It reflected the washing effect of rain on atmospheric particulates and highlighted the urban non-point source pollution effected by atmospheric deposition. AOD was demonstrated to perform well in reflecting regional air quality. A trajectory analysis conducted by HYSPLIT model in conjunction with the spatial distribution of AOD in the Beijing-Tian-Hebei (BTH) region depicted paths of air pollutants from long-range transport. The dominant trace was to the south of region. Cities around BTH were provided with different emission-reducing targets. Both Inner Mongolia and Henan province were suggested to control agricultural emissions. Shanxi, Shandong and cities around Bohai Bay should supervise the energy consuming industries. Furthermore, NO3--N was introduced to be an indicator of effect of the regional joint prevention and control in the future.