Comparative Analysis of Rainfall Trends in the Jinghe River Basin During 1959-2014

Trend analysis is widely applied in hydrometeorological research. Considering that Innovative Trend Analysis (ITA) and Innovative Polygonal Trend Analysis (IPTA) can detect small variations on annual and smaller scale, rainfall trends at 14 hydrometeorological stations in the Jinghe River Basin were analyzed by ITA, IPTA and Mann Kendall test (MK). The results showed that the rainfall trends are subsistent from 1959 to 2014. Comparing the results of ITA and MK on annual level, it was determined that trends are consistent, but only two stations passed the 90% significance test through MK, while all stations passed the significance test through ITA. Accordingly, the ITA method proved to be better than MK in detecting small changes in time series. Changes in high and low values, obtained by the ITA method, reflected flood and drought trends in the basin. In addition, IPTA is an improved ITA method that is suitable for a relatively short time span. Through the IPTA method for analyzing the monthly precipitation trends, the results showed that rainfall at 14 stations increased in January, February, March, June and December, and decreased significantly in September. Therefore, the methodology applied in this study can provide detailed recommendations for hydrometeorological research.

Causes of Variations in Sediment Yield in the Jinghe River Basin, China

The Jinghe River remains the major sediment source of the Yellow River in China; however, sediment discharge in the Jinghe River has reduced significantly since the 1950s. The objective of this study is to identify the causes of sediment yield variations in the Jinghe River Basin based on soil and water conservation methods and rainfall analyses. The results revealed that soil and water conservation projects were responsible for half of the total sediment reduction; sediment retention due to reservoirs and water diversion projects was responsible for 1.3% of the total reduction. Moreover, the Jinghe River Basin has negligible opportunity to improve its vegetation cover (currently 55% of the basin is covered with lawns and trees), and silt-arrester dams play a smaller role in reducing sediment significantly before they are entirely full. Therefore, new large-scale sediment trapping projects must be implemented across the Jinghe River Basin, where heavy rainfall events are likely to substantially increase in the future, leading to higher sediment discharge.

Spatial Distribution Characteristics and Optimum Layout of Urban and Rural Areas in Different Geomorphological Types

Taking Jinghe River Basin in the Loess geomorphological area and Guangnan County in the karst geomorphological area as the study area, the spatial distribution characteristics of urban and rural areas of different geomorphological types are analyzed. By using GIS and related statistical analysis software, this paper summarizes three basic urban and rural types: river channel type, plateau surface type, and loess terrace horizon prototype in the Loess Landscape Jinghe River Basin. It is known that most towns in the loess plateau gully area are in the Jinghe River Basin. According to the spatial distribution characteristics of urban and rural areas, the optimal layout based on the main structure of five districts, nine River corridors, and four plates is proposed. Using the DEM module of ArcGIS to divide the elevation and gradient of Guangnan County, we know that the density of urban and rural settlements in Guangnan County is low and the spatial distribution is dispersed, and the distribution of urban and rural settlements shows a strong elevation orientation. The distribution of urban and rural settlements has a normal distribution relationship with the elevation. The largest number of urban and rural settlements is between 2.1° and 25°. According to the present situation of settlement distribution, this paper puts forward some optimization strategies, such as appropriate settlement scale, settlement space development monitoring, and so on.

Characterizing Hydrological Drought and Water Scarcity Changes in the Future: A Case Study in the Jinghe River Basin of China

The assessment of future climate changes on drought and water scarcity is extremely important for water resources management. A modeling system is developed to study the potential status of hydrological drought and water scarcity in the future, and this modeling system is applied to the Jinghe River Basin (JRB) of China. Driven by high-resolution climate projections from the Regional Climate Modeling System (RegCM), the Variable Infiltration Capacity model is employed to produce future streamflow projections (2020–2099) under two Representative Concentration Pathway (RCP) scenarios. The copula-based method is applied to identify the correlation between drought variables (i.e., duration and severity), and to further quantify their joint risks. Based on a variety of hypothetical water use scenarios in the future, the water scarcity conditions including extreme cases are estimated through the Water Exploitation Index Plus (WEI+) indicator. The results indicate that the joint risks of drought variables at different return periods would decrease. In detail, the severity of future drought events would become less serious under different RCP scenarios when compared with that in the historical period. However, considering the increase in water consumption in the future, the water scarcity in JRB may not be alleviated in the future, and thus drought assessment alone may underestimate the severity of future water shortage. The results obtained from the modeling system can help policy makers to develop reasonable future water-saving planning schemes, as well as drought mitigation measures.

How to Optimize Ecosystem Services Based on a Bayesian Model: A Case Study of Jinghe River Basin

Based on a Bayesian Network Model (BBN), we established an ecological service network system of the Jinghe River Basin in 2015. Our method consisted of using the distributed eco-hydrological model (Soil and Water Assessment Tool (SWAT) model) to simulate water yield, the Carnegie-Ames-Stanford Approach (CASA) model to estimate Net Primary Productivity (NPP), the Universal Soil Loss Equation (USLE) model to calculate soil erosion and the Crop Productivity (CP) model to simulate agricultural productivity to quantify the four ecosystem services. Based on the network established, the key variable subset and the visual optimal state subset, which we visualized, were analyzed and used to provide spatial optimization suggestions for the four kinds of ecosystem services studied. Our results indicate that water yield, concentrated in the middle and lower reaches of the mountain and river areas, is increasing in the Jinghe River Basin. NPP is continuously increasing and is distributed in the middle and lower reaches of the mountain areas on both sides of the river. Agricultural productivity also shows an upward trend, with areas of high productivity concentrated in the southern downstream mountain areas. On the contrary, the amount of soil erosion is declining, and the high erosion value is also declining, mainly in the upper reaches of the basin (in the Loess Hilly Area). Additionally, we found that a synergistic relationship exists between water yield, NPP and agricultural productivity, which can increase vegetation cover, leading to enhanced agricultural productivity. However, water yield can be reduced as required in order to balance the tradeoff between water yield and soil erosion. Clear regional differences exist in ecosystem services in the river basin. In the future, the two wings of the middle and lower reaches of the river basin will be the main areas of optimization, and it is likely that an optimal ecosystem services pattern can be reached.