Correlation Analysis of Landscape Structure and Water Quality in Suzhou National Wetland Park, China

What is the relationship between land use and surface water quality? A review and prospects from remote sensing perspective

Good surface water quality is critical to human health and ecology. Land use determines the surface water heat and material balance, which cause climate change and affect water quality. There are many factors affecting water quality degradation, and the process of influence is complex. As rivers, lakes, and other water bodies are used as environmental receiving carriers, evaluating and quantifying how impacts occur between land use types and surface water quality is extremely important. Based on the summary of published studies, we can see that (1) land use for agricultural and construction has a negative impact on surface water quality, while woodland use has a certain degree of improvement on surface water quality; (2) statistical methods used in relevant research mainly include correlation analysis, regression analysis, redundancy analysis, etc. Different methods have their own advantages and limitations; (3) in recent years, remote sensing monitoring technology has developed rapidly, and has developed into an effective tool for comprehensive water quality assessment and management. However, the increase in spatial resolution of remote sensing data has been accompanied by a surge in data volume, which has caused difficulties in information interpretation and other aspects.

Dynamic Characteristics of Drought Conditions during the Growth of Winter Wheat Based on an Improved SWAT Model

This study aimed at investigating the applicability of a SWAT (Soil and Water Assessment Tool) model in understanding the effects of drought on winter wheat. This study is based on the water requirement of the crop and addresses the absence of a SWAT model with real-time irrigation simulation. A real-time irrigation module was developed for the downstream irrigation area of the Yellow River to estimate the real-time irrigation of crops. By further simulating the dynamic evolution process of soil moisture content, a dynamic drought evaluation model of winter wheat was established, and the relative soil moisture was set as the evaluation index to assess and analyze the dynamic variation of drought evolution during the growth of winter wheat. The results showed that the improved SWAT model has strong applicability. During the growth of winter wheat, the variation trend of droughts is consistent with that of natural precipitation. For winter wheat, drought is quite normal during all growth stages, and the average frequency is 93.5%, 89.1%, 84.8%, 89.1% and 95.7%. Severe drought and extra-severe drought usually occur during the sowing–tillering stage and the tillering–greening stage, and the frequency of occurrence is 30.4% and 19.6%, respectively. This paper provides a novel approach for the study of agricultural drought in the downstream irrigation area of the Yellow River.