Spatial analysis is a basic component of scientific research, including ecology, evolution and environmental science, epidemiology, geology, geography and mathematics. Recent technological advances in genome sequencing, global positioning systems and remote sensing technology have led to a rapid expansion in the number and scale of spatial explicit data sets available for analysis. These new data extend the scope of spatial analysis to a wider range of human activities, but also rapidly surpass the capabilities of traditional spatial analysis software and methods.
Qual2k is a one-dimensional comprehensive water quality model with multiple uses, which is widely used in water quality planning and management of rivers. It aims to represent a modern version of QUAL2E (or q2e) model (brown and Barnwell 1987). Q2k is similar to q2e in the following aspects:
Epic is a continuous simulation model used to study the long-term effects of various soil erosion factors on crop production. Epic is a public domain model for studying the impact of soil erosion on crop production in more than 60 countries in Asia, South America and Europe. The model is used to study soil erosion, economic factors, hydrological models, weather effects, nutrition, plant growth dynamics and crop management. The main components of the epic are weather simulation, hydrology, erosion deposition, nutrient cycling, pesticide fate, plant growth, soil temperature, farming, economy and plant environmental control. Epic assessed the impact of soil erosion on productivity and predicted the impact of management decisions on soil, water, nutrient and pesticide movement, as well as their combined effects on soil fertility and managed soil loss, water quality and crop yield.
As a global 3D atmospheric chemical transport model (CTM), geoschem mainly aims at the source and sink of atmospheric components and the physical and chemical effects in the transport process, so as to simulate the actual concentration distribution and evolution process of each component. GEOS Chem uses the meteorological plants from GEOS assimilation provided by NASA's global modeling and data assimilation Office (gmao) as the initial field to drive the model. The geoschem model includes a detailed tropospheric ozone NOx VOC aerosol Hox chemical process. It fully considers the joint effect of emission sources and natural sources. It considers that the emission of CO, NOx and SO2 is taken as the default in geoschem, using Edgar 3.2's monthly global inventory in 2000, while the anthropogenic non methane VOC is used as the default, using retro 2000 as the default Geoschem uses the advection algorithm of tpcore to simulate the horizontal transport process, which is consistent with the GEOS GCM meteorological simulation, while the convective mass flux calculation includes wet deposition, dry deposition and sea salt deposition. The geoschem mixing in the boundary layer uses a non local scheme, and the simulation of mercury is extended from the original geoschem air sea coupling simulation to a coupled atmosphere ocean land model.
MM5 model has the main functions of non static dynamic frame, multi-layer grid nesting, various physical process options, four-dimensional variation, and more extensive computer platform transplantation. The simulation area of MM5 adopts Lambert projection, and the two true latitudes are 25 degrees north latitude and 40 degrees north latitude respectively. In order to ensure the accuracy of boundary meteorological field, MM5 simulation area has three grids more than the horizontal boundaries of air quality simulation area; the top of the simulation layer is 100MB, which is vertically divided into the following 23 σ layers. The data of terrain and surface type are global data of USGS; the objective analysis is based on the ADP global surface and high-altitude observation data of NCEP to conduct grid four-dimensional data assimilation. The parameterization of physical processes in the simulation domain are as follows: Kain Fritsch's cumulus parameterization scheme; pleim Xu's boundary layer and land surface parameterization scheme; Reisner's multiphase explicit water vapor scheme; cloud radiation parameterization method; and multi-layer soil model.
DRAINMOD is a computer simulation model, which simulates the hydrological conditions of poorly drained high water level soil hourly with a long climate record (for example, 50 years). The model predicts the impacts of drainage and related water management practices on groundwater table, soil moisture status and crop yield. The parallel method is mainly used to analyze the hydrological conditions of some types of wetlands to determine whether the wetland hydrological standards meet the requirements of drainage or part of the drainage site. The model is also used to determine the hydropower capacity of the sewage treatment system. The model has been successfully tested and applied to various geographical and soil conditions. Over the past 20 years, the model's capacity has been extended to predict the impact of drainage and water resource management practices on hydrology and water quality in farmland and watershed wide agriculture and woodland.
ARPS model is a non-static equilibrium regional forecast system developed by the storm analysis and Prediction Center of the University of Oklahoma. ARPS model adopts generalized terrain coordinate system, arakawa-c staggered horizontal grid and second-order leapfrog leaping time integration scheme, including cloud microphysical process, sub grid scale turbulence and other physical processes. ARPS model is suitable for small and medium-sized and storm scale weather systems, such as tornado, supercell storm, etc. ARPS model is mainly aimed at non energetic high-resolution regional forecast system of storm scale, including variational assimilation of real-time data, forward prediction and post-processing module.
HYSIM is a hydrological simulation model (rainfall runoff model), which uses rainfall and potential evaporation data to simulate the hydrological cycle (surface runoff, infiltration into groundwater and river flows). HYSIM can use data from rainfall, potential evaporation (PET), snow melting and extraction from groundwater and surface water. Only data on rainfall and potential evaporation are essential. The simulation time can be a day or less. Typical uses of HYSIM include: