Coupling ITO3dE model and GIS for spatiotemporal evolution analysis of agricultural non-point source pollution risks in Chongqing in China

Spatial distribution of pesticide use based on crop rotation data in La Plata River basin: a case study from an agricultural region of Uruguay

The intensive global use of pesticides presents an escalating threat to human health, ecosystems, and water quality. To develop national and local environmental management strategies for mitigating pollution caused by pesticides, it is essential to understand the quantities, timing, and location of their application. This study aims to estimate the spatial distribution of pesticide use in an agricultural region of La Plata River basin in Uruguay. Estimates of pesticide use were made by surveying doses applied to each crop. This information was spatialized through identifying agricultural rotations using remote sensing techniques. The study identified the 60 major agricultural rotations in the region and mapped the use and application amount of the nine most significant active ingredients (glyphosate, 2,4-dichlorophenoxyacetic acid, flumioxazin, S-metolachlor, clethodim, flumetsulam, triflumuron, chlorantraniliprole, and fipronil). The results reveal that glyphosate is the most extensively used pesticide (53.5% of the area) and highest amount of use (> 1.44 kg/ha). Moreover, in 19% of the area, at least seven active ingredients are applied in crop rotations. This study marks the initial step in identifying rotations and estimating pesticide applications with high spatial resolution at a regional scale in agricultural regions of La Plata River basin. The results improve the understanding of pesticide spatial distribution based on data obtained from agronomists, technicians, and producers and provide a replicable methodological approach for other geographic and productive contexts. Generating baseline information is key to environmental management and decision making, towards the design of more robust monitoring systems and human exposure assessment.

Impact of Future Development Scenario Selection on Landscape Ecological Risk in the Chengdu-Chongqing Economic Zone

The management of regional eco-environmental risks is the key to promoting regional economic sustainability from the macro level, and accurate evaluation of the evolutionary trends of regional ecological risk in the future is of high importance. In order to clearly identify the possible impact of future development scenario selection for the Chengdu-Chongqing Economic Zone (C-C E Zone) on the evolution of landscape ecological risk (LER), we introduced the Patch-generating Land Use Simulation (PLUS) model to simulate land use data for the C-C E Zone from 2030 to 2050 for two scenarios: natural development (ND) and ecological protection (EP). Based on the ecological grid and landscape ecological risk index (LERI) model, the landscape ecological risk (LER) evolutionary trends seen in the C-C E Zone from 2000 to 2050 were analyzed and identified. The results showed that: (1) The PLUS model can obtain high-precision simulation results in the C-C E Zone. In the future, the currently increasing rate of land being used for construction will be reduced, the declining rates of forest and cultivated land area will also be reduced, and the amount of land being used for various purposes will remain stable going into the future. (2) This study found that the optimal size of the ecological grid in the LERI calculation of the mountainous area was 4 × 4 km. Additionally, the mean values of the LERI in 2030, 2040, and 2050 were 0.1612, 0.1628, and 0.1636 for ND and 0.1612, 0.1618, and 0.1620 for EP. (3) The hot spot analysis results showed that an area of about 49,700 km2 in the C-C E Zone from 2000 to 2050 belongs to high agglomeration of LER. (4) Since 2010, the proportions of high and extremely high risk levels have continued to increase, but under the EP scenario, the high and extremely high risk levels in 2040 and 2050 decreased from 14.36% and 6.66% to 14.33% and 6.43%. Regional analysis showed that the high and extremely high risk levels in most regions increased over 2010–2050. (5) Under the ND scenario, the proportions of grids with decreased, unchanged, and increased risk levels were 15.13%, 81.48%, and 3.39% for 2000–2010 and 0.54%, 94.75%, and 4.71% for 2040–2050. These trends indicated that the proportion of grids with changed risk levels gradually decreased going into the future. This study analyzed the evolutionary trends of LER at the C-C E Zone for the ND and EP scenario. On the whole, the LER for the C-C E Zone showed an upward trend, and the EP scenario was conducive to reducing the risk. These research results can serve as a valuable data reference set for regional landscape optimization and risk prevention and control.