Climate change impacts on agricultural non‐point source pollution with consideration of uncertainty in CMIP5

Abstract

Changes in non‐point source pollutant loads in the Mankyeong River Basin for the 30‐year future period (2011–2040) were assessed with consideration of the uncertainties in the climate change scenario data. The downscaled weather variables from eleven Climate Models for the Representative Concentration Pathways (RCP) 8.5 scenario were used as input to the calibrated and validated Soil and Water Assessment Tool (SWAT) model for simulating the changes of future NPS pollutant loads. The bias‐corrected data appropriately reproduced the spatial and temporal patterns of the NPS pollutant load, which was derived by using observed weather data. The rates of change in sediment, total nitrogen (TN) and total phosphorus (TP) loads within each sub‐basin under the RCP8.5 future scenario showed an average increase of 13.1 to 143%, −13.4 to 49.5%, and 0.40 to 128%, respectively. It can be concluded that sediment and TP loads are sensitive to changes in the characteristics of climate variables by showing an increase trend in most of the sub‐basins. Looking at the temporal distribution, the uncertainty ranges for both sediment and TP were higher during the wet season from June to September. Copyright © 2016 John Wiley & Sons, Ltd.

Impacts of Climate Change Scenarios on Non-Point Source Pollution in the Saemangeum Watershed, South Korea

“…Global climate models (GCMs) are generally the primary models used for constructing future climate change scenarios, and they provide the basis for assessing climate change on all scales. GCMs can provide the six major variables (precipitation, maximum temperature, minimum temperature, wind speed, solar radiation, and relative humidity) that are needed for modeling [12]. However, studies rarely use GCM outputs directly due to the significant errors in GCM historical simulations [17].…”

“…In the Saemangeum watershed, the scenario data were based on four Automated Synoptic Observation System (ASOS) weather stations (Gunsan, Jeonju, Buan, and Jeongup) of the Korea Meteorological Administration in the Saemangeum watershed, and used the simple quantile mapping (SQM) downscaling method [18] for downscaling and bias correction. The SQM downscaling method uses non-parametric quantile mapping for downscaling and bias correction to produce reliable daily climate data for future periods [12]. In this study, RCP 4.5 and RCP 8.5 climate change scenarios were used as the model input for predicting future trends of streamflow and NPS pollution in the Saemangeum watershed.…”

“…Monica and Choi [11] performed temporal and spatial analyses of water quality in the watershed using multivariate techniques. However, the simulation of water quality using the soil and water assessment tool (SWAT) has not been thoroughly explored for the analysis of large watersheds [12]. The abovementioned studies focused only on one of the two major sub-watersheds of the Saemangeum watershed.…”

Climate change impacts on streamflow and non‐point source pollutant loads in the 3S Rivers of the Mekong Basin

“…Azari et al (2016) used SWAT to simulate changes in streamflow and sediment yield under climate change scenarios in the North of Iran and indicated that increases in streamflow and sediment yield are predicted in the future. Cho et al (2016) investigated the impacts of climate change on NPS pollutant loads in the Mankyeong River Basin (Korea), and found that the NPS pollutant loads are sensitive to climate change scenarios by showing an increase trend in the basin. In general, those studies indicate that hydrological processes and NPS pollutant loads are sensitive to climate change, and impacts of climate change on hydrology and NPS pollution vary from region to region.…”

Non-Point Source Pollution Modelling: An Overview

“…TP concentration in the eastern region of Yuqaio Reservoir was observed to exceed that in the west and the mean TP concentration was at its peak in August (1.56 mg/L). In another research carried out in Korea, SWAT was also used to examine NPS pollution changes of TN, TP and sediment for 30 years giving regard to uncertainties in climate change scenario data (Cho et al, 2016). The results showed that sediment and TP loads are more likely to be affected by the features of climate variables by presenting an increasing trend in most sub-basins.…”