Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains

Nolan, Bernard T.; Dubus, Igor G.; Surdyk, Nicolas; Fowler, Hayley J.; Burton, A.; Hollis, J. M.; Reichenberger, Stefan; Jarvis, Nicholas

doi:10.1002/ps.1587

Cited by 59 publications

(30 citation statements)

References 26 publications

(29 reference statements)

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“…If, for example, geochemical processes such as pollutant mobilisation are an overwhelming concern, sensitivity studies can be conducted to identify Nolan et al, 2008). In this paper the processes of interest are river flows from mountainous headwaters and agricultural production, both of which depend upon inputs of mass (precipitation) and energy (ambient temperature and incoming radiation).…”

Section: Selection Of Climate Variables Governing Water Resources Andmentioning

confidence: 99%

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

2015

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Abstract.A three-step climate classification was applied to a spatial domain covering the Himalayan arc and adjacent plains regions using input data from four global meteorological reanalyses. Input variables were selected based on an understanding of the climatic drivers of regional water resource variability and crop yields. Principal component analysis (PCA) of those variables and k-means clustering on the PCA outputs revealed a reanalysis ensemble consensus for eight macro-climate zones. Spatial statistics of input variables for each zone revealed consistent, distinct climatologies. This climate classification approach has potential for enhancing assessment of climatic influences on water resources and food security as well as for characterising the skill and bias of gridded data sets, both meteorological reanalyses and climate models, for reproducing subregional climatologies. Through their spatial descriptors (area, geographic centroid, elevation mean range), climate classifications also provide metrics, beyond simple changes in individual variables, with which to assess the magnitude of projected climate change. Such sophisticated metrics are of particular interest for regions, including mountainous areas, where natural and anthropogenic systems are expected to be sensitive to incremental climate shifts.

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Section: Selection Of Climate Variables Governing Water Resources Andmentioning

confidence: 99%

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

2015

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“…포아송 클러스터 강우생성 모형은 기존의 자 기 상관성에 기반을 둔 모형과 비교하였을 때, (1) 넓은 시간대(1시간-1개월)에 대하여 관측강우의 통계치를 재 현할 수 있으며, (2) 세밀한 시간 해상도(1시간 단위)를 가 진 강우시계열의 생성이 가능하고, (3) 극한값들을 잘 재 현한다는 강점을 가지고 있다 . 이러 한 모형의 장점으로 인하여, 포아송 클러스터 강우생성 모형은 도시지역에서의 홍수 (Moretti and Montanari, 2004;Brath et al, 2006, Dawson et al, 2006, 농약의 확 산 (Nolan et al, 2008), 산사태 (Bathurst et al, 2005), 사막 화 (Bathurst and Bovolo, 2004), 수자원 평가 (Fowler et al, 2005), 홍수위험도 평가 (Kilsby et al, 2000) (1)…”

Section: Fig 1 the Concept Of Poisson Cluster Rainfall Generation Munclassified

The Application of the Poisson Cluster Rainfall Generation Model to the Flood Analysis

김동균¹,

신지예²,

이승오³

et al. 2013

Journal of Korea Water Resources Association

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The applicability of the parameter map of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) model for the Korean Peninsula was assessed from the perspective of flood prediction. The design rainfalls estimated from the MBLRP model were smaller than those from observed values by 5% to 40%, and the degree of underestimation of design rainfall increases with the increase of the recurrence interval of the design rainfall. The design floods at a virtual watershed estimated using the simulated rainfall time series based on MBLRP model were also smaller than those derived from the observed rainfall time series by 20% to 45%. The degree of underestimation of design flood increases with the increase of the recurrence interval of the design flood.

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“…Capel et al, 2001;Holvoet et al, 2007;Nolan et al, 2008;Lewan et al, 2009). In a lysimeter study, Beulke et al (2002) found an exponential relationship between pesticide losses and total outflow for soils susceptible to preferential flow.…”

Section: Introductionmentioning

confidence: 99%

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

Steffens

Larsbo

Moeys

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Assessing climate change impacts on pesticide leaching requires careful consideration of different sources of uncertainty. We investigated the uncertainty related to climate scenario input and its importance relative to parameter uncertainty of the pesticide leaching model. The pesticide fate model MACRO was calibrated against a comprehensive one-year field data set for a well-structured clay soil in southwestern Sweden. We obtained an ensemble of 56 acceptable parameter sets that represented the parameter uncertainty. Nine different climate model projections of the regional climate model RCA3 were available as driven by different combinations of global climate models (GCM), greenhouse gas emission scenarios and initial states of the GCM. The future time series of weather data used to drive the MACRO model were generated by scaling a reference climate data set for an important agricultural production area in south-western Sweden based on monthly change factors for 2070-2099. 30 yr simulations were performed for different combinations of pesticide properties and application seasons. Our analysis showed that both the magnitude and the direction of predicted change in pesticide leaching from present to future depended strongly on the particular climate scenario. The effect of parameter uncertainty was of major importance for simulating absolute pesticide losses, whereas the climate uncertainty was relatively more important for predictions of changes of pesticide losses from present to future. The climate uncertainty should be accounted for by applying an ensemble of different climate scenarios. The aggregated ensemble prediction based on both acceptable parameterizations and different climate scenarios has the potential to provide robust probabilistic estimates of future pesticide losses.

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Identification of key climatic factors regulating the transport of pesticides in leaching and to tile drains

Cited by 59 publications

References 26 publications

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

Exploring objective climate classification for the Himalayan arc and adjacent regions using gridded data sources

The Application of the Poisson Cluster Rainfall Generation Model to the Flood Analysis

Modelling pesticide leaching under climate change: parameter vs. climate input uncertainty

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