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Droogers, P.; Allen, Richard G.

doi:10.1023/a:1015508322413

Cited by 766 publications

(196 citation statements)

References 7 publications

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“…The information on distribution of land cover for three periods (2000, 2005 and 2010) (Droogers and Allen, 2002). This process was completed in interactive data language (IDL) which is a programming language used for data analysis.…”

Section: Data Sourcesmentioning

confidence: 99%

Optimizing hotspot areas for ecological planning and management based on biodiversity and ecosystem services

Xiao

Ouyang

et al. 2016

Chin. Geogr. Sci.

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Abstract:The significance of biodiversity and ecosystem services are gradually recognized by human as an approach towards sustainability, so it is important to understand relationships and congruence between them to support conservation planning, especially in the hotspot areas with a prominent role in conservation. However, the management of most conservation hotspots mainly focused on biodiversity, and rarely concerned with ecosystem services. With the aim of proposing criteria for conservation strategies that contribute to the optimization of biodiversity and ecosystem services, in this study, a Geographic Information System (GIS)-based approach was designed to estimate and map the biodiversity and ecosystem services in Chongqing Municipality of China. Furthermore, the distributions of hotspot areas for biodiversity and ecosystem services were mapped based on the relationship between cumulative ecosystem services and areas. Finally the statistical analysis was processed focused on specific conservation objectives. The results showed that hotspot areas can conserve the most biodiversity but with the least ecosystem services under the conservation plans target to biodiversity conservation. In contrast, depending on the ecosystem services of interest, hotspot areas can conserve the largest ecosystem services but with the least biodiversity. By integrating biodiversity and ecosystem services into conservation plan, we found that the conservation and regeneration of these small areas, would contribute to a conservation of 44% of the biodiversity hotspot and 14%-42% of the ecosystem services hotspot. Moreover, the current nature reserve selection was not maximize the biodiversity and ecosystem services compared to integration strategy, indicating that hotspot areas conservation and selection is vital for optimization protection of biodiversity and ecosystem services, and has practical significance for natural resources and ecosystem management. Keywords: biodiversity; ecosystem services; hotspot; nature reserve; Chongqing Municipality, China Citation: Xiao Yang, Ouyang Zhiyun, Xu Weihua, Xiao Yi, Zheng Hua, Xian Chaofan, 2016. Optimizing hotspot areas for ecological planning and management based on biodiversity and ecosystem services.

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Section: Data Sourcesmentioning

confidence: 99%

Optimizing hotspot areas for ecological planning and management based on biodiversity and ecosystem services

Xiao

Ouyang

et al. 2016

Chin. Geogr. Sci.

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“…A partir de resultados de inúmeros estudos conduzidos nas últimas décadas, a equação combinada de Penman-Monteith (PM), modificada por Allen et al (1998), é a que melhor representa os fatores físicos e fisiológicos que regem o processo da evapotranspiração. A principal desvantagem dessa equação é o grande número de variáveis meteorológicas necessárias para a sua aplicação, ao se considerar que muitas estações meteorológicas não têm todos os sensores necessários, os quais, mesmo quando presentes, muitas vezes, fornecem dados com baixa qualidade (Droogers & Allen, 2002). Esse fato é importante, especialmente para países em desenvolvimento, onde conjuntos confiáveis de dados de radiação, umidade relativa do ar e velocidade do vento nem sempre são comuns (Trajkovic & Kolakovic, 2009).…”

Section: Introductionunclassified

Estimativa da evapotranspiração de referência a partir de dados meteorológicos limitados

Carvalho

Rocha

Bonomo

et al. 2015

Pesq. agropec. bras.

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Resumo -O objetivo deste trabalho foi avaliar a estimativa da evapotranspiração de referência (ETo), para a região Sudeste do Brasil, a partir de dados meteorológicos limitados. O método de Penman-Monteith FAO 56 (PM p ) foi tomado como referência. Três cenários com dados meteorológicos limitados, obtidos de rede de estações automáticas, foram utilizados para estimação da ETo: método padrão (PM p ) com uso da radiação solar estimada pelo balanço entre ondas curtas e longas (PM Krs ); método padrão com uso da pressão de vapor estimada pelas temperaturas máxima e mínima, e pela umidade relativa do ar (PM ea ); e método padrão com uso da velocidade de vento constante (2 m s -1 ; PM u2 ). A ETo também foi estimada pelos métodos de Hargreaves-Samani (HS) e de Turc. Os modelos foram analisados por meio de indicadores estatísticos de desvio absoluto médio (MBE), erro relativo (ER), raiz quadrada do erro quadrático médio (RMSE) e índice de Willmott (d). O método PM ea é a melhor alternativa para estimar a ETo, seguido pelos métodos PM u2 , para Espírito Santo e Rio de Janeiro, e PM Krs , para São Paulo e Minas Gerais. Os maiores erros são obtidos com o método de Hargreaves-Samani, que superestimou a ETo em comparação ao PM p , para a maioria das estações avaliadas.Termos para indexação: Hargreaves-Samani, mínimo de dados, Penman-Monteith, radiação solar, Turc, velocidade do vento. Estimating reference evapotranspiration with limited meteorological dataAbstract -The objective of this work was to evaluate the estimate of reference evapotranspiration (ETo) for the Southeast Region of Brazil using limited meteorological data. The FAO 56 Penman-Monteith method (PM p ) was used as reference. Three scenarios of limited meteorological data, obtained from automatic network stations, were used for estimating ETo: standard method (PM p ), with solar radiation estimated from the balance between short and wide wavelengths (PM Krs ); standard method using vapor pressure estimated from minimum and maximum temperatures, and from air relative humidity (PM ea ); and standard method using constant wind speed (2 m s -1 ; PM u2 ). ETo was also estimated by the Hargreaves-Samani (HS) and Turc methods. The models were analyzed by statistical indicators of mean absolute deviation (MBE), relative error (RE), root mean square error (RMSE), and Willmott index (d). The PM ea method is the best alternative to estimate ETo, followed by PM u2 , for the states of Espírito Santo and Rio de Janeiro, and PM Krs , for the states of São Paulo and Minas Gerais. The largest errors are obtained with the Hargreaves-Samani method, which overestimated ETo compared with PM p , for most of the evaluated stations.

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“…Note that equations requiring minimum and maximum temperature (Droogers and Allen, 2002;Hargreaves, 1983;Heydari and Heydari, 2014) were not considered here as they are not always available outside the observation period (e.g. from forecasts).…”

Section: Temperature-based Equationsmentioning

confidence: 99%

Historical gridded reconstruction of potential evapotranspiration for the UK

Tanguy¹,

Prudhomme²,

Smith³

et al. 2018

Preprint

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Abstract. Potential Evapotranspiration (PET) is a necessary input data for most hydrological models and is usually needed at a daily or shorter time-step. An accurate estimation of PET requires many input climate variables which are in most cases not 10 available prior to the 1960s for the UK, nor indeed most parts of the world. Therefore, when applying hydrological models for reconstructing earlier periods, modellers have to rely on PET estimation derived from simplified methods. Given that only monthly observed temperature data is readily available for the late 19th and early 20th century at a national scale for the UK, the objective of this work was to derive the best possible UK-wide gridded PET dataset with the limited data available.To that end, firstly, a combination of (i) seven temperature-based PET equations, (ii) four different calibration approaches and 15 (iii) seven input temperature data were evaluated against a gridded daily PET product based on the physically-based PenmanMonteith equation (the CHESS PET dataset), the rationale being that this provides a reliable 'ground-truth' PET dataset for evaluation purposes, given that no directly observed, distributed PET datasets exist. The performance of the models was also compared to the simplest possible estimation of PET ('naïve method') in the absence of any available climate data, the CHESS PET daily long term average (the period from 1961 to 1990 was chosen for this study), or CHESS-PET daily climatology. The 20 analysis revealed that the type of calibration and the input temperature dataset had only a minor effect in the accuracy of the PET estimations at catchment scale. From the seven equations tested, only the calibrated version of the McGuinness-Bordne equation was able to outperform the 'naïve method' and was therefore used to derive the gridded, reconstructed dataset. The equation was calibrated using 43 catchments across Great Britain.The dataset produced is a 5-km gridded PET dataset for the period 1891 to 2015, using as input data for the PET equation the 25 Met Office 5-km monthly gridded temperature data available for that time period, which was disaggregated to daily temperature using pchip (piecewise cubic hermite interpolating polynomial) method. The dataset includes daily and monthly PET grids and is complemented with a suite of mapped performance metrics to help users assess the quality of the data spatially.The data can be accessed here: https://doi.org/10.5285/17b9c4f7-1c30-4b6f-b2fe-f7780159939c.Earth Syst. Sci. Data Discuss., https://doi

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Untitled

Cited by 766 publications

References 7 publications

Optimizing hotspot areas for ecological planning and management based on biodiversity and ecosystem services

Optimizing hotspot areas for ecological planning and management based on biodiversity and ecosystem services

Estimativa da evapotranspiração de referência a partir de dados meteorológicos limitados

Historical gridded reconstruction of potential evapotranspiration for the UK

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