Quantifying the impacts of land-cover changes on global evapotranspiration based on the continuous remote sensing observations during 1982–2016

Cheng

Hydrol. Earth Syst. Sci.

et al. 2022

Self Cite

Abstract. Multiyear drought has been demonstrated to cause non-stationary rainfall–runoff relationship. But whether this change can occur in catchments that have also experienced vegetation change and whether it invalidates the most widely used methods for estimating impacts of vegetation change – i.e., the paired-catchment method (PCM), the time–trend method (TTM), and the sensitivity-based method (SBM) – on runoff is still unknown and rarely discussed. Estimated inconsistent afforestation impacts were 32.8 %, 93.5 %, and 76.1 % of total runoff changes in the Red Hill paired experimental catchments in Australia during the period of 1990–2015 by the PCM, TTM, and SBM, respectively. In addition to afforestation, the Red Hill paired experimental catchments have experienced a 10-year drought (2000–2009) and have been demonstrated to lead to non-stationary rainfall–runoff relationships of paired catchments. Estimated impacts of vegetation change by the PCM (32.8 %) is still reliable and is not invalided by multiyear drought-induced non-stationarity, because the PCM can eliminate all impacts by different factors on paired catchments (multiyear drought and climate variability), except the purposed treatment (afforestation). For the TTM and SBM, traditional application did not further differentiate different drivers of non-stationary rainfall–runoff relationship (i.e., multiyear drought and vegetation change), which led to significant overestimation of afforestation effects. A new framework was further proposed to separate the effects of three factors on runoff changes, including vegetation change, climate variability, and hydroclimatic non-stationarity (i.e., multiyear drought). Based on the new framework, impacts of multiyear drought and climate variability on runoff of the control catchment (Kileys Run) were 87.2 % and 12.8 %, respectively. Impacts of afforestation, multiyear drought, and climate variability on runoff of the treated catchment (Red Hill) were 32.8 %, 54.7 %, and 23.9 %, respectively. Impacts of afforestation on runoff were 38.8 % by the TTM and 21.4 % by the SBM, agreeing well with that by the PCM (32.8 %). This study not only demonstrated that multiyear drought can induce non-stationary rainfall–runoff relationship using field observations, but also proposed a new framework to better separate the impact of vegetation change on runoff under climate-induced non-stationary condition. More importantly, it is shown that non-stationarity induced by multiyear drought does not invalidate the PCM, and PCM is still the most reliable method even though the control catchment experienced climate-induced shift in the rainfall–runoff relationship.

Section: Differences In Estimated Impacts Of Vegetation Change On Run...mentioning

confidence: 99%

Does non-stationarity induced by multiyear drought invalidate the paired-catchment method?

Cheng

Hydrol. Earth Syst. Sci.

et al. 2022

Self Cite

“…This is misleading as the model predictions have not demonstrated the needed skill. Even on the global scale, skill in predicting changes in the global averages shows limited skill [34,35]. The large-scale outcomes are also sensitive to issues raised with respect to the forcings from emissions [36][37][38].…”

Section: Terminologymentioning

confidence: 99%

Environmental and Social Risks to Biodiversity and Ecosystem Health—A Bottom-Up, Resource-Focused Assessment Framework

Pielke

Adegoke

Hossain

et al. 2021

Earth

Risks from human intervention in the climate system are raising concerns with respect to individual species and ecosystem health and resiliency. A dominant approach uses global climate models to predict changes in climate in the coming decades and then to downscale this information to assess impacts to plant communities, animal habitats, agricultural and urban ecosystems, and other parts of the Earth’s life system. To achieve robust assessments of the threats to these systems in this top-down, outcome vulnerability approach, however, requires skillful prediction, and representation of changes in regional and local climate processes, which has not yet been satisfactorily achieved. Moreover, threats to biodiversity and ecosystem function, such as from invasive species, are in general, not adequately included in the assessments. We discuss a complementary assessment framework that builds on a bottom-up vulnerability concept that requires the determination of the major human and natural forcings on the environment including extreme events, and the interactions between these forcings. After these forcings and interactions are identified, then the relative risks of each issue can be compared with other risks or forcings in order to adopt optimal mitigation/adaptation strategies. This framework is a more inclusive way of assessing risks, including climate variability and longer-term natural and anthropogenic-driven change, than the outcome vulnerability approach which is mainly based on multi-decadal global and regional climate model predictions. We therefore conclude that the top-down approach alone is outmoded as it is inadequate for robustly assessing risks to biodiversity and ecosystem function. In contrast the bottom-up, integrative approach is feasible and much more in line with the needs of the assessment and conservation community. A key message of our paper is to emphasize the need to consider coupled feedbacks since the Earth is a dynamically interactive system. This should be done not just in the model structure, but also in its application and subsequent analyses. We recognize that the community is moving toward that goal and we urge an accelerated pace.

“…It is well known from the level of application value that changes in vegetation cover and land use in ecosystems strongly influence hydrothermal equilibrium, and exert a notable force on the evolution of PET. Consequently, it primarily Water 2022, 14, 814 2 of 19 affects the productivity of natural resources [3][4][5]. Significances and challenges still exist in dissecting and quantifying internal correlations between PET and vegetation cover/land use in mid-high latitudes, which are highly influenced by featured climatological type.…”

Section: Introductionmentioning

confidence: 99%

“…The most representative items that were adopted to establish spatiotemporal characteristics and laws of PET included Global Land-surface Evaporation: the Amsterdam Methodology (GLEAM), Moderate Resolution Imaging Spectroradiometer (MODIS) Global Evapotranspiration Project (MOD16), and Operational Simplified Surface Energy Balance/evapotranspiration (SSEBop/ET). These collections are widely used as they improve the capability of data acquisition and analysis of regional environmental monitoring [5]. Taking the application of MOD16 as an example, the corresponding processes during the formal stage focus on depicting the temporal-spatial characters and adopting the attribution analysis of other factors [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Dissecting the Mutual Response of Potential Evapotranspiration with Vegetation Cover/Land Use over Heilongjiang River Basin, China

Zhou

Wang

Grigorieva

et al. 2022

Water

Spatiotemporal changes in potential evapotranspiration (PET) are important referential data for monitoring the variation in ecohydrology under climate change. As the key area of agricultural/forestry reserves and trade, research on the interactions between vegetation cover and land use with accurate PET among the Heilongjiang River basin, China is vital for the sustainability of this cross-border region. To obtain high-suitability PET estimation based on the proven Penman–Monteith (PM) principle, two schemes were adopted using 36-year in situ meteorological data (1984–2019) and derived remote-sensing product MOD16A2 from 2001 to 2019. At meteorological sites with heterogeneous underlying surfaces, the coefficients of the evaluation factors between MOD_PET and the referrable observations were better. This suggests that remotely sensed estimation was preferentially chosen as the input to study the mutual responses. The results indicated that the annual PET and fractional vegetation cover (FVC) changes differed significantly depending on the land use. The proportions of PET according to equal intervals initially increased and then decreased with increasing vegetation coverage, and changing trends indicated a negative correlation. The strongest correlations appeared in the middle to northern sub-basins, which were affected by their distinctive climatic characteristics. The response of PET was reverse-related with changes in the area of each selected land type, but could change with the expected climatic conditions.