Estimating LAI and mapping canopy storage capacity for hydrological applications in wattle infested ecosystems using Sentinel-2 MSI derived red edge bands

This study assessed the strength of Sentinel-2 multispectral instrument (MSI) derived Red Edge (RE) bands in estimating Leaf Area Index (LAI) and mapping canopy storage capacity (CSC) for hydrological applications in wattle infested ecosystems. To accomplish this objective, this study compared the estimation strength of models derived, using standard bands (all bands excluding the RE band) with those including RE bands, as well as different vegetation indices. Sparse Partial Least Squares (SPLSR) and Partial Least Squares Regression (PLSR) ensembles were used in this study. Results showed that the RE spectrum covered by the Sentinel-2 MSI satellite reduced the estimation error by a magnitude of 0.125 based on simple ratio (RE SR) vegetation indices from 0.157 m²· m^?2 based on standard bands, and by 0.078 m²· m^?2 based on red edge normalised difference vegetation (NDVI-RE). The optimal models for estimating LAI to map CSC were obtained based on the RE bands centered at 705 nm (Band 5), 740 nm (Band 6), 783 nm (Band 7) as well as 865 nm (Band 8a). A root mean square error of prediction (RMSEP) of 0.507 m²· m^?2 a relative root mean square error of prediction (RRMSEP) of 11.3% and R² of 0.91 for LAI and a RMSEP of 0.246 m²/m² (RRMSEP = 7.9%) and R² of 0.91 for CSC were obtained. Overall, the findings of this study underscore the relevance of the new copernicus satellite product in rapid monitoring of ecosystems that are invaded by alien invasive species.     

The CLIVAR C20C project: skill of simulating Indian monsoon rainfall on interannual to decadal timescales. Does GHG forcing play a role?

The ability of atmospheric general circulation models (AGCMs), that are forced with observed sea surface temperatures (SSTs), to simulate the Indian monsoon rainfall (IMR) variability on interannual to decadal timescales is analyzed in a multimodel intercomparison. The multimodel ensemble has been performed within the CLIVAR International “Climate of the 20th Century” (C20C) Project. This paper is part of a C20C intercomparison of key climate time series. Whereas on the interannual timescale there is modest skill in reproducing the observed IMR variability, on decadal timescale the skill is much larger. It is shown that the decadal IMR variability is largely forced, most likely by tropical sea surface temperatures (SSTs), but as well by extratropical and especially Atlantic Multidecadal Oscillation (AMO) related SSTs. In particular there has been a decrease from the late 1950s to the 1990s that corresponds to a general warming of tropical SSTs. Using a selection of control integrations from the World Climate Research Programme’s (WCRP’s) Coupled Model Intercomparison Project phase 3 (CMIP3), it is shown that the increase of greenhouse gases (GHG) in the twentieth century has not significantly contributed to the observed decadal IMR variability.     

SRES情景下多模式集合对淮河流域未来气候变化的预估

采用偏差修正/空间降尺度方法处理后的IPCC AR4中8个全球海气耦合模式的集合平均结果,分析了SRESA2、A1B和B1情景下淮河流域未来30 a(2011 2040年)相对于现状(1961 1990年)地面温度和降水的可能变化.结果表明:(1)多模式集合能较好地反映流域现状年、季温度和降水的大尺度空间分布特征;对温度和降水的年内分配过程模拟较好,各月温度集合平均与观测值相差0.2℃左右(冬季各月除外),而降水集合平均与观测值相对误差在5%左右(9月除外).(2)不同情景下未来流域年、季温度一致增加,年温度增加幅度在0.85～1.12℃之间;冬、春季温度增加相对明显,而夏、秋季温度增加并不显著;年际和年代际温度增加趋势显著.(3)不同情景下未来流域年降水有增加趋势,增加幅度为0.13%～5.24%,增幅不明显;降水季节变化有增有减,季节、年际和年代际降水变化较为复杂,不同情景下降水空间变化差异显著.     

Investigating the application of climate models in flood projection across the UK

Regional climate models (RCMs) have emerged as the preferred tool in hydrological impact assessment at the catchment scale. The direct application of RCM precipitation output is still not recommended; instead, a number of alternative methods have been proposed. One method that has been used is the change factor methodology, which typically uses changes to monthly mean or seasonal precipitation totals to develop change scenarios. However, such simplistic approaches are subject to significant caveats. In this paper, 18 RCMs covering the UK from the ENSEMBLES and UKCP09 projects are analysed across different catchments. The ensembles' ability in capturing monthly total and extreme precipitation is outlined to explore how the ability to make confident statements about future flood risk varies between different catchments. The suitability of applying simplistic change factor approaches in flood impact studies is also explored. We found that RCM ensembles do have some skill in simulating observed monthly precipitation; however, seasonal patterns of bias were evident across each of the catchments. Moreover, even apparently good simulations of extreme rainfall can mis‐estimate the magnitude of flood‐generating rainfall events in ways that would significantly affect flood risk management. For future changes in monthly mean precipitation, we observe the clear ‘drier summers/wetter winters’ signal used to develop current UK policy, but when we look instead at flood‐generating rainfall, this seasonal signal is less clear and greater increases are projected. Furthermore, the confidence associated with future projections varies from catchment to catchment and season to season as a result of the varying ability of the RCM ensembles, and in some cases, future flood risk projections using RCM outputs may be highly problematic. Copyright © 2013 John Wiley & Sons, Ltd.     

Improved regional scale processes reflected in projected hydrological changes over large European catchments

For the fourth assessment report of the Intergovernmental Panel on Climate Change (IPCC), the recent version of the coupled atmosphere/ocean general circulation model (GCM) of the Max Planck Institute for Meteorology has been used to conduct an ensemble of transient climate simulations These simulations comprise three control simulations for the past century covering the period 1860–2000, and nine simulations for the future climate (2001–2100) using greenhouse gas (GHG) and aerosol concentrations according to the three IPCC scenarios B1, A1B and A2. For each scenario three simulations were performed. The global simulations were dynamically downscaled over Europe using the regional climate model (RCM) REMO at 0.44° horizontal resolution (about 50 km), whereas the physics packages of the GCM and RCM largely agree. The regional simulations comprise the three control simulations (1950–2000), the three A1B simulations and one simulation for B1 as well as for A2 (2001–2100). In our study we concentrate on the climate change signals in the hydrological cycle and the 2 m temperature by comparing the mean projected climate at the end of the twenty-first century (2071–2100) to a control period representing current climate (1961–1990). The robustness of the climate change signal projected by the GCM and RCM is analysed focussing on the large European catchments of Baltic Sea (land only), Danube and Rhine. In this respect, a robust climate change signal designates a projected change that sticks out of the noise of natural climate variability. Catchments and seasons are identified where the climate change signal in the components of the hydrological cycle is robust, and where this signal has a larger uncertainty. Notable differences in the robustness of the climate change signals between the GCM and RCM simulations are related to a stronger warming projected by the GCM in the winter over the Baltic Sea catchment and in the summer over the Danube and Rhine catchments. Our results indicate that the main explanation for these differences is that the finer resolution of the RCM leads to a better representation of local scale processes at the surface that feed back to the atmosphere, i.e. an improved representation of the land sea contrast and related moisture transport processes over the Baltic Sea catchment, and an improved representation of soil moisture feedbacks to the atmosphere over the Danube and Rhine catchments.     

Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa

Abstract

The increasing demand for water in southern Africa necessitates adequate quantification of current freshwater resources. Watershed models are the standard tool used to generate continuous estimates of streamflow and other hydrological variables. However, the accuracy of the results is often not quantified, and model assessment is hindered by a scarcity of historical observations. Quantifying the uncertainty in hydrological estimates would increase the value and credibility of predictions. A model-independent framework aimed at achieving consistency in incorporating and analysing uncertainty within water resources estimation tools in gauged and ungauged basins is presented. Uncertainty estimation in ungauged basins is achieved via two strategies: a local approach for a priori model parameter estimation from physical catchment characteristics, and a regional approach to regionalize signatures of catchment behaviour that can be used to constrain model outputs. We compare these two sources of information in the data-scarce region of South Africa. The results show that both approaches are capable of uncertainty reduction, but that their relative values vary.

Editor D. Koutsoyiannis

Citation Kapangaziwiri, E., Hughes, D.A., and Wagener, T., 2012. Incorporating uncertainty in hydrological predictions for gauged and ungauged basins in southern Africa. Hydrological Sciences Journal, 57 (5), 1000–1019.