Incentives for field hydrology and data sharing: collaboration and compensation: reply to “A need for incentivizing field hydrology,especially in an era of open data”*

ABSTRACT

We thank Allen and Berghuijs for continuing the discussion on field hydrology and data sharing and discuss two incentives to promote data collection and sharing in hydrological sciences: a collaborative attitude and additional funding to make data publicly available.     

Impact of Climate Change on Agricultural Production in the Sahel – Part 1. Methodological Approach and Case Study for Millet in Niger

In the last 30 years the climate of the West African Sahel has shown various changes, especially in terms of rainfall, of which inter-annual variabilityis very high. This has significant consequences for the poor-resource farmers, whose incomes depend mainly on rainfed agriculture. The West African Sahel is already known as an area characterized by important interaction between climate variability and key socio-economic sectors such as agriculture and water resources. More than 80% of the 55 million population of West African Sahel is rural, involved in agriculture and stock-farming, the two sectors contributing almost 35% of the countries' GDPs. It is thereforeobvious that climate change seriously affects the economies of these countries. Adding to this situation the high rate of population increase(3%), leading to progressive pressure upon ecosystems, and poorsanitary facilities, one comes to the conclusion that Sahelian countries, Niger amongst them, will be highly vulnerable to climate change.This paper investigates the impact of current climate variability and future climate change on millet production for three major millet-producing regions in Niger. Statistical models have been used to predict the effects of climate change on future production on the basis of thirteen available predictors. Based on the analysis of the past 30-years of rainfall and production data, the most significant predictors of the model are (i) seasurface temperature anomalies, (ii) the amount of rainfall in July, August and September, (iii) the number of rainy days and (iv) the wind erosion factor. In 2025, production of millet is estimated to be about 13% lower as a consequence of climate change, translated into a reduction of the total amount of rainfall for July, August and September, combined with an increase in temperature while maintaining other significant predictors at a constant level. Subsequently,various potential strategies to compensate this loss are evaluated, including those to increase water use efficiency and to cultivate varieties that are adapted to such circumstances.     

ASCA Observation of the Quiescent X-Ray Counterpart to SGR 1627-41

We present a 2-10 keV ASCA observation of the field around the soft gamma repeater SGR 1627-41. A quiescent X-ray source, whose position is consistent both with that of a recently discovered BeppoSAX X-ray source and with the Interplanetary Network localization for this soft gamma repeater, was detected in this observation. In 2-10 keV X-rays, the spectrum of the X-ray source may be fit equally well by a power-law, blackbody, or bremsstrahlung function, with unabsorbed flux approximately 5x10-12 ergs cm-2 s-1. We do not confirm a continuation of a fading trend in the flux, and we find no evidence for periodicity, both of which were noted in the earlier BeppoSAX observations.     

Spatial distribution and bonding forms of heavy metals in sediments along the middle course of the River Elbe (km 287ċ390)

Sediments of eight groyne fields along the middle course of the River Elbe (river km 287?390) were geochemically studied. The 78 sediment samples were analysed for pH and grain size distribution. The grain size fraction < 2 μm was used for mineralogical and chemical analysis: semiquantitative clay mineral analysis; total element content (Al, Ca, Fe, K, Mn, Cd, Cr, Cu, Ni, Pb, Zn), total inorganic and organic C, and bonding form fractionation with a six‐step sequential chemical extraction. The latter was performed on selected samples (n = 32). The sediments along the Elbe's course are still contaminated with heavy metals far above the local geogenic background level. An enrichment factor of more than 15 was calculated for zinc. Cr and Ni are the elements with the lowest enrichment. The bonding form analysis of selected heavy metals shows a dominance of relatively immobile bonding forms, e. g. the moderately reducible and the residual fraction, which implies a relative low mobility potential. Only Zn poses a higher potential threat to the environment, since it has a higher percentage of the first three extracted phases: adsorbed, carbonate, and easily reducible fraction.     

Ground viscosity and stiffness measurements for near surface seismic velocity

In land surveys, the weathering layer can often distort the seismic signal due to it passing through rapid velocity and density changes, dispersion, scattering and inelastic absorption. In a simple spring‐dashpot model for the earth response, an equivalent medium groups these complex phenomena into two parameters only; these are called ground viscosity and ground stiffness. The most recent controllers for vibrators can estimate both parameters. To validate these measurements, Saudi Aramco conducted an experiment measuring ground viscosity and stiffness from two different vibrator control systems over an area of varying terrain conditions, including unconsolidated sand and limestone outcrop. The two systems measured different values, but detected similar trends that correlated well with weathering conditions and surface geology, e.g. lower viscosity values on the outcrop than on the sand. The ratio of ground viscosity to ground stiffness can approximate the shallow S‐wave velocity, which we converted into P‐wave velocity through calibration with sparse uphole data. Static corrections incorporating this velocity information somewhat improved the focusing of seismic time sections. This new approach does not require additional acquisition efforts, and can model shallow complex formations in arid areas where classical static methods often fail.     

Restoration of submerged vegetation in shallow eutrophic lakes – A guideline and state of the art in Germany

One of the most serious problems caused by eutrophication of shallow lakes is the disappearance of submerged macrophytes and the switch to a turbid, phytoplankton-dominated state. The reduction of external nutrient loads often does not result in a change back to the macrophyte-dominated state because stabilising mechanisms that cause resilience may delay a response. Additional internal lake restoration measures may therefore be needed to decrease the concentration of total phosphorus and increase water clarity. The re-establishment of submerged macrophytes required for a long-term stability of clear water conditions, however, may still fail, or mass developments of tall-growing species may cause nuisance for recreational use. Both cases are often not taken into account when restoration measures are planned in Germany, and existing schemes to reduce eutrophication consider the topic inadequately. Here we develop a step-by-step guideline to assess the chances of submerged macrophyte re-establishment in shallow lakes. We reviewed and rated the existing literature and case studies with special regard on (1) the impact of different internal lake restoration methods on the development of submerged macrophytes, (2) methods for the assessment of natural re-establishment, (3) requirements and methods for artificial support of submerged macrophyte development and (4) management options of macrophyte species diversity and abundance in Germany. This guideline is intended to help lake managers aiming to restore shallow lakes in Germany to critically asses and predict the potential development of submerged vegetation, taking into account the complex factors and interrelations that determine their occurrence, abundance and diversity.     

Remotely sensed estimation of forest canopy density: A comparison of the performance of four methods

In recent years, a number of alternative methods have been proposed to predict forest canopy density from remotely sensed data. To date, however, it remains difficult to decide which method to use, since their relative performance has never been evaluated. In this study the performance of: (1) an artificial neural network, (2) a multiple linear regression, (3) the forest canopy density mapper and (4) a maximum likelihood classification method was compared for prediction of forest canopy density using a Landsat ETM+ image. Comparison of confusion matrices revealed that the regression model performed significantly worse than the three other methods. These results were based on a z-test for comparison of weighted kappa statistics, which is an appropriate statistic for analysis of ranked categories. About 89% of the variance of the observed canopy density was explained by the artificial neural networks, which outperformed the other three methods in this respect. Moreover, the artificial neural networks gave an unbiased prediction, while other methods systematically under or over predicted forest canopy density. The choice of biased method could have a high impact on canopy density inventories.     

The ‘Stained Glass Procedure’, a new method to compare classification performance of images acquired with different pixel sizes

Objective comparison of classification performance of earth observation images, acquired at different spatial resolutions (e.g. NOAA-AVHRR, IRS-MOS, IRS-WiFS, Landsat-TM, IRS-LISS), is complicated because both class definition and training site selection are hampered by the inherent scale differences. This paper presents a new, generic method to compare the information content of such a set of images, the “Stained Glass Procedure”. It overcomes the stated problems by computing the scale-dependent, internal spectral variation in an image and by using this as an indicator for land cover information. The Stained Glass Procedure creates segments in the images and calculates the internal spectral variation in a high-spatial-resolution image for each segment. For each image from the set the average variance, weighted to area, is calculated. The Stained Glass Procedure can be used to predict the performance of sensors that are not available, yet, or to roughly determine the optimal spatial resolution for the classification of a specific area.The procedure was applied to images with pixel sizes ranging from 23 to 1100 m. Classification detail of Envisat-MERIS (300 m pixel size), not included in the image set, could be predicted accurately using the Stained Glass Procedure.The Stained Glass Procedure applies one procedure to all images, without any subjective decision during the analysis, thus offering a method to compare images with different pixel sizes in terms of classification detail that is truly objective.     

The Consistency of IPCC's SRES Scenarios to 1990–2000 Trends and Recent Projections

The greenhouse gas emissions scenarios published by the IPCC in the Special Report on Emission Scenarios (SRES) continue to serve as a primary basis for assessing future climate change and possible response strategies. These scenarios were developed between 1996 and 1999 and sufficient time has now passed to make it worth examining their consistency with more recent data and projections. The comparison performed in this paper includes population, GDP, energy use, and emissions of CO₂, non-CO₂ gases and sulfur. We find the SRES scenarios to be largely consistent with historical data for the 1990–2000 period and with recent projections. Exceptions to this general observation include (1) in the long-term, relatively high population growth assumptions; in some regions, particularly in the A2 scenario; (2) in the medium-term, relatively high economic growth assumptions in the LAM (Latin America, Africa and Middle East) region in the A1 scenario; (3) in the short-term, CO₂ emissions projections in A1 that are somewhat higher than the range of current scenarios; and (4) substantially higher sulfur emissions in some scenarios than in historical data and recent projections. In conclusion, given the relatively small inconsistencies for use as global scenarios there seems to be no immediate need for a large-scale IPCC-led update of the SRES scenarios that is solely based on the SRES scenario performance vis-a-vis data for the 1990–2000 period and/or more recent projections. Based on reported findings, individual research teams could make, and in some cases already have made, useful updates of the scenarios.     

Role of land-surface temperature feedback on model performance for the stable boundary layer

At present a variety of boundary-layer schemes is in use in numerical models and often a large variation of model results is found. This is clear from model intercomparisons, such as organized within the GEWEX Atmospheric Boundary Layer Study (GABLS). In this paper we analyze how the specification of the land-surface temperature affects the results of a boundary-layer scheme, in particular for stable conditions. As such we use a well established column model of the boundary layer and we vary relevant parameters in the turbulence scheme for stable conditions. By doing so, we can reproduce the outcome for a variety of boundary-layer models. This is illustrated with the original set-up of the second GABLS intercomparison study using prescribed geostrophic winds and land-surface temperatures as inspired by (but not identical to) observations of CASES-99 for a period of more than two diurnal cycles. The model runs are repeated using a surface temperature that is calculated with a simple land-surface scheme. In the latter case, it is found that the range of model results in stable conditions is reduced for the sensible heat fluxes, and the profiles of potential temperature and wind speed. However, in the latter case the modelled surface temperatures are rather different than with the original set-up, which also impacts on near-surface air temperature and wind speed. As such it appears that the model results in stable conditions are strongly influenced by non-linear feedbacks in which the magnitude of the geostrophic wind speed and the related land-surface temperature play an important role.