The use of remotely sensed rainfall for managing drought risk: a case study of weather index insurance in Zambia

Remotely sensed rainfall is increasingly being used to manage climate-related risk in gauge sparse regions. Applications based on such data must make maximal use of the skill of the methodology in order to avoid doing harm by providing misleading information. This is especially challenging in regions, such as Africa, which lack gauge data for validation. In this study, we show how calibrated ensembles of equally likely rainfall can be used to infer uncertainty in remotely sensed rainfall estimates, and subsequently in assessment of drought. We illustrate the methodology through a case study of weather index insurance (WII) in Zambia. Unlike traditional insurance, which compensates proven agricultural losses, WII pays out in the event that a weather index is breached. As remotely sensed rainfall is used to extend WII schemes to large numbers of farmers, it is crucial to ensure that the indices being insured are skillful representations of local environmental conditions. In our study we drive a land surface model with rainfall ensembles, in order to demonstrate how aggregation of rainfall estimates in space and time results in a clearer link with soil moisture, and hence a truer representation of agricultural drought. Although our study focuses on agricultural insurance, the methodological principles for application design are widely applicable in Africa and elsewhere.

Exploiting satellite-based rainfall for weather index insurance: the challenges of spatial and temporal aggregation

Lack of access to insurance exacerbates the impact of climate variability on smallholder famers in Africa. Unlike traditional insurance, which compensates proven agricultural losses, weather index insurance (WII) pays out in the event that a weather index is breached. In principle, WII could be provided to farmers throughout Africa. There are two data-related hurdles to this. First, most farmers do not live close enough to a rain gauge with sufficiently long record of observations. Second, mismatches between weather indices and yield may expose farmers to uncompensated losses, and insurers to unfair payouts – a phenomenon known as basis risk. In essence, basis risk results from complexities in the progression from meteorological drought (rainfall deficit) to agricultural drought (low soil moisture). In this study, we use a land-surface model to describe the transition from meteorological to agricultural drought. We demonstrate that spatial and temporal aggregation of rainfall results in a clearer link with soil moisture, and hence a reduction in basis risk. We then use an advanced statistical method to show how optimal aggregation of satellite-based rainfall estimates can reduce basis risk, enabling remotely sensed data to be utilized robustly for WII.

Contributions of labile and resistant organic materials to the immobilization of inorganic soil N when used in the restoration of abandoned agricultural fields

We have examined the contributions sucrose and sawdust make to the net immobilization of inorganic soil N and assimilation of both C and N into microbial biomass when they are used as part of a restoration plan to promote the establishment of indigenous vegetation on abandoned agricultural fields on the Central Hungarian Plain. Both amendments led to net N immobilization. Sucrose addition also led to mobilization of N from the soil organic N pool and its immobilization into microbial biomass, whereas sawdust addition apparently immobilized soil N into a non-biomass compartment or a biomass component that was not detected by the conventional biomass N assay (CHCl3 fumigation and extraction). This suggests that the N was either cycled through the biomass, but not immobilized within it, or that it was immobilized in a protected biomass fraction different to the fraction into which N was immobilized in response to sucrose addition.

Microbial and biochemical soil quality indicators and their potential for differentiating areas under contrasting agricultural management regimes

The aim of this study was to examine interrelationships between functional biochemical and microbial indicators of soil quality, and their suitability to differentiate areas under contrasting agricultural management regimes. The study included five 0.8 ha areas on a sandy-loam soil which had received contrasting fertility and cropping regimes over a 5 year period. These were organically managed vegetable, vegetable -cereal and arable rotations, an organically managed grass clover ley, and a conventional cereal rotation. The organic areas had been converted from conventional cereal production 5 years prior to the start of the study. All of the biochemical analyses, including light fraction organic matter (LFOM) C and N, labile organic N (LON), dissolved organic N and water-soluble carbohydrates showed significant differences between the areas, although the nature of the relationships between the areas varied between the different parameters, and were not related to differences in total soil organic matter content. The clearest differences were seen in LFOM C and N and LON, which were higher in the organic arable area relative to the other areas. In the case of the biological parameters, there were differences between the areas for biomass-N, ATP, chitin content, and the ratios of ATP: biomass and basal respiration: biomass. For these parameters, the precise relationships between the areas varied. However, relative to the conventionally managed area, areas under organic management generally had lower biomass-N and higher ATP contents. Arbuscular mycorrhizal fungus colonization potential was extremely low in the conventional area relative to the organic areas. Further, metabolic diversity and microbial community level physiological profiles, determined by analysis of microbial community metabolism using Biolog GN plates and the activities of eight key nutrient cycling enzymes, grouped the organic areas together, but separated them from the conventional area. We conclude that microbial parameters are more effective and consistent indicators of management induced changes to soil quality than biochemical parameters, and that a variety of biochemical and microbial analyses should be used when considering the impact of management on soil quality. (C) 2004 Elsevier Ltd. All rights reserved.

Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data

Site-specific management requires accurate knowledge of the spatial variation in a range of soil properties within fields. This involves considerable sampling effort, which is costly. Ancillary data, such as crop yield, elevation and apparent electrical conductivity (ECa) of the soil, can provide insight into the spatial variation of some soil properties. A multivariate classification with spatial constraint imposed by the variogram was used to classify data from two arable crop fields. The yield data comprised 5 years of crop yield, and the ancillary data 3 years of yield data, elevation and ECa. Information on soil chemical and physical properties was provided by intensive surveys of the soil. Multivariate variograms computed from these data were used to constrain sites spatially within classes to increase their contiguity. The constrained classifications resulted in coherent classes, and those based on the ancillary data were similar to those from the soil properties. The ancillary data seemed to identify areas in the field where the soil is reasonably homogeneous. The results of targeted sampling showed that these classes could be used as a basis for management and to guide future sampling of the soil.

The Phosphorus Indicators Tool: a simple model of diffuse P loss from agricultural land to water

The Phosphorus Indicators Tool provides a catchment-scale estimation of diffuse phosphorus (P) loss from agricultural land to surface waters using the most appropriate indicators of P loss. The Tool provides a framework that may be applied across the UK to estimate P loss, which is sensitive not only to land use and management but also to environmental factors such as climate, soil type and topography. The model complexity incorporated in the P Indicators Tool has been adapted to the level of detail in the available data and the need to reflect the impact of changes in agriculture. Currently, the Tool runs on an annual timestep and at a 1 km(2) grid scale. We demonstrate that the P Indicators Tool works in principle and that its modular structure provides a means of accounting for P loss from one layer to the next, and ultimately to receiving waters. Trial runs of the Tool suggest that modelled P delivery to water approximates measured water quality records. The transparency of the structure of the P Indicators Tool means that identification of poorly performing coefficients is possible, and further refinements of the Tool can be made to ensure it is better calibrated and subsequently validated against empirical data, as it becomes available.

Towards a nutrient export risk matrix approach to managing agricultural pollution at source

A generic Nutrient Export Risk Matrix (NERM) approach is presented. This provides advice to farmers and policy makers on good practice for reducing nutrient loss and is intended to persuade them to implement such measures. Combined with a range of nutrient transport modelling tools and field experiments, NERMs can play an important role in reducing nutrient export from agricultural land. The Phosphorus Export Risk Matrix (PERM) is presented as an example NERM. The PERM integrates hydrological understanding of runoff with a number of agronomic and policy factors into a clear problem-solving framework. This allows farmers and policy makers to visualise strategies for reducing phosphorus loss through proactive land management. The risk Of Pollution is assessed by a series of informed questions relating to farming intensity and practice. This information is combined with the concept of runoff management to point towards simple, practical remedial strategies which do not compromise farmers' ability to obtain sound economic returns from their crop and livestock.

The role of uncomposted materials, composts, manures, and compost extracts in reducing pest and disease incidence and severity in sustainable temperate agricultural and horticultural crop production - A review

This review evaluates evidence of the impact of uncomposted plant residues, composts, manures, and liquid preparations made from composts (compost extracts and teas) on pest and disease incidence and severity in agricultural and horticultural crop production. Most reports on pest control using such organic amendments relate to tropical or and climates. The majority of recent work on the use of organic amendments for prevention and control of diseases relates to container-produced plants, particularly ornamentals. However, there is growing interest in the potential for using composts to prevent and control diseases in temperate agricultural and horticultural field crops and information concerning their use and effectiveness is slowly increasing. The impact of uncomposted plant residues, composts, manures, and compost extracts/teas on pests and diseases is discussed in relation to sustainable temperate field and protected cropping systems. The factors affecting efficacy or such organic amendments in preventing and controlling pests and disease are examined and the mechanisms through which control is achieved are described.

An inventory of heavy metals inputs to agricultural soils in England and Wales

An inventory of heavy metal inputs (Zn, Cu, Ni, Pb, Cd, Cr, As and Hg) to agricultural soils in England and Wales in 2000 is presented, accounting for major sources including atmospheric deposition, sewage sludge, livestock manures, inorganic fertilisers and lime, agrochemicals, irrigation water, industrial by-product 'wastes' and composts. Across the whole agricultural land area, atmospheric deposition was the main source of most metals, ranging from 25 to 85% of total inputs. Livestock manures and sewage sludge were also important sources, responsible for an estimated 37-40 and 8-17% of total Zn and Cu inputs, respectively. However, at the individual field scale sewage sludge, livestock manures and industrial wastes could be the major source of many metals where these materials are applied. This work will assist in developing strategies for reducing heavy metal inputs to agricultural land and effectively targeting policies to protect soils from long-term heavy metal accumulation. (C) 2003 Elsevier Science B.V. All rights reserved.

Wetland restoration within agricultural watersheds: Balancing water quality protection with habitat conservation

Peat wetlands that have been restored from agricultural Land have the potential to act as Long term sources of phosphorus (P) and, therefore have to potenital to accelerate freshwater eutrophication. During a two-year study the water table in a eutrophic fen peat that was managed by pump drainage fluctuated annually between +20 cm and -60 cm relative to ground Level. This precise management was facilitated by the high hydraulic conductivity (K) of the humified peat (1.1 x 10(-5) m s(-1)) below around 60 cm depth. However, during one week of intermittent pumping, as much as 50 g ha(-1) dissolved P entered the pumped ditch. Summer. rainfall events and autumn reflooding also triggered P losses. The P Losses were attributed to the low P sorption capacity (217 mg kg(-1)) of the saturated peat below 60 cm, combined with its high K and the reductive dissolution of Fe bound P.

Degradation and plant uptake of nonylphenol (NP) and nonylphenol-12-ethoxylate (NP12EO) in four contrasting agricultural soils

Nonylphenol polyethoxylates (NPEOs) are surfactants found ubiquitously in the environment due to widespread industrial and domestic use. Biodegradation of NPEOs produces nonylphenol (NP), an endocrine disruptor. Sewage sludge application introduces NPEOs and NP into soils, potentially leading to accumulation in soils and crops. We examined degradation of NP and nonyl phenol-12-ethoxylate (NP12EO) in four soils. NP12EO degraded rapidly (initial half time 0.3-5 days). Concentrations became undetectable within 70-90 days, with a small increase in NP concentrations after 30 days. NP initially degraded quickly (mean half time 11.5 days), but in three soils a recalcitrant fraction of 26-35% remained: the non-degrading fraction may consist of branched isomers, resistant to biodegradation. Uptake of NP by bean plants was also examined. Mean bioconcentration factors for shoots and seeds were 0.71 and 0.58, respectively. Removal of NP from the soil by plant uptake was negligible (0.01-0.02% of initial NP). Root concentrations were substantially higher than shoot and seed concentrations. (C) 2008 Elsevier Ltd. All rights reserved.

Evaluation of two hybrid metric-conceptual models, for simulating phosphorus transfer from agricultural land in the river enborne, a lowland UK catchment

Across Europe, elevated phosphorus (P) concentrations in lowland rivers have made them particularly susceptible to eutrophication. This is compounded in southern and central UK by increasing pressures on water resources, which may be further enhanced by the potential effects of climate change. The EU Water Framework Directive requires an integrated approach to water resources management at the catchment scale and highlights the need for modelling tools that can distinguish relative contributions from multiple nutrient sources and are consistent with the information content of the available data. Two such models are introduced and evaluated within a stochastic framework using daily flow and total phosphorus concentrations recorded in a clay catchment typical of many areas of the lowland UK. Both models disaggregate empirical annual load estimates, derived from land use data, as a function of surface/near surface runoff, generated using a simple conceptual rainfall-runoff model. Estimates of the daily load from agricultural land, together with those from baseflow and point sources, feed into an in-stream routing algorithm. The first model assumes constant concentrations in runoff via surface/near surface pathways and incorporates an additional P store in the river-bed sediments, depleted above a critical discharge, to explicitly simulate resuspension. The second model, which is simpler, simulates P concentrations as a function of surface/near surface runoff, thus emphasising the influence of non-point source loads during flow peaks and mixing of baseflow and point sources during low flows. The temporal consistency of parameter estimates and thus the suitability of each approach is assessed dynamically following a new approach based on Monte-Carlo analysis. (c) 2004 Elsevier B.V. All rights reserved.