Uptake and Accumulation of Arsenic in Different Organs of Carrot Irrigated with As‐Rich Water

Irrigation with arsenic (As)‐rich water in agricultural soil may increase high levels of As in crops and cause food chain contamination. In this study, a greenhouse experiment was established using Spanish agricultural soil (Valladolid and Segovia provinces), that are extensively cultivated for carrot plant, to investigate the process of As uptake, bioaccumulation, and translocation of As from root to shoot and leaves in carrot plant. Arsenic concentrations in different organs of carrot plant, rhizosphere soil, and soil solutions were determined by hydride generation atomic absorption spectrometry (AAS). High concentrations of As in irrigation water, and the alkaline and sandy character of this soil enhanced As uptake in carrot plants indicating the potential health risk from consumption of carrots cultivated in these areas. Bioaccumulation of As into the leaves and roots increased with increase of As concentration in irrigation water. Both roots and leaves demonstrated a higher accumulation rate of As at an As concentration of 41 than 131 µg L^?1 in the soil solution. The ratios of As_root/As_leaves showed no statistically significant differences for the different irrigation treatments, and had an average value of 0.36 indicating the high magnitude of As translocation from roots to leaves in carrot plants. The leaves of carrots had a higher affinity for As than roots did. The correlation between As uptake by leaves or roots of carrots and the soluble As in rhizosphere soil did not demonstrate a linear or a plateau curve, indicating a slow but continuous constant As absorption which could be prolonged over time with high potential environmental risks.     

Modern disturbances to a long-lasting community-based resource management system: The Taos Valley acequias

Long-lasting community-based resource management systems have offered scholars important lessons in the study of human-environment relations. The examination of such systems has suffered from a sampling bias, however, in that it has focused disproportionately on successful systems. There are fewer studies that have explored the deterioration of such systems, particularly with an interdisciplinary approach. This shortfall is problematic given the increasing social and biophysical disturbances that communities are facing as they become more integrated into, and affected by, larger-scale processes.This study addresses this gap by analyzing the modern condition of a long-lasting community-based irrigation system known as the acequias in northern New Mexico. Using a mix of interview, survey, remote sensing, and census data, I examine the extent to which important indicators for the acequias have shifted in the last several decades and explore reasons for these changes. A mix of statistical and qualitative comparative techniques is used to conduct the analysis.By examining longitudinal data we find that the acequias are producing less than they have in the past and have mostly lost their common-property-based livestock pasturing system. While some of these changes can be attributed to similar declines in water availability, much of the change results from social drivers including demographic changes, regional-to-global market forces, and public policies. Overall the shift of the acequias to their current state is a result of their integration into a much larger-scale set of social and economic forces than they have experienced in the past. This shift will be very difficult to reverse, meaning the acequia farmers must adapt to the current condition. It is likely that these themes are common across many community-based resource management systems in many locations. In the future, further progress should be made in synthetically comparing such cases in ways that have already been done for long-lasting successful systems.     

Pathogenic agents in freshwater resources

Numerous pathogenic agents have been found in freshwaters used as sources for water supplies, recreational bathing and irrigation. These agents include bacterial pathogens, enteric viruses, several protozoans and parasitic worms more common to tropical waters. Although infected humans are a major source of pathogens, farm animals (cattle, sheep, pigs), animal pets (dogs, cats) and wildlife serve as significant reservoirs and should not be ignored. The range of infected individuals within a given warm-blooded animal group (humans included) may range from 1 to 25%. Survival times for pathogens in the water environment may range from a few days to as much as a year (Ascaris, Taenia eggs), with infective dose levels varying from one viable cell for several primary pathogenic agents to many thousands of cells for a given opportunistic pathogen. As pathogen detection in water is complex and not readily incorporated into routine monitoring, a surrogate is necessary. In general, indicators of faecal contamination provide a positive correlation with intestinal pathogen occurrences only when appropriate sample volumes are examined by sensitive methodology. Pathways by which pathogens reach susceptible water users include ingestion of contaminated water, body contact with polluted recreational waters and consumption of salad crops irrigated by polluted freshwaters. Major contributors to the spread of various water-borne pathogens are sewage, polluted surface waters and stormwater runoff. All of these contributions are intensified during periods of major floods. Several water-borne case histories are cited as examples of breakdowns in public health protection related to water supply, recreational waters and the consumption of contaminated salad crops. In the long term, water resource management must focus on pollution prevention from point sources of waste discharges and the spread of pathogens in watershed stormwater runoff.     

Estimation of field irrigation water demand based on lumped kinematic wave model considering soil moisture balance

An estimation model of farm field irrigation water demand is developed. The model is based on the lumped kinematic wave model considering soil water balance. The lumped model approach reduces the computational load in rainfall-runoff analysis and allows application to large river basins. Evapotranspiration is estimated on hourly basis by the improvement of FAO’s method. Not only water volume necessary for farm field irrigation but also the number of the water charge and its interval can be estimated by the combined use of the lumped runoff model and the hourly evapotranspiration model.     

Modeling an irrigation ditch opens up the world. Hydrology and hydraulics of an ancient irrigation system in Peru

Ancient Peruvian irrigation systems have been studied extensively, but much remains unknown about technical and hydrological aspects of these irrigation systems. The Pampa de Chaparrí irrigation system in Peru is used as an example to show how modeling approaches for hydrological and hydraulic features of irrigation can yield results to improve our understanding of irrigation in the area. Analysis focuses on water availability compared demand, the way available water may have been applied to crops and whether the water needed could be delivered through the canal system. Results suggest that on the Pampa some 2500 hectares may have been cultivated within certain security limits for acceptable yields. The rhythm with which the irrigation requirement was applied to crops most likely influenced yields and thus food security. Furthermore, the influence of groundwater on crop growth may have been considerable. The hydraulic behavior of the irrigation system suggests that it should not be taken for granted that theoretically required water flows could actually be diverted and/or distributed to water users. The many questions coming out of the results define important items for a joint research agenda of archeologists and irrigation scientists.     

Grain yield reliability analysis with crop water demand uncertainty

A new method of reliability analysis for crop water production function is presented considering crop water demand uncertainty. The procedure uses an advanced first-order second moment (AFOSM) method in evaluating the crop yield failure probability. To determine the variance and the mean of actual evapotranspiration as the component of interest for AFOSM analysis, an explicit stochastic optimization model for optimal irrigation scheduling is developed based on the first and second-order moment analysis of the soil moisture state variables. As a result of the study, the violation probabilities of crop yield at different levels were computed from AFOSM method. Also using the optimization results and the double bounded density function estimation methodology, the weekly soil moisture density function is derived which can be used as a short term reliability index. The proposed approach does not involve any discretization of system variables. The results of reliability analysis and optimization model compare favorably with those obtained from simulation.     

An efficient cost-sharing program to reduce nonpoint-source contamination: theory and an application to groundwater contamination

This research evaluates the economics of cost-sharing improved irrigation technologies to reduce agricultural, nonpoint-source contamination. Irrigation and fertilization inefficiencies are modeled within a nonjoint production process to evaluate both private and public costs of technology adoption and its effect on groundwater nitrate-contamination levels. A central Nebraska application indicates that even without a current government subsidy, a farmer is economically better off switching from gravity-flow to surge-flow irrigation rather than a center-pivot system. An annual government subsidy of $22.50 (US$) per hectare per year is required over the life of a center-pivot system to make the farmer financially indifferent. However, cost-sharing center-pivot adoption improves the groundwater contamination level, while other irrigation systems result in continued deterioration of groundwater quality. Received: 3 November 1998 · Accepted: 15 February 1999     

ITOM: an interval-parameter two-stage optimization model for stochastic planning of water resources systems

Planning of water resources systems is often associated with many uncertain parameters and their interrelationships are complicated. Stochastic planning of water resources systems is vital under changing climate and increasing water scarcity. This study proposes an interval-parameter two-stage optimization model (ITOM) for water resources planning in an agricultural system under uncertainty. Compared with other optimization techniques, the proposed modeling approach offers two advantages: first, it provides a linkage to pre-defined water policies, and; second, it reflects uncertainties expressed as probability distributions and discrete intervals. The ITOM is applied to a case study of irrigation planning. Reasonable solutions are obtained, and a variety of decision alternatives are generated under different combinations of water shortages. It provides desired water-allocation patterns with respect to maximum system benefits and highest feasibility. Moreover, the modeling results indicate that an optimistic water policy corresponding to higher agricultural income may be subject to a higher risk of system-failure penalties; while, a too conservative policy may lead to wastage of irrigation supplies.     

From rainfed agriculture to stress-avoidance irrigation: I. A generalized irrigation scheme with stochastic soil moisture

With vast regions already experiencing water shortages, it is becoming imperative to manage sustainably the available water resources. As agriculture is by far the most important user of freshwater and the role of irrigation is projected to increase in face of climate change and increased food requirements, it is particularly important to develop simple, widely applicable models of irrigation water needs for short- and long-term water resource management. Such models should synthetically provide the key irrigation quantities (volumes, frequencies, etc.) for different irrigation schemes as a function of the main soil, crop, and climatic features, including rainfall unpredictability. Here we consider often-employed irrigation methods (e.g., surface and sprinkler irrigation systems, as well as modern micro-irrigation techniques) and describe them under a unified conceptual and theoretical framework, which includes rainfed agriculture and stress-avoidance irrigation as extreme cases. We obtain mostly analytical solutions for the stochastic steady state of soil moisture probability density function with random rainfall timing and amount, and compute water requirements as a function of climate, crop, and soil parameters. These results provide the necessary starting point for a full assessment of irrigation strategies, with reference to sustainability, productivity, and profitability, developed in a companion paper [Vico G, Porporato A. From rainfed agriculture to stress-avoidance irrigation: II. Sustainability, crop yield, and net profit. Adv Water Resour 2011;34(2):272-81].