An accurate evaluation of water availability in sub-arid Mediterranean watersheds through SWAT: Cega-Eresma-Adaja

Simulation of flow processes in hyper-regulated Mediterranean watersheds is critical when examining general water demand and established ecological flows of River Basin Management Plans. Weather dynamics in the Mediterranean zone in recent decades have been characterised by a natural variation of drought cycles. In addition, exacerbated climate change proves that water fluxes must be estimated with more exhaustive models. The aim of this study is to assess the water balance of the Cega-Eresma-Adaja (CEA) watershed, including a detailed assessment of land uses and management practices to quantify agricultural water demand for the time period 2004–2014. We used the Soil and Water Assessment Tool (SWAT), given that it is a widespread tool that involves complex processes of the water cycle on a basin scale, providing information on water dynamics related to land use as a fundamental characteristic for water balance calculation. The Nash-Sutcliffe coefficient efficiency value, the main index of calibration and validation performance, was 0.86 for the Eresma-Adaja River and 0.67 for the Cega River. This presents a good result considering the large-scale watershed studied. Analysing dry hydrological years, we found that the estimation of ecological flows for sub-arid zones needs to consider the shallow aquifer-river relationship. During spring-summer periods, with very low flow, monitoring the shallow aquifer levels ensures a good ecological status. The study reveals that aspects such as crop rotation, soil management and their associated measures in Mediterranean basins are key factors for water resource management during drought periods. These results are expected to serve stakeholders and river basin authorities in conducting better-integrated water management practices in the watershed

Enhancing LULC scenarios impact assessment in hydrological dynamics using participatory mapping protocols in semiarid regions

Land use and land cover (LULC) scenarios in rural catchment hydrology are crucial to describe the effects of future water dynamics. However, there is a lack of understanding of the effectiveness of including static land covers at the subbasin level to provide inter-annual stability in changing the different water balance components. We developed a step-by-step mapping protocol to extend and enrich the hydrological assessment of future LULC scenarios defined through participatory stakeholder involvement. This novelty included specific allocation of static and dynamic LULC change among the scenarios and then compared the change of water dynamics to the current situation. For this, we quantified the LULC impact on the components of the water balance from three contrasting participatory scenarios implemented with the SWAT model in a rural basin in central Spain. The Land-sharing scenario (LSH) had the highest percentage of permanent grassland and shrubs and no increase of irrigated land compared to baseline. The land-sparing scenario (LSP) intensified agricultural land use close to urban areas, and the land balance scenario (LBA) was intermediate. The LSH increased the aquifer recharge by +1.7% and streamflow by +1.5%, while evapotranspiration and soil water storage decreased by -0.2%. In contrast, the LBA decreased in the riverine flux of -0.5%, an aquifer recharge of -0.6%, a soil water storage of -3.5%, and an evapotranspiration rate of +0.3%. Thus, LSH revealed that the allocation of permanent land cover such as grassland could buffer water dynamics, suggesting that dedicated planning and allocation of permanently vegetated LULC will favour land and water conservation

A Multi-Fractal approach to soil thin sections in gray levels.

In the environment, as it is complex flows where Reynold number is quite high due to non-linear interactions in flows, several scales are developed. This type of hierarchy is detected in velocities as well as in the structure of scalar fields, as temperatures, tracer concentrations, density, etc. In these cases is interesting to relate in some way the geometrical o topological characteristics observed in flow images with their physical properties and dynamics. In the last decades many scientist has been applying fractal analysis to these types of images extracting several fractal dimensions for different intensity intervals. This type of analysis is what we call Multi-Fracta

Shadow analysis: A method for measuring soil surface roughness

Erosion potential and the effects of tillage can be evaluated from quantitative descriptions of soil surface roughness. The present study therefore aimed to fill the need for a reliable, low-cost and convenient method to measure that parameter. Based on the interpretation of micro-topographic shadows, this new procedure is primarily designed for use in the field after tillage. The principle underlying shadow analysis is the direct relationship between soil surface roughness and the shadows cast by soil structures under fixed sunlight conditions. The results obtained with this method were compared to the statistical indexes used to interpret field readings recorded by a pin meter. The tests were conducted on 4-m2 sandy loam and sandy clay loam plots divided into 1-m2 subplots tilled with three different tools: chisel, tiller and roller. The highly significant correlation between the statistical indexes and shadow analysis results obtained in the laboratory as well as in the field for all the soil–tool combinations proved that both variability (CV) and dispersion (SD) are accommodated by the new method. This procedure simplifies the interpretation of soil surface roughness and shortens the time involved in field operations by a factor ranging from 12 to 20

Determination of the uptake and translocation of nitrogen applied at different growth stages of a melon crop (Cucumis melo L.) using 15N isotope.

In order to establish a rational nitrogen (N) fertilisation and reduce groundwater contamination, a clearer understanding of the N distribution through the growing season and its dynamics inside the plant is crucial. In two successive years, a melon crop (Cucumis melo L. cv. Sancho) was grown under field conditions to determine the uptake of N fertiliser, applied by means of fertigation at different stages of plant growth, and to follow the translocation of N in the plant using 15N-labelled N. In 2006, two experiments were carried out. In the first experiment, labelled 15N fertiliser was supplied at the female-bloom stage and in the second, at the end of fruit ripening. Labelled 15N fertiliser was made from 15NH415NO3 (10 at.% 15N) and 9.6 kg N ha−1 were applied in each experiment over 6 days (1.6 kg N ha−1 d−1). In 2007, the 15N treatment consisted of applying 20.4 kg N ha−1 as 15NH415NO3 (10 at.% 15N) in the middle of fruit growth, over 6 days (3.4 kg N ha−1 d−1). In addition, 93 and 95 kg N ha−1 were supplied daily by fertigation as ammonium nitrate in 2006 and 2007, respectively. The results obtained in 2006 suggest that the uptake of N derived from labelled fertiliser by the above-ground parts of the plants was not affected by the time of fertiliser application. At the female-flowering and fruit-ripening stages, the N content derived from 15N-labelled fertiliser was close to 0.435 g m−2 (about 45% of the N applied), while in the middle of fruit growth it was 1.45 g m−2 (71% of the N applied). The N application time affected the amount of N derived from labelled fertiliser that was translocated to the fruits. When the N was supplied later, the N translocation was lower, ranging between 54% at female flowering and 32% at the end of fruit ripening. Approximately 85% of the N translocated came from the leaf when the N was applied at female flowering or in the middle of fruit growth. This value decreased to 72% when the 15N application was at the end of fruit ripening. The ammonium nitrate became available to the plant between 2 and 2.5 weeks after its application. Although the leaf N uptake varied during the crop cycle, the N absorption rate in the whole plant was linear, suggesting that the melon crop could be fertilised with constant daily N amounts until 2–3 weeks before the last harvest

Predicción de días de helada a partir de temperaturas mensuales

Although frost can cause considerable crop damage, and practices have been developed to mitigate forecasted frost, frost forecasting technologies have not changed for years. This paper reports on a new method based on successive application of two models to forecast the number of monthly frost days for several Community of Madrid (Spain) meteorological stations. The first is an autoregressive integrated moving average (ARIMA) stochastic model that forecasts minimum monthly absolute temperature (t min) and average monthly minimum temperature (micro t) following Box and Jenkins methodology. The second model relates monthly temperatures (t min, micro t) to the minimum daily temperature distribution during one month. Three ARIMA models were identified. They present the same seasonal behaviour (integrated moving average model) and different non-seasonal part: autoregressive model (Model 1), integrated moving average model (Model 2) and autoregressive and moving average model (Model 3). The results indicate that minimum daily temperature (t dmin) for the meteorological stations studied followed a normal distribution each month with a very similar standard deviation through out the years. This standard deviation obtained for each station and each month could be used as a risk index for cold months. The application of Model 1 to predict minimum monthly temperatures produced the best frost days forecast. This procedure provides a tool for crop managers and crop insurance companies to assess the risk of frost frequency and intensity, so that they can take steps to mitigate frost damage and estimate the damage that frost would cause.Aunque las heladas pueden causar considerables daños a los cultivos y existen prácticas que mitigan las heladas, las técnicas utilizadas no han cambiado en muchos años. Este artículo proporciona un nuevo método para predecir el número de días de heladas para varias estaciones meteorológicas en la Comunidad de Madrid (España) basado en la aplicación sucesiva de dos modelos. El primero es un modelo estocástico, autorregresivo integrado de media móvil (ARIMA), que predice la temperatura mínima absoluta mensual (t min) y la temperatura media de mínimas mensual (micro t) siguiendo la metodología de Box and Jenkins. El segundo modelo relaciona las temperaturas mensuales (t min, micro t) con la distribución de temperaturas mínimas diarias de un mes. Se identificaron tres modelos ARIMA. Todas presentan el mismo comportamiento estacional (modelo de media móvil diferenciado) y diferente no estacional: modelo autorregresivo (Modelo 1), modelo de media móvil diferenciado (Modelo 2) y modelo autorregresivo y de media móvil (Modelo 3). Los resultados indican que las temperaturas mínimas diarias (t dmin) siguen una distribución normal con una desviación estándar similar a lo largo de los años. Esta desviación estándar podría utilizarse como índice de riesgo para los meses fríos. La aplicación del Modelo 1 para predecir temperaturas mínimas mensuales mostró la mejor predicción en días de helada. Este procedimiento proporciona una metodología para prevenir los daños por heladas en cosechas y estimar el incremento en los daños cuando aparece un escenario inesperado, siendo útil para los agricultores y para las compañías de seguros agrarios

Multifractal analysis of the pore- and solid-phases in binary two-dimensional images of natural porous structures

We use multifractal analysis (MFA) to investigate how the Renyi dimensions of the solid mass and the pore space in porous structures are related to each other. To our knowledge, there is no investigation about the relationship of Renyi or generalized dimensions of two phases of the same structure. Images of three different natural porous structures covering three orders of magnitude were investigated: a microscopic soil structure, a soil void system visible without magnification and a mineral dendrite. Image size was always 1024 x 1024 pixels and box sizes were chosen as powers of 2. MFA was carried out according to the method of moments, i.e., the probability distribution was estimated for moments ranging from - 10 < q < 10 and the Renyi dimensions were calculated from the log/log slope of the probability distribution for the respective moments over box sizes. A meaningful interval of box sizes was determined by estimating the characteristic length of the pore space and taking the next higher power of 2 value as the smallest box size, whereas the greatest box size was determined by optimizing the coefficients of determination of the log/log fits for all q. The optimized box size range spans from 32 to 1024 pixels for all images. Good generalized dimension (Dq) spectra were obtained for this box size range, which are capable of characterizing heterogeneous spatial porous structure. They are alike for all images and phases which the exception of the solid mass of the soil void system, which shows a rather flat Dq behavior. A closer examination reveals that similar patterns of structure gain similar spectra of generalized dimensions. The capacity dimension for q=0 is close to the Euclidian dimension 2 for all investigated images and phases. (c) 2006 Elsevier B.V. All rights reserved

Drought assessment and risk analysis

Drought is a slow-onset natural hazard recurring regionally, which is often considered as a creeping phenomenon. Drought is characterized by an accumulated departure of precipitation from the normal or expected, which may occur over a short period of time or may take months. Drought impacts affect the environment, society, and several sectors of the economy with closer links to climate, such as agriculture and food security. A holistic and integrated approach to environmental hazards, including droughts, has been gradually considered using risk analysis. This chapter addresses drought assessment and risk analysis. The different drought types are quantified, and several features are analyzed based on drought indices developed from conventional and/or remote sensing data and algorithms. Drought hazard methodologies, such as severity-duration- frequency relationships, early warnings, costbenefit analysis, and similar aspects, are incorporated within the risk management framework, namely, risk identification, risk estimation, risk evaluation, and risk governance. © 2017 by Taylor & Francis Group, LLC

Multiscaling of vegetation and moisture indices from MODIS satellite data

Scaling processes are increasingly understood to be the result of nonlinear dynamical mechanisms repeating scale after scale over a large range of scales leading to non-classical resolution dependencies. Statistical properties consequently vary in power law ways with the spatial resolution. When classical (single scale) remote sensing algorithms are applied to surrogates derived from such ?elds, they can at most be correct at the unique (and subjective) calibration resolution. Scaling analysis and modeling techniques are applied to MODIS TERRA bands 1-7 satellite data and the standard derived vegetation and soil moisture indices in order to quantitatively characterize the wide range scaling of these ?elds. The scaling exponents we ?nd are not so large; however, they act over wide scale ranges and imply large effects. For example for statistics near the mean, the MODIS (500 m) resolution would be biased by a factor 1.52 when compared to similar results from an ideal sensor at 1 mm resolution. Applying the standard index algorithms on lower and lower resolution satellite data we obtain indices with signi?cantly different statistical properties than if the same algorithm was used at ?ner resolution and then degraded to an intermediate value (a difference of a factor ~1.54). Our results demonstrate that these commonly used algorithms can at best be accurate at the unique calibration scale and point to the urgent need to develop resolution independent algorithms based on the scaling exponents