Julio Pérez-Sánchez

The economic value of conjoint local management in water resources: Results from a contingent valuation in the Boquerón aquifer (Albacete, SE Spain).

In the field of water resources management, the Water Framework Directive is the first directive to adopt an ecosystem approach, establishing principles and economic tools for an integrated management of water resources to protect, conserve and restore all water bodies. The incorporation of local authorities in this management involves quality benefits that are perceived by users in an effective and lasting way. The purpose of this paper is to present the economic value of the environmental recovery of the overexploited Boquerón aquifer in Hellín (Albacete, SE Spain) and all of its associated ecosystems. This aquifer operates as a regulating reservoir for the surface waters of the Hellín Canal. The contingent valuation method (CVM) applied in this environmental assessment of the aquifer showed that its non-use value was €147,470 per year, due to the high environmental awareness of the Hellín people, which is enough to ensure the survival of the ecosystems linked to the aquifer.

A comparative study of fire weather indices in a semiarid south-eastern Europe region. Case of study: Murcia (Spain)

Forest fires are an important distortion in forest ecosystems, linked to their development and whose effects proceed beyond the destruction of ecosystems and material properties, especially in semiarid regions. Prevention of forest fires has to lean on indices based on available parameters that quantify fire risk ignition and spreading. The present study was conducted to compare four fire weather indices in a semiarid region of 11,314km2 located in southern Spain, characterised as being part of the most damaged area by fire in the Iberian Peninsula. The studied period comprises 3033 wildfires in the region during 15years (2000-2014), of which 80% are >100m2 and 14% >1000m2, resulting around 40km2 of burnt area in this period. The indices selected have been Angström Index, Forest Fire Drought Index, Forest Moisture Index and Fire Weather Index. Likewise, four selection methods have been applied to compare the results of the studied indices: Mahalanobis distance, percentile method, ranked percentile method and Relative Operating Characteristic curves (ROC). Angström index gives good results in the coastal areas with higher temperatures, low rainfall and wider range of variations while Fire Weather Index has better results in inland areas with higher rainfall, dense forest mass and fewer changes in meteorological conditions throughout the year. ROC space rejects all the indices except Fire Weather Index with good performance all over the region. ROC analysis ratios can be used to assess the success (or lack thereof) of fire indices; thus, it benefits operational wildfire predictions in semiarid regions similar to that of the case study.

Using Multiple Monthly Water Balance Models to Evaluate Gridded Precipitation Products over Peninsular Spain

The availability of precipitation data is the key driver in the application of hydrological models when simulating streamflow. Ground weather stations are regularly used to measure precipitation. However, spatial coverage is often limited in low-population areas and mountain areas. To overcome this limitation, gridded datasets from remote sensing have been widely used. This study evaluates four widely used global precipitation datasets (GPDs): The Tropical Rainfall Measuring Mission (TRMM) 3B43, the Climate Forecast System Reanalysis (CFSR), the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and the Multi-Source Weighted-Ensemble Precipitation (MSWEP), against point gauge and gridded dataset observations using multiple monthly water balance models (MWBMs) in four different meso-scale basins that cover the main climatic zones of Peninsular Spain. The volumes of precipitation obtained from the GPDs tend to be smaller than those from the gauged data. Results underscore the superiority of the national gridded dataset, although the TRMM provides satisfactory results in simulating streamflow, reaching similar Nash-Sutcliffe values, between 0.70 and 0.95, and an average total volume error of 12% when using the GR2M model. The performance of GPDs highly depends on the climate, so that the more humid the watershed is, the better results can be achieved. The procedures used can be applied in regions with similar case studies to more accurately assess the resources within a system in which there is scarcity of recorded data available.

A novel fuzzy clustering approach to regionalise watersheds with an automatic determination of optimal number of clusters

Abstract One of the most important problems faced in hydrology is the estimation of flood magnitudes and frequencies in ungauged basins. Hydrological regionalisation is used to transfer information from gauged watersheds to ungauged watersheds. However, to obtain reliable results, the watersheds involved must have a similar hydrological behaviour. In this study, two different clustering approaches are used and compared to identify the hydrologically homogeneous regions. Fuzzy C-Means algorithm (FCM), which is widely used for regionalisation studies, needs the calculation of cluster validity indices in order to determine the optimal number of clusters. Fuzzy Minimals algorithm (FM), which presents an advantage compared with others fuzzy clustering algorithms, does not need to know a priori the number of clusters, so cluster validity indices are not used. Regional homogeneity test based on L-moments approach is used to check homogeneity of regions identified by both cluster analysis approaches. The validation of the FM algorithm in deriving homogeneous regions for flood frequency analysis is illustrated through its application to data from the watersheds in Alto Genil (South Spain). According to the results, FM algorithm is recommended for identifying the hydrologically homogeneous regions for regional frequency analysis.

Estimating Rainfall Erositivity in Semiarid Regions. Comparison of Expressions and Parameters Using Data from the Guadalentín Basin (SE Spain)

Perez-Sanchez J., Senent-Aparicio J. (2016): Estimating rainfall erositivity in semiarid regions. Comparison of expres sions and parameters using data from the Guadalentin Basin (SE Spain). Soil & Water Res., 11: 75–82. One of the many factors that leads to soil erosion is rainfall erositivity, which is a basic physical factor enabling us to understand the geomorphological processes that take place in a basin. Results worldwide have shown that the erositivity R factor of the Universal Soil Loss Equation (USLE) has a high correlation with soil loss. In the past there have been few pluviometers capable of recording rainfall with continuous measurements. As a result of this lack of accuracy in the available series of rainfall intensity data, the calculation of the R factor has been restricted for a long time and various simplified models were developed on an international scale that relied on information obtained from existing stations. However, the modernisation of stations over the last few decades has provided to be a valuable tool for validating models, as well as for designing others that are more hardwearing and correlate better with the available information. In this paper, we have calculated the rainfall erositivity R factor for a semiarid basin in SE Spain using the formula developed in the USLE model for a series of 20 years of rainfall with 5-minute intervals, obtaining the mean R factor value of 620 MJ/ha∙ mm/h per year and maximum values of up to 6000 MJ/ha∙ mm/h per year . In addition, a comparative analysis of various simplified expressions was carried out to obtain the R factor. To obtain this value, w e came up with a simplified equation based on annual maximum daily rainfall and average monthly rainfall, which resulted in a correlation coefficient of r = 0.936 and a P-value of 0.033 for the basin under study. Thus, from this structure of the equation we have compiled a series of parametric maps which enable us to calculate the R factor from any position within the basin under study.