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Deconstructing the drivers of large-scale vegetation change is critical to predicting and managing projected climate and land use changes that will affect regional vegetation cover in degraded or threated ecosystems. We investigate the shared dynamics of spatially variable vegetation across three large watersheds in the southern Africa savanna. Dynamic Factor Analysis (DFA), a multivariate time-series dimension reduction technique, was used to identify the most important physical drivers of regional vegetation change. We first evaluated the Advanced Very High Resolution Radiometer (AVHRR)- vs. the Moderate Resolution Imaging Spectroradiometer (MODIS)-based Normalized Difference Vegetation Index (NDVI) datasets across their overlapping period (2001–2010). NDVI follows a general pattern of cyclic seasonal variation, with distinct spatio-temporal patterns across physio-geographic regions. Both NDVI products produced similar DFA models, although MODIS was simulated better. Soil moisture and precipitation controlled NDVI for mean annual precipitation (MAP) < 750 mm, and above this, evaporation and mean temperature dominated. A second DFA with the full AVHRR (1982–2010) data found that for MAP < 750 mm, soil moisture and actual evapotranspiration control NDVI dynamics, followed by mean and maximum temperatures. Above 950 mm, actual evapotranspiration and precipitation dominate. The quantification of the combined spatio-temporal environmental drivers of NDVI expands our ability to understand landscape level changes in vegetation evaluated through remote sensing and improves the basis for the management of vulnerable regions, like the southern Africa savannas.

The Kabul River basin (KRB) of Afghanistan, a lifeline of around 10 million people, has multiplicity of governance, management, and development-related challenges leading to inequity, inadequacy, and unreliability of irrigation water distribution. Prior to any uplifting intervention, there is a need to evaluate the performance of irrigation system on a long term basis to identify the existing bottlenecks. Although there are several indicators available for the performance evaluation of the irrigation schemes, we used the coefficient of variation (CV) of actual evapotranspiration (ETa) in space (basin, sub-basin, and provincial level), relative evapotranspiration (RET), and temporal CV of RET, to assess the equity, adequacy, and reliability of water distribution, respectively, from 2003 to 2013. The ETa was estimated through a surface energy balance system (SEBS) algorithm and the ETa estimates were validated using the advection aridity (AA) method with a R2 value of 0.81 and 0.77 at Nawabad and Sultanpur stations, respectively. The global land data assimilation system (GLDAS) and moderate-resolution imaging spectroradiometer (MODIS) products were used as main inputs to the SEBS. Results show that the mean seasonal sub-based RET values during summer (May–September) (0.37 ± 0.06) and winter (October–April) (0.40 ± 0.08) are below the target values (RET ≥ 0.75) during 2003–2013. The CV of the mean ETa, within sub-basins and provinces for the entire study period, has an equitable distribution of water from October–January (0.09 ± 0.04), whereas the highest inequity (0.24 ± 0.08) in water distribution is during early summer. The range of the CV of the mean ETa (0.04–0.06) on a monthly and seasonal basis shows the unreliability of water supplies in several provinces or sub-basins. The analysis of the temporal CV of mean RET highlights the unreliable water supplies across the entire basin. The maximum ETa during the study period was estimated for the Shamal sub-basin (552 ± 43 mm) while among the provinces, Kunar experienced the highest ETa (544 ± 39 mm). This study highlights the dire need for interventions to improve the irrigation performance in time and space. The proposed methodology can be used as a framework for monitoring and implementing water distribution plans in future.

Reduction in channel capacity can trigger an increase in flood hazard over time. It represents a geomorphic driver that competes against its hydrologic counterpart where streamflow decreases. We show that this situation arose in the Guadalquivir River (Southern Spain) after impoundment. We identify the physical parameters that raised flood hazard in the period 1997–2013 with respect to past years 1910–1996 and quantify their effects by accounting for temporal trends in both streamflow and channel capacity. First, we collect historical hydrological data to lengthen records of extreme flooding events since 1910. Next, inundated areas and grade lines across a 70 km stretch of up to 2 km wide floodplain are delimited from Landsat and TerraSAR-X satellite images of the most recent floods (2009–2013). Flooded areas are also computed using standard two-dimensional Saint-Venant equations. Simulated stages are verified locally and across the whole domain with collected hydrological data and satellite images, respectively. The thoughtful analysis of flooding and geomorphic dynamics over multi-decadal timescales illustrates that non-stationary channel adaptation to river impoundment decreased channel capacity and increased flood hazard. Previous to channel squeezing and pre-vegetation encroachment, river discharges as high as 1450 m3·s−1 (the year 1924) were required to inundate the same areas as the 790 m3·s−1 streamflow for recent floods (the year 2010). We conclude that future projections of one-in-a-century river floods need to include geomorphic drivers as they compete with the reduction of peak discharges under the current climate change scenario.

Evapotranspiration (ET) is a variable of the climatic system and hydrological cycle that plays an important role in biosphere–atmosphere–hydrosphere interactions. In this paper, remote sensing-based ET estimates with the simplified surface energy balance index (S-SEBI) model using Landsat 8 data were compared with in situ lysimeter measurements for different land covers (Grass, Wheat, Barley, and Vineyard) at the Barrax site, Spain, for the period 2014–2018. Daily estimates produced superior performance than hourly estimates in all the land covers, with an average difference of 12% and 15% for daily and hourly ET estimates, respectively. Grass and Vineyard showed the best performance, with an RMSE of 0.10 mm/h and 0.09 mm/h and 1.11 mm/day and 0.63 mm/day, respectively. Thus, the S-SEBI model is able to retrieve ET from Landsat 8 data with an average RMSE for daily ET of 0.86 mm/day. Some model uncertainties were also analyzed, and we concluded that the overpass of the Landsat missions represents neither the maximum daily ET nor the average daily ET, which contributes to an increase in errors in the estimated ET. However, the S-SEBI model can be used to operationally retrieve ET from agriculture sites with good accuracy and sufficient variation between pixels, thus being a suitable option to be adopted into operational ET remote sensing programs for irrigation scheduling or other purposes.

This paper proposes an efficient and simplified procedure for the 3D modelling of buildings, based on the semi-automatic processing of point clouds acquired with mobile LiDAR scanners. The procedure is designed with the aim at generating BIM, in gbXML format, from the point clouds. In this way, the main application of the procedure is the performance of energy analysis, towards the increase of the energy efficiency in the construction sector, and its consequent contribution to the mitigation of the climate change. Thus, the main contribution of the methodology proposed is its easiness of use and its level of automation, which allow its utilization by users who are experts in the use of energy in buildings but non-experts on 3D modelling. The software provides a solution for the 3D modelling of complex point clouds of various millions of points in times of execution less than 10 minutes. The system is evaluated through its application to three different real-world scenarios and compared with manual modelling. Moreover, the results are used for an example of an energy application, proving their performance against manually elaborated models.

The spectral distribution of the solar irradiance incident on photovoltaic (PV) modules is a key variable controlling their power production. It is required to properly simulate the production and performance of PV plants based on technologies with different spectral characteristics. Spectroradiometers can only sense the solar spectrum within a wavelength range that is usually too short compared to the actual spectral response of some PV technologies. In this work, a new methodology based on the Simple Model of the Atmospheric Radiative Transfer of Sunshine (SMARTS) spectral code is proposed to extend the spectral range of measured direct irradiance spectra and to increase the spectral resolution of such experimental measurements. Satisfactory results were obtained for both clear and hazy sky conditions at a radiometric station in southern Spain. This approach constitutes the starting point of a general methodology to obtain the instantaneous spectral irradiance incident on the plane of array of PV modules and its temporal variations, while evaluating the magnitude and variability of the abundance of atmospheric constituents with the most impact on surface irradiance, most particularly aerosols and water vapor.

The transition to renewable energies is an unavoidable step to guarantee a peaceful and sustainable future for humankind. Although solar radiation is one of the main sources of renewable energy, there are broad regions of the planet where it has not been characterized appropriately to provide the necessary information for regional and local planning and design of the different solar powered systems. The Caribbean, and Cuba in particular, lacked until very recently at least one long-term series of surface solar radiation measurements. Here we present the first long-term records of solar radiation for this region. Solar radiation measurements manually conducted and recorded on paper were rescued, reprocessed and quality controlled to develop the solar radiation climatology at the Actinometrical Station of Camagüey, in Cuba (21.422°N; 77.850°W; 122 m a.s.l.) for the period 1981–2016. The diurnal cycle based on the average hourly values of the global, direct and diffuse horizontal variables for the entire period have been determined and analyzed showing the dependence on solar zenith angle (SZA) and clouds. The annual cycle of global solar component given by the mean monthly daily values presents two maxima, one in April and another one in July with values of 5.06 and 4.91 kWh m−2, respectively (18.23 and 17.67 MJ m−2 per day for insolation), and the minimum in December (3.15 kWh m−2 or 11.33 MJ m−2). The maxima are governed by the direct solar components and are modulated by cloudiness. Both, diurnal and annual cycles of the diffuse solar component show a smoothed bell shaped behavior. In general solar radiation at this station presents a strong influence of clouds, with little seasonal variation but with higher values during the rainy season. Daily global radiation annual averages showed its maximum value in the year 1983, with 17.45 MJ m−2 explained by very low cloudiness this year, and the minimum value was reported in 2009 with a value of 12.43 MJ m−2 that could not explained by the cloud coverage or the aerosols optical depths registered that year. The effects of the 1982 El Chichón and 1991 Mount Pinatubo volcanic eruptions on the solar radiation variables at Camagüey are also shown and discussed. The results achieved in this study shown the characteristics of solar radiation in this area and their potential for solar power applications.