Ecuador has the highest deforestation rate in South America, causing large‐scale soil erosion. Inter‐Andean watersheds are especially affected by a rapid increase of the population leading to the conversion of large areas of montane forest into pasture and cropland. In this study, we estimate soil erosion risk in a small mixed land‐use watershed in the southern Andes of Ecuador. Soil loss was estimated at a spatial resolution of 30 m, using the Revised Universal Soil Loss Equation (RUSLE) where the RUSLE factors were estimated on the basis of limited public available data. Land‐cover maps for 1976, 2008 and 2040 were created assuming increasing deforestation rates over the ensuing decades. Greater erosion rates are estimated for succession areas with agricultural cropland and pasture with maximum values of 936 Mg ha−1 y−1, where slopes and precipitation amounts are the greatest. Under natural forest vegetation, the estimated soil erosion rates are negligible (1·5 to 40 Mg ha−1 y−1) even at steep slopes and higher elevations where rainfall amounts and intensities are generally higher. When the entire watershed has undergone substantial deforestation in 2040, erosion values may reach 2,021 Mg ha−1 y−1. Vegetation cover is the most important factor for potential soil erosion. Secondary factors are related to rainfall (R‐factor) and topography (LS factors). Although the spatial predictions of potential soil erosion have only limited meaning for erosion risk, this method provides an important screening tool for land management and assessment of land‐cover change. Copyright © 2013 John Wiley & Sons, Ltd.

Water availability in semiarid regions is endangered, which is not only due to changing climate conditions, but also to anthropogenic land use changes. The present study analyzed the annual and monthly water balance (WBc) and the soil moisture deficit (Ds) for different vegetation units under semiarid conditions in the Andes of southern Ecuador, based on limited meteorological station data and field measurements (soil samples). To calculate crop evapotranspiration (ETc) the Blaney-Criddle method was applied, and the specific crop factor (Kc) included, because only temperature (T) and precipitation (P) data were available. By means of the soil samples the water retention capacity (RC) of the different soil types present in the study area were estimated, which, in combination with WBc, provided reliable results respective to water surpluses or deficits for the different vegetation units. The results indicated highest Ds for cultivated areas, particularly for corn and sugarcane plantations, where annual deficits up to −1377.5 mm ha −1 and monthly deficits up to −181.1 mm ha −1 were calculated. Natural vegetation cover (scrubland, forest and paramo), especially at higher elevations, did not show any deficit throughout the year (annual surpluses up to 1279.6 mm ha −1 ; monthly surpluses up to 280.1 mm ha −1 ). Hence, it could be concluded that the prevailing climate conditions in semiarid regions cannot provide the necessary water for agricultural practices, for which reason irrigation is required. The necessary water can be supplied by areas coved by natural vegetation, but these areas are endangered due to population growth and the associated land use changes.

The prediction of river discharge using hydrological models (HMs) is of utmost importance, especially in basins that provide drinking water or serve as recreation areas, to mitigate damage to civil structures and to prevent the loss of human lives. Therefore, different HMs must be tested to determine their accuracy and usefulness as early warning tools, especially for extreme precipitation events. This study simulated the river discharge in an Andean watershed, for which the distributed HM Runoff Prediction Model (RPM) and the semi-distributed HM Hydrologic Modelling System (HEC-HMS) were applied. As precipitation input data for the RPM model, high-resolution radar observations were used, whereas the HEC-HMS model used the available meteorological station data. The obtained simulations were compared to measured discharges at the outlet of the watershed. The results highlighted the advantages of distributed HM (RPM) in combination with high-resolution radar images, which estimated accurately the discharges in magnitude and time. The statistical analysis showed good to very good accordance between observed and simulated discharge for the RPM model (R2: 0.85–0.92; NSE: 0.77–0.82), whereas for the HEC-HMS model accuracies were lower (R2: 0.68–0.86; NSE: 0.26–0.78). This was not only due to the application of means values for the watershed (HEC-HMS), but also to limited rain gauge information. Generally, station network density in tropical mountain regions is poor, for which reason the high spatiotemporal precipitation variability cannot be detected. For hydrological simulation and forecasting flash floods, as well as for environmental investigations and water resource management, meteorological radars are the better choice. The greater availability of cost-effective systems at the present time also reduces implementation and maintenance costs of dense meteorological station networks.

This study was conducted in the Zamora Huayco (ZH) river basin, located in the inter-Andean region of southern Ecuador. The objective was to describe, through land use/land cover change (LUCC), the natural physical processes under current conditions and to project them to 2029. Moreover, temperature and precipitation forecasts were estimated to detail possible effects of climate change. Using remote sensing techniques, satellite images were processed to prepare a projection to 2029. Water recharge was estimated considering the effects of slope, groundcover, and soil texture. Flash floods were estimated using lumped models, concatenating the information to HEC RAS. Water availability was estimated with a semi-distributed hydrological model (SWAT). Precipitation and temperature data were forecasted using autoregressive and exponential smoothing models. Under the forecast, forest and shrub covers show a growth of 6.6%, water recharge projects an increase of 7.16%. Flood flows suffer a reduction of up to 16.54%, and the flow regime with a 90% of probability of exceedance is 1.85% (7.72 l/s) higher for 2029 than for the 2019 scenario, so an improvement in flow regulation is evident. Forecasts show an increase in average temperature of 0.11 °C and 15.63% in extreme rainfall by 2029. Therefore, intervention strategies in Andean basins should be supported by prospective studies that use these key variables of the system for an integrated management of water resources.

The potential risk of pesticide exposure in developing countries needs further study as data are limited and simple tools to assess the risks on human health and the environment caused by pesticides are lacking. This article introduces a potential pesticides exposure index (PPEI) as a modeling tool to assess the risk of human and environmental pesticide exposure in agricultural basins. The PPEI is based on a number of factors including: human population centers and their proximity to agricultural crops, the toxicological properties of pesticides, and their application frequency. The index was applied to a region in southern Ecuador (approximately 7200 km 2 ) where corn, rice, and sugarcane are the predominant crops, and where hot spots with the highest vulnerability to pesticide residues were identified. Of the total of 5326 neighborhoods for the entire study area, 1030 had high, 1124 had medium, and 1009 had low PPEI scores. Among the practical uses of PPEI are to help to assist regulatory agencies and academics evaluate the effects of land use policies on pesticide vulnerability. Also, it can be easily expanded to include other parameters, such as data from other agricultural crops, or frequency of pesticide application. The PPEI can be a valuable indicator of risk of pesticide exposure, as it is reliable and applicable to developing countries, where data and resources are limited.