Seasonal Auto Regressive Integrative Moving Average models (SARIMA) were developed for monthly rainfall time series. Normality of the rainfall time series was achieved by using the Box Cox transformation. The best SARIMA models were selected based on their autocorrelation function (ACF), partial autocorrelation function (PACF), and the minimum values of the Akaike Information Criterion (AIC). The result of the Ljung–Box statistical test shows the randomness and homogeneity of each model residuals. The performance and validation of the SARIMA models were evaluated based on various statistical measures, among these, the Student’s t-test. It is possible to obtain synthetic records that preserve the statistical characteristics of the historical record through the SARIMA models. Finally, the results obtained can be applied to various hydrological and water resources management studies. This will certainly assist policy and decision-makers to establish strategies, priorities, and the proper use of water resources in the Sinú river watershed.

The geomorphology of a basin makes it possible for us to understand its hydrological pattern. Accordingly, satellite-based remote sensing and geo-information technologies have proven to be effective tools in the morphology analysis at the basin level. Consequently, this present study carried out a morphological analysis of the Sinú river basin, analyzing its geometric characteristics, drainage networks, and relief to develop integrated water resource management. The analyzed zone comprises an area of 13,971.7 km² with three sub-basins, the upper, the middle, and the lower Sinú sub-basins, where seventeen morphometric parameters were evaluated using remote sensing (RS) and geographical information system (GIS) tools to identify the rainwater harvesting potential index. The Sinú basin has a dendritic drainage pattern, and the results of the drainage network parameters make it possible for us to infer that the middle and lower Sinú areas are the ones mainly affected by floods. The basin geometry parameters indicate an elongated shape, implying a lesser probability of uniform and homogeneous rainfall. Additionally, the hypsometric curve shape indicates that active fluvial and alluvial sedimentary processes are present, allowing us to conclude that much of the material has been eroded and deposited in the basin’s lower zones as it could be confirmed with the geological information available. The obtained results and GIS tools confirm the basin’s geological heterogeneity. Furthermore, they were used to delimit the potential water harvesting zones following the rainwater harvesting potential index (RWHPI) methodology. The research demonstrates that drainage morphometry has a substantial impact on understanding landform processes, soil characteristics, and erosional characteristics. Additionally, the results help us understand the relationship between hydrological variables and geomorphological parameters as guidance and/or decision-making instruments for the competent authorities to establish actions for the sustainable development of the basin, flood control, water supply planning, water budgeting, and disaster mitigation within the Sinú river basin.

Intensity–Duration–Frequency (IDF) curves describe the relationship between rainfall intensity, rainfall duration, and return period. They are commonly used in the design, planning and operation of hydrologic, hydraulic, and water resource systems. Considering the intense rainfall presence with flooding occurrences, limited data used to develop IDF curves, and importance to improve the IDF design for the Ensenada City in Baja California, this research study aims to investigate the use and combinations of pluviograph and daily records, to assess rain behavior around the city, and select a suitable method that provides the best results of IDF relationship, consequently updating the IDF relationship for the city for return periods of 10, 25, 50, and 100 years. The IDF relationship is determined through frequency analysis of rainfall observations. Also, annual maximum rainfall intensity for several duration and return periods has been analyzed according to the statistical distribution of Gumbel Extreme Value (GEV). Thus, Chen’s method was evaluated based on the depth-duration ratio (R) from the zone, and the development of the IDF relationship for the rain gauges stations was focused on estimating the most suitable (R) ratio; chosen from testing several methods and analyzing the rain in the region from California and Baja California. The determined values of the rain for one hour and return period of 2 years $(P_1^2)$ obtained were compared to the values of some cities in California and Baja California, with a range between 10 and 16.61 mm, and the values of the (R) ratio are in a range between 0.35 and 0.44; this range is close to the (R) ratio of 0.44 for one station in Tijuana, a city 100 km far from Ensenada. The values found here correspond to the rainfall characteristics of the zone; therefore, the method used in this study can be replicated to other semi-arid zones with the same rain characteristics. Finally, it is suggested that these results of the IDF relationship should be incorporated on the Norm of the State of Baja California as the recurrence update requires it upon recommendation. This study is the starting point to other studies that imply the calculation of a peak flow and evaluation of hydraulic structures as an input to help improve flood resilience in the city of Ensenada.

To sustainably use water resources, it is important to quantify water availability in a certain region. Due to climate change, population increase, and economic development, water demand increases continuously. Consequently, the difference between supply and demand of water becomes a significant issue, especially in arid and semi-arid regions. In this research, the Soil and Water Assessment Tool (SWAT) model has been applied to the Guadalupe river basin, to assess supply and demand analysis of water resources in this area, specifically for the irrigation of agricultural crops and municipal uses. From the land use, soil type, and terrain slope maps, 763 Hydrostatic Release Units (HRU) were estimated, distributed in the diverse relief types making up the basin, featured by mountains, hills, plateaus, plains, and valleys. For the crop area, 159 HRU were found with the three slope classification types, where 57 HRU represent 91% of the cultivated area on slopes, from 0 to 15%, located in the Ojos Negros and Guadalupe Valleys. The Soil Conservation Service method (SCS) was used to estimate the average monthly runoff and soil moisture content. As a result, water resource parameters related to the supply were determined with this, e.g., runoff, aquifer recharge, flow, infiltration, and others. Crop coefficient values (K_c) were used to determine crop evapotranspiration (ET_c), to estimate the water demand of these for each month, using the multi-year monthly average reference evapotranspiration (ET_o) calculated with the SWAT model. Overall good performance was obtained considering average monthly discharges data from the Agua Caliente gauging station. The model was calibrated, modifying the parameters chosen according to sensitivity analysis: SCS curve number, base-flow factor, ground-flow delay, and the threshold for return-flow occurrence. The Soil and Water Assessment Tool–Calibration and Uncertainty Programs SWAT-CUP has different goodness-of-fit indicators for the model e.g., determination coefficient (R²), standard deviation of the measured data (RSR), Nash–Sutcliffe coefficient of efficiency (NSE), and others. Multiple iterations were performed, resulting in a ratio between the root mean square error and the standard deviation of the measured data (RSR) of 0.61, a coefficient of determination (R²) of 0.70, and a Nash–Sutcliffe efficiency coefficient (NSE) of 0.63. A supply–demand analysis of the volume generated by the runoff from the basin was performed using the method of estimating useful volume for a reservoir. It is observed in these results that only positive deviations were obtained, implying that runoff in this basin is not enough to meet monthly demand. Finally, the need to establish actions to ensure water management efficiency is highlighted, both for irrigation of agricultural crops and for supply to the region population.

Robotic applications, such as educational programs, are well-known. Nonetheless, there are challenges to be implemented in other settings, e.g., mine detection, agriculture support, and tasks for industry 4.0. The main challenge consists of robotic operations supported by autonomous decision using sensed-based features extraction. A prototype of a robot assembled using mechanical parts of a LEGO MINDSTORMS Robotic Kit EV3 and a Raspberry Pi controlled through servo algorithms of 2D and 2D1/2 vision approaches was implemented to tackle this challenge. This design is supported by simulations based on image, position, and a hybrid scheme for visual servo controllers. Practical implementation is operated using navigation guided by running up image-based visual servo control algorithms embedded in a Raspberry Pi that uses a control criterion based on error evolution to compute the difference between a target and sensed image. Images are collected by a camera installed on a mobile robotic platform manually and automatically operated and controlled using the Raspberry Pi. An Android application to watch the images by video streaming is shown here, using a smartphone and a video related to the implemented robot’s operation. This kind of robot might be used to complete field reactive tasks in the settings mentioned above, since the detection and control approaches allow self-contained guidance.

Drying of three varieties of cassava, was conducted in a tunnel type dryer; the effect of temperature, variety and velocity of drying air on the drying time, using a completely randomized design in factorial arrangement with three factors: temperature (45, 55 and 70°C), speed drying air (1, 3 and 4 m/s) and range (Corpoica Tai, Gines and Veronica), performing three replicates per treatment, resulting in a decrease in drying time to the temperature of 70 ° C for the three varieties. The results obtained were built drying curves, in which it was found that this process took place in the period decreasing. Drying curves were fitted to mathematical models, determining by the R² and the sum of squared errors (SSE), that page is the model that best describes the drying process.