Supply and Demand Analysis of Water Resources. Case Study: Irrigation Water Demand in a Semi-Arid Zone in Mexico

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 (Kc) were used to determine crop evapotranspiration (ETc), to estimate the water demand of these for each month, using the multi-year monthly average reference evapotranspiration (ETo) 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

Santa Ana Winds: Fractal-Based Analysis in a Semi-Arid Zone of Northern Mexico

A fractal analysis based on the time series of precipitation, temperature, pressure, relative humidity, and wind speed was performed for 16 weather stations located in the hydrographic basin of the Guadalupe River in Baja California, Mexico. Days on which the phenomenon known as Santa Ana winds occurs were identified based on the corresponding criteria of wind speed (≥4.5 m/s) and wind direction (between 0° and 90°). Subsequently, the time series was formed with data representing the days on which this phenomenon occurs in each of the analyzed weather stations. A time series was additionally formed from the days in which the Santa Ana winds condition does not occur. Hurst exponents and fractal dimension were estimated applying the rescaled range method to characterize the established time series in terms of characteristics of persistence, anti-persistence, or randomness along with the calculation of the climate predictability Index. This enabled the behavior and correlation analysis of the meteorological variables associated with Santa Ana winds occurrence. Finally, this type of research study is instrumental in understanding the regional dynamics of the climate in the basin, and allows us to establish a basis for developing models that can forecast the days of occurrence of the Santa Ana winds, in such a way that actions or measures can be taken to mitigate the negative consequences generated when said phenomenon occurs, such as fires and droughts

Santa Ana Winds: Fractal-Based Analysis in a Semi-Arid Zone of Northern Mexico

A fractal analysis based on the time series of precipitation, temperature, pressure, relative humidity, and wind speed was performed for 16 weather stations located in the hydrographic basin of the Guadalupe River in Baja California, Mexico. Days on which the phenomenon known as Santa Ana winds occurs were identified based on the corresponding criteria of wind speed (≥4.5 m/s) and wind direction (between 0° and 90°). Subsequently, the time series was formed with data representing the days on which this phenomenon occurs in each of the analyzed weather stations. A time series was additionally formed from the days in which the Santa Ana winds condition does not occur. Hurst exponents and fractal dimension were estimated applying the rescaled range method to characterize the established time series in terms of characteristics of persistence, anti-persistence, or randomness along with the calculation of the climate predictability Index. This enabled the behavior and correlation analysis of the meteorological variables associated with Santa Ana winds occurrence. Finally, this type of research study is instrumental in understanding the regional dynamics of the climate in the basin, and allows us to establish a basis for developing models that can forecast the days of occurrence of the Santa Ana winds, in such a way that actions or measures can be taken to mitigate the negative consequences generated when said phenomenon occurs, such as fires and droughts