Effect of the Evapotranspiration of Thornthwaite and of Penman-Monteith in the Estimation of Monthly Streamflows Based on a Monthly Water Balance Model

The river discharge monitoring networks are generally sparser and more recent than those of other hydrological variables, like rainfall or temperature. Furthermore, most of the streamflow series show long periods without records and several gaps, thereby limiting their use. Hydrological modeling provides a tool to overcome the poor quality of the streamflow data. However, its applicability to fill in the gaps or increase the time spans of the existing series and also to estimate streamflows at ungauged catchments depends on the simplicity and on the few data requirements of the approach selected, which makes the water balance models suitable choices. In the previous scope, the role of evapotranspiration in a water balance model was investigated for Portugal based on two approaches: a more complex with more data requirements, the Penman-Monteith method, and a very simple one only based on temperature data, the Thornthwaite method. The results showed that the monthly streamflows estimated based on any of the previous evapotranspiration models are almost the same. In fact, when the differences between the two models are higher, the surface runoff process is no longer controlled by the evapotranspiration but instead by the absence of rainfall and by the dryness of the soil

Trends in crop reference evapotranspiration and climatological variables across Ceará state: Brazil.

Irrigation has a substantial share in total world water demand. At the global level, the withdrawal ratio for agriculture is 69 percent. Irrigation is necessary to compensate evapotranspiration (ET) deficit due to insufficient precipitation. Knowing the impacts of climatic changes on meteorological variables that directly affect the ET is important for successful climate adaptation. This paper analyzes annual trends in measured meteorological variables and in the crop reference evapotranspiration (ET0), at eight climatological stations in Ceará State, Brazil. Two statistical tests for trend analysis were used - Mann-Kendall and linear regression. The results indicate positive trend, statistically significant, in the maximum air temperature in five of eight stations. Minimum air temperature showed positive trend in three stations. Wind speed, sunshine hours and relative humidity presented positive and negative trends. These irregular patterns directly impacted ET0 in three stations. It seems that the increasing trend in ET0 was probably due to a significant increase detected in maximum temperature and minimum air temperature, not fully offset by the decrease in wind speed and relative humidity. The warning from these results is that water demand for irrigation is expected to significantly increase over the next decades on in Jaguaribe River Basin

A Continuous Drought Probability Monitoring System, CDPMS, Based on Copulas

The standardized precipitation index (SPI), is one of the most used drought indices. However, it is difficult to use to monitor the ongoing drought characteristics because it cannot be expeditiously related to precipitation deficits. It also does not provide information regarding the drought probability nor the temporal evolution of the droughts. By assigning the SPI to drought-triggering precipitation thresholds, a copula-based continuous drought probability monitoring system (CDPMS), was developed aiming to monitor the probability of having a drought as the rainy season advances. In fact, in climates with very pronounced rainy seasonality, the absence of precipitation during the rainy season is the fundamental cause of droughts. After presenting the CDPMS, we describe its application to Mainland Portugal and demonstrate that the system has an increased capability of anticipating drought probability by the end of the rainy season as new precipitation records are collected. The good performance of the system results from the ability of the copula to model complex dependence structures as those existing between precipitations at different time intervals. CDPMS is an innovative and user-friendly tool to monitor precipitation and, consequently, the drought probability, allowing the user to anticipate mitigation and adaptation measures, or even to issue alerts

On the Rainfall Intensity–Duration–Frequency Curves, Partial-Area Effect and the Rational Method: Theory and the Engineering Practice

This research evaluates the partial-area effect and its relationship with the rainfall intensity–duration–frequency (IDF) equations. In the Rational Method, if the critical rainfall duration is shorter than the time of concentration, the partial-area effect occurs. We proved that the partial area could exist for the general ID equation i=a/(b+td)c, only when c>1. For these equations, in the application of the Rational Method, the maximum discharge at basin outlet occurs for rainfall duration (td) equal to b/(c−1). Nevertheless, for that case, the Depth Duration Frequency (DDF) has a maximum at that rainfall duration. These situations are present in engineering practice and will be discussed in this paper. Research was done to look for IDF equations with c>1 in hydrologic engineering practice. It found 640 inconsistent IDF equations (c>1) in four countries (Brazil, Mexico, India, and USA), which means that a fundamental principle for building consistent IDF equations (i.e., c>1), published in the scientific literature since 1998, did not reach the hydrologic engineering practice fully. We provided some analysis regarding this gap between theory and engineering practice

Copula-Based Multivariate Frequency Analysis of the 2012–2018 Drought in Northeast Brazil

The 2012–2018 drought was such an extreme event in the drought-prone area of Northeast Brazil that it triggered a discussion about proactive drought management. This paper aims at understanding the causes and consequences of this event and analyzes its frequency. A consecutive sequence of sea surface temperature anomalies in the Pacific and Atlantic Oceans, at both the decadal and interannual scales, led to this severe and persistent drought. Drought duration and severity were analyzed using run theory at the hydrographic region scale as decision-makers understand impact analysis better at this scale. Copula functions were used to properly model drought joint characteristics as they presented different marginal distributions and an asymmetric behavior. The 2012–2018 drought in Ceará State had the highest mean bivariate return period ever recorded, estimated at 240 years. Considering drought duration and severity simultaneously at the level of the hydrographic regions improves risk assessment. This result advances our understanding of exceptional events. In this sense, the present work proposes the use of this analysis as a tool for proactive drought planning

GROUNDWATER VULNERABILITY TO AGROCHEMICAL CONTAMINATION

This research aimed at evaluating groundwater vulnerability to agrochemical contamination. To that end, we developed an index called Hydric Vulnerability and Agrochemical Contamination Index (HVACI), which integrates a geographic information system and fuzzy logic to measure catchment vulnerability to agrochemical contamination. Our case study investigates two sub-basins, the Baixo Jaguaribe and the Médio Jaguaribe, in the state of Ceará, Brazil. We built a logical relationship matrix involving economic and environmental information as a tool to enhance public managers’ decision-making capabilities. Evaluation was based on four categories of vulnerability — high, medium-high, medium-low, and low —, and we found that the joint area of the Baixo Jaguaribe and Médio Jaguaribe sub-basins presented the following levels of risk contamination: 80.3% of the area had low vulnerability, 3.5% had medium-low vulnerability, 3.0% had medium-high vulnerability, and 13.2% had high vulnerability. Geographically, the municipalities with high vulnerability to contamination by pesticides were Aracati, Icapuí, Limoeiro do Norte, Tabuleiro do Norte, and Quixeré. Therefore, HVACI is an important tool for directing environmental management efforts toward areas identified as highly vulnerable to agrochemical contamination

Jointly Modeling Drought Characteristics with Smoothed Regionalized SPI Series for a Small Island

The paper refers to a study on droughts in a small Portuguese Atlantic island, namely Madeira. The study aimed at addressing the problem of dependent drought events and at developing a copula-based bivariate cumulative distribution function for coupling drought duration and magnitude. The droughts were identified based on the Standardized Precipitation Index (SPI) computed at three and six-month timescales at 41 rain gauges distributed over the island and with rainfall data from January 1937 to December 2016. To remove the spurious and short duration-dependent droughts a moving average filter (MA) was used. The run theory was applied to the smoothed SPI series to extract the drought duration, magnitude, and interarrival time for each drought category. The smoothed series were also used to identify homogeneous regions based on principal components analysis (PCA). The study showed that MA is necessary for an improved probabilistic interpretation of drought analysis in Madeira. It also showed that despite the small area of the island, three distinct regions with different drought temporal patterns can be identified. The copulas approach proved that the return period of droughts events can differ significantly depending on the way the relationship between drought duration and magnitude is accounted for

Flash Flood Reconstruction and Analysis—A Case Study Using Social Data

This work proposes a methodology for post-flood analysis in ungauged basins with low data availability located in semi-arid regions. The methodology combines social perception with recorded data. Social perception can be a useful tool to enhance the modeling process in cases where official records are nonexistent or unsatisfactory. For this aim, we structured a four-step methodology. First, we create a repository with the information that reconstructs the analyzed event. Photos and news of the flood event are collected from social media platforms. The next step is to consult official government agencies to obtain documented information about the disaster. Then, semi-structured interviews are carried out with residents to obtain the extension and depth of the flooded spot. This social information creates an overview of the flood event that can be used to evaluate the hydraulic/hydrological modeling of the flood event and the quality of the recorded data. We analyzed a flood event in a city in semi-arid Brazil. The event caused several damages such as the breaking of dams and about 40% of the population was somehow impacted although the official rain data pointed to non-extreme precipitation