Open AccessArticle

Hydrological Monitoring System of the Navío-Quebrado Coastal Lagoon (Colombia): A Very Low-Cost, High-Value, Replicable, Semi-Participatory Solution with Preliminary Results

Andrea Gianni Cristoforo Nardini

^1,*

Jairo R. Escobar Villanueva

and

Jhonny I. Pérez-Montiel

^2,*

Fundación CREACUA-Centro Recuperación Ecosistemas ACUÁticos, Riohacha 440001, Colombia

Grupo de Investigación GISA, Facultad de Ingeniería, Universidad de La Guajira, km 3 + 354 Vía a Maicao, Riohacha 440007, Colombia

Authors to whom correspondence should be addressed.

Water 2024, 16(16), 2248; https://doi.org/10.3390/w16162248

Submission received: 11 July 2024 / Revised: 29 July 2024 / Accepted: 4 August 2024 / Published: 9 August 2024

(This article belongs to the Special Issue Climate Change and Hydrological Processes)

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Figure 1
Scheme of the typical hydrological and ecological cycle of a coastal lagoon in La Guajira: (a) dry season; (b) flood season with opening of la boca and outflow of semi-fresh water; (c) sea–lagoon exchange according to the tide. "> Figure 2
Navío-Quebrado (Camarones) lagoon: (a) wet season; (b) opening of the mouth (“la boca”); (c) the bar between the sea and lagoon (closed mouth). "> Figure 3
Study area: (a) general location; (b) location of specific points of interest. "> Figure 4
Location of hydrometers: (a) view from downstream at Puente Troncal; (b) view from the observation point at Puente Viejo; (c) rule at Puente Troncal; (d) rule at the same site during a flood (this is located on the opposite side of the pillar). "> Figure 5
Cross-section at Puente Troncal. It can be noted that the 0 of the hydrometer (on the right) was placed where the water was on the day of installation; however, the water level can be lower (the depth was estimated by directly wading into the section). This means that negative values of the water height h are also possible. The wetted topography was manually surveyed by measuring depth with respect to the water surface every 100 cm, as represented in the figure. "> Figure 6
Difficult Access to the measurement sites: (a) Puente Troncal; (b) Puente Viejo. "> Figure 7
Stage–discharge relationship (polynomial regression) of the Tomarrazon-Camarones River in Puente Troncal with gauging data from 23 April 2022 until 23 October 2023 (y denotes elevation m asl). "> Figure 8
Analytic relationships (approximated) for the cross-section of the river at P.Troncal: (a) wetted area A = A(h); (b) wetted perimeter p = p(h). "> Figure 9
Matching between measured Q and Q estimated via the Chezy–Manning equation (R2 = 0.9738), with data from 23 April 2022–23 October 2023. "> Figure 10
Surprise from new data on the Tomarrazon-Camarones River in Puente Troncal: (a) Stage–discharge relationship (power law regression, R2 = 0.9172) with gauging data from 23 April 2022 until 23 November 2023; (b) matching between measured and estimated values (red line: perfect matching, dotted line: linear regression with R2 = 0.9119). "> Figure 11
Deviation Q measured vs. Q estimated by the found stage–discharge relationship (m3/s) as a function of the water elevation yLagoon (in cm above sea level). The blue dotted line interpolates the points linearly. "> Figure 12
Improvement of the matching between measured Q and Q estimated by the Q = Q(yriver, ylagoon) relationship (light blue dots are the same as in <a href="#water-16-02248-f009" class="html-fig">Figure 9</a> for ease of comparison). Data until 23 November 2023. "> Figure 13
Extract of the time series of recorded data (at hourly time steps) showing the inconsistency between lagoon data and sea data, which are always higher than 0 and higher than the lagoon levels (top: sea elevation data kindly provided by DIMAR: daily moving average indicated by the darker line; bottom: lagoon water elevation data collected by our project). "> Figure 14
General view of the lagoon water level measurement system. "> Figure 15
Construction details of the water surface measurement system: (a) sealed inlet of the hydrometer; (b) filtering lateral surface of the piezometer covered by a plastic grid and inserted into gravel-filled holes; (c) fully installed system. "> Figure 16
Scheme of the construction details of the measuring systems: (a) hydrometer and (b) piezometer. "> Figure 17
Alteration of the measurement of the water level h because of the volume of the inserted rule. "> Figure 18
“Instantaneous altimetry” criterion: Elevation pattern of lagoon perimeter according to satellite images taken in 2017 (basis of the adopted DEM). The local peaks (“outliers”) are attributed to DEM imperfections, possibly due to imprecision in the definition of the water surface polygon which may create incorrect height values. What counts here, anyway, is the prevailing behavior. The mean elevation is denoted by the brown bar. "> Figure 19
Horizontality check: synchronic monitoring criterion: (a) original data obtained; (b) the three sets of curves refer to three different survey days (in May, no exchange with the sea or river inflow and negligible evaporation effect during daytime, so constant values; in June, outgoing flow is emptying the lagoon, although a moderate river inflow was present; in November a significant river inflow is filling the lagoon, in spite of a moderate open mouth); the top curves refer to the lagoon, the bottom ones to the river at the same time: a synchronic behavior is apparent, as well as the existence of an elevation difference of about 12–20 cm. "> Figure 20
Instantaneous altimetry test based on DEM analysis: Shore affected by lower (a) and higher (b) elevations; location of anomalous points: the most depressed point (y= −1 m.a.s.l) corresponds to the boca and was most probably captured near the surface of the sea; the highest one, on the other hand, lies in the middle of nowhere and seems to be a local imperfection. "> Figure 21
Details of the mouth and velocity measurements: (a) lagoon during an “open period”; (b) Our vehicle for surveying the cross-section; (c) Manual measurement of depth and velocity. "> Figure 22
Spatial pattern of 111 GNSS-RTK points (red). The background image is a Landsat 8 of 20 September 2022 when the lagoon was at maximum filling. The false color image identifies water (dark blue tone) under a combination of bands: NIR, SWIR1, and Red. "> Figure 23
Hypsometric curves: Surface area S = S(y) (m2); Storage volume V= V(y) (m3) related to lagoon elevation yL [masl]. Polynomial curves: S(y) = 8010914.35 y3 − 8335673.88 y2 + 7166288.16 y + 16056191.36 (R2 = 1.00); V(y) = 4983114.71 y2 + 15272088.13 y + 8414661.47 (R2 = 1.00). "> Figure 24
Climatological variables of the study area (from IDEAM data: Rain from Camarones station ID 15050010. All others from Riohacha station ID 15065180). "> Figure 25
Output of the monitoring system for the period of 10 December 2021 to 14 January 2023 (hourly time step; one square is 500 h), with no correction for the sea level data. At the bottom is the status of the lagoon mouth: C: closed; O: Open; S: Semi-open. "> Figure 26
Summary of the whole exercise conducted to set up the hydrological monitoring system. ">

Versions Notes

Abstract

Like many coastal lagoons in several countries, the “Navío Quebrado” lagoon (La Guajira, Colombia) is a very delicate and precious environment; indeed, it is a nationally recognized Flora and Fauna Sanctuary. Several factors, including climate change, are threatening its existence because of changes in the governing hydro-morphological and biological processes. Certainly, the first step to addressing this problem is to understand its hydrological behavior and to be able to replicate, via simulation, its recent history before inferring likely futures. These potential futures will be marked by changes in the water input by its tributary, the Camarones River, and by modified water exchange with the sea, according to a foreseen sea level rise pattern, as well as by a different evaporation rate from the free surface, according to temperature changes. In order to achieve the required ability to simulate future scenarios, data on the actual behavior have to be gathered, i.e., a monitoring system has to be set up, which to date is non-existent. Conceptually, designing a suitable monitoring system is not a complex issue and seems easy to implement. However, the environmental, socio-cultural, and socio-economic context makes every little step a hard climb. An extremely simple—almost “primitive”—monitoring system has been set up in this case, which is based on very basic measurements of river flow velocity and water levels (river, lagoon, and sea) and the direct participation of local stakeholders, the most important of which is the National Park unit of the Sanctuary. All this may clash with the latest groovy advances of science, such as in situ automatized sensors, remote sensing, machine learning, and digital twins, and several improvements are certainly possible and desirable. However, it has a strong positive point: it provides surprisingly reasonable data and operates at almost zero additional cost. Several technical difficulties made this exercise interesting and worthy of being shared. Its novelty lies in showing how old, simple methods may offer a working solution to new challenges. This humble experience may be of help in several other similar situations across the world.

Keywords:

monitoring; coastal lagoons; tidal water exchange; low-cost technology; participatory approach; Colombia

1. Introduction

1.1. Peculiarities of Coastal Lagoons

Coastal lagoons are among the most productive systems in the world [1,2]. Indeed, many species take advantage of the lagoons to feed and reproduce, remaining in these places for part of their life cycle. They provide a significant number of socioeconomic benefits for humans who exploit this productivity, particularly by fishing [3]. Coastal lagoons are characterized by shallow depths, differing greatly in size, morphology, trophic state, and salinity characteristics, which drive the biological structure, species composition, and fishing performance [4]. At its boundaries, the entry of freshwater—typically by rivers—provides hydrological forcing, as does the exchange of water between the lagoon and the open sea [5]. Due to the above, these ecosystems generate great motivation for researchers to study not only their productivity but also their hydrological and hydrodynamic behavior (inflow, exchange of flows, and water levels).

Coastal lagoons are characterized by a typical annual cycle (Figure 1). This usually starts when the feeding river system is flooding, thus originating a period of “high waters”, where the water level rises until the natural sand bar, separating the lagoon from the open sea, breaks down and creates an open mouth (“la boca”; in some cases, local inhabitants contribute to artificially creating an opening to avoid flooding their houses). In these conditions, the outgoing flow of semi-fresh water is felt by sea populations of fish (for Navio-Quebrado: Litopenaeus schmitti, Macrobrachium acanthurus, Centropomus undecimalis, Elops saurus, Micropogonias furnieri, Mugil curema, Mugil incilis, Mugil liza, Cathrorops spixii, Eugerres plumieri lito, Mugil liza, and Mugil curema) and crustaceans, which hence enter the lagoon looking for appropriate zones for reproduction and nursery. While the river freshwater input reduces (often remaining null for several months), the lagoon volume drops, and for a few months, an alternate flow exchange of water into and from the sea is established, according to the tidal pattern. In this period, the fingerlings and grown fish take advantage of this opportunity to exit into the open sea and “look for freedom and a new life”. This goes on until the sea waves prevail on this exchange process and recreate a sand bar, closing la boca. From this moment on, until the next cycle starts, the lagoon water evaporates, lowering its level (depth) and area, while salinity strongly increases. All fauna trapped inside are destined to die due to the hypersaline conditions unless a new flood comes in time. Regarding Navío-Quebrado, curious local fishermen collect dead or dying biomass—mostly composed of Elops saurus followed by mugilids [6]—as a delicious, although stinky, food (named “cachirra” by the natives of the area).

1.2. The Case of the Navío-Quebrado Lagoon

On the one hand, the interest in the Navío-Quebrado lagoon (Figure 2) stems from its intrinsic environmental value, primarily linked to the presence of a significant population of flamingos (Flamenco Rosado, Phoenicopterus rube). Indeed, it is because of this that it is a National Fauna and Flora Sanctuary. On the other hand, it provides important environmental services such as fishery, particularly shrimps (from which the alternate name “Camarones” comes), and is a tourist attraction, both for its scenery and for the observation of local fauna.

Threats and Problem Addressed

Since the first River Basin Management Plan (POMCA), developed by the Italian NGO Ricerca e Cooperazione in collaboration with the regional Environmental Authority Corpoguajira and the local Universidad de La Guajira [7] and coordinated by one of us, sedimentation induced by the sediment load of the Camarones River has been identified as a major potential threat. This issue was supposed to be linked to landslides in the headwaters, which transported large amounts of sandy material (as occurred in 1985). This awareness opened the query towards further investigation efforts. Nevertheless, until now, the only additional information acquired refers to a stratigraphic analysis of a nearby sample [8] (but not from the lagoon itself) and a more recent attempt by Parques Nacionales Naturales de Colombia Nacionales (jurisdiction of the Santuario de Fauna y Flora los Flamencos-SFFF) to measure the productivity of the lagoon and the fishing effort applied, as well as the counting of the Flamencos Rosados, the emblematic species of the lagoon, usually found mostly between November and March [9]. Fish suffer from a strong anthropogenic pressure given that fishing is the most important livelihood of local inhabitants, which makes rational control problematic. An eco-anthropogenic problem is due to the early capture of fish by locals (many of which are Wayuu indigenous people), preventing their growth to commercial size and consequently leading to a virtual income loss [10]. This reality generates a certain level of conflict between different fishermen groups and competition to capture the shrimp population before others can take advantage of it. Although there is scientific information from studies on the fish and insect communities [11,12], no recent information about the hydrology of the lagoon has been generated. There also are other threats due to the use of fertilizers and agro-chemicals in the basin, and also due to direct sewage discharge into the lagoon [13], manifested, for instance, in some episodes of bad water quality [14]. More generally, the Camarones river basin is subject to furious exploitation of its natural resources: industrial agriculture, raising cattle, and clearing the forest to feed the necessary ovens for cooking clay bricks are the major pressure factors affecting the hydrological regime. Finally, pressure from tourism is boosting urbanization and all connected problems.

Another very significant threat is associated with climate change. Rising sea levels, a likely reduction of freshwater supply, and increased evaporation, associated with a possible reduction of the available lagoon volume because of sedimentation, spontaneously raise the question of whether this system will survive as it is or will soon be incorporated into the sea. On the contrary, it could also be transformed into a productive mangrove zone or alternatively a rotten marsh (as seems to have happened in the far past, according to [8].

Therefore, it was decided to undertake a first attempt to set up a hydrological monitoring system. Once established, the data provided by such a system could allow us to set up a hydrological simulation model (water balance). With this model, it may be possible to explore future scenarios, possibly deriving useful indications for action.

1.3. Paper Aim and Structure

This humble paper presents the difficulties encountered in setting up a monitoring system and the solutions adopted. Its aim is to make decision-makers aware of the difficulties inherent in a territory such as La Guajira and, at the same time, to provide practitioners and managers with useful hints to simplify their efforts. It can also stimulate researchers to search for new ideas to overcome our difficulties. Finally, we believe that the whole exercise depicts an interesting scientific process where several potentially viable options are explored and a specific pathway is progressively defined. Its novelty lies in showing how old, simple methods may offer a working solution to new challenges, often in a more appropriate fashion than the more advanced technology.

The Method chapter of this paper is its core. It presents, in a plain fashion, the different attempts performed in order to set up the different components of the monitoring system. Therefore, it may look more like a project report than a paper, as it faces different issues, rather than setting up a particular specific methodology. However, this exercise, in our opinion, has the characteristics of scientific research, where the objective is indeed to set up the monitoring system. The data and graphs presented in each component of the Method chapter are not intended to be results; they are an intrinsic part of the definition of the method itself. Therefore, the Results chapter is simply the display of the data that have been collected during almost a year and a half of monitoring by the system, accompanied by a discussion about their meaningfulness. Strengths and weaknesses of the monitoring system are finally pointed out and indications for future development are established in the Conclusions, where a synthetic overview of the exercise conducted is provided.

As the reader may note, the literature review and discussion section is quite limited. This is due to the fact that we could not find significant contributions facing a similar problem. Many papers discuss specific methods/techniques, which have been carefully considered here, but they proved unsuitable in the end—as clarified—and, hence, a full related discussion would be out of scope and would further extend an already quite lengthy paper.

As the search for a feasible set up of the monitoring system has been a “long trip”, the information generated is quite extensive. To help the reader, a summary table is made available in the Conclusions section. This may be consulted, while reading the paper, as a kind of compass.

2. Methods: Practical Challenges and Adopted Solutions to Set Up a Monitoring System for the Camarones Lagoon

A hydrological monitoring system, aimed at feeding a hydrological model (water balance), for a coastal lagoon should include at least the following:

(a): Freshwater inflow by the tributary (the Tomarrazón-Camarones River). The discharge should be measured at a station sufficiently close to the lagoon to represent the whole water basin supply, but at the same time sufficiently far away to be influenced by the backwater effect as little as possible.
(b): Storage and release flows from changes in water volume stored in the lagoon. This implies being able to measure the level of its water surface and to know the morphometric relationships linking such levels to the stored volume (and surface area).
(c): Salty or brackish water exchange between the lagoon and sea (only when the boca is open), as this may be a key component of the water balance. Measuring this variable is not easy, but for systematic monitoring, the idea is to measure essential variables, namely the water surface elevation of the lagoon and of the sea, and to derive a relationship linking them to the exchange flow.
(d): Freshwater inflow from precipitation directly falling on the lagoon itself and from runoff from the local watershed into the lagoon. Both can be estimated from measurements of the precipitation at nearby sites and the area of the two components (the local water basin and lagoon); however, the latter requires data on rainfall–runoff relationships (model).
(e): Evaporation losses from the water surface of the lagoon: this can be calculated from direct estimates of evaporation rates or from indirect estimates based on formulas where the measured variables would be temperature, humidity, etc.

Filtration exchanges with the sea and the nearby area can be neglected at first as the bottom of the lagoon is considered to be basically sealed by fine sediments (silt and clay) and the water head’s potential to generate filtration with the sea is very low, while the potential zone of exchange (the mouth) is quite limited.

The physical system is shown in Figure 3, together with key elements.

It is spontaneous to think of a (possibly low-cost) technological system to measure several such variables. Low-cost systems are generally modular, thus allowing for the easy replacement of damaged parts. Modularity also allows for a wide freedom in the selection of components, including sensors, recorders, measurement algorithms, communication technology, the feeding source, and other characteristics [15,16,17]. These systems are suited for a variety of contexts, e.g., water quality monitoring (nutrients, dissolved oxygen, etc.) in a river [15]; environmental monitoring, e.g., the aquifer level, air quality, sediments, or the dynamics of wind-transported sands [16]; management of urban waters [17]; and measurement of water levels in a river [18]. Therefore, we first evaluated this possibility for the different components of the target system.

2.1. River Inflow

No gauging station exists on the Tomarrazón-Camarones River; therefore, the first idea was clearly to set up a new, low-cost monitoring station of the river stage h with automatic measurements (by a pressure or distance sensor) and possibly tele-transmission of data [18,19]. In parallel, the goal was also to set up a suitable stage–discharge relationship Q(h), analogously to what has been achieved by [5].

Unfortunately, our experience in the area led us to immediately discard this idea due to the high probability (or certainty) of rapid robbery of or damage to the devices: very poor people, who are quite numerous in the area, are prone to stealing anything that can reward them with amounts even smaller than a dollar.

Another option was to adopt satellite measurements of water level via-sensors, such as TOPEX/Poseidon, Jason-1, 2, and 3, ERS-1/2, Environmental Satellite-Envisat, ICESat, CryoSat-2, SARAL/AltiKa, and SWOT, with the support of software such as AlTiS, version 2.2.9 [20]. However, analogously, this option was discarded for several reasons. The channel is almost invisible from above owing to the riparian vegetation cover, the channel is too narrow (10–20 m), and the frequency of survey of satellites is too low for our purposes. Nevertheless, these tools have produced data for two decades that can be very useful for studying, for instance, the evolution of water bodies in general [21,22,23,24].

As the rainy season was about to start when we were designing the system—and missing it would be a significant loss of data—a very simple but robust and even economic solution was set up. A rule was painted on a fixed vertical part of the wall of the foundation pillar of a bridge. Two rules were set up in the only two bridges in the area (Figure 3b): Puente Troncal, the one selected for the routine measurements, and Puente Viejo, which is some distance upstream. This was conducted to perform a check on data coherence, explore the possible existence of a backwater effect, and provide an alternative calculation of flow based on the gradient of the water level (as explained later in this paper). Details of the rules on both bridges can be observed in Figure 4.

The selected cross-sections are sufficiently stable because the riparian material is mainly organogenic claystone conglomerate, although, of course, a certain level of change in the sediment deposits may take place. With a survey during dry conditions, we determined the geometry of the cross-section so that the relationship A = A(h) was obtained, where A is the area of the wet cross-section for water level h (Figure 5).

To simplify the routine measurement process as much as possible, we ensured that the water surface and the rule were visible in any condition from a selected site on top of the bridge and opted for just taking a picture, ideally a couple of times each day at (more or less) fixed times (early morning and mid-afternoon). Providentially, we could arrange a formal agreement with the local National Parks office, which immediately and enthusiastically shared the necessity of setting up such a project and accepted the pledge to have one of its staff members pass by the site and take the picture. In addition, we made a private agreement with a local person (muchacho) with a motorcycle, who, under a very reasonable payment, would commit to echar un ojo (having a look) at the river every day and who, in case of a flood or an emergency (e.g., the impossibility of a Parks servant passing by), would take an additional picture registering the time and immediately send it to us by WhatsApp^® version 2.22.7.73. In spite of all these arrangements, in practice, however, most of the time, only one measurement a day was obtained (and some days even that was missing).

Still, the second part of the problem had to be faced: setting up a stage–discharge relationship. This meant gauging the flow rate, particularly during high flows, which is quite a dangerous task. The use of a classic current meter was out of the question because the bridge is too high over the water to hold the device with a long rigid arm, while an ADCP (Acoustic Doppler, Current-meter Profiler; [25]) would require accessing the water body during high water to place a guiding rope/wire, a method that is physically very hard and dangerous owing to the dense vegetation one must cross and the slippery ground (Figure 6). In addition, and most importantly, our University simply had no such device yet. On the other side, wading into the river would certainly be impossible because it becomes very deep and fast with a slippery bottom, while in low water, wading would interfere with the flow we had to measure. Other methods such as salt concentrations or dyes were not viable again because of the impossible access and because the river feeds a natural protected area. This is why we chose the old, somehow “primitive” method of throwing a floater and measuring the time elapsed to cover a fixed, known distance (of 11 m), and averaging amongst several (at least three) launches along different flow lines across the section. Only biodegradable objects such as fruits (ideal because they float but are almost fully immersed, meaning that the wind effect is minimal) or short wooden sticks were used. The flow rate was then obtained by just multiplying the average velocity by the area of the wet section, determined based on the water level h and the known geometric section A = A(h) previously determined in dry conditions (from Figure 5). No correction to the velocity for the border effect was applied because the velocity field is quite complex and the main flow sometimes occurs on the side rather than in the central sector.

This approach would appear to most readers, as it does to us, as quite anachronistic and primitive. Nevertheless, the obtained data after more than one and a half years of observations behave surprisingly well, as shown in Figure 7 (interpolated by a polynomial regression equation).

It is reasonable to wonder whether these 32 data pairs are sufficient to accurately calculate the relationship. The answer can perhaps be found in the final result, the reasonable consistency of modeled lagoon behavior (depending also on river inputs, estimated through this relationship) with respect to measurements of the lagoon state; however, this is dealt with in another forthcoming paper. Here, to confirm this positive result, and for scientific curiosity, a different method was adopted to estimate the flow rate based on classic hydraulics, i.e., by applying Chezy Manning’s Equations (1) and (2) [26], which is often used in current research (e.g., [27,28,29]). Here, we used the area A = A(h) and wetted perimeter p = p(h) relationships obtained from the cross-section geometry of Figure 5 by points (Figure 8), and for the slopes [m/m] of each measurement (at a given date and time), the water elevation difference Δy between the two bridges monitored (y_T at P.Troncal and y_V at P.Viejo, see Figure 3), divided by their distance L along the stream axis (L = 1132 m from Google Earth^® images), establishes a reference elevation for both (the “IGAC 0”; with IGAC: Instituto Geográfico Agustin Codazzi, the official Colombian entity in charge of geographical issues and maps), so transforming the water depth h of our hydrometer into an elevation y. With this position, the stage–discharge curve at the P.Troncal station, as shown in Figure 9, was obtained by estimating the Manning friction coefficient n from manual trial and error to fit the measured values as far as possible (obtaining the value n = 0.0447 in the SI system). Again, the results are surprisingly nice, as demonstrated by Figure 9. Nevertheless, for the monitoring exercise, the empirical stage–discharge curve (based on our measurements) is preferred simply because this is closer to reality and because more data will be available in time, hopefully making it more reliable gradually.

v(h) = 1/n R(h)^2/3 s^1/2

(1)

Q(h) = V(h) A(h)

(2)

with:

v [m/s]: average velocity in the cross-section

Q [m³/_s]: flow rate

h [m]: water depth in the section

A [m²]: area of the wetted cross-section

R [m]: hydraulic radius, i.e., R(h) = A(h)/p(h)

s [-]: the river slope

p [m]: wetted perimeter

y [m.a.s.l]: water elevation: y = h + h₀ with h₀ IGAC reference [m.a.s.l].

Figure 8. Analytic relationships (approximated) for the cross-section of the river at P.Troncal: (a) wetted area A = A(h); (b) wetted perimeter p = p(h).

Figure 9. Matching between measured Q and Q estimated via the Chezy–Manning equation (R² = 0.9738), with data from 23 April 2022–23 October 2023.

Novelties

However, things are never as smooth as they appear at first sight. While the data collection process was ongoing, we updated the exercise after an additional month (November 2023), when new significant flood events took place. Figure 10 shows the stage–discharge curve with the new data, which shows significantly worse behavior, although it is still not bad.

The suspicion arose then that the deviations detected in the stage–discharge curve of Figure 10 could depend on the backwater effect from the lagoon. Indeed, Figure 11 plots the flow rate deviations (Q measured and Q estimated by the empirically found stage–discharge relationship) as a function of the water surface level of the lagoon, showing a certain tendency to over-estimate Q (i.e., a negative deviation) for increasing values of the water elevation in the lagoon (i.e., towards the right), as expected.

Therefore, we sought to improve the found power–law relationship by incorporating a dependency on the water elevation in the lagoon y_L, i.e., Q = Q(y_T, y_L). Specifically, a relationship with a term that would reduce the flow value Q for a lagoon elevation y_L closer to the river stage elevation y_T at P.Troncal (always higher than y_L) was set up, as shown by Equation (3), that simply mathematically expresses this concept. Its four parameter values have been calibrated by trial and error (y in [cm.a.s.l]):

Q = a (y_T − y₀)^b [1 − 1/e^θ(yT−yL)] [m³/_s]

(3)

where the parameters “a, b, y₀, and θ” were determined via calibration and assume the following values (Equations (4) and (5):

a = 0.13299; b = 1.00927

(4)

y₀ = −1.900; θ = 0.02600

(5)

The result is shown by the corresponding matching graph (Figure 12), where a certain improvement is apparent both in terms of a closer position of the linear tendency line to the perfect matching line (solid red, 45 degrees) and in terms of dots that are closer, in general, to that line (indeed, R² = 0.9335 overcomes the value obtained by the mono-dimensional regression, Figure 9). The improvement, however, is more relevant for low values of Q; however, this is clearly reasonable as the backwater effect of the lagoon vanishes for high flows as they are associated with high river stages while the lagoon water elevation moves in quite a limited range. It is certainly possible to better calibrate the set of parameters and even to find better functional relationships; however, for the moment, this is the stage–discharge relationship adopted hereafter.

2.2. Sea Level

The sea level is a fundamental variable because it determines the exchange relationship between the lagoon and the sea according to tides and the status of the mouth and, as such, it governs the annual life cycle of the same lagoon.

At first, the idea was to install a dedicated sensor to measure water levels with high frequency (as reported, for instance, in [30]), but this idea was immediately discarded for the same security reasons already explained above and also for the absence of a suitable installation site. A much simpler solution was hence adopted by simply using existing reported sea elevation data (y_S); in our case, the tide gauge at Puerto Brisa (see Figure 1a) located 39 km away from the mouth of the lagoon is the closest one.

However, getting the data—which are collected and owned by DIMAR (Colombian Dirección General Marítima y Portuaria)—is a process that requires administrative steps and time, as hourly data are not available online; hence, data are always obtained with a delay of a few months and only under explicit request. Another difficulty is the format of the data: they are delivered partly with a dd-mm-yyyy date format and partly with a mm-dd-yyyy format. A harsher difficulty is creating, within a continuous, hourly (Excel^® 2019 MSO version 2406) data record sheet, an automatic reference to other sheets where our discontinuous time data of measurements of river flowrate and level, measurements of the lagoon level (usually bi-daily between 7–9 a.m. and 4–6 p.m., but with exceptions), and measurements of the area of the mouth and lagoon–sea exchange flow rate were recorded (by transcription of the physical field data formats). These data are collected at different, irregular times with many missing data (“holes”). To deal with this situation, we developed a specific Excel spreadsheet with suitable algorithms that proved to be indispensable, although far from trivial.

However, another, more serious problem concerned the altimetric consistency of data. According to common sense, the tide should oscillate most of the time around 0 with positive and negative values, although periods of higher or lower moving averages are possible due to particular combinations of astronomic and the meteorological drivers. However, here, almost all of the sea elevation data appeared to be much higher (about 60 cm) than the topographic IGAC 0 (Figure 13), which is impossible because, in those conditions, no flow from the lagoon to the sea could occur, while it is clearly physically expected and was indeed observed in the field. We then asked for formal explanations from the relevant institutions (DIMAR, IGAC, and IDEAM—Instituto de Hidrología, Meteorología y Estudios Ambientales) and understood that the tide gauge, like the entirety of the Colombian national geodesic network managed by IGAC, is referenced to a sea level of 0 located on the Pacific coast in Bonaventura town, which is a completely different water body. Indeed, the average sea level in the Caribbean—where Puerto Brisas and Camarones are located—is in general 28 cm lower (in [31,32]). However, this fact does not solve the mismatch as both the river elevation and that of the lagoon are referenced to the same IGAC 0 and as such should be consistent. Therefore, the final explanation is that a deviation exists between the geoidal and the ellipsoidal models of the Earth’s surface in Colombia, as at present, there is no official update of the Colombian model. This is indeed consistent with the results found by [33] when trying to validate geometric leveling points with classic topography and LIDAR data, finding an average difference of 0.63 m.

In order to proceed, it was therefore assumed that the P.Brisa tide gauge utilizes a different (unknown to us) local reference and without searching for that datum, the mismatching was solved by adopting a very operational criterion. As will be detailed in a forthcoming paper, we just imposed that the lagoon–sea flow exchange process was physically meaningful. This means that when the observed flow was outgoing (from the lagoon into the sea), the lagoon water elevation should be higher than that of the sea, and vice versa. Luckily, a meaningful value of a fixed vertical translation of the tide gauge data could be found by trial and error, which could fulfill this condition in all observed cases, except one. Considering that just a tiny level difference (a few centimeters) is involved, and that the tide gauge is 39 km apart and that there are often strong winds, the obtained result (denoted with y_S*) can be considered fully satisfactory.

2.3. Lagoon: Water Level

The most spontaneous solution for the measurement of the water elevation of the lagoon seemed to be the installation of a rule fixed at a pole in a relatively central place in the lagoon so that even for low levels, the rule would still be immersed (as the lagoon is quite shallow and the bottom is characterized by a very gentle slope). Measurements would be taken by the personnel of National Parks from their headquarters on the shore using binoculars. However, this idea was soon discarded because the reflection of sunlight on the water would make remote reading impossible and because wind, the perennial companion of sunlight, generally provokes a high-frequency, irregular wave system with an amplitude of about 5–15 cm, which would severely affect the measurements. Even an automatic sensor, which might allow a certain degree of digital filtering of data, was discarded because of the usual security problem and in line with the idea of creating a very basic system.

Therefore, a manual device installed at the National Parks’ headquarters located on the lagoon shore (Figure 1 for general location and Figure 14) was chosen.

It is licit to wonder whether the foreseen monitoring frequency of twice a day is sufficient to capture the dynamics of the lagoon. According to Shannon [34], in a linear (linearized) dynamic system, sampling should be carried out with a frequency not lower than T/10, where T is the minimum time constant. This criterion, as will be explained in a forthcoming publication, leads to a very wide range of values; specifically, when the mouth is open, the criterion provides values of 1.6 to about 5 h (depending on the filling status of the lagoon, being quicker when it is low); when the mouth is closed, and the core dynamics are governed by evaporation, values range from a couple of days to three months. Evidently, only in this second case is our monitoring definitely adequate, while, when the mouth is open, our measurements cannot capture the full oscillation process, which is tuned to the tide oscillations. Nevertheless, the data obtained can be very informative, as shown in the rest of this paper.

A mixed solution was eventually preferred, comprising a hydrometer (Figure 15a) on the shore to be used for medium-high levels and a piezometer for situations with lower levels and, consequently, a dry hydrometer (Figure 15b). As water levels can become lower than the local terrain, the hydrometer is enclosed in a typical yellow sewerage pipe set in a vertical position and the reading is performed by manually inserting a rule and reading the depth with respect to a horizontal reference set on the headquarters’ structure as indicated. To avoid the disturbance from the high-frequency wave oscillations, the device has a feeding tube with a reduced diameter section of Φ = 1.27 cm (which allows only a very small flow to pass through, according to the change of head from the lagoon surface and local, vertical movement), while the main vertical pipe section is proportionally much larger (Φ = 7.62 cm) so that the water volume input due to a flow increment translates into a much smaller vertical change, so fulfilling the dampening effect (“low-pass filter”). This function, on the other hand, is intrinsically guaranteed for the piezometer as the seepage across the soil cannot accelerate significantly; however, on the opposite side, this may dampen frequent (hourly) oscillations. The important difference is that water enters the hydrometer through the tiny tube, directly governed by the head on top of it, while water enters the piezometer by direct seepage across the soil matrix around it; therefore, the former cannot provide reliable data when the lagoon level drops below the sucking tip of the tube, while the piezometer works improperly when the level overcomes the ground level and even more so when it pours into the pipe from the top of the device.

The implementation of the devices is based on “home-made” very-low-cost technology, as shown in Figure 16).

Measurements, after training, were taken by National Parks personnel twice a day, usually around 8 a.m. and 4 p.m. The operation consists of inserting a rigid rule inside the pipe with a block to set on the pipe edge and reading the wetted depth; from this, knowing the elevation of the reference beam edge, the elevation of water inside the pipe is determined. An alternative would have been a transparent cylinder with graduations marked on its external surface; however, the intense sunlight of the site would very soon deteriorate any plastic material, making reading impossible. The method adopted is more robust, but it requires corrections to be made because, as shown in Figure 17, while inserting the rule (with a cross-section a*b), there is a Δh super-elevation that must be removed from the reading.

This correction is determined by imposing that the volume increment inside the pipe be equal to the volume of the piece of wet rule, according to Equation (6):

Δh (A_c − a b) = a b h

(6)

A_c = π D²/4: area of the pipe’s internal cross-section

D [cm]: internal diameter of the pipe

h [cm]: depth of water inside the pipe already altered by the presence of the partly wet rule (which is the reading effectuated by Parks staff)

Δh [cm]: height difference generated by the rule

a, b: dimensions of the rule stick (specifically: width, a = 3.8 cm; thickness b = 1 cm).

From this, one obtains the correction to be applied to the reading, as shown in Equation (7):

Δh(h) = a b h/(A_c − a b)

(7)

2.4. Lagoon: Horizontality Hypothesis

A doubt arose about the fact that the water surface of the lagoon may not be horizontal all the time (or never), mainly because of the effect of wind or due to the hydraulic conditions governing the input and output of water flows when the mouth is open or when the river is flooding.

To ascertain whether the horizontality hypothesis can be acceptable, we adopted two criteria:

“instantaneous altimetry”: The digital elevation model (DEM) we utilized is based on photogrammetry and was generated from an aerial image dataset collected in 2017 (generously provided by a national government agency called ‘Fondo de Adaptación). The resulting orthophoto mosaic survey can be assumed to be instantaneous; therefore, the elevation of the water surface border, all around the lagoon, would be constant, were the hypothesis of horizontality verified. Unfortunately, the photo was taken in a dry period, and hence with a low level and small water surface, so that any structural difference cannot be very marked; nevertheless, from Figure 18, a certain non-uniformity is seemingly evident, indicating that there might have indeed been a certain degree of tilt;
“synchronic monitoring”: By measuring the water elevation during the day with a relatively high frequency (every hour or so), both with our installed hydrometer and at the same time at an opposite point, namely the river at P. Viejo (so close to the lagoon that it can be assumed to coincide with its level at that point; see Figure 1), it should be possible to detect any height difference. The results show a systematic elevation difference of approximately 15–20 cm between the two points (Figure 19).

The outcome of these tests is not that straightforward to interpret. The first test is consistent with the conclusion that a certain tilt does exist, meaning that the horizontality hypothesis should be dropped. Possible reasons for this behavior are the sea outlet drawdown effect (as witnessed by our own data on the lagoon–sea exchange process according to hydraulics), the river input hydraulic load (e.g., [35]), and wind seiches, although the latter are more relevant in large water bodies (e.g., [36,37]). However, the three campaigns were conducted on different days with different conditions at the mouth. Only in November was the river inflow really significant, eliminating the first two options; however, this would explain why the difference visible in Figure 19b is smaller, as the river carrying a higher flood rose a bit. In turn, frequent moderate winds are a reality, which would explain the presence of seiches.

However, as visible from Figure 20 and Figure 1, it would be logical that the object with a higher elevation was the site at the river mouth (P.Viejo). However, from Figure 19, it is evidently the reverse, as the river elevation is always lower than the lagoon elevation at its hydrometer. Several explanations can be conceived. One is that the seiche changes periodically and, by chance, all three campaigns resulted in the opposite situation to that of the satellite image taken in 2017. However, this is very unlikely as our (qualitative) record of wind direction says that the wind was more or less the same in the three conditions in terms of direction and intensity.

Another possibility is that the DEM assessment is not reliable; however, this hypothesis is likely to be dropped because we found a relatively reasonable consistency between the elevations and surface areas derived from the DEM and the lagoon elevation measurements (see the paragraph on morphometry). It may be possible, however, that it is reliable on average, but the differences it shows (higher and lower zones) are not, a possibility that could also be due to imprecisions in the definition of the water surface polygon. A third possible explanation is that there is a structural bias in the topographic survey fixing the “zeros” of the hydrometers. Indeed, this seems the most likely option as, although the survey started from official IGAC references in both cases, they were not physically coincidental owing to logistic constraints (absence of signal for the RTK equipment close to the lagoon mouth): an absolute difference between 20 and 40 cm is therefore possible. We cannot conclude whether there is a tilt or not because according to the instantaneous test (DEM), there seems to be; however, the time pattern test seems to contradict this conclusion as the detected difference has an opposite sign (however, this might be explained by a different topographic reference). More importantly, on all three days (with very different conditions at the mouth and the river), the results kept the same sign and even the same absolute value (which was a little lower in the third case, but this can be reasonably explained by the significant river inflow), which seems less likely and is more consistent with a hypothesis of identical levels (i.e., a horizontal surface or the absence of tilt) plus constant topographic bias.

However, it is important to observe that the measurement station of the lagoon level (hydrometer and piezometer) lies outside of the likely affected zones (Figure 1 and Figure 20). Therefore, assuming that the identified conditions (higher and lower zones) do not rotate around the lagoon, the water surface measurements can be considered representative of the real water surface elevation, which is extremely important for monitoring and modeling purposes. In principle, the possible bias between the river hydrometer and the lagoon hydrometer would not affect data acquisition because river elevation is used just to feed the local river stage–discharge relationship (and the relationship with the upstream station at P.Troncal that is using the same reference). However, there may be a subtle influence when the backwater effect is important through Equation (3), but this is negligible for high flows (which are the most important ones). On the other hand, lagoon elevation data are used just in relation to sea elevation data. However, the possible tilt of the lagoon water surface could be affecting hydrodynamic modeling.

In any case, our investigation still goes on to fully understand what is happening there. As a collateral note, it is important to note that the data on which this discussion is based cannot be considered exhaustive and fully representative as the DEM is quite imprecise (see par. 2.6), while our synchronic monitoring did not capture data at nighttime.

2.5. Lagoon: Exchange with the Sea

Being able to measure the exchange flow between the lagoon and the sea is key to setting up a water balance, even more so when water quality is dealt with. The key issue is finding a way to measure (or estimate) this flow in the simplest way.

Normally, there are one or two periods of the year when the lagoon mouth (“la boca”) opens and a significant flow of freshwater outgoing occurs; after a few days, the flow alternates twice a day between outgoing and incoming depending on the tide (and possible additional river floods) until the mouth closes again. This is quite a complex phenomenon, which is not easy to measure and hard to predict. Indeed, the opening date depends mainly on the arrival of the first significant river flood. This moment may vary greatly from year to year and may occur twice a year, owing to the bimodal hydrological regime with two wet seasons from April to June and September to November, respectively [38]. Once the mouth is open, its geometry varies depending on the river inflow, the tide pattern, and the average sea level, usually approaching its maximum area in about two weeks. That configuration is usually held for one or two months and then the closure process starts, which is quite slow at the beginning and then accelerates, possibly during an interval of a month. The mouth area also varies during the day. However, this process is clearly different every year. In 2022, the opening lasted 36 days (from May 29 until July 4), and the second opening period, usually stronger, lasted a bit longer than 3 months (from 21 September 2022 until 5 January 2023, a total of 106 days).

The key problem to be addressed at this stage of monitoring is just measuring the water flow in several moments during the open mouth period, for both outgoing and incoming flows, and then setting up a relationship that determines the exchange flow Q_B (positive or negative) as a function of, possibly, the cross section area A, and the height difference between the lagoon water elevation (y_L) and that (y_S) of the sea, as shown in (Equation (8)):

Q_B = Q_B(A; y_L, y_S) = Q_B(A; y_L − y_S)

(8)

Probably, the most suitable manner to carry out such a measurement is by using a digital current meter such as ADCP (Acoustic Doppler, Current-meter Profiler; [25]) guided by a cable through the section. However, several reasons impeded this solution. Firstly, very pragmatically, our institution does not own such a device and the regional environmental authority was reluctant to lend us theirs because it can quickly become spoiled in brackish or salty water. Secondly, the wind can become quite strong and so does the wave surge. Therefore, the device, floating on the surface, would move significantly and irregularly and the data would become very noisy. On the other hand, consistently with the framework adopted, we chose to keep technology very simple and low-cost; therefore, we just pulled a rope as a reference across the section, and onboard a boat driven by hand through poles (an engine would alter measurements and easily get into trouble because of the vertical oscillations and irregular bottom), we measured the depth every 2 or 3 m (detected by colored knots on the rope) with a rule and the velocity with a current meter (two different devices to conduct a quality check on data: Manufacturer General Oceanics Environmental, Model 2030R Mechanical and manufacturer The Geography Specialists, Gepacks brand, model MFP126) at a depth of about 60% of the total depth to be hopefully more representative of the vertical averaged longitudinal velocity (see Figure 21).

By adopting this method, several measurements have been carried out in different conditions, capturing both outgoing and incoming flows. This allowed us to set up a reliable relationship as expected and hoped (as will be described in a forthcoming paper). Therefore, actual systematic monitoring is reduced to components that have already been considered: the lagoon and sea water elevations.

2.6. Lagoon: Morphometric Relationships

As a basis for monitoring the storage changes, it is key to count the functional relationships: elevation–surface area and elevation–volume; these changes are indeed key components for the water balance. The water surface greatly varies with its elevation; this makes it imperative to merge a topographic representation of the zone with a bathymetric one.

We disposed of a set of aerial images taken during the dry season (17 March 2017) by a photogrammetric tripulated flight from an elevation of 1100 m above sea level (size of pixel: 20 cm). By using photogrammetric processing (via the Agisoft Metashape^® software version 2.1.2), we generated an orthophoto mosaic of the whole scene and a dense points cloud describing the topography of the surrounding area around the lagoon. These points were manually edited and classified by using the ‘Auto-Classify ground points’ tool of Global Mapper Pro version 18^®.

The bathymetry was reconstructed based on a set of 111 lagoon bottom elevation measurements directly determined by a GNSS-RTK from a boat, during 19, 20 of September 2022, together with an SIG-supported spatial analysis. The spatial pattern of measurement points reflects more operational navigation constraints (wind, depth, and distance) than logical planning (Figure 22).

The adopted GIS strategy (ArcGIS Pro) to generate the bathymetric surface is articulated in 6 steps: (i) Geo-statistical interpolation (Kriging) of acquired points via GNSS-RTK. (ii) Extraction and smoothing of the resulting elevation curves. (iii) Interpolation of curves through TIN. (iv) Rasterization of the TIN generated. (v) Conversion of the bathymetric raster into a cloud points format “*.las” by utilizing the option “Export Layer to New File” in Global Mapper. (vi) Integration and interpolation of the photogrammetric points cloud and bathymetric surface to achieve their connection and thus the final topo-bathymetric DEM. For this last step, we adopted the tool “LAS Dataset to Raster” of ArcGIS Pro.

Independently, measurements of depth were taken by a sonar device (Garmin Striker) during the same bathymetric campaign, while in dry conditions, we carried out point GNSS-RTK measurements in the floodable zone of the lagoon (then in dry conditions). All of this was to create a database with which validation of the generated topo-bathymetric DEM would be possible.

The key outputs of this activity are the surface area–elevation S(y) and volume–elevation V(y) relationships which have been obtained by points (Figure 23) by means of the r.lake.xy module, a spatial modeling tool hosted in GRASS GIS ^® software version 7.8.7. This module fills the water body (topo-bathymetric DEM) from a given elevation until a specified elevation is achieved. This tool requires an input of a raster DEM, a maximum water elevation, and its location coordinates (x,y).

A final key check was to ascertain the coincidence of DEM elevation with measurements of the lagoon water surface. More precisely, the idea was to identify some dates with different conditions of the lagoon (at least 4); given the date, we would determine the area S of the water surface from satellite images (transformed into a polygon and eliminating possible “holes”). Then, from the inverse curve y = y(S), we would obtain the elevation y to be compared with the elevation measured that day by the hydrometer/piezometer devices and determine a fitting measure. We obtained an RMSE value of just 8.4 cm (Table 1), which is considered satisfactory. Data from May 31 show the maximum deviation; however, a measurement error seems unlikely because both the piezometer and the hydrometer devices recorded a similar jump between morning and afternoon (a cause for this jump is a possible pressure effect due to stronger winds on the water surface). The significant deviation with respect to the DEM value is probably due to the fact that this value is not associated with a specific time instant, while the measurement is, so they are most probably out of phase.

2.7. Evaporation, Inflow from Runoff, and Direct Precipitation

Evaporation from the lagoon water surface is obtained as surface area S times the evaporation rate e(t) [mm/day]; for the latter, the simplest way is to acquire data about the relevant meteo-climatic variables already monitored in a nearby gauging station (visible in Figure 3) and then apply a suitable formula from the literature. Among the existing stations, the only one with data in our period is Camarones (point in Figure 3). However, it has to be noted that—apart from the rainy days—the meteorological conditions are quite constant in the area, with strong solar radiation, temperature, low cloudiness, and moderate to strong winds. Therefore, evaporation does not vary much (Figure 24).

To determine the direct precipitation input to the lagoon, it is sufficient to know the precipitation itself, which is one of the classic variables already measured in nearby stations. The only issue is ensuring their availability for the period of interest for ex-post simulations and continuous measurements for new monitoring. Luckily, there exists a rainfall gauging station on the official IDEAM network (available at http://dhime.ideam.gov.co/atencionciudadano/, accessed on 18 April 2024) in the nearby town of Camarones (Figure 3).

For the runoff from the local catchment draining into the lagoon, the same discourse holds, although a kind of rainfall runoff model must be developed, which is described in another forthcoming paper.

3. Results

Figure 25 shows the output of the monitoring exercise obtained until this paper was written. The sea data shown are the original ones, without the correction established (see Par. 2.2) to avoid overlapping curves and allow an easier interpretation of the Figure. It is apparent that the hourly tidal cycle is well-hidden behind additional oscillations that are quite complex and irregular; moreover, there appears to be a growing trend (notice that a 500-step interval corresponds to 20.8 days, which is approximately a Moon month).

The data from the piezometer and the lagoon hydrometer are quite consistent in general, although there is a certain unexplained deviation. Many factors can intervene such as wind pressure, which acts more directly on the free water surface than on the underground phreatic surface, or reading errors. Apart from the initial period (until 4 April 2022 when the devices were adjusted and deepened), it can be noted that for low levels, the piezometer provides higher values, while for high levels, in most cases, the opposite occurs. Consistent with the spirit of using the two devices, we decided to utilize the hydrometer data for y (cm.a.s.l) > −20 (cm.a.s.l), which is where the feeding tube is fully immersed, while the piezometer data are utilized below that threshold (see Figure 16).

It is worth noting that, in spite of their numerosity, there are only two measurements a day and this means that it is possible that these data do not capture the maximum and minimum values that actually occurred (i.e., as already noted, the sampling frequency is not high enough to capture the whole phenomenon). This is why they are represented as points with no connecting lines.

The behavior of the lagoon level is fully consistent with the status of the boca: as soon as it opens (fully or partly), the surface starts to oscillate synchronically to the sea tide. As soon as the boca closes, the level starts dropping because of evaporation, unless a flood input comes from the river. It is also apparent, however, that several river inputs are missing or underestimated (top graph), which is unavoidable as the river was measured just once a day.

4. Discussion

A system quite similar to ours is described in [5] for some North African coastal lagoons. However, to measure the water level, they adopted both human-read hydrometers (or “stage boards”) and a set of automatic sensors (that could not be installed everywhere). Their effort, differently from ours, was not aimed at providing all the variables needed to set up a water balance; in particular, they did not measure the lagoon–sea water exchange, although interesting observations were provided. In addition, they explored how the tidal effect propagates across the lagoon, but they did not show the simultaneous plot of the relevant variables that is illuminating when searching for a cause–effect relationship.

The monitoring system set up for Navío-Quebrado relies on a number of assumptions that may be worth highlighting as they also mark the intrinsic limitations of the output. Concerning river discharge measurements, an underlying assumption is that the river section selected is suitable for capturing the whole flow rate transported by the river and this, rigorously speaking, is not always the case: when the values are very high, part of the flow can occur by direct runoff outside the river channel. However, these are quite exceptional events. Another assumption is that the river section’s geometry does not vary with time, but this is quite certain because of the geomorphic character of the site, as already mentioned. The possible dependence on the lagoon level (backwater effect) has been explored and explicitly included, although in an approximate form. However, the greatest limitation is that the manual “once a day” measurement cannot fully capture the relevant flow hydrograph, which is therefore missing several significant inputs. This is made evident by the overall data plotting (Figure 25).

Concerning the lagoon water body, an explicit assumption is that filtration into and from the lagoon is negligible, a fact that could and should be ascertained by installing a number of piezometers capable of detecting filtration fields. We do believe, however, that this flow is quite marginal, based on the type of soil. The horizontality assumption has been explored, but the conclusion cannot be considered final and should be verified by more careful instruments and campaigns; this can be an important element affecting the quality of measurements. A related, implicit, assumption is that the sea level data obtained from the tidal gauging station Puerto Brisa, located about 40 km apart, can be transferred instantaneously and without correction to the lagoon mouth (“la boca”); this can be a serious limitation because of the interplay of winds and water currents and would require thorough study. However, the checks performed in this study seem to affirm that this assumption is acceptable.

Another, quite crude, assumption is that the adopted selection criterion between the piezometer and hydrometer data to provide a water surface elevation, now based just on a water elevation threshold, is appropriate. Perhaps, a different threshold would have worked better, a varying threshold is necessary, or even the explicit representation of some dynamic (currently unidentified) process is needed. Several experiments can be conducted in this sense. Another obliged assumption is that the manual “twice-a-day” reading of water levels is enough to capture the dynamic behavior; this is, in principle, a significant limitation where the rapid variations associated with the tides during open-mouth periods are concerned. However, the overall data obtained still seem sufficient to meaningfully reveal the actual behavior of the lagoon.

Despite all of these doubts, we have a very pragmatic criterion: the data obtained are quite consistent (Figure 25 and comments); moreover, when adopted to feed a simulation model (as explained in a forthcoming paper), the outputs are quite satisfactory.

Last but not least, there is a non-technical issue that deeply characterizes and severely limits the functionality of our system: its participatory dimension, which is simultaneously a strength and a weakness. This is further commented on in the next paragraph.

5. Conclusions

Conceiving and installing a monitoring system for the Camarones lagoon has been a small adventure, through which many doubts have been solved and suitable methods and tools have been tested and applied. Figure 26 summarizes the key components of the whole exercise.

The system is sufficiently reliable, as the various consistency tests (alternative estimation methods and matching graphs) and the observation of outputs demonstrate. Some weaknesses are nevertheless evident, such as the frequent lack of river input data.

Although the project has already provided information suitable for testing a simulation model, which will be described in a forthcoming paper, it is intended to be continued and strengthened. A significant improvement would be the ability to monitor the river inputs continuously (at least hourly); at the moment, the only way to address this need seems to be the installation of a basic automatic station, integrated with the manual monitoring already put in place and with the awareness that the devices will have to be replaced with a certain frequency because of damage and theft. Certainly, an automatic station can also be installed in the lagoon site, which is much more protected, again in parallel with manual monitoring.

This improvement would give us the opportunity to focus on the conformity of the measurement methods adopted; for instance, measurements obtained by standard equipment could be compared with our simpler methods, allowing us to define bias and potentially provide bias correction. Advanced data tests could furthermore be applied such as consistency, homogeneity, stationarity, and randomness, and even concordance checks with some standard data (e.g., satellite data) could be developed.

The highest-level use of the acquired data will eventually be the analysis of the future under climate change by setting up future scenarios of river inflow, evaporation rates, and sea level rise, and hypothesizing about morphological evolution.

A completely different and complementary issue concerns sediment balance and aggradation. During the river flow measurements, a water sample was taken to assess the concentration of suspended solids (SS) with the hope of building a relationship with the flow, i.e., SS = f(Q). Analogous data for the sea in front of the lagoon mouth are available from other entities (although with a much lower frequency). However, the difficulty is measuring the bed load carried by the river and exchanged through the lagoon mouth (in and out). We attempted several methods, but at the moment, our hopes rely on a macro scale, i.e., observing the morphological evolution delta of the Tomarrazón-Camarones River, which seems to be prograding into the lagoon. A direct comparison of satellite images and aerial photos can provide a first estimate, while the analysis of a DEM of differences in the same area might allow us to perform a quantitative estimation. However, much longer times are required to cope with the vertical precision of drone images (at the moment, we have performed a first survey by creating control points where vertical bars of known position and depth have been installed to observe, in the future, possible aggradation of the floodplain). A key element, in addition, will be the coring of the sediment bed and its stratigraphic and dating analysis.

Concerning the future of our system, it must be emphasized that it is based on a participatory basis, thanks to the very nice relationship established with the National Parks institution and its staff. In particular, a number of on-the-field training sessions and office seminars succeeded in motivating the personnel on the usefulness and reliability of the exercise they were involved in. In addition, some local people have been directly involved in providing information and executing some measurements. Therefore, we can state that the exercise has involved a significant participatory dimension. However, systematic long-term monitoring certainly cannot be based on voluntary effort only; the benefits of measuring with such a system will only be evident in the long run and hence cannot be a sufficiently solid reason to motivate local stakeholders to take charge of operating the system alone. Only National Parks can potentially hold the commitment on a long-term basis, but even this may not be guaranteed as each year, some personnel adjustments take place. This is why a long-term agreement between the local University and National Parks has been proposed and is being considered.

Overall, this experience may clash with the latest groovy advances of science, such as in situ automatized sensors, remote sensing, machine learning, and digital twins. However, it recalls that before the latest technological advances, science may emerge even through old, very simple methods when rooted in a sincere, humble search for insight.

Author Contributions

Conceptualization, A.G.C.N.; methodology, A.G.C.N. and J.I.P.-M.; software (to elaborate DEMs and specific Excel sheets to analyze and plot data), J.R.E.V., A.G.C.N. and J.I.P.-M.; validation, J.I.P.-M. and A.G.C.N.; formal analysis, A.G.C.N.; investigation, J.I.P.-M. and J.R.E.V.; resources, J.I.P.-M. and J.R.E.V.; data curation, J.I.P.-M., J.R.E.V. and A.G.C.N.; writing—original draft preparation, A.G.C.N.; writing—review and editing, J.I.P.-M. and J.R.E.V.; visualization, J.I.P.-M., A.G.C.N. and J.R.E.V.; supervision, A.G.C.N.; project administration, J.I.P.-M.; funding acquisition, J.I.P.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially funded by Ministerio de Ciencia, Tecnología e Innovación of Colombia, call for proposals 890-2020, project 82511, resources administered by the Colombian Institute of Educational Credit and Technical Studies Abroad–ICETEX, but a self-funding share was necessary at the beginning as the start of the formal project suffered a significant delay.

Data Availability Statement

Data generated within this effort are available under direct request to the corresponding authors.

Acknowledgments

We are grateful to the Universidad de La Guajira for the contributions and the agreement with JIPM to allocate time to the project; the authors also thank CREACUA Foundation (Riohacha, Colombia) for the impulse given to this initiative. A special greeting goes to Parques Nacionales Naturales de Colombia, and particularly to all the public servants of the Santuario de Fauna y Flora los Flamencos and their illuminated director Nianza Angulo Paredes. We also want to warmly thank Rosa Rodriguez Fernandez for the support in the installation of the measurement systems as well as Jose Fragozo Arevalo for the help in the topographic surveys. Last, but not least, warm thanks to Yesenia Zuñiga for her help in the preparation of the figures.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Scheme of the typical hydrological and ecological cycle of a coastal lagoon in La Guajira: (a) dry season; (b) flood season with opening of la boca and outflow of semi-fresh water; (c) sea–lagoon exchange according to the tide.

Figure 2. Navío-Quebrado (Camarones) lagoon: (a) wet season; (b) opening of the mouth (“la boca”); (c) the bar between the sea and lagoon (closed mouth).

Figure 3. Study area: (a) general location; (b) location of specific points of interest.

Figure 4. Location of hydrometers: (a) view from downstream at Puente Troncal; (b) view from the observation point at Puente Viejo; (c) rule at Puente Troncal; (d) rule at the same site during a flood (this is located on the opposite side of the pillar).

Figure 5. Cross-section at Puente Troncal. It can be noted that the 0 of the hydrometer (on the right) was placed where the water was on the day of installation; however, the water level can be lower (the depth was estimated by directly wading into the section). This means that negative values of the water height h are also possible. The wetted topography was manually surveyed by measuring depth with respect to the water surface every 100 cm, as represented in the figure.

Figure 6. Difficult Access to the measurement sites: (a) Puente Troncal; (b) Puente Viejo.

Figure 7. Stage–discharge relationship (polynomial regression) of the Tomarrazon-Camarones River in Puente Troncal with gauging data from 23 April 2022 until 23 October 2023 (y denotes elevation m asl).

Figure 10. Surprise from new data on the Tomarrazon-Camarones River in Puente Troncal: (a) Stage–discharge relationship (power law regression, R² = 0.9172) with gauging data from 23 April 2022 until 23 November 2023; (b) matching between measured and estimated values (red line: perfect matching, dotted line: linear regression with R² = 0.9119).

Figure 11. Deviation Q measured vs. Q estimated by the found stage–discharge relationship (m³/_s) as a function of the water elevation y_Lagoon (in cm above sea level). The blue dotted line interpolates the points linearly.

Figure 12. Improvement of the matching between measured Q and Q estimated by the Q = Q(y_river, y_lagoon) relationship (light blue dots are the same as in Figure 9 for ease of comparison). Data until 23 November 2023.

Figure 13. Extract of the time series of recorded data (at hourly time steps) showing the inconsistency between lagoon data and sea data, which are always higher than 0 and higher than the lagoon levels (top: sea elevation data kindly provided by DIMAR: daily moving average indicated by the darker line; bottom: lagoon water elevation data collected by our project).

Figure 14. General view of the lagoon water level measurement system.

Figure 15. Construction details of the water surface measurement system: (a) sealed inlet of the hydrometer; (b) filtering lateral surface of the piezometer covered by a plastic grid and inserted into gravel-filled holes; (c) fully installed system.

Figure 16. Scheme of the construction details of the measuring systems: (a) hydrometer and (b) piezometer.

Figure 17. Alteration of the measurement of the water level h because of the volume of the inserted rule.

Figure 18. “Instantaneous altimetry” criterion: Elevation pattern of lagoon perimeter according to satellite images taken in 2017 (basis of the adopted DEM). The local peaks (“outliers”) are attributed to DEM imperfections, possibly due to imprecision in the definition of the water surface polygon which may create incorrect height values. What counts here, anyway, is the prevailing behavior. The mean elevation is denoted by the brown bar.

Figure 19. Horizontality check: synchronic monitoring criterion: (a) original data obtained; (b) the three sets of curves refer to three different survey days (in May, no exchange with the sea or river inflow and negligible evaporation effect during daytime, so constant values; in June, outgoing flow is emptying the lagoon, although a moderate river inflow was present; in November a significant river inflow is filling the lagoon, in spite of a moderate open mouth); the top curves refer to the lagoon, the bottom ones to the river at the same time: a synchronic behavior is apparent, as well as the existence of an elevation difference of about 12–20 cm.

Figure 20. Instantaneous altimetry test based on DEM analysis: Shore affected by lower (a) and higher (b) elevations; location of anomalous points: the most depressed point (y= −1 m.a.s.l) corresponds to the boca and was most probably captured near the surface of the sea; the highest one, on the other hand, lies in the middle of nowhere and seems to be a local imperfection.

Figure 21. Details of the mouth and velocity measurements: (a) lagoon during an “open period”; (b) Our vehicle for surveying the cross-section; (c) Manual measurement of depth and velocity.

Figure 22. Spatial pattern of 111 GNSS-RTK points (red). The background image is a Landsat 8 of 20 September 2022 when the lagoon was at maximum filling. The false color image identifies water (dark blue tone) under a combination of bands: NIR, SWIR1, and Red.

Figure 23. Hypsometric curves: Surface area S = S(y) (m²); Storage volume V= V(y) (m³) related to lagoon elevation y_L [masl]. Polynomial curves: S(y) = 8010914.35 y³ − 8335673.88 y² + 7166288.16 y + 16056191.36 (R² = 1.00); V(y) = 4983114.71 y² + 15272088.13 y + 8414661.47 (R² = 1.00).

Figure 24. Climatological variables of the study area (from IDEAM data: Rain from Camarones station ID 15050010. All others from Riohacha station ID 15065180).

Figure 25. Output of the monitoring system for the period of 10 December 2021 to 14 January 2023 (hourly time step; one square is 500 h), with no correction for the sea level data. At the bottom is the status of the lagoon mouth: C: closed; O: Open; S: Semi-open.

Figure 26. Summary of the whole exercise conducted to set up the hydrological monitoring system.

Table 1. Consistency check between DEM output and measurements of lagoon elevation (“Area” is the area of the surface identified by satellite image after eliminating the holes left by the process; “Y Lagoon Topo-Bati” (third column) is the corresponding elevation determined from the DEM through the y(S) relationship; “when” discerns the two daily measurements of the piezometer (“Y Lag Piezo”, fifth column) and of the hydrometer (“Y Lag Hydro”); “Y-Lagoon” is the selection between the two according to the threshold −0.2; “Diff” (Y Lagoon Topo-Bati – Y Lagoon) is the deviation).

Date	Area	Y Lagoon Topo-Bati (m.a.s.l)	When	Y Lag Piezo (m.a.s.l)	Y Lag Hydro (m.a.s.l)	Y Lagoon (m.a.s.l)	Diff (cm)
Date	(m²)	Y Lagoon Topo-Bati (m.a.s.l)	When	Y Lag Piezo (m.a.s.l)	Y Lag Hydro (m.a.s.l)	Y Lagoon (m.a.s.l)	Diff (cm)
2 May 2023	4,949,302	−0.707	morning	−0.711	−0.770	−0.711	0.4
		−0.707	afternoon	−0.700	−0.772	−0.700	−0.7
15 March 2023	8,484,668	−0.540	morning	−0.593	−0.653	−0.593	5.3
		−0.540	afternoon	−0.596	−0.652	−0.596	5.6
31 May 2022	13,673,330	−0.241	morning	−0.084	−0.089	−0.089	−15.2
		−0.241	afternoon	−0.156	−0.161	−0.161	−8.0
20 September 2022	17,554,393	0.263	morning	0.446	0.367	0.367	−10.4
		0.263	afternoon	0.451	0.365	0.365	−10.2

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Nardini, A.G.C.; Escobar Villanueva, J.R.; Pérez-Montiel, J.I. Hydrological Monitoring System of the Navío-Quebrado Coastal Lagoon (Colombia): A Very Low-Cost, High-Value, Replicable, Semi-Participatory Solution with Preliminary Results. Water 2024, 16, 2248. https://doi.org/10.3390/w16162248

AMA Style

Nardini AGC, Escobar Villanueva JR, Pérez-Montiel JI. Hydrological Monitoring System of the Navío-Quebrado Coastal Lagoon (Colombia): A Very Low-Cost, High-Value, Replicable, Semi-Participatory Solution with Preliminary Results. Water. 2024; 16(16):2248. https://doi.org/10.3390/w16162248

Chicago/Turabian Style

Nardini, Andrea Gianni Cristoforo, Jairo R. Escobar Villanueva, and Jhonny I. Pérez-Montiel. 2024. "Hydrological Monitoring System of the Navío-Quebrado Coastal Lagoon (Colombia): A Very Low-Cost, High-Value, Replicable, Semi-Participatory Solution with Preliminary Results" Water 16, no. 16: 2248. https://doi.org/10.3390/w16162248

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