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Article

Mangrove Zonation as a Tool to Infer the Freshwater Inflow Regime in the Data-Poor Ruvu Estuary, Tanzania

by
Amartya Kumar Saha
1,* and
Michael Honorati Kimaro
2
1
Archbold Biological Station, 300 Buck Island Ranch Rd., Lake Placid, FL 33865, USA
2
Tanzania Research and Conservation Organization, P.O. Box 6873, Morogoro 67109, Tanzania
*
Author to whom correspondence should be addressed.
Water 2025, 17(23), 3404; https://doi.org/10.3390/w17233404
Submission received: 16 September 2025 / Revised: 19 November 2025 / Accepted: 24 November 2025 / Published: 28 November 2025
(This article belongs to the Special Issue Impacts of Environmental Change and Human Activities on Aquatic Ecosystems, 2nd Edition)
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Abstract

Estuaries provide numerous ecosystem services, including fisheries, coastal community livelihoods, and resistance to saltwater intrusion. Despite this knowledge, estuaries worldwide are threatened by decreasing and/or aseasonal freshwater inflows, which negatively affect ecosystem structure and function. Sound estuarine management requires an understanding of the natural freshwater inflow regime and knowledge of the salinity tolerances of local plant and animal communities—data that are completely lacking in most estuaries. This paper describes a 2-week field survey of mangrove zonation in the Ruvu River estuary carried out during the wet–dry season transition to obtain a multi-decadal proxy for the salinity regime within the estuary. Salinity conditions arising from the mixing of freshwater inflows and sea tides influence the species composition of mangroves. The mouth of the estuary (highest salinity −35 ppt) had monospecific stands of Sonneratia alba—the mangrove with the highest salinity tolerance. Salinity decreased going upriver, from 30 ppt to 5 ppt over 13 km, with 7 other mangrove species progressively appearing in the riverbank forests, ultimately transitioning to palms and other trees intolerant of salinity (<5 ppt). The resulting map relating mangrove zonation with salinity can then be used to calibrate estuary salinity mixing models for calculating minimum freshwater inflows necessary to maintain the estuarine ecosystem. Such periodic surveys and maps can also serve to calibrate/validate remote sensing products for continued coastal vegetation monitoring. The study also reviews available information on climate and land use relating to river flow in the Ruvu basin to summarize the hydrologic vulnerability of the Ruvu estuary to climate change, land use change, and river water demands in the Basin.

1. Introduction

Estuaries are amongst Earth’s highly productive ecosystems, created by the mix of nutrients brought in by freshwater and marine tides [1]. In the tropics and subtropics, seagrass beds cover the estuary and coastal offshore muddy/sandy bottoms, serving as nurseries for most marine fish species by providing both shelter for juvenile fish from predation and sustenance in the form of submerged aquatic vegetation and marine invertebrates [2]. Mangroves occurring on the riverbanks and coasts of tropical and subtropical estuaries protect the coast from wave and storm erosion as well as slowing down river flow, thereby facilitating sedimentation and nutrient deposition [3]. Coastal fisheries thus depend on seagrass and mangrove habitats remaining in a healthy condition [4]. A detailed description of the natural resources in mangrove forests and seagrasses, as well as their uses by local communities in Tanzania, is given by [5]. The livelihoods of local human populations are often largely dependent on these resources, such as fish and mangrove poles, which have been exported for centuries throughout Tanzania and beyond [6,7]. There is also increasing recognition of mangrove forests as being blue carbon ecosystems for carbon uptake from the atmosphere [8]. Still, estuaries and mangrove ecosystems are increasingly imperiled worldwide by human activities—both local, such as deforestation, land reclamation, aquaculture, and changes in freshwater inflows because of water abstractions and land use change, and global reasons such as ocean acidification and sea level rise [9].

1.1. Decreased Freshwater River Flows Threaten Estuaries

The physicochemical characteristics, biological structure, and productivity of estuaries are closely linked to seasonal changes in the timing and volume of freshwater inflow [10,11,12,13,14]. However, a decrease in freshwater inflow to levels lower than the natural seasonal flow regime results in increased seawater intrusion into the estuary [15,16]. Prolonged exposure to high salinity reduces water uptake in mangroves by stressing the salt-exclusion mechanisms in roots and leaves [17]. Even though mangrove species differ in their tolerances to salinity, high levels of flooding with saline water can stress even the most salinity-resistant species, ultimately leading to mangrove dieback. Similarly, hyper-saline conditions in bays stress seagrasses, as well as the various organisms that reside in these habitats. Not much is known about the impacts of prolonged high salinity on biogeochemical decomposition cycles, growth, and metabolism of juvenile invertebrates, molluscs, crustaceans, and fish. Decreased river inflows into estuaries also lead to decreased nutrient and sediment inputs; decreased sediment inputs can lead to accelerated erosion of the estuary by ocean waves, which has been noticed in the Pangani river estuary [18]. Seawater intrusion into the estuary, and possibly into coastal aquifers, can lead to salinization of drinking water wells in coastal villages. This is already happening in Bagamoyo district, Tanzania [19]. While coastal salinization is reportedly occurring over a wider section of coastline in Tanzania [15], maintaining the seasonal freshwater flows into estuaries can resist the salinization of aquifers underlying the estuary. Increasing saltwater intrusion has been occurring in the Pangani estuary over the past several decades and is attributed to two significant factors: decreasing freshwater discharge on account of irrigation/hydropower reservoir abstractions and increasing erosion at the marine end on account of less deposition of river sediment [18]. At the same time, very high freshwater flows can also disrupt the life cycle processes of estuarine ecosystems [13,20].

1.2. Ensuring Estuarine Freshwater Inflows Requires a Basinwide Perspective

Maintaining an adequate freshwater inflow regime is thus essential for maintaining estuaries and the surrounding connected environments. However, this inflow is at the mercy of all other river water abstractions upstream in the basin. Furthermore, the widespread attitude of utilizing all fresh river water for human needs is unfortunately detrimental to coastal ecosystems and their human populations [21,22]. Policymakers and water resource authorities are thus faced with the difficult task of developing basin-wide water resource management programs that allocate freshwater between dynamic human and ecosystem needs sustainably [23]. Furthermore, the vulnerability of water resources to both shifting climatic patterns (primarily seasonal/interannual precipitation variability) and land use change (deforestation, wetland loss, and drainage) needs to be assessed and taken into consideration in basin-wide water allocation planning [24,25,26]. A section of this paper summarizes available data on climate, river flow, and land use from a water resource vulnerability perspective, obtained from various Tanzanian government sources and studies, including several by the same authors [27,28].

1.3. Obtaining Field Data in a Data-Poor Region

Sustainable estuarine management requires knowledge of seasonally varying minimum freshwater inflows that are needed to maintain the estuarine ecosystem. An Environmental Flow Assessment (EFA), as related to an estuary, aims to determine the quality, quantity, and timing of freshwater flow required to maintain the estuarine ecosystems in a desired state [29]. Typically, the determination of these freshwater inflow requirements requires both ecological data on the salinity tolerance ranges of estuarine flora and fauna, as well as long-term (several decades) discharge and salinity data.
However, such estuarine hydrological data are lacking in Tanzania and indeed throughout much of the tropical and subtropical world, given the considerable technical, financial and logistical challenges involved in continuous sensor-based monitoring. Meanwhile, the rapid degradation of estuarine ecosystems caused by mounting anthropogenic pressures and climate change make it imperative for water basin authorities to have this local knowledge of freshwater inflow requirements as the first step towards sustainable estuary management. The technical report by the same authors [30] describes a rapid assessment in the Ruvu estuary to obtain this baseline data on plant, animal, and human communities’ links with river salinity. This paper delves deeper into the riparian vegetation surveys along the estuarine and freshwater sections of the Ruvu, relating plant community composition with river salinity.

1.4. Mangrove Zonation in Estuaries

A range of abiotic and biotic factors influence mangrove establishment and zonation, including salinity, hydroperiod, surface elevation, propagule dispersal, and competition [31,32]. The dominant factor that governs species distributions from the estuary mouth to the freshwater end, however, is species-level tolerance to salinity and inundation extent [3,33,34,35,36,37,38]. Mangroves with the highest tolerance to both salinity and inundation duration occur in the estuary mouth, followed by mangroves with decreasing tolerance upriver, accompanying decreasing salinity and ultimately freshwater where palms and trees intolerant of salinity occur. This zonation also exists along transects from riverbank to inland [39]; plants at the tidally flooded riverbank have higher salinity and inundation tolerances than plants inland.
The current tree species composition thus indicates the salinity conditions that have prevailed in the estuary over the lifespans of the adult trees, thereby going back several decades or more. This floristic composition data can be obtained via boat-based and inland surveys and combined with river salinity readings in different seasons. This data can then be input into spatially explict freshwater-seawater end-member mixing models for the Ruvu estuary to determine the volumes of freshwater required to attain the requisite salinity levels.
Published information on the distribution and salinity tolerance of mangrove species in coastal Tanzania is available [7,33,40,41]. In this study, we hypothesized that (i) species with the highest salinity tolerance would be present in the estuary mouth, followed by species with decreasing salinity tolerance as one goes upriver; (ii) vegetation known to be salinity—intolerant would indicate the extent of seawater intrusion upriver and (iii) species with lower tolerance would replace higher tolerance species as one moves upland away from the river shore. The methodology is especially pertinent for data-poor regions where the swift degradation of the estuarine ecosystem necessitates immediate action for water management.

2. Methods

2.1. Study Area

The Ruvu River, whose watershed supplies much of the water for Dar Es Salaam City, arises in the southern flanks of the Uluguru Mountains which form part of the biodiversity-rich Eastern Arc Mountains (Figure 1). It is joined by its major tributary, the Mgeta River, which drains the western Ulugurus. The Ruvu thereafter flows northeastwards and is joined by the River Ngerengere, which drains the eastern parts of the Uluguru Mountains. It continues flowing northeast through agricultural and grassland landscapes, past industrial zones around Dar es Salaam to drain into the Indian Ocean north of Bagamoyo, forming the Ruvu estuary.
The Ruvu River estuary (Figure 1 and Figure 2), is fringed by mangrove forests occurring from the mouth of the river until 13 km upriver where palms and other vegetation intolerant of saline water starts to appear. A few kilometers further upriver appear rice farms and scattered rural settlements until the bridge on the Mtoni-Kigongoni road. Unlike the Wami estuary to the north, which is protected within Saadani National Park [42], no such protection is afforded to the Ruvu River estuary.

2.2. Rapid Ecohydrological Assessment of the Ruvu Estuary

The technical report [30], also written by the same authors, details the findings from a rapid ecohydrological survey conducted over two weeks (18–27 June 2013) that corresponds to the transition between wet and dry seasons with freshwater flow in between the wet season high and the dry season low values. Financial and technical logistics permitted only one 2-week-long expedition with several trips a day at both flood and ebb tides along the entire 28 km upstream end-estuary mouth distance. Hence, the transition season was chosen to observe and record water salinity between the expected predominantly fresh conditions at peak wet season high flows and saltiest conditions in the dry season, when the freshwater inflows are at their annual minimum.
The boat-based riparian vegetation species composition survey commenced from the Indian Ocean into the mouth of the Ruvu River and proceeded upstream, past the mangrove–palm transition zone and agricultural areas till the bridge on the road from Bagamoyo between Mtoni and Kigongoni (Figure 2). The river is ~20 m wide at the Mtoni bridge end and remains within ~20–30 m width until about 4 km from the mouth of the river, when the channel begins to widen to 1–1.5 km width.

2.3. Salinity Measurements

Salinity is the primary water quality parameter that governs aquatic and riparian ecosystem structure and function in estuaries. A hand-held electrical conductivity probe (EC Ecosense 300A, YSI, Yellow Springs, OH, USA) with a 10 m cable was used to measure salinity and temperature approximately every 100 m along the 28 km marine-freshwater transect. GPS coordinates were taken at each sampling point. At river bends, measurements were taken on both scour and depositional sections on opposite banks to account for the faster and slower flow conditions, respectively. Salinity and temperature were measured at three different depths (surface, 1, 2, and 3 m deep) under both flood and ebb tidal conditions. In places with strong flow, the cable at 3 m moved off at an angle; therefore, 3 m readings under these conditions are not included. The bridge at Mtoni (labelled “freshwater end” in Figure 2) was chosen as the starting point to serve as a fixed geographical reference for future salinity measurements, which can change seasonally and interannually. In this study, at high tide, seawater was found to extend almost 11 km upstream from the mouth of the river (5.5 km as the crow flies), with the furthest inland salinity being noticed at (−6.417 S, 38.8344 E) under high tide conditions, measuring about 5 parts per thousand (ppt). Periodic calibration of the EC probe was carried out every other day using 10–50 mS/cm conductivity standards (YSI, USA) following rinsing with distilled water (available locally in petrol stations). The resolution of the Ecosense 300 A is 0.1 ppt with a stated accuracy of ±0.2% and a measurement range of 0–70 ppt.
Salinity values at each depth and tidal condition (rising flood, falling ebb) were then plotted in Google Earth, saved as a .kml file and imported to create a shapefile in ArcGIS 10.3.1, where the kriging tool was used to display the point salinity values in the estuary (Figure 3a).

2.4. Vegetation Composition and Relationship to Salinity

In this slow-moving (5–10 kmph) boat-based survey, the tree species composition on both banks of the Ruvu River was recorded visually via digital photographs with GPS coordinates recorded by the camera (EOS Rebel 750-D, Canon, Tokyo, Japan. For the first 5 km in the estuary, photographs were taken every 15 s from the moving boat (photos about 25 m apart) that were subsequently examined to add to visual observations of riverbank mangrove species composition. After 5 km, photos were taken every minute. Mangrove species can be easily identified from photographs given their physically distinct characteristics, as can be seen in the photos included in this paper. The GPS coordinates of the pictures were used to mark photo locations in Google Earth. While thousands of photos were taken, a subset was added to Google Earth as points, representing monospecific stands and areas where mixed species appeared. These points were saved as .kml files and prior to importing into ArcGIS as a shapefile, were categorized into four vegetation types based upon their degree of salinity as follows:
(i)
Mangroves that are fully tolerant of marine salinity levels (30–35 ppt) and long periods of continuous inundation;
(ii)
Mangrove species with intermediate tolerance to salinity level (brackish conditions: 10–30 ppt);
(iii)
Mangroves and palms with low tolerance to salinity (<10 ppt);
(iv)
Plants intolerant to salinity.
In addition to riverbank vegetation observations from the boat, a survey was conducted ashore on a high sandbank with high mangrove diversity (−6.378786° S, 38.854517° E, Figure 2 and Table 1), to observe how mangrove community composition varied inland from the bank, and to visually relate species composition with habitat characteristics such as local topography, extent of flooding, and soil type. All mangrove species (adults and saplings) occurring 2 m on either side of a random line transect (approximately 100 m in length) were noted, along with notes on local topography, high tide flooding evidence (such as moist or cracked soil from recent drying), and soil type, whether clayey or sandy. Three such transects were taken in the same area. In general, it was hard to access the shore owing to densely overhanging branches, together with the presence of hippopotami and Nile crocodiles.
Note that metrics such as species density, diversity indices and canopy cover were not measured, as these would be useful in a study monitoring change in forest composition due to various abiotic and biotic factors, while our study seeks to determine species occurrences along riverbanks in relation to salinity.

3. Results and Interpretation

The current rapid assessment has obtained the first available data on estuary salinity and the plant communities present. The salinity data pertains to the spring tide phase in the transition from the rainy season (March–May) to the dry season (July–September).

3.1. River Salinity

This survey noted full marine salinity (>30 parts per thousand) at high tide (Figure 3a) from the Ruvu estuary mouth up to 2 km inland. There were some lower salinity spots in the mouth, possibly caused by freshwater mixing. Lower salinity values were observed at low tide in the same sampling spots.
Salinity values increased with depth. For instance, the lighter colored region in the mouth in Figure 3a pertains to low salinity spots at the surface; these remain low at 1 m depth but increase at 2 and 3 m depths (Figure 3b). This is expected as freshwater, being less dense, floats over seawater.
Figure 4 shows the salinity values plotted with distance (in km) from the freshwater end (bridge at Mtoni) to the river mouth and the open ocean. As mentioned before, the bridge was chosen as the origin, as it represents a fixed spot for future sampling, unlike the mouth, which has no clear landmark. The water at the bridge was entirely fresh even at peak high tide. It remained fresh until 15 km downstream, when the first slightly brackish water was observed (~5 ppt) during high tide at 2 m depth, suggesting a saltwater plume beneath the surface. Similar salinity values were observed until approximately 22 km downstream from the bridge, where the salinity began to increase. By 25 km downstream, values reached 25 ppt at high tide. The mouth lay 28 km downstream from the Bridge.

3.2. Mangrove Zonation in the Ruvu Estuary

The study recorded different riparian plant communities from the estuary mouth all the way to the freshwater section (Figure 5 and Table 1). The zone within 13 km upstream from the river mouth has different mangrove communities (Figure 5), followed by the mangrove–palm transition zone for about 2 km and thereafter paddy farms and salinity-intolerant trees (such as Acacia senna) on the bank. The following sections describe the different zones and their plant communities, starting from the estuary mouth going upriver to the freshwater end.
In total, seven species of mangroves were observed in the mangrove forests of the Ruvu estuary (Table 2), consistent with reports for coastal Tanzania [7,33,40,41]. A detailed description of the communities and the environment along the Ruvu estuary shoreline is given below.

3.2.1. Estuary Mouth

The mouth of the river has sandbanks extending >100 m from the coastline into the Indian Ocean (Figure 6a,b). The landward portions of these sandbanks have stunted Rhizophora mucronata and Sonneratia alba due to being entirely submerged during high tide. At the same time, the seaward sections and isolated mudbanks are inundated even during low tide, especially around full moon. The almost monospecific stands would indicate that these are the only mangrove species able to tolerate prolonged flooding by seawater on a diurnal basis. Sonneratia alba is known to inhabit low intertidal zones of downstream estuarine systems and is one of the most pervasive and salt-tolerant mangrove species, with the capacity to tolerate high salinity and hypoxia in the root zone brought on by continuous inundation [43]. Sonneratia has been reported as being the most flood-tolerant of the mangroves along the East African coast [3].

3.2.2. Low-Lying Riverbanks—Fully Inundated at High Tide

Entering the river, low-lying banks and islands have monospecific stands of Sonneratia with a few individuals of Avicennia. These banks were observed to be totally inundated by the high tide (Figure 6c,d). Both Sonneratia and Avicennia have pneumatophores as root respiratory adaptations to prolonged flooded conditions, while Rhizophora has stilt or prop roots. A physiological description of mangrove function in flooding and saline environments is found in the literature [33,40,44]. The riverbank coastlines have Rhizophora and Sonneratia along the banks, with stands of Avicennia marina inland (Figure 6d).

3.2.3. Elevated Sandy Banks

The western riverbank has a higher elevation upstream from the mouth, accompanied by an increase in mangrove species diversity. Ceriops tagal is noticed with its characteristic bunched roots at the base of the trunk, along with Rhizophora and Avicennia. At the same time, Sonneratia is absent (Figure 6e), probably outcompeted by these other mangrove species that perform better under the less stressful conditions of lower salinity and shorter hydroperiod on higher ground.
To observe species diversity inland away from the riverbank and to examine how community composition is related to distance from the bank, local topography, and soil type, shore-based investigations were undertaken. Banks that were up to 0.5 m higher than the high tide level (such as in Figure 6f left) showed a diverse assemblage of mangroves, including Ceriops tagal, Brugeria gymnorrhiza, Hereteria littoralis, and Xylocarpus granatum, apart from Avicennia marina and Rhizophora mucronata (Figure 6g). Soils under these diverse mangrove communities were sandy, thereby allowing free drainage at low tide; the availability of well-aerated conditions is an important factor in permitting these other mangrove species to exist that are not as tolerant of prolonged flooding as Sonneratia and Rhizophora.
On the bank, there were also relatively low-lying areas with little vegetation and cracked soil, indicating periodic flooding and drying (Figure 6h). During the survey, the tide began entering inland along these low-lying areas, not from the riverbank, which was still higher than the river level, but from other small channels that came in from the coastline. These streamflow channels are visible on the Google Earth map (Figure 6f, right). This map shows the bank at high tide with clusters of mangroves flooded off the bank shore that are mainly Rhizophora. Salinity in the river varied between 23 ppt (surface) and −35 ppt (2 m depth) at high tide. About a kilometer inland, the north bank is dominated by Avicennia, while the south bank has a diverse mangrove assemblage. Salinity varied from 14–22 ppt.

3.2.4. Mangrove—Palm Transition Zone

About 9 km upriver, the first palms appear (Figure 6i), and then get more numerous. Unlike Cocos nucifera (coconut palm found on coasts) or Nypa fruticans (toddy or mangrove palm introduced to East Africa), the palms in these forests, such as Phoenix reclinata, are not known to be tolerant of salinity, although they can withstand some degree of soil anoxia from partly saturated soils. Hence, the presence of palms on riverbanks indicates water conditions in the root zone that are largely fresh throughout the year. This is corroborated by this study’s salinity measurements, which at low tide were zero ppt while at high tide were 0, 0.3, and 0.6 ppt at the surface, 1, and 2 m depths.
Note that a plume of seawater, being denser than freshwater, may advance further upriver via shear action along the river bottom as noted by Wami Ruvu Basin Water Office (WRBWO) hydrologists. However, the presence of Phoenix suggests that the root zone is largely dominated by freshwater. The mangrove–palm transition thus can be reasonably assumed to indicate the average extent of seawater intrusion into the Ruvu, at least in the root zone of riparian vegetation. A similar transition zone has been observed in the Wami estuary [42]. Note that only riverbank palms can be considered indicators; inland palms may be situated on higher ground with a layer of entrapped less dense rainwater (freshwater lens) serving as the water source [45].

3.2.5. Freshwater-Dependent Vegetation Zone

Further upriver, Palms (primarily Phoenix reclinata) became more dominant on the riverbanks, until acacias and other terrestrial evergreen and deciduous trees appeared, interspersed with rice fields (Figure 6j). The water was completely fresh in these regions. WRBWO hydrologists have observed saline water past the bridge, which is 5 km further upstream from the mangrove–palm transition zone. Seawater may extend further upriver when spring tides coincide with the lowest freshwater flow in the dry season. However, the vegetation is dominated by freshwater-dependent plants and also paddy farms. This is because the banks are high enough to avoid prolonged flooding by the river, the top water layer is fresh, and, eventually, upon wet season flows, the freshwater pulse can flush saline water from the riverbed soil interstices. Additionally, the high banks collect rainwater, which constitutes the primary water source for plants.
These observations are in accordance with the general mangrove zonation patterns described for coastal Tanzania [7,46], with S. alba occupying the seaward edge, R. mucronata, C. tagal, and B. gymnorhiza occupying the middle zone, and X. granatum and H. littoralis to the landward edge. Avicennia marina tends to be broadly distributed and often occurs across all three zones. These authors also note that a range of biological, physical, and chemical factors, topographic gradients dictating inundation, and anthropogenic activities can affect the zonation of species at a site.

4. Discussion

4.1. Using Mangrove Zonation to Infer Salinity Regime via Estuary Modeling

This study has created a vegetation composition map in relation to estuarine salinity for the Ruvu estuary as a result of a two-week survey to gather baseline data on plant composition and estuary salinity (Figure 5). Mangrove zonation data—especially the mangrove—palm interface can be used to specify salinity boundaries in spatially explicit estuarine models with seawater and freshwater as the end members [47,48,49]. The freshwater inflows into the estuary necessary to resist seawater entry past the mangrove–palm transition zone can be estimated from models such as those described by [50,51]. Ref. [52] describes the use of salinity and water level data in an estuarine mixing model to infer the amounts of fresh and seawater sources in a tropical mangrove estuary. The spatial bounds for finite-element models can be obtained from a bathymetric survey, such as shown in Figure 7, which measures depth to the river bottom from the water surface. More information on this specific bathymetric study can be found in [30]. Salinity mixing models can be run on a suitable time step (e.g., hourly) in accordance with the tidal regime, to determine the volumes of freshwater and seawater present to yield an expected salinity profile, which can be calibrated and validated with periodic salinity monitoring across several transects during different tidal periods.
Given the complexity of developing and running 3-dimensional models, an alternative approach for a salinity model is presented for the Caloosahatchee estuary in Florida, based on 20 years of time series salinity data [53]. However, such time series data is currently unavailable for most estuaries across the Global South, including the Ruvu estuary. Hence, mangrove zonation species composition data can be used for mangrove species-salinity modeling.

4.2. Ancillary Use of Mangrove Species Composition Data for Mangrove Monitoring

While Figure 5 indicates a broad snapshot of plant communities, including the freshwater–seawater transition zone, detailed species-level maps layered onto a high-resolution Digital Elevation Model (DEM) in a Geographic Information System (GIS) can form the baseline for a periodic monitoring program tracking floristic changes over time.
Monitoring the vegetation zonation in the estuary provides a snapshot of the salinity regime prevailing in the estuary over the past 30–40 years—the age of the existing mangroves and palms. Periodic monitoring of vegetation zonation can serve as a useful proxy for salinity conditions (and hence freshwater inflows and rising sea levels), in the absence of further studies or expensive instrumented monitoring of water quality. Monitoring programs, however, need to acknowledge the lag in species response to changing salinity patterns accompanying upstream freshwater inflow changes and ongoing sea level rise; disease and harvesting of mangroves are other factors influencing compositional changes over time.
Obtaining a high-resolution DEM may pose a challenge, as the vertical resolution of Landsat collection 2 is around 30 m—too coarse for the elevation scale of 1–2 m that leads to changes in mangrove composition. LIDAR maps have better vertical resolution (~5 cm) but are expensive as they have to be generated by drones fitted with LIDAR sensors flying over at low tide in the dry season (as submerged land is not detected by LIDAR). The higher the DEM resolution, the better the sensitivity of the relationship between ground elevation and species composition, as ground elevation indicates low-lying areas that can flood with seawater from back channels, as noted in Section 3.2.3. However, as ground elevation can change over decades due to land subsidence, tidal erosion and sediment accretion, LIDAR images would ideally be required every few decades.
Mangrove species composition data can also be used to calibrate/validate 2-dimensional mechanistic models of mangrove forests [54] that are useful for predicting species composition and the fate of mangrove forests in different climate and freshwater inflow scenarios. Remote sensing has emerged as a particularly powerful and practical technique for monitoring mangrove extent and composition [55,56,57]. Shore-based vegetation mapping, as done in this field survey, is indispensable to calibrate/validate remote sensing products to correctly identify species in remotely sensed images. The use of unmanned aerial vehicles (UAV or drones) can extend observations to the entire canopy of the forests, and thereby also aid in the calibration of remote sensing products—and in that regard, a boat-based survey can in turn help identify the species noted in UAV-sourced photos.
Apart from obtaining the minimum data necessary to begin understanding the ecosystem, a riparian vegetation monitoring program provides feedback on the current ecological and environmental state of the ecosystem on which fisheries depend. A local example [58] is of a proposed monitoring program for Mnazi Bay Ruvuma Estuary Marine Park as a step to increase the effectiveness of government initiatives to protect coastal ecosystems and livelihoods. Information from monitoring programs can point out the degree of success of management initiatives and suggest adaptive changes in management plans.

4.3. The Ruvu River Basin: Climate, Land Use, and Vulnerability of Water Resources

Water abstraction, deforestation, afforestation, agricultural and industrial activities in the upstream areas of the Ruvu River basin directly affect the ecology of the estuary as well as the goods and services it provides humanity, such as fisheries, tourism and coastal groundwater quality. With respect to the Ruvu basin as a whole, water management tools such as the Ruvu Environmental Flow Assessment can be applied to balance freshwater needs for humans and nature and provide guidelines for future water resources development as well as for coastal zone management. Further data and studies over an entire year can enable a better understanding of how estuarine aquatic and terrestrial communities in this estuary are connected to seasonally varying salinity, flow, and nutrient regimes. Using the baseline data, an EFA can be carried out, as described in [59] for the adjacent Wami River estuary. In this section, we bring together information from the literature on climate and land use change that affects water resources throughout the basin, and thereby the freshwater available to the Ruvu estuary.
The climate of the Ruvu basin has been described in detail in several publications [27,60,61]. The major rainy season occurs between March and May, while a smaller season occurs between November and January. The highest rainfall in the Ruvu basin is consistently observed in the higher elevations of the Uluguru Mountains (average annual rainfall > 2000 mm) that trap moisture-bearing winds blowing west from the Indian Ocean. In the plains, rainfall drops to 1000–1200 mm per year [27,62]. Annual evapotranspiration is on the order of annual rainfall. The Annual Hydrological Reports by the Wami Ruvu Basin Water Office [63] describe the flow in streams in the headwater Mgeta and Ngerengere catchments as being flashy, i.e., with an immediate response to rainfall (Figure 8)—behavior associated with headwater streams in the extensively deforested Uluguru mountains, bereft of the water-holding capacity of intact multiple-layered canopy forests together with a deep litter layer. In comparison, the Lower Ruvu catchment downstream has a relatively stable flow regime. The period of high discharge in all tributaries of the Ruvu drainage, April to May, coincides with the main rainy season (March–May) as seen in Figure 8.
There is no available freshwater inflow data for the Ruvu estuary; the monitoring station on the Ruvu River closest to the estuary is approximately 45 km upriver from the estuary, at the Morogoro Road Bridge named 1H8A (Figure 8, upper right corner). Riparian vegetation here is entirely freshwater-dependent. Hence, long-term discharge data from this station can be used as a proxy for freshwater inflows into the estuary, in the absence of data on water inflows, abstractions and losses for the section of the river between the Bridge and the mangrove-palm interface downstream, which can be considered as the long-term limit of the ingress of seawater into the root zone of riverbank vegetation. Based on the flow data at 1H8A as well as stations further upriver throughout the basin, the period of high flows over April-June suggests the lowest salinity in the estuary during this time. Likewise, the lowest freshwater inflows into the estuary are expected over August-October, leading to conditions with the highest salinity in the year.
River flow in the Ruvu basin is thus entirely dependent on the monsoon winds from the Indian Ocean and, hence, is subject to climate teleconnections, especially the Indian Ocean Dipole [27], whose cycles are changing. Climate change projections for the Ruvu basin, based on a consortium of General Circulation Models (GCMs), unanimously predict rising temperatures, with attendant rises in evapotranspiration. However, there is no clear consensus on precipitation trends [27], except for increasing uncertainty at the beginning of the rainy seasons, irregularity of rainfall, and increasing extreme events such as intense rain events and drought. To add to the increasing uncertainty of precipitation are the negative effects of land use change upon the water cycle via altered interception, evapotranspiration, and groundwater recharge accompanying deforestation and wetland drainage [25,64].
Land use in the basin has a direct connection with water quality in the estuary [25,62,65]. The headwaters of the Ruvu arise in the Uluguru mountains, which have lost most of their original montane evergreen forest cover, with anecdotal evidence of springs drying up earlier in the dry season, suggesting decreased infiltration and the disappearance of perennial streams with scientifically undocumented freshwater aquatic communities [28]. The lack of a sustained river flow monitoring program hampers the observation of interannual and inter-decadal changes in river discharge in both headwater streams and downstream river reaches, hence posing a challenge to characterize the freshwater inflow regime of the estuary. Agriculture in the Upper Ruvu is primarily rain-fed. Many farms extend up deforested mountain slopes and become sources of soil erosion [27,28,66]. There are several irrigation projects in the lowlands that primarily rely on the Ruvu River. The Lower Ruvu basin also has various industries in the hinterland of Dar Es Salaam, including textiles, sisal production, beverages, breweries, tobacco processing, pharmaceuticals, and soaps [60], and service industries such as slaughterhouses and garages, discharging effluents. Waste streams from these industries, along with domestic sewage, ultimately discharge into the Ruvu River [65]. The prospects for growth of irrigated agriculture and industrialization in the Ruvu River basin not only increase the potential for pollution but also could lead to increased water demands, some of which are already being supplied by groundwater.
As an estuary receives water inputs from both ends, sea level rise can also lead to shore erosion and increasing salinization, especially in the dry season, which could lead to changes in species composition with lower salinity-tolerant species retreating up the estuary [67] where they may come in competition with agriculture or another human land use.
The fact that mangrove forests still exist in the Ruvu estuary despite a lack of any official protection, and despite the centuries-old exploitation for mangrove poles, is encouraging. However, the increasing pressure on natural resources, together with the dangers of increasing salinization resulting from a combination of decreased freshwater inflows and sea level rise, could compromise the health of these forests and ecosystem services provided [7].

5. Conclusions

In estuaries with scarce or no data on freshwater inflows, the composition of mangrove species provides definitive spatial clues to the salinity conditions prevailing in the estuary over the lifespan of the mangrove forests. Estuaries, being a mix of tidally and seasonally varying freshwater and seawater, can be used to demarcate the gradient of salinity conditions that govern mangrove species zonation. This information can then be used in spatially-defined estuarine freshwater-seawater mixing models to ultimately obtain the required seasonally varying freshwater inflows needed to maintain salinity conditions in the estuary. In addition, periodic mangrove zonation data can also calibrate and validate remote sensing-based monitoring of mangrove forest structure, as an additional proxy for estuarine health. By describing this simple tool of using mangrove zonation to infer the salinity regime in an estuary, it is hoped that this article may be useful to all who work towards managing and protecting estuaries and their valuable ecosystems, especially in data-poor areas.

Author Contributions

The lead author (A.K.S.) wrote this article with inputs from the co-author (M.H.K.), who also assisted with fieldwork related to mangrove photography. All authors have read and agreed to the published version of the manuscript.

Funding

This field study was supported by the American people via the United States Agency for International Development (USAID) through the Tanzania Integrated Water and Sanitation Program (iWASH) led by Vivienne Abbott and Maria C. Donoso.

Data Availability Statement

The georeferenced salinity raw data file is available. Mangrove photos and higher-resolution map files are available upon request.

Acknowledgments

The authors are very grateful to the Bagamoyo District Administration for permission to conduct fieldwork in the Ruvu River estuary. We would like to thank the District Commissioner, Hon. Ahmed Kipozi, for his suggestions, encouragement, and interest in the outcome of this project. We thank Abubakary Mposo, the Head of the Fisheries Department, Bagamoyo, for his helpful suggestions about the area and for facilitating the use of their boat. We thank the Wami Ruvu Basin Water Office (WRBWO), Morogoro, for their support, participation, and provision of their truck and zodiac inflatable boat. In particular we thank Praxeda Kalugendo, the Basin Water Officer, for her wholehearted support. We are grateful to the University of Dar Es Salaam Marine Station for the use of their equipment (anchors and buoys). Halima Kiwango and Roman Evarist assisted with the salinity sampling. We also thank Elizabeth Anderson, Cathy McNally, Doreen Summerlin, and Jason Gritzner for sharing data, suggestions, and experiences of their studies in the Wami River estuary.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analysis, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. Ruvu River arising in the Uluguru Mountains south of Morogoro, with the Ruvu Estuary located on the Indian Ocean just north of Bagamoyo.
Figure 1. Ruvu River arising in the Uluguru Mountains south of Morogoro, with the Ruvu Estuary located on the Indian Ocean just north of Bagamoyo.
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Figure 2. Location of the Ruvu River estuary northwest of Bagamoyo. Orange circles denote the extent of the present survey from the estuary mouth, past the palm–mangrove transition zone, up to the bridge on the Mtoni-Kigongoni road. Map source: Google Earth.
Figure 2. Location of the Ruvu River estuary northwest of Bagamoyo. Orange circles denote the extent of the present survey from the estuary mouth, past the palm–mangrove transition zone, up to the bridge on the Mtoni-Kigongoni road. Map source: Google Earth.
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Figure 3. (a): Surface Salinity gradient at high tide in the Ruvu estuary between 18–26 June 2013, corresponding to the wet–dry seasonal transition. Deeper blue indicates higher salinity. (b): Salinity profiles at 1 m, 2 m, and 3 m depths under high tide conditions over 19–22 June 2013. Note increasing salinity with depth.
Figure 3. (a): Surface Salinity gradient at high tide in the Ruvu estuary between 18–26 June 2013, corresponding to the wet–dry seasonal transition. Deeper blue indicates higher salinity. (b): Salinity profiles at 1 m, 2 m, and 3 m depths under high tide conditions over 19–22 June 2013. Note increasing salinity with depth.
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Figure 4. Salinity measurements at surface, 1 and 2 m depth carried out over both low and high tide conditions from the freshwater to the marine end of the Ruvu river over 18–28 June 2013.
Figure 4. Salinity measurements at surface, 1 and 2 m depth carried out over both low and high tide conditions from the freshwater to the marine end of the Ruvu river over 18–28 June 2013.
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Figure 5. Riparian vegetation communities in the Ruvu estuary (freshwater to marine end) classified by salinity tolerance and shown along with salinity measurements in the Ruvu river (high tide phase at 2 m depth over 19–22 June 2013). The deeper the shade of blue, the higher the salinity.
Figure 5. Riparian vegetation communities in the Ruvu estuary (freshwater to marine end) classified by salinity tolerance and shown along with salinity measurements in the Ruvu river (high tide phase at 2 m depth over 19–22 June 2013). The deeper the shade of blue, the higher the salinity.
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Figure 6. (a): Sonneratia alba on a sandbank at low tide at the mouth of the Ruvu. (b): Sonneratia alba on sandbanks in Ruvu estuary mouth, immersed at high tide; the Indian Ocean is on the horizon. (c): Pure stand of Sonneratia alba on an island that gets inundated at high tide. (d): Foreground—Rhizophora (with stilt roots), Sonneratia (right), inundated at high tide with Avicennia in the background, partially inundated. (e): Rhizophora (left), Ceriops on sandbank with Avicennia on higher ground, Salinity conditions vary between brackish and marine. (f): (Left) High sandy bank on an incoming tide with an Avicennia marina tree on the left and smaller Avicennia on the bank. (Right) Google Earth satellite image taken at high tide, showing Rhizophora and Sonneratia trees inundated at the edge of the bank, as well as the presence of channels that flood at high tide. (g): Diversity of intermediate-salinity-tolerant mangroves on high bank. Ceriops (left), Xylocarpus (centre), and Avicennia (right) in the back, with a relatively low-lying area (moist dark soil on the right). (h): Low-lying area with cracked soil indicating periodic wetting and drying. (i): Phoenix reclinata palms (left) coexisting with Avicennia marina (center) in the mangrove–palm transition zone. (j): Palms get more numerous, and paddy farms appear up to the bank.
Figure 6. (a): Sonneratia alba on a sandbank at low tide at the mouth of the Ruvu. (b): Sonneratia alba on sandbanks in Ruvu estuary mouth, immersed at high tide; the Indian Ocean is on the horizon. (c): Pure stand of Sonneratia alba on an island that gets inundated at high tide. (d): Foreground—Rhizophora (with stilt roots), Sonneratia (right), inundated at high tide with Avicennia in the background, partially inundated. (e): Rhizophora (left), Ceriops on sandbank with Avicennia on higher ground, Salinity conditions vary between brackish and marine. (f): (Left) High sandy bank on an incoming tide with an Avicennia marina tree on the left and smaller Avicennia on the bank. (Right) Google Earth satellite image taken at high tide, showing Rhizophora and Sonneratia trees inundated at the edge of the bank, as well as the presence of channels that flood at high tide. (g): Diversity of intermediate-salinity-tolerant mangroves on high bank. Ceriops (left), Xylocarpus (centre), and Avicennia (right) in the back, with a relatively low-lying area (moist dark soil on the right). (h): Low-lying area with cracked soil indicating periodic wetting and drying. (i): Phoenix reclinata palms (left) coexisting with Avicennia marina (center) in the mangrove–palm transition zone. (j): Palms get more numerous, and paddy farms appear up to the bank.
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Figure 7. (Left) Water depth of the Ruvu Estuary and adjacent upstream river under flood tide conditions on 21 June 2013. Tiny circles show measurement locations. (Right) Continuous water depth profile of a close-up of the Ruvu estuary taken on 24 August 2013. Taken from [30] authored by us.
Figure 7. (Left) Water depth of the Ruvu Estuary and adjacent upstream river under flood tide conditions on 21 June 2013. Tiny circles show measurement locations. (Right) Continuous water depth profile of a close-up of the Ruvu estuary taken on 24 August 2013. Taken from [30] authored by us.
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Figure 8. Monthly discharge (m3/s) in select tributaries and sections of the Ruvu river, averaged over 1950–2010. Error bars depict 0.5 standard deviation on either side of the plot. Figure adapted from [28] written by the same authors. Data source: WRBWO.
Figure 8. Monthly discharge (m3/s) in select tributaries and sections of the Ruvu river, averaged over 1950–2010. Error bars depict 0.5 standard deviation on either side of the plot. Figure adapted from [28] written by the same authors. Data source: WRBWO.
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Table 1. Tree communities observed during the survey in the Ruvu estuary, along with representative GPS locations.
Table 1. Tree communities observed during the survey in the Ruvu estuary, along with representative GPS locations.
CommunityLatitudeLongitudeRemarks
Sonneratia−6.368287°38.871491°A sandbar jutting out into the sea is completely inundated at high tide
Sonneratia, Rhizophora−6.375122°38.858313°North bank, estuary mouth
Rhizophora, Avicennia, Ceriops, Brugeria, Hereteria−6.378841°38.852970°Diverse high sandy bank in the estuary, floods from behind
Sonneratia−6.390415°38.853958°Island in a river channel
Avicennia, Rhizophora, Sonneratia−6.386967°38.860841°South bank in the estuary mouth
Avicennia−6.396982°38.861010°Avicennia forest on the north bank
Hereteria, Rhizophora, Ceriops, Avicennia−6.398293°38.871330°High bank on the south side
Brugeria, Ceriops, Avicennia−6.407859°38.858598°High bank on the south side, further upriver
Phoenix palm, Avicennia−6.409481°38.845097°First palms appear on banks in the upriver
Phoenix palm, Avicennia−6.416805°38.835464°Mangrove–palm transition zone
Paddy farms−6.425406°38.845945°Paddy farm situated a few meters away inland
Table 2. List of mangrove species observed in the Ruvu estuary.
Table 2. List of mangrove species observed in the Ruvu estuary.
SpeciesLocal NameRelative Salinity/Flood Tolerance
Sonneratia albaMpira, Mlilane, Evening blossom mangroveHigh, monospecific stands on flooded sandbanks
Rhizophora mucronataMkoko, red mangroveHigh, on coastal margins, flooded at high tide
Avicennia marinaMchu, white mangroveMedium–high
Ceriops tagalMkandaaMedium–low, occurs on high sandbanks
Hereteria littoralisMkungu, silver mangroveMedium–low, occurs on high sandbanks
Bruguiera gymnorrhizaMshinziMedium–low
Xylocarpus granatumMkomafiMedium–low, occurs on high sandbanks
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Saha, A.K.; Kimaro, M.H. Mangrove Zonation as a Tool to Infer the Freshwater Inflow Regime in the Data-Poor Ruvu Estuary, Tanzania. Water 2025, 17, 3404. https://doi.org/10.3390/w17233404

AMA Style

Saha AK, Kimaro MH. Mangrove Zonation as a Tool to Infer the Freshwater Inflow Regime in the Data-Poor Ruvu Estuary, Tanzania. Water. 2025; 17(23):3404. https://doi.org/10.3390/w17233404

Chicago/Turabian Style

Saha, Amartya Kumar, and Michael Honorati Kimaro. 2025. "Mangrove Zonation as a Tool to Infer the Freshwater Inflow Regime in the Data-Poor Ruvu Estuary, Tanzania" Water 17, no. 23: 3404. https://doi.org/10.3390/w17233404

APA Style

Saha, A. K., & Kimaro, M. H. (2025). Mangrove Zonation as a Tool to Infer the Freshwater Inflow Regime in the Data-Poor Ruvu Estuary, Tanzania. Water, 17(23), 3404. https://doi.org/10.3390/w17233404

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