Time distance effect of damming on the degree of hydrological and ecological alteration in floodplain river and wetland

doi:10.21203/rs.3.rs-1750331/v1

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Time distance effect of damming on the degree of hydrological and ecological alteration in floodplain river and wetland

https://doi.org/10.21203/rs.3.rs-1750331/v1

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Usually, the effects of any episodic incident minimize overtime. The time distance effect of hydrological alteration in the river on the ecological condition of a river and the hydrological and ecological conditions of the riparian wetland was examined in this present study. For doing this, an investigation of the degree of hydrological alteration in the river and at 30 × 30m pixel scale water richness (WWR) mapping using weighted overlaying was carried out along with assessing its degree of alteration. Periodicity of river flow at season scale was performed following wavelet transform model. Similarly, the degree of ecological alteration was measured using the range of variability approach (RVA), and flow duration curve (FDC) in three phases (pre-dam (up to 1992), post-dam phase 1 (1993–2012), and phase 2 (2013–2020). From the analysis, it was revealed that after damming, the monthly flow failure rate ranged from 70 to 96%. Eco-deficit in the river was aggravated to some extent with increasing time distance. As a consequence of this, wetland water richness maps of different phases exhibited continuous wetland loss from the poor WWR parts and continued degradation of WWR in post-dam phases. Eco-deficit condition of the wetland was also weakened in post-dam phase 1 and it was continued in the next phase. So, this study clarified that time distance minimizing the effect of damming on rivers and wetlands was not found rather its trend was like a positive feedback mechanism, the wave of impact radiated after damming has been continuing. The study output would be instrumental for river and wetland management and precautions on manmade hydrological modification. The study recommends carrying out similar works with more post-dam length to establish a reliable theory in this regard.

Hydrological alteration

River

Wetland ecology

Wetland water richness

Degree of alteration

and Time distance effect

Previous literature has discussed how far damming is responsible for bringing change in the hydrological, geomorphological, and ecological environment of the river and riparian flood plain. Most of the literature explored that damming has reduced the flow volume in the dam-downstream segment of a river, flood frequency, magnitudes, flood spill area with varying rates across the world based on the nature of flow regulation through damming and other forms of water extraction (Hecht et al., 2019; Chong et al., 2021). It also affects the flood plain wetland considerably. Wang et al, (2019); Singh and Katpatal (2018) worked on the effect of hydrological modification on wetland area, hydrological strength, and consistency in water appearance in a seasonally inundated wetland. Talukdar and Pal, (2019) identified two distinct hydrological regimes of a river due to damming (pre and post-dam periods). Some works like Zheng et al., (2019); Annys et al., (2020); Huđek et al., (2020); Mezger et al., (2021); in different areas like Northeast China, Northern Ethiopia, Southeast Europe; Spain respectively reported habitat health impact of river and flood plain wetland and reported gradual degradation of the habitat health. Khatun and Pal, (2021) studied the effect of hydrological modification on biodiversity and fishing habitats and found very adverse results. A sharp decline of suitable fish habitat areas of some commonly found economic fishes like carp fishes, shrimps, tilapia, and catfishes in India and Bangladesh flood plain was also reported by Khatun and Pal (2022).

Here the Tobler's First Law (TFL) (Tobler, 1970) could be remembered that stating "everything is related to everything else, but near things are more related than distant things”. This law is invoked as a core technique and conception of geographical spatial analysis (Miller, 2004). According to such law, it can be derived that the environmental impact of an event decays with physical distance. Like this spatial distance dependency of the environmental impact of any event, it should be tested for time-distance dependency. Taking motivation from this perspective, the present study attempted to explore a few research questions, such as (1) how long the effects of hydrological modification triggered by damming may continue both in the river and riparian floodplain after damming? (2) Is this effect decaying over time? (3) Are the rate of hydrological alteration and eco-hydrological impacts similar in the river and dependent floodplain wetland? Does it mean the present study wishes to explore whether the damming triggered hydrological and eco-hydrological instability affects resilience? Like the negative feedback mechanism, after a certain period will it be restabilized or like the positive feedback mechanism, the instability effect created will continue? The answer to these questions is of planning importance concerning wetland conservation, restoration, and planning of human well-being. Practically, human well-being planning will not be sustainable without having any plans for natural capital like rivers and wetlands.

Many works of literature (Lu et al., 2018; Tian et al., 2019; Hecht et al., 2019; López-Ballesteros et al., 2020) focused on the hydrological alteration of the river. Gabiri et al., (2018); Harvey et al., (2019); Liu et al., (2020); Yeo et al., (2019) also focused on pixel scale hydrological modification of wetland. However, using indicators of hydrological alteration (IHA) at the pixel scale of such analysis is rare. As far the knowledge is concerned, Pal and Sarda, (2020); Pal et al., (2020); Pal and Sarda, (2021); Pal et al., (2022) worked on this particular issue in the Barind flood plain region of India and Bangladesh. Eco-hydrological indices based on ecological analysis were done by Ramchandra et al., (2018); Liu et al., (2019); Tang et al., (2021) in different rivers across the world. For instance, Fernandez-Palomino et al., (2021) used the baseflow index in the Andean Vilcanota river of Peru; Banerjee and Biswas, (2021) used the Fluvial functioning index in Himalayan foothill rivers to explore the ecological health, particularly eco-deficit and eco-surplus of a river. However, only two works conducted by Talukdar and Pal, (2019); Pal and Sarda, (2021) applied eco-hydrological indices like the range of variability approach based on ecological thresholding, ecological flow failure rate, eco-deficit at the pixel level to explore the nature of eco-deficit and surplus in flood plain wetland area. But no one tried to examine the time distance effect of damming on the eco-hydrological threshold, ecological flow failure rate, and eco-deficit/surplus in a wetland in the post-dam period as far the knowledge is concerned. Therefore, the present study attempted to investigate this issue.

Wetland is a precious natural capital with immense ecological goods and services supporting human well-being (TEEB, 2010; Ramsar Convention on wetland, 2018). But with the increase in human population and expansion of their activities, these precious resources are under significant threat. Many vectors like reclamation for agricultural land (Zou et al., 2018), built-up area (Mao et al., 2018), coastal reclamation (Wu et al., 2018), fragmentation of wetland morphology (Lu et al., 2019), qualitative degradation of wetland (Das and Basu, 2020), hydrological modification due to climate change (Dwire et al., 2018), damming (Zheng et al., 2019), direct water withdrawal (Yu et al., 2021), groundwater level lowering (Zou et al., 2018), etc are responsible for wetland loss and eco-hydrological deterioration. It is caused for growing imbalances in the environmental system and concerns human well-being in general. In the first section, it is already stated that many scholars worked on damming effect on downstream and upstream river segments. However, the longevity of damming impact on river and wetland hydrological and eco-hydrological alteration is still unexplained. It needs extensive research. The present study intended to explore the effect of damming on the hydrological and eco-hydrological transformation of river and flood plain associated wetland at multi-phase in the post-dam period. It tried to examine was such effect decayed over time? If so, was it the same both in river and wetland?

Punarbhaba River (length: 160 km and basin: 5265.93 km², a sub-basin of Mahananda River, flowing over the neo-tectonically emerged older alluvium dominated Barind tract of Indo-Bangladesh) (Rashid et al., 2014) is chosen as the study area (Fig. 1). This Barind tract is characterized by a dendritic drainage pattern having a firmly meandering entrenched channel (Rashid et al., 2014). Rashid et al. (2014), Pal and Saha (2017) have depicted that the lateritic soil-dominated area of the study region has experienced high strength of neo-tectonic upliftment and rolling landscape. The alluvium part of the valley is highly affluent with wetland and moist agricultural land. However, this densely populated (> 1500person/km² as of the 2011 census) basin is characterized by fertile alluvial soil with incredible potentiality for agricultural activities. This area has evidence of momentous hydrological modification with time (Talukdar and Pal, 2017b). For extenuating seasonal water paucity of irrigation, the Komardanga dam has been installed over the Dhepa River (the main water supplier to Punarbhaba river) in 1992 resulting from the emergences of modifying hydrological paradigm the downstream of the river where 80% of the total wetland is found (Fig. 1.5). These rain or flood-water-fed wetlands are predominantly seasonal (68.08%, out of the total wetland). Talukdar and Pal (2017a) accounted that after the installation of the dam, discharge is declining by 34.35% in monsoon, 32.34% in post-monsoon, and 52.24% in pre-monsoon seasons. Declining of 59.64% inundation frequency is liable to destroying the lateral linkages of riparian wetlands with the main river.

Daily discharge data of Balurghat gauge station in Atryee river at Balurghat was used for the river-centric analysis of the degree of hydrological alteration, periodicity, and eco-hydrological analysis. Monthly Landsat TM, ETM, and OLI data (path/row: 139/43; spatial resolution: 30 m.) of the United States Geological Survey (USGS) from 1987 to 2021 were used for wetland mapping and pixel scale hydrological analysis. The entire study period was classified into the pre-dam phase (before 1992), post-dam period, phase I (1992 to 2012), and post-dam phase II (2013 to 2021) to reach the objectives. Details of the images are tabulated in the supplementary section (Supplementary Table S1).

Measuring hydrological alteration and periodicity in river

The periodicity analysis on the time series data using wavelet transformation has not very old and it’s a modified form of Fourier transformation. In the case of Fourier transformation, it reveals the information in one dimension. If it gives information about the time domain, the scale domain will be lost and vice versa. The wavelet transformation can able to give both time and scale domain information (Wang et al., 2018; Liu et al., 2016; Amezquita-Sanchez & Adeli, 2015). This is why wavelet transformation has become a popular technique to solve time series problems (Amezquita-Sanchez & Adeli, 2015). The non-stationary time series data (mean, variance, covariance, and autocorrelation are changed over time and not able to get back to their previous original state) are most appropriate to run the wavelet analysis to explore the variability of the data. Therefore, the wavelet transform method is always applied to the hydro-meteorological time series data because of its non-stationary nature.

Goupillaud et al. (1984) first considered wavelets as a family of functions constructed from the translations and dilations of a single function, which is called the ‘‘mother wavelet”. The wavelet transform is defined by Eq. (1)

\({\psi _{a,b}}(t)=\frac{1}{{\sqrt {\left| a \right|} }}\psi (\frac{{t - b}}{a});a,b \in R;a \ne 0\) ------------------(Eq. 1)

Where, the scale parameter is represented by ‘a’ that evaluates the degree of compression, whereas, the translation parameter that computes the time location of the wavelet is represented by ‘b’. The ‘a’ parameter in the mother wavelet will be characterized by higher frequencies (smaller support in the time domain) when\(\left| a \right|\)will be less than 1. When \(\left| a \right|\)will is more than 1, then \({\psi _{a,b}}(t)\)has a larger time width than \(\psi (t)\) that will corresponds to lower frequencies. Thus, wavelets have time widths that are adapted to their frequency which is the real reason behind the success and exclusive usefulness of the Morlet wavelets in signal processing and time-frequency signal analysis.

Measuring Hydrological Alteration In Wetland Through Water Richness Mapping

Three major hydrological indicators like water presence frequency (WPF), hydro-period (HP), and water depth (WD) were used for computing the water richness of the wetland. WPF refers to the frequency of water appearance in a wetland pixel over a selected period (Sarda and Das, 2018). This analysis is very essential in the seasonally inundated flood plain wetland since the wetland in this region is highly erratic in behavior (Talukdar and Pal, 2019). Before developing the layers, spectral water indices based on wetland delineation were performed for each year following the Normalized differences water index (NDWI). Amongst other water indices, NDWI was reported suitable in the Barind flood plain region by Das and pal (2016). NDWI map of each year was turned into a binary map with 0 to non-wetland and 1 to wetland pixel and finally combined. The percentage of frequency in each period was computed about the selected period. WPF of each phase was classified into high, moderate, and low WPF zones using Eq. (2). High WPF signifies consistent wetland appearance and is ecologically more viable (Pal and Sarda, 2020; Pal et al., 2020). Hydro-period refers to the duration of water stagnation within the wetland. This map was prepared by averaging monthly binary NDWI images of the selected period using Eq. (3). Ecologically a perennial wetland is much more feasible than a non-perennial wetland (Yue et al., 2020). The water depth of wetland is very difficult. Field-level data is scarce. Therefore, following Talukdar and Pal (2019), Debanshi and Pal (2020), and Pal and Sarda (2021) the present work also simulated water depth data from the NDWI map using 36 ground-level data. NDWI-based water depth mapping idea was based on Gao et al. (1996) who established NDWI value indicates the thickness of water. Linear regression between NDWI value and water depth data was conducted and the resultant regression coefficient was used for simulating the NDWI map to obtain water depth data. The computed regression coefficient is y = 0.475 + 14.05x

\(WP{F_j}=\frac{{\sum\limits_{{i=1}}^{n} {{I_j}} }}{n} \times 100\) ……………………………… (Eq. 2)

WPF _j= Water presence frequency of j^th pixels in a period; I_j= j^th pixel having water in the selected NDWI images; n = number of images. This value ranges from 0-100%.

\(HP=\sum\limits_{{i=1}}^{{n=12}} {{I_j}}\) ……………………………… (Eq. 3)

The value ranges from 0 to 12. Value 0 means non-wetland, 1 means only one month there is water stagnation, and 12 means water is available all through the year.

Wetland Water Richness (Wwr) Mapping And Validation

The above-mentioned hydrological components were integrated using both the non-weighted and weighted overlaying methods in the Arc-Gis environment. For weighting the parameters, the analytical hierarchy process (AHP) of Saaty (2004) was followed. AHP is a semi-quantitative approach for pair-wise comparison of parameters or subclasses of a parameter to estimate the weight of the concerned parameters or subclasses. The consistency check of this approach was 3% and therefore be accepted. The hydro-period was discovered to be the most important component (weight: 0.46). Eq. (4) was developed for weighted overlaying. The integrated WWR map was then divided into three classes: high, moderate, and low. Longer hydro-period, deeper wetland, consistent water appearance, defines high WWR class and vice-versa in the case of low WWR.

WCL= \(\sum\limits_{{j=1}}^{n} {{a_{ij}}{w_j}}\)…………………….. (Eq. 4)

Where, a_ij= i^th rank of j^th attribute; w_j= weighted of j^th attribute.

For validating the WWR models, 27 field validation sites from different WWR zones were taken and the employed parameters were observed directly from the field and taken from people’s experiences in this regard (Supplementary Table S3). Based on this, a composite score following the weighted compositing method was computed. The individual/max method was applied for data standardization. For weighting parameters, AHP weight as computed for spatial modeling was applied. AHP weight of the computed field parameters was 0.55 in the case of hydro-period, 0.29 in the case of water depth, and 0.17 in the case of WPF. The consistency check was 1%. A higher composite score signifies good water richness and vice versa. Pearson’s product-moment correlation coefficient was carried out between WWR and field-based WWR score. t-test was done for statistical significance.

Measuring Eco-hydrological Effects In River And Wetland

Ecological thresholding and degree of hydrological failure

Defining the hydrological failure rate and threshold Richter et al. (1998) proposed a range of dispersion metrics for measuring ecological flow status, including the twentieth and eightieth percentiles, one standard deviation (SD), and two standard deviations (SD), among others. Such approaches are commonly used for controlled river flow assessments, but they are rarely used for wetland assessments. Using calibrated water depth, RVA thresholds were set in the case of wetland, Based on the flow level of river water during the pre-dam period, the RVA threshold was determined in the case of the river. SD ± 1 method under RVA was applied to define lower and upper thresholds of ecologically viable water depth. If the depth value is less than Mean-SD1, the state is eco-hydrologically stressed, and if it is greater than Mean + SD1, the state is eco-hydrologically affluent. Depth value within Mean ± SD1 could be considered as a natural range of ecological (optimum) water depth. Based on the above-mentioned thresholds, the failure rate was computed. RVA thresholds of pre-dam periods of the selected seasons were computed and converted into a binary map. 0 was assigned to the pixels beyond the ecological threshold (< Mean + SD1 and > Mean-SD1) and 1 was assigned to the pixels with values within Mean ± SD1. This was done for each year and these were integrated and divided by total years considered in pre and post-dam phases separately. It could be expressed in decimal or percentage. The failure rate varies from 0–1 or from 0 to 100%. A value near 0 means the very least failure rate (ecologically viable) and a value near 100% indicates a high failure rate (ecologically stress).

Eco-deficit/surplus Estimation In Rivers And Mapping In Wetland

Time series data is commonly used for developing the flow duration curve (FDC). Discharge /water level data, water depth data, rainfall data, etc. are used for this. In this case, both discharge data of river and pixel scale water depth data of wetland were used. In FDC mean/median flow/depth was plotted against the exceedance probability. FDC was simply computed using Eq. (5).

\({\text{P=}}\left[ {\frac{{\text{M}}}{{{\text{n+1}}}}} \right]{\text{Χ 100}}\) …………………….. (Eq. 5)

Where, P = the probability that a given flow will be equaled or exceeded (% of the time), M = the ranked position on the time series discharge or depth data (dimensionless), n = the number of events for a period of record (dimensionless)

The flow duration curve (FDC) was used to calculate the eco-surplus and deficit (Vogel et al., 2007). First, median annual water flows duration curves for both unregulated (pre-dam) and regulated (post-dam) hydrological conditions were recorded. When the position of the regulated median FDC is below that of the uncontrolled median flow, the situation is called an eco-hydrological deficit, and the reverse condition can be treated as an eco-hydrological surplus (Talukdar and Pal, 2019). The same method was applied for measuring the eco-deficit/surplus of the wetland using water depth data. Considering the FDC of different hydrological phases, the eco-hydrological condition was studied. A spatial map of the same was done at pixel scale. This approach is common at river scale, however, rare at spatial scale.

Hydrological alteration and periodicity in river

The heat map of WL (Fig. 2A) shows a considerable decrease in water level after damming and it was recorded high during pre-monsoon months. In the same way, the degree of hydrological alteration was as high as > 30% during this season. Rest other seasons also recorded a negative degree of hydrological alteration with a rate of 5–35%. No significant difference was noticed between phases 1 and 2 during the post-dam period. During the pre-dam period, about the average WL, positive alteration maximum up to 18% was recorded. In the post-dam period (both in phases 1 and 2), some discrete years were identified where positive change was noticed and majorly these were during the monsoon season triggered by extreme monsoon rainfall (Fig. 2B).

In pre-monsoon, monsoon, and post-monsoon seasons, a significant power spectrum (at 5% level) was identified at a higher band (3.5 to 4) after 1992 (damming year). During monsoon season, another periodicity was noticed in the 3 to 3.5 power spectrum band (Fig. 3). In the winter season, another periodicity was observed from 2005 onward in a weaker power spectrum band. However, a major change occurred after damming (1992) in most of the seasons.

Ecological Alteration In River

In effect of hydrological alteration, flow within ecological thresholds defined based on RVA was found to decline in trend. As a consequence, the ecological flow failure rate was enhanced considerably. After damming, the flow failure rate ranged from 70 to 96% with varying seasonality (Supplementary Table S2). Modification of flow was continued even after a long time distance from damming year. There was no difference in ecological flow failure rate between phases 1 and 2 in the post-dam periods. The Uniform type of flow failure rate was also reported by Talukdar and Pal (2018), however, the phase-wise difference was not examined. Based on FDC of eco-deficit and surplus were examined for different seasons from pre-dam to post-dam phase 1 and pre-dam to post-dam phase 2. In all the seasons, unregulated FDC remained above regulated FDC and therefore eco-deficit condition was detected. It is true both in the case of pre-dam to post-dam phases 1 and 2. The degree of eco-deficit was found to proliferate between pre-dam to post-dam phase 2 during non-monsoon seasons (Fig. 4). It was found maximum in the pre-monsoon season. Monsoon season did not show any such difference between the two phases considered. It does signify that the time distance effect enhanced over time to some extent. In terms of feedback mechanisms, positive feedback continues.

Wetland Water Richness (Wwr) Mapping And Validation

For water richness mapping WPF, hydro-period and water depth parameters were taken and maps of each parameter were sub-classed. Over the phases, the area under high WPF (> 67%) was declined. For instance, the area under this sub-class during the pre-dam period was 93.53% of the total wetland area, it was decreased to 82.28% during post-dam phase 1 (gap: 11.25%) and to 69.74% during post-dam phase 2 (gap: 23.79%). In between phase post-dam phase 1 to 2, this area gap was 12.54 and it does signify that inconsistency in water appearance continued to rise after damming. A huge transformation in the hydro-period was noticed between pre and post-dam periods. In the pre-dam period, about 77.5% area was identified with a hydro-period greater than nine months, but it was declined to only 10.75% in post-dam phase 1 and 7.82% in phase 2. The same trend was also recorded in the case of water depth. The area under high depth was 48.96% during the pre-dam period and it declined to 40.03% in post-dam phase 1 and it was further decreased to 10.03% in post-dam phase 2 (Table 1). In post-dam phases, the rate of shallowing of wetland was found significantly high. A spatial view of the wetland transformation also exhibited that its rate was detected high in the wetland fringe area, In the case of hydro-period, even the core wetland tract was also transformed into a highly seasonal wetland (Fig. 5). From these results, it is very clear that damming effect was caused for hydrological deterioration, however, the time distance effect from damming was a mixed response in case of different parameters. So, to draw the inference, integration of all the hydrological parameters was done for considered three phases.

Table 1

Area under different subclasses of hydrological components over the phases
Phase	WPF (%)			Hydro-period (Month)			Depth (m)
Phase	Categories	Area in sq. km	Area in %	Categories	Area in sq. km	Area in %	Categories	Area in sq. km	Area in %
Pre-Dam	< 33	4.24	1.98	< 3	0.0009	0.0004	< 1.5	51.36	24
	33–67	9.61	4.49	3–9	48.36	22.5	1.5–5.64	58.26	27.22
	> 67	200.2	93.53	> 9	166.58	77.5	> 5.64	104.78	48.96
Post-dam Phase 1	< 33	1.8	2.04	< 3	18.04	20.71	< 1.5	22.82	25.86
	33–67	13.83	15.68	3–9	59.7	68.54	1.5–5.64	30.09	34.11
	> 67	72.59	82.28	> 9	9.36	10.75	> 5.64	34.88	40.03
Post-dam Phase 2	< 33	3.27	4.95	< 3	0.14	74.2	< 1.5	46.11	69.59
	33–67	16.77	25.31	3–9	2.12	17.98	1.5–5.64	13.67	20.63
	> 67	46.21	69.74	> 9	5.27	7.82	> 5.64	6.65	10.03

Figure 6 depicts the WWR maps of different phases built based on weighted and un-weighted overlaying methods. Visual comparison of WWR maps of different phases clarified that negligible fringe wetland parts (1.74%) during the pre-dam phase were under a low WWR zone but it was increased to 14.54% and the wider part was transformed into a high to moderate WWR zone. The core wetland part was turned into moderate WWR from phases 1 to 2 during the post-dam period (Fig. 6). WWR map of different phases clarified that after damming the area under high WWR continued to decrease. For instance, in the pre-dam period, its area under high WWR was 96.25% which declined to 58.17% and 11.81% in post-dam phases 1 and 2 respectively. From these statistics, it can be stated that over the progress of time in the post-dam phase, the rate of weakening of the hydrological state was increased (Table 2). The gap of the area under high WWR between pre-dam to post-dam phase 1 was 38.09% and it was inflated to 46.36% between post-dam phase 1 to post-dam phase 2. So, the time distance effect is not clear and a positive feedback mechanism is strongly noticed.

Since non-weighted or un-weighted and weighted overlaying provide a slightly dissimilar result, the validation of the WWR is required.

Field data-based WWR scores computed for 27 wetland sites varied from 0.24 to 1 (Supplementary Table S3). In most of the cases, it was found that high and low scores were found in the high and low WWR classes respectively in both the non-weighted and weighted WWR maps. However such adjacency was more in the case of the weighted map. The correlation coefficient computed between the WWR value from the constructed map and WWR scores computed based on field data of the respective sites were 0.79 and 0.9 in the case of non-weighted and weighted WWR maps respectively. Both the values are statistically significant at a 0.01 confidence level. Since the degree of association is quite greater in the case of weighted WWR, it was finally taken for further process of analysis.

Table 2

Area under different WWR zones
Types	Classes	Pre Dam		Post-dam Phase 1		Post-dam Phase 2
Types	Classes	Area in km²	Area in %	Area in km²	Area in %	Area in km²	Area in %
Weighted	Low	4.08	1.74	7.24	7.37	11.13	14.54
	Moderate	4.71	2	33.87	34.46	56.37	73.65
	High	226.3	96.26	57.17	58.17	9.04	11.81
Non-Weighted	Low	7.36	3.13	9.7	9.87	4.36	5.62
	Moderate	6.43	2.74	38.11	38.78	27.97	36.07
	High	221.3	94.13	50.47	51.35	45.21	58.3

Eco-hydrological Impacts

Ecological threshold and degree of eco-hydrological failure

Figure 8 depicts the area within ecological thresholds or beyond and also shows the depth failure rate. In the pre-dam period wetland was mostly within ecological thresholds or above the ecological threshold and therefore, was ecologically viable. In this period, wetland at the confluence segment of the main river and major tributaries was above the ecological threshold In post-dam phase 1, about 19% area above upper RVA was turned into within threshold zone. In post-dam phase 2, the same trend was further enhanced. Some wetland patches that remained above the ecological threshold limit (9.07% area) during phase 1 were turned into a weaker class in phase 2 (Fig. 8). In parity with this, the failure rate was computed and an increasing trend in failure rate was recorded. For instance, in the pre-dam phase, 72.11% was ecologically safe, in post-dam phase 1, this proportion was turned into 10.52% and zero in the next phase (Table 3). Contrarily, an area under high and moderate failure rate (> 33%) was about 14% in the pre-dam phase and it was increased to 43.53% in post-dam phase 1 and 100% in phase 2 (Fig. 7C). It signifies that the time distance effect is insignificant and positive feedback is very strong.

Table 3

Area under different ecological depth thresholds and failure rates
Parameter	Classes	Pre Dam		Phase I		Phase II		Phase II in reference to Phase-1
Parameter	Classes	Area in km²	Area in %	Area in km²	Area in %	Area in km²	Area in %	Area in km²	Area in %
RVA classes	Below Threshold	78.36	28.29	6.09	6.90	10.33	28.29	5.58	15.27
	Within Threshold	118.39	42.74	74.18	84.03	26.19	71.71	30.94	84.73
	Above Threshold	80.26	28.97	8.00	9.07	0	0	0	0
Failure rate (%)	Safe	124.73	72.11	9.28	10.52	0	0	4.72	13.14
	Low (< 33)	23.71	13.71	40.56	45.95	0	0	14.08	39.15
	Moderate (33–66)	21.42	12.38	35.33	40.03	0	0	12.14	33.76
	High (> 66)	3.11	1.80	3.09	3.50	36.52	100	5.02	13.96

Ecological Condition (Eco-deficit/surplus)

Unregulated and regulated FDC of water depth about pre-dam and post-dam phases clarified the continuity of eco-deficit. Expectedly when the same was plotted at pixel scale, an eco-deficit condition was obtained. For a better understanding of the degree of difference in eco-deficit, it was sub-classified into three zones low, moderate, and high zones (Fig. 9). Phase-wise analysis revealed that the degree of eco-deficit was slightly increased from post-dam phase 1 to 2. Figure 7D (Ternary diagram) shows a plot of areal proportion under different eco-deficit zones and found clustering nature signifying similar nature of change in post-dam phases 1 and 2. At the core area of the wetland, its degree was quite low than the fringe area. Highly eco-deficit-prone areas were abolished from the wetland map over the progress time. It is also very clear from the phase-wise wetland map.

Table 4

FDC curves of different phases for showing eco-deficit and surplus and pixel scale eco-deficit and surplus maps
Ecological condition	Classes	Phase I		Phase II		Phase II in reference to Phase-1
Ecological condition	Classes	Area in km²	Area in %	Area in km²	Area in %	Area in km²	Area in %
Eco-deficit classes	Low (< 33)	74.51	84.4	30.17	82.62	32.09	87.86
	Moderate (33–66)	12.32	13.96	5.69	15.58	2.89	7.91
	High (> 66)	1.45	1.64	0.66	1.8	1.54	4.22

Figure 10 displays the linkage among WWR, ecological threshold, and failure rate in pre and post-dam conditions. In the pre-dam phase, most of the sample sites were clustered in a zone where WWR was high, the ecological threshold was above the upper limit and the failure rate was very low to nil. However, the situation was reversed during post dam condition. Sample sites were very scattered and majorly located in the ecological stress zone. Since the ecological measures were based on hydrological parameters, hydrological alteration in rivers and wetlands had directly influenced the ecological condition.

The results revealed damming-induced hydrological alteration in the river and dependent riparian wetland. The impact of damming in such a way is well reported worldwide (Liro, 2019; Wu et al., 2019). In this region, since the dam construction curtailed the river flow significantly, which can be witnessed in the FDCs, the riparian wetlands faced a reduction in the water supply. There are several examples (van Oorschot et al., 2018; Wang et al., 2018; Burbano et al., 2020) where dam construction and regulation of water in the upstream paced negative footprint on the downstream region. Among the negative footprints, the riparian wetland is affected the most. Zheng et al., (2019) reported 44% reduction in wetland surface area due to a reduction in peak discharge, flood frequency, and flood magnitude. In the present region also, a similar trend can be seen; the very physical appearance of the wetland is reduced, which negatively affected WWR. With the reduction of flood height and magnitude, the river spilling became rare, making the dependent wetland die. This trend was not observed to be stabilizing or improving immediately after the dam construction. With the sudden changes in the river regime, the inevitable impact was observed on the downstream flow characteristics and riparian wetland ecosystem. Under this curtailed water supply and stressful conditions, the peripheral parts of the wetland suffered maximum, and the effect was most visible in those parts. Which eventually made those parts disappear or pushed from the higher category of WWR to the lower category. Over time the regulation the upstream of the river did not allow the improvement in the river regime. As a result, following the positive feedback mechanism, wetland hydrological conditions also deteriorated. Such incidents enhanced the man-environment conflict and enabled the anthropogenic footprint to expand towards the wetland bed, even in some cases in the core parts. This positive feedback of flow regulation resulted from hydrological alteration posed its impact on every factor that maintains the wetland's water richness and ecological health. These factors are WPF, water depth, and hydro-duration, which are considered critically vital for the hydrological health of the wetland in a floodplain environment (Pal and Debanshi, 2021). The higher WPF zone was squeezed with reduced flood frequency. Similarly, the curtailed water supply reduced the depth of wetland water that in turn exposing larger parts of the wetland bed out of the water and ultimately contributed to the squeezing of the WPF. The regulated peak discharge of the river also enhanced the effect of seasonality, insisting a greater period of dryness in the hydro-duration of the wetland. Once a year after year similar trend continued after dam construction, the higher WPF permanently became confined in the core parts only, moderate WWR became low, and most of the wetlands having lower WWR lost their entity. Under such a completely unfavorable environment for wetland sustenance, other ancillary causes like the reclamation of wetland beds, landscape fragmentation, and conversion to other land use like built-up areas or plantations made a permanent loss of wetland area. Another essential factor for the wetland sustenance in the floodplain region is the presence of active tie channels that bares spilled river water to the wetlands. With time these tie channels became abandoned and eventually breached or occupied with the lowering of peak discharge in the main feeding channel. This is a widespread phenomenon in this region and the adjacent floodplain (Paul and Pal, 2020). After the breaching of these tie channels, it became almost impossible for the river water to reach the wetland located farther from the main channel in some of the discrete years when water level achieved the spilling limit due to heavy rainfall. The time distance effect of the damming was noticed in the case studies also (Fig. 11). Various hydrological phenomena like water depth, hydro-period, inundation frequency, and magnitude decreased over time. In many cases, the degree of decrease was high to very high, and the rate of decrease was high. As a result of this time distance effect, the ancillary causes of wetland deterioration were also evident in the case study sites. The agricultural encroachment, overexploitation, construction activities, flow modification, etc., slightly or highly increased with a higher degree. From the phase-wise analysis of wetland change, especially its areal extent, hydrological phenomena, WWR, it became clear that the wetland kept deteriorating without significant improvement. The time distance impact of damming enhanced this deterioration year after year, and in many cases, the wetland beds have already been permanently converted to other land use. Under such circumstances, the restabilization of the hydrological regime in the river and the alongside wetlands was not very prominent within the considered period of the study.

The effect of damming and hydrological alteration harmed the physical state of the wetland and its biological environment. With the areal squeezing and qualitative deterioration of WWR, habitat health of the wetland continued to deteriorate. The ecological impact of dam construction on downstream biodiversity is a concerning issue nowadays (Wu et al., 2019). During the field investigation, the species abundance was observed in cases of aquatic vegetation. The eutrophicated state with high growth and occupancy of water hyacinth was noticed in the wetlands. Under such eutrophication, the habitat state of the wetland became poorer for fish cultivation and food production like leafy vegetation or shells. Apart from that, the hydrological alteration induced habitat loss causing the reduction of fish diversity in the wetlands. In many cases the non-cultivated indigenous fishes like Boyal (Wallago attu), Shol (Channa striata), Magur (Clarias batrachus), Shingi (Heteropneustes fossilis), Tangra (Batasio batasio), Koi (Anabas testudineus) become rare, or their growth and production became limited. In this way, with the ecological impact, damming induced hydrological alteration and its positive feedback effect, along with other ancillary causes, significantly reduced the ecosystem goods and services and affected local livelihood wellbeing. A similar trend was observed in the outer world also (Gwimbi and Rakuoane, 2019), where due to dam construction in the upper reach of the river, the local people the downstream reported reduction in the wetland ecological provisions that were essential for their livelihood. As a result of this hardship and poor awareness of the regulating services of the wetlands, for the local people, wetlands become lucrative for conversion in search of more significant economic gain that ultimately contributed externally to enhance positive feedback of the time distance impact of damming and hydrological alteration. The considerable role of poor awareness and curtailed materialistic service was noticed in the present study area. It was reported in the previous literature also (Debanshi and Pal, 2020), that fish cultivation was seen to be positively contributing to the local livelihood and wetland conservation.

The impact of hydrological modification of rivers due to damming on wetland water richness and ecological states of the river and wetland was well illustrated. Since the study aimed to explore the time distance effect on such changes in post-dam phases, the analysis was carried out in three phases and the impact was quantified for each phase. After damming river flow failure rate was recorded by 70 to 96% in different seasons and the rate of such alteration was continued in post-dam phase 2. As this consequence of hydrological alteration, eco-deficit was accounted quite higher in post-dam phase 2 than and phase 1. As the riparian wetlands are highly dependent on rainfall and river water for their sustenance, hydrological modification in the river brought significant change in the riparian flood plain wetland of this basin. Remarkable hydrological alteration in wetland water richness and ecological condition was also accounted for. Along with huge loss in the wetland area, existing wetland areas also experienced immense hydrological deterioration in both the phases of the post-dam period. A larger proportion of the area was turned into a low ecological threshold limit and higher water depth failure zone. The entire wetland area was transformed into the eco-deficit area in the post-dam phases. Its degree was slightly higher in phase 2. From this finding, it can be stated that time distance usually minimizes the impact of any incident, however, in the present case it has not happened so far, rather it was proliferated to some extent. This rate of proliferation was quite more in the river that was directly impacted due to damming.

To control the situation, flow restoration would be the sole alternative. The study output would be instrumental for the planning of riparian hydrological and ecological management. This lesson would be very useful for other regions, particularly where a new dam will be planned to be implemented. The study recommends applying this approach to establish the time distance effect in a similar case. Since the length of the post-dam period in this present case was only 30 years, more length could effectively be established this effect. More work on this could help to build a reliable theoretical understanding.

Ethical Approval

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Consent to Publish

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Authors Contributions

All authors contributed to the study's conception and design. Conceptualization; Methodology designing; Writing – review & editing were performed by Dr. Swades Pal. Data curation; Investigation; Software; Validation; and Writing - original draft were performed by Rajesh Sarda, Rumki Khatun and Sandipta Debanshi. All the authors read and approved the final manuscript.

Funding

No fund receive to conduct the research work.

Competing Interests

The authors declare that they have no competing interests

Availability of data and materials

The datasets used and/or analyzed during the research work are available from the corresponding author on reasonable request.

Acknowledgments

For this study, we would like to extend my gratitude to USGS for providing Landsat imageries. We are also thankful to Pankaj Singha and Tamal Kanti Saha for their assistance during the field survey and software handling.

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Time distance effect of damming on the degree of hydrological and ecological alteration in floodplain river and wetland

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Abstract

Figures

Introduction

Study Area

Materials

Methods

Measuring hydrological alteration and periodicity in river

Measuring Hydrological Alteration In Wetland Through Water Richness Mapping

Wetland Water Richness (Wwr) Mapping And Validation

Measuring Eco-hydrological Effects In River And Wetland

Ecological thresholding and degree of hydrological failure

Eco-deficit/surplus Estimation In Rivers And Mapping In Wetland

Result

Hydrological alteration and periodicity in river

Ecological Alteration In River

Wetland Water Richness (Wwr) Mapping And Validation

Eco-hydrological Impacts

Ecological threshold and degree of eco-hydrological failure

Ecological Condition (Eco-deficit/surplus)

Discussion

Conclusion

Declarations

Acknowledgments

References

Supplementary Files

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