Evidence map›Paper›PMID 39285219›Full record

ArticleScientific reports2024

Effectiveness of wetlands as reservoirs for integrated water resource management in the Ruzizi plain based on water evaluation and planning (WEAP) approach for a climate-resilient future in eastern D.R. Congo.

Géant B Chuma, Jean M Mondo, Joost Wellens, Jackson M Majaliwa, Anthony Egeru, Espoir M Bagula, Prince Baraka Lucungu, Charles Kahindo, Gustave N Mushagalusa, Katcho Karume and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Géant B ChumaFaculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu, South-Kivu, Democratic Republic of Congo. geant.ch@gmail.com.
Jean M MondoFaculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu, South-Kivu, Democratic Republic of Congo.
Joost WellensUR SPHERES, University of Liège, Liège, Belgium.
Jackson M MajaliwaRUFORUM, Makerere University, Kampala, Uganda.
Anthony EgeruRUFORUM, Makerere University, Kampala, Uganda.
Espoir M BagulaFaculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu, South-Kivu, Democratic Republic of Congo.
Prince Baraka LucunguDepartment of Natural Resources Management, Faculty of Agricultural Sciences and Environment, University of Kinshasa, Kinshasa, Democratic Republic of Congo.
Charles KahindoDoctoral School of Agroecology and Climate Sciences, Université Evangélique en Afrique (UEA), Bukavu, Democratic Republic of Congo.
Gustave N MushagalusaFaculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu, South-Kivu, Democratic Republic of Congo.
Katcho KarumeFaculty of Agriculture and Environmental Sciences, Université Evangélique en Afrique (UEA), Bukavu, South-Kivu, Democratic Republic of Congo.
Serge SchmitzUR SPHERES, University of Liège, Liège, Belgium.

Funding

Support for this research was made possible through a capacity building competitive grant Training the Next Generation of Scientists for Africa provided by Carnegie Cooperation of New York through the Regional University Forum for Capacity Building in Agriculture (RUFORUM) Grant number: RU/2024/Post-Doc/02
6 · The paper itself

Abstract

It is widely predicted that climate change's adverse effects will intensify in the future, and along with inadequate agricultural practices, settlement development, and other anthropic activities, could contribute to rapid wetland degradation and thus exert significant negative effects on local communities. This study sought to develop an approach based on the Integrated Water Resource Management (IWRM) in the Ruzizi Plain, eastern Democratic Republic of Congo (DRC), where adverse effects of the climate change are increasingly recurrent. Initially, we analyzed the trends of climate data for the last three decades (1990-2022). Subsequently, the Water Evaluation and Planning (WEAP) approach was employed on two contrasting watersheds to estimate current and future water demands in the region and how local wetlands could serve as reservoirs to meeting water demands. Results indicate that the Ruzizi Plain is facing escalating water challenges owing to climate change, rapid population growth, and evolving land-use patterns. These factors are expected to affect water quality and quantity, and thus, increase pressure on wetland ecosystems. The analysis of past data shows recurrence of dry years (SPI ≤  - 1.5), reduced daily low-intensity rainfall (Pmm < 10 mm), and a significant increase in extreme rainfall events (Pmm ≥ 25 mm). The WEAP outcomes revealed significant variations in future water availability, demand, and potential stressors across watersheds. Cropland and livestock are the main water consumers in rural wetlands, while households, cropland (at a lesser extent), and other urban uses exert significant water demands on wetlands located in urban environments. Of three test scenarios, the one presenting wetlands as water reservoirs seemed promising than those considered optimal (based on policies regulating water use) and rational (stationary inputs but with a decrease in daily allocation). These findings highlight the impact of climate change in the Ruzizi plain, emphasizing the urgency of implementing adaptive measures. This study advocates for the necessity of the IWRM approach to enhance water resilience, fostering sustainable development and wetland preservation under changing climate.

Indexed as

Climate-smart agriculture (CSA)IWRMRuzizi plainWater demandWatershedWEAP

Identifiers

PMID39285219
PMCPMC11405933

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.