Machine learning model based analysis of land use land cover change and assessing its potential impact on surface runoff in meki watershed, rift valley lakes basin, Ethiopia

<p>Land Use Land Cover (LULC) change is widely recognised as one of the most important factors impacting river basin hydrology.  It is therefore imperative that the hydrological impacts of various LULC changes are considered for effective flood management strategies and future infrastructure decisions within a catchment.  The Soil and Water assessment Tool (SWAT) has been used extensively to assess the hydrological impacts of LULC change.  Areas with assumed homogeneous hydrologic properties, based on their LULC, soil type and slope, make up the basic computational units of SWAT known as the Hydrologic Response Units (HRUs).  LULC changes in a catchment are typically modelled by SWAT through alterations to the input files that define the properties of these HRUs.  However, to our knowledge at least, the process of making such changes to the SWAT input files is often cumbersome and non-intuitive.  This affects the useability of SWAT as a decision support tool amongst a wider pool of applied users (e.g., engineering teams in environmental regulatory agencies and local authorities).  In this study, we seek to address this issue by developing a user-friendly toolkit that will: (1) allow the end user to specify, through a Graphical User Interface (GUI), various types of LULC changes at multiple locations within their study catchment, (2) run the SWAT+ model (the latest version of SWAT) with the specified LULC changes, and (3) enable interactive visualisation of the different SWAT+ output variables to quantify the hydrological impacts of these scenarios.  Importantly, our toolkit does not require the end user to have any operational knowledge of the SWAT+ model to use it as a decision support tool.  Our toolkit will be trialled at 15 catchments in Gwynedd county, Wales, which has experienced multiple occurrences of high flood events, and consequent economic damage, in the recent past.  We anticipate this toolkit to be a valuable addition to the decision-making processes of Gwynedd County Council for the planning and development of future flood alleviation schemes as well as other infrastructure projects.</p>

The assessment of the effects of land use land cover changes is crucial to know the hydrological status of the river basins. Various applications like remote sensing, geographic information system (GIS), and hydrological modeling approach are required to visualize and understand these effects on the watershed hydrological system. The research focuses on assessing the effects of land use land cover (LU/LC) changes and its impacts on the runoff in the Hiranyakeshi watershed using a semi-distributed hydrological model viz. soil and water assessment tool (SWAT). Therefore, this research was initially carried out by analyzing changes in LULC by classifying Landsat 7 and Landsat 8 satellite images for the year 2000 and 2015. The LULC classification is prepared with different classes such as forest, agriculture, fallow land, plantation, water bodies, and urban area. The accuracy assessment of the classified images was performed by error matrix; the values were found to be 65% (for two classified images); the kappa coefficient value found to be 0.51 and 0.56 for the year 2000 and 2015. The classification results obtained are within satisfactory limits; hence, the classified image is used to assess the changes in LULC over the period. Results show an increase in agricultural activities (11.45%), urban area (1.15%), water body (0.15%), and a decrease in barren land (11.46%) and forest (1.42%). To simulate the changes in the runoff, the classified LULC image for the year 2000 is used in the SWAT model during the calibration (from 1995 to 1999) and validation (from 2000 to 2005). The performance results of the model are evaluated with statistical indicators R2 and NSE, and the value 0.73 and 0.83 during the calibration and 0.70 and 0.84 during the validation period was achieved. Further, the model is simulated using classified LULC image of the year 2015 to assess changes in annual runoff; it is observed a decrease in annual runoff in the study area with respect to changes in LULC.

Quantification of Land Use Land Cover (LULC) change influence river basin on hydrology will enable local government and policy makers to formulate and implement effective and appropriate strategies to minimize the effect of future LULC change. In this research Soil and Water Assessment Tool (SWAT) with Sequential Uncertainty Fitting Intervals (SUFI-2) was used for analyzing the LULC changes on the Water balance of Katar and Meki River Basins, in the Rift Valley of Ethiopia. LULC map of 1996 and 2014 was used for the change analysis and the results revealed that the reduction of Forest and expansion of Agriculture and Built-up areas have an influence on the surface water spatial distribution and the water balance components. During the land use change periods, the increment of annual surface runoff from 67.54 mm to 129.14 mm has resulted from Katar river basin and 40.64 mm to 59.56 mm has resulted from Meki river basins. This result has revealed that the above land use changes are the main contributors to the increment of surface runoff on both river basins. With this regard, major changes from the Forested region on both river basins have resulted in runoff depth increment. Forexample, runoff depth increment of 4-53 mm to 10-65 mm on Katar river basin and 2-34 mm to 23-60 mm range from Meki river basin mainly from forested regions resulted. Therefore, LULC change is becoming a serious threat to Katar and Meki river basin, hence appropriate measures should have to be taken for the stabilization of the land cover change with the regional development plan. Furthermore, the outcome of this study serves for policymakers as a valuable information for the planning of best land management strategies and priorities for the region.

<p>The land use and land cover (LULC) change induces hydrologic variability in a catchment and studying this variability is central to efficient water management practice in a catchment. The assessment of the alteration in hydrological processes due to LULC change and its influence on overall river ecosystem functioning is even more pertinent to developing nations that face the issue of water scarcity and pollution. In this work, we investigate the influence of the LULC change over a period of ~40 years (1970-2013) on the variability of natural or virgin flow in the Ramganga river, a major tributary of the Ganga river, India. For LULC change data, object-based image classification was performed on high-resolution satellite imageries acquired for the Ramganga river basin – CORONA (1970) and LISS IV (2013) images. The natural or virgin flows (i.e., the flow in the river without regulation practices such as construction of dams or barrages) were estimated by performing hydrological modeling using the Soil and Water Assessment Tool (SWAT). Initially, the SWAT model was set up, calibrated, and validated for the present flow scenario (i.e. with all management practices present) using LULC data of the year 2013. Natural flows were derived by removing all interventions and keeping agricultural practices only rain-fed. Next, keeping all parameters unchanged, the LULC data of the year 2013 was replaced by the LULC data of the year 1970. This enabled us to study the effects of LULC change on river hydrology between the period 1970-2013. The model showed good agreement between the observed and simulated flows with R<sup>2</sup> values of 0.82 for the calibration period (2002-2014) and 0.68 for the validation period (1990-1999). The Nash-Sutcliffe efficiency values were 0.81 and 0.66 for calibration and validation periods respectively. The comparison of LULC data between the study period (1970 and 2013) reveals that land cover classes of agriculture, built-up, mixed forest, barren land, shrubs and bushes, and water areas were altered by nearly 6%, 102%, -7%, -59%, -75%, and -2% respectively (‘-’ sign indicates decrement in the land cover area). The influence of this LULC change was evident in the results from the hydrological model. For the years 2002-2013 (calibration period), the natural flows estimated using the LULC map of 2013 at the basin outlet were observed to be higher by 3-12% compared to flows estimated using the LULC input of 1970. The estimates of mean monthly flows for the years 2002-2013 at the basin outlet reveal that while the natural flows estimated using the LULC map of 2013 were higher compared to flow estimates using the LULC map of 1970 for most of the months, the flows during the dry months (May-July) were observed to be lower for the former compared to the latter. Our work provides valuable insights into hydrological variability in a major sub-basin of the Ganga river induced due to LULC changes and we advocate that alterations associated with LULC must be incorporated into water management strategies.</p>

Climate and land use land cover (LULC) changes play a vital role in the hydrology of any river basin. This study was aimed to investigate the impact of climate and LULC changes on streamflow in the Kunhar river basin, Pakistan. The Soil and Water Assessment Tool (SWAT), calibrated on a monthly basis, was used as a hydrological model to study the impact of climate and LULC changes on the streamflow. The change in average annual runoff due to LULC was increased but not significant; on the other hand, the flow was decreased by 24 m3/s (20%) as compared to the baseline (122 m3/s), due to climate change. On the seasonal and monthly scale, a difference emerged between high and low flows; high flows were increasing and low flows were decreasing in the wet and dry seasons, respectively, due to LULC changes. However, due to climate change, the seasonal and monthly runoffs were decreased significantly. Problems such as depletion in surface water and environmental flow during the dry season were more prominent due to the changes in the streamflow. These problems can be mitigated by afforestation in the bare lands and grasslands and taking structural measures to conserve the water in the high flow season for later use.

The expansion of cultivated land in place of natural vegetation has a substantial influence on hydrologic characteristics of a watershed. However, due to basin characteristics and the nature and intensity of landscape modification, the response varies across basins. This study aims to evaluate the performance of a soil and water assessment tool (SWAT) model and its applicability in assessing the effects of land use land cover (LULC) changes on the hydrological processes of the upper Genale River basin. The results of satellite change detection over the past 30 years (between 1986 and 2016) revealed that the landscape of the basin has changed considerably. They showed that settlement, cultivated, and bare land areas had increased from 0.16% to 0.28%, 24.4% to 47.1%, and 0.16% to 0.62%, respectively. On the contrary, land cover units such as forest, shrubland, and grassland reduced from 29.6% to 13.5%, 23.9% to 19.5%, and 21.8% to 18.9%, respectively. Based on monthly measured flow data, the model was calibrated and validated in SWAT-CUP using the sequential uncertainty fitting (SUFI-2) algorithm. The result showed that the model performed well with coefficient of determination (R2) ≥ 0.74, Nash–Sutcliffe efficiency (NSE) ≥ 0.72, and percent bias (PBIAS) between −5% and 5% for the calibration and validation periods. The hydrological responses of LULC change for the 1986, 2001, and 2016 models showed that the average annual runoff increased by 13.7% and 7.9% and groundwater flow decreased by 2.85% and 2.1% between 1986 and 2001 and 2001 and 2016, respectively. Similarly, the total water yields increased from 324.42 mm to 339.63 mm and from 339.63 mm to 347.32 mm between 1986 and 2001 and 2001 and 2016, respectively. The change in hydrological processes, mainly the rise in runoff and total water yield as well as the reduction in lateral and groundwater flow in the watershed, resulted from LULC changes. This change has broader implications for the planning and management of the land use and water resource development.


 
 
 Floods are one of the most common natural disasters worldwide. Apart from rainfall, Land Use Land Cover (LULC) changes too are a main contributory factor for floods. This study attempted to understand the link between floods and LULC changes in Kalu river basin, which is the second largest river basin and an area that experiences recurrent floods in Sri Lanka. We studied peak water levels, number of flood events, changes in land use types and impacts in rapidly urbanizing two districts, Rathnapura (upper basin) and Kalutara (lower basin) during 2001-2020. The satellite images (LANDSAT) were obtained for 2001, 2009, 2015 and 2020 and land use classification was done using ArcGIS and Remote Sensing Tools. Main land use types and their transformations were investigated and ground-truthing was carried out. Accordingly, the main types of land uses identified were Natural Vegetation and forests (NV), Settlements (ST- housing and industrial lands), Cultivated Lands (CL), Water Bodies (WB) and Bare Lands (BL). The results indicated that the most drastic change was found in the natural areas (NV) and they have diminished while the lands with anthropogenic impacts (ST, CL and BL) have increased across years. The NV had occupied the highest land area in 2001 (42.4%) and has reduced by 14.2% by 2020. The ST and CL have increased by 8.6 % and 5.2% respectively. The monthly rainfall of Rathnapura and Kalutara (Source: Department of Meteorology, Sri Lanka) has increased with time, which is a main reason for the increasing peak water levels of these areas (Source: Department of Irrigation, Sri Lanka). However, a significant correlation also exists between the change of the settlement area with the peak river water levels in the lower basin (p=0.03, R2=99%; regression analysis). Rathnapura has experienced 3 major floods (floods above the high water alert level) from 2001-2020, while 16 major floods have occurred in Kalutara. During the major flood in 2017, the number of child deaths in Rathnapura was 14 while in Kalutara it was 24. Accordingly, the LULC changes of the whole basin along with rainfall seem to influence on the severity of floods in Kalutara more, as it is located in the lowest elevation level. When natural lands are transformed to anthropogenic- impacted areas with disturbances to the water cycle, increased impervious surfaces, reduced water storage capacities and loss of natural drainage, the flood risk tends to increase. Proactive approaches including proper land use planning and rainwater storage are urgently needed as the climate change too would trigger more floods. Thus, the flood mitigatory actions, especially, in the lower river basin should be a priority to ensure resilience and sustainability.
 Keywords: Kalu river basin, Land Use Land Cover (LULC) changes, Floods
 
 

This study evaluates the implications of multiple climatic and non-climatic factors on the water resource of the Lake Tana sub-basin, Ethiopia. The study focuses on three drivers: land use change, irrigation expansion, and climate change (CC), and their impact on the current and future water availability across the sub-basin. The study uses a random forest (RF) machine learning classifier in the Google Earth Engine (GEE) platform to detect land use land cover change (LULC) and for mapping the actual irrigated-area. The Climate Hazards Group InfraRed Precipitation and temperature data were used with station data to evaluate the implication of CC on the water availability of Lake Tana sub-basin. The supply-demand relationship was done for Gumara catchment within Tana sub-basin as an experimental site. Based on the LULC analysis, plantation, cropland, bare lands, built-up, and wetland showed an increasing trend, while forest, bush land, and grassland showed a decreasing trend. The increasing rate of crop land in the expense of natural forest, shrub land, grassland may cause runoff/flood, high soil erosion, and lower rate of groundwater recharge. The actual irrigated area mapping analysis shows a widespread irrigation near the Lake Shore and upstream parts of the sub-basin. The climate change analysis shows an increasing trend of potential evapotranspiration during the irrigation period attributed to increase in maximum temperature. The rising of potential evapotranspiration during the irrigation period creates a water shortage in the study and future periods as the crops need more water for growth. The estimated stream flow for Gumara catchment shows an increasing trend for the future period. The supply-demand relationship of the catchment shows an uneven distribution of water in the Gumara catchment both in the current and future periods resulting in unbalance abstraction of irrigation water. The study reveals that climate change, land cover change, and uncontrolled expansion of irrigated land area are likely to increase the unmet demand by increasing irrigation water demand, and this can cause conflict of interest between the users. Therefore, sustainable water resource management practices such as land management practices, and adaptive management of irrigation should be applicable to prevent or reduce the occurrence of conflict over the water demand.

In the recent decade, the change in land use and land cover have changed the ecosystem services more rapidly than the previous similar periods. Land use land cover (LULC) change is the major factor that affect the watershed response. The main objective of this study was to assess the impact of land use and land cover change on the response of the Borkena watershed. The LULC change analysis was evaluated using supervised classification in ENVI software. The SWAT model was used to assess the impact of LULC change on streamflow for the period from 1996 to 2016. The study result revealed that the Borkena watershed experienced significant LULC changes from 1986 to 2016. Most of the grass land, cultivated land, and shrub land were changed to build-up and bare Land. The LULC map showed an increase of buildup area and bare land by 3.6% and 5.9%, respectively. There was a good agreement between simulated flow and observed data with a coefficient of determination (R2) and Nash-Sutcliff Efficiency (NSE) values of 0.81 and 0.79 in calibration, and 0.75 and 0.74 in validation periods, respectively. The evaluation of the SWAT hydrologic response due to the change in LULC showed that monthly streamflow was increased by 5.4 m3/s in the wet season and decreased by 0.5 m3/s in the dry season, and there was a significant effect (p < 0.05) of LULC change on watershed response. The changes in land use have resulted in changes in streamflow, due to the expansion of urbanization and land degradation.KeywordsLand use land coverStreamFlowSWAT modelAwash basinEthiopia

Understanding trends of land use land cover (LULC) changes is important for biodiversity monitoring and conservation planning, and identifying the areas affected by change and designing sustainable solutions to reduce the changes. The study aims to evaluate and quantify the historical changes in land use and land cover in Mukumbura (Ward 2), Mt Darwin, Zimbabwe, from 2002 to 2022. The objective of the study was to analyse the LULC changes in Ward 2 (Mukumbura), Mt Darwin, Northern Zimbabwe, for a period of 20 years using geospatial techniques. Landsat satellite images were processed using Google Earth Engine (GEE) and the supervised classification with maximum likelihood algorithm was employed to generate LULC maps between 2002 and 2022 with a five (5) year interval, investigating the following variables, forest cover, barren land, water cover and the fields. Findings revealed a substantial reduction in forest cover by 38.8%, water bodies (wetlands, ponds, and rivers) declined by 55.6%, whilst fields (crop/agricultural fields) increased by 93.3% and the barren land cover increased by 26.3% from 2002 to 2022. These findings point to substantial changes in LULC over the observed years. LULC changes have resulted in habitat fragmentation, reduced biodiversity, and the disruption of ecosystem functions. The study concludes that if these deforestation trends, cultivation, and settlement land expansion continue, the ward will have limited indigenous fruit trees. Therefore, the causes for LULC changes must be controlled, sustainable forest resources use practiced, hence the need to domesticate the indigenous fruit trees in arborloo toilets.

The effects of land use land cover (LULC) changes on sediment yield (SY) are crucial for downstream river ecology. Understanding LULC change rates and impacts on SY in watersheds is essential for water management. This study assessed LULC dynamics and their influence on SY in the Upper Bilate Watershed (UBW), Ethiopia. Using supervised classification for Landsat images from 1992, 2002, 2012, and 2022, we estimated LULC changes. The Soil and Water Assessment Tool (SWAT) and partial least squares regression (PLSR) simulated LULC effects on sediment generation. Results indicated a 56% impact on the study area from 1992 to 2022. Agriculture and settlements increased by 384.8 and 76.6 km2, while wetlands and grasslands decreased by 212.7 and 107.7 km2. Major conversions were from forestland and wetlands to agriculture. SY effects were most pronounced at the watershed outlet and varied significantly within sub-watersheds. Four sub-watersheds were the highest contributors to SY in the 2022 LULC classification scenario. Increased agriculture and settlements, coupled with reduced wetlands, forests, and grasslands, were key SY influencers. The PLSR model highlighted agriculture, wetlands, and forests as dominant LULC classes affecting SY. These findings underscore the need for LULC-based watershed management to prevent wetland degradation and sediment accumulation in Lake Abaya.

Study region: Densu River Basin (DRB) in Ghana. Study focus: Urbanization, agricultural expansion, and population growth are transforming land use across West Africa, impacting hydrological regimes and ecosystem resilience. This study assesses land use and land cover (LULC) changes in Ghana’s Densu River Basin (DRB) using the Soil and Water Assessment Tool (SWAT). The model, calibrated (2012–2019) and validated (1990–2011) with streamflow data, showed strong performance (NSE = 0.79; R² = 0.85). Three LULC scenarios – agriculture-, forest-, and urban-dominated – were simulated using satellite imagery from 1990 to 2019. The 2018 Landsat baseline map, validated with 91.5% accuracy, showed the urban scenario increased surface runoff (>50% of water yield) and sediment load (>83,000 metric tons/year), while the forest scenario enhanced percolation and groundwater recharge. Sedimentation in the Weija Reservoir, a key water source for Greater Accra, deposits ∼47,500 m³ annually, posing long-term risks to reservoir capacity and water security. These findings highlight tropical catchment's vulnerability to land use changes and support scenario-based hydrological modelling for river basin planning in rapidly urbanizing, data-scarce sub-Saharan Africa.

Planning for water resources management requires an understanding of how a watershed's hydrology responds to changes in land use and land cover (LULC). This study assesses the effects of LULC changes on the hydrological processes and analysis of wetland change in the Yewula watershed, located in the East Gojjam Zone, Ethiopia. Landsat images from 1994 and 2023 were used to classify LULC through supervised classification. LULC changes were assessed hydrologically using the Soil and Water Assessment Tool (SWAT). Key input data included land use/land cover (LULC), digital elevation model (DEM), soil, and meteorological datasets. Results revealed substantial reductions in wetland (−55.96%), forest (−44.17%), shrubland (−31.76%), and woodland (−31.44%) cover, while cropland (+15.5%), barren land (+19.34%), and settlement areas (+19.15%) expanded over the same period. The LULC changes, which occurred during the period of 1994–2023, had increased the average surface runoff (17.5%) and water yield (15.05%). Conversely, the observed changes had reduced lateral flow (28.14%), groundwater flow (28.95%), and evapotranspiration (ET) (22.15%). Understanding how LULC changes affect hydrology and analyzing the wetland change is essential for managing water resources and LULC together. Water resource development planning must consider LULC changes to achieve sustainable development in the catchment.

Land use/cover change (LUCC) affects canopy interception, soil infiltration, land-surface evapotranspiration (ET), and other hydrological parameters during rainfall, which in turn affects the hydrological regimes and runoff mechanisms of river basins. Physically based distributed (or semi-distributed) models play an important role in interpreting and predicting the effects of LUCC on the hydrological processes of river basins. However, conventional distributed (or semi-distributed) models, such as the soil and water assessment tool (SWAT), generally assume that no LUCC takes place during the simulation period to simplify the computation process. When applying the SWAT, the subject river basin is subdivided into multiple hydrologic response units (HRUs) based on the land use/cover type, soil type, and surface slope. The land use/cover type is assumed to remain constant throughout the simulation period, which limits the ability to interpret and predict the effects of LUCC on hydrological processes in the subject river basin. To overcome this limitation, a modified SWAT (LU-SWAT) was developed that incorporates annual land use/cover data to simulate LUCC effects on hydrological processes under different climatic conditions. To validate this approach, this modified model and two other models (one model based on the 2000 land use map, called SWAT 1; one model based on the 2009 land use map, called SWAT 2) were applied to the middle reaches of the Heihe River in northwest China; this region is most affected by human activity. Study results indicated that from 1990 to 2009, farmland, forest, and urban areas all showed increasing trends, while grassland and bare land areas showed decreasing trends. Primary land use changes in the study area were from grassland to farmland and from bare land to forest. During this same period, surface runoff, groundwater runoff, and total water yield showed decreasing trends, while lateral flow and ET volume showed increasing trends under dry, wet, and normal conditions. Changes in the various hydrological parameters were most evident under dry and normal climatic conditions. Based on the existing research of the middle reaches of the Heihe River, and a comparison of the other two models from this study, the modified LU-SWAT developed in this study outperformed the conventional SWAT when predicting the effects of LUCC on the hydrological processes of river basins.

It is important to understand how changing climate and Land Use Land Cover (LULC) will impact future spatio-temporal water availability across the Munneru river basin as it aids in effective water management and adaptation strategies. The Munneru river basin is one of the important sub-basins of the Krishna River in India. In this paper, the combined impact of LULC and Climate Change (CC) on Munneru water resources using the Soil and Water Assessment Tool (SWAT) is presented. The SWAT model is calibrated and validated for the period 1983–2017 in SWAT-CUP using the SUFI2 algorithm. The correlation coefficient between observed and simulated streamflow is calculated to be 0.92. The top five ranked Regional Climate Models (RCMs) are ensembled at each grid using the Reliable Ensemble Averaging (REA) approach. Predicted LULC maps for the years 2030, 2050 and 2080 using the CA-Markov model revealed increases in built-up and kharif crop areas and decreases in barren lands. The average monthly streamflows are simulated for the baseline period (1983–2005) and for three future periods, namely the near future (2021–2039), mid future (2040–2069) and far future (2070–2099) under Representation Concentration Pathway (RCP) 4.5 and 8.5 climate change scenarios. Streamflows increase in three future periods when only CC and the combined effect of CC and LULC are considered under RCP 4.5 and RCP 8.5 scenarios. When compared to the CC impact in the RCP 4.5 scenario, the percentage increase in average monthly mean streamflow (July–November) with the combined impact of CC and LULC is 33.9% (near future), 35.8% (mid future), and 45.3% (far future). Similarly, RCP 8.5 increases streamflow by 33.8% (near future), 36.5% (mid future), and 38.8% (far future) when compared to the combined impact of CC and LULC with only CC. When the combined impact of CC and LULC is considered, water balance components such as surface runoff and evapotranspiration increase while aquifer recharge decreases in both scenarios over the three future periods. The findings of this study can be used to plan and develop integrated water management strategies for the basin with projected LULC under climate change scenarios. This methodology can be applied to other basins in similar physiographic regions.