Runoff and Sediment Yield Modeling Using Arc SWAT -A Case of Meki River Watershed

The objective of this study was to model the runoff and sediment yield to control soil erosion and sedimentation problems of the Meki River Watershed. The main materials and methodology were Arc GIS, Arc SWAT, Rainbow, excel stat, data collection, data preparation and quality assurance, data analysis and model setup, running model, model performance evaluation and model result interpretation. Simulation of the stream ow of Meki River watershed for the period from 1993 – 2010 and sediment yield was computed by developing sediment rating curve. The main results of stream ow calibration and validation are; coecient of determination (R²) = 0.81, Nash – Sutcliffe model eciency (NSE) = 0.76, percent bias (Pbias) = 18 and coecient of determination (R²) = 0.81, Nash – Sutcliffe model eciency (NSE) = 0.74, percent bias (Pbias) =17.1. As a result of the study, the total annual runoff and sediment yield were determined as 367.95mm and 75.896 ton/ha/yr. respectively.


Introduction
Runoff and sediment yield modeling is important in the watershed. Even though watershed has only one outlet point, it is characterized by different socio-economic activities, spatial, hydrological and climatic variability. Modeling the hydrological process such as runoff and sediment yield of the watershed is useful to manage the natural resources. In turn, this can be help for sustainable soil and water management, which are key resources of the community living in the watershed (Daniel et al., 2011). Soil erosion accelerated by human activity has a serious ecological impact that costs a nation due to on-site effects such as soil nutrient and economic loss and off-site effects due to reservoir sedimentation. Additionally, in the downstream, irrigation and water resources project may be damaged.
Furthermore, erosion also reduces the products of crops due to the soil fertility reduction (Upadhya et al., 2012) ood hazards, and this, has further problems of water availability, water quality, food security and food supply. Deforestation, overgrazing of the forest lands and expansion of the agricultural area are activities of the people perform in the watershed. The watershed is also faced high erosion by the effects of intense rainfall that contributes to the land cover change in the watershed. At farming land, erosion problem initiated by tillage practice in which the soil surface destructed, overgrazing, deforestation and poor land management practice; especially on slope land. Runoff and sediment yield can be estimated using different watershed models (Lelis and Calijuri, 2010). Several studies have reported using Soil Water Assessment Tool (SWAT) to predict surface runoff, soil erosion and sediment yield.
The model is calibrated and validated with good performance on the hydrological process (Jha and Gassman, 2014). Therefore, in this paper, SWAT was used to accomplish the general objectives of this study that was modeling of runoff and sediment yield of the Meki River watershed. Emphasis should now be given to either directly modeling the high level, or emergent, properties of watersheds, or producing models that can reproduce these high-level properties (Ogwo et al., 2012

SWAT Model Set Up
The

Flow Sensitivity Analysis
Initially twelve parameter were identi ed to select the most sensitive parameters during ow calibration. Monthly stream ow input data from 1993 to 2010 was used for ow sensitivity parameter identi cation.
From 100-iteration output, eight parameters were assigned as sensitive for further calibration process.
The highest ow sensitive parameters were the curve number (CN2), soil evaporation compensation factor (ESCO), available water capacity of the soil layer (SOL_AWC).

Sediment Rating Curve Development
The sediment rating curve is a relationship between the river discharge and sediment concentration. It is widely used to estimate the sediment load being transported by a river. Generally, a sediment rating curve may be plotted showing average sediment concentration or load as a function of discharge averaged over different periods. Since the sediment measurement in the watershed is less, a rating curve is developed to estimate sediment yield from ow measurement (Aga et al., 2018). The Sediment ow measurement in the Meki River was not in continuous time step; so that by using stream ow and measured sediment data can generate sediment rating curve.

Sediment Computation for the Model Performance Evaluation
From the Fig. of 7 and 8, the results show that model performance was very good (R 2 = 0.8743 > 0.8) and well agreement between sediment obtained from rating curve and simulated sediment obtained from SWAT. The total annual sediment yield from watershed in to the Lake Batu during Simulation period was estimated by using SWAT model was 75.896 ton/ha/yr. variable for analyzing the water balance of a watershed, but also the spatial patterns within the entire watershed was important. Study of ( Hurni 1988) con rmed that sub basins can be classi ed as none to slight (), slight (80-130), medium (130-220), high (220-612), and very high () mm for runoff.

Runoff Spatial Distribution
From SWAT simulation the runoff produced at the Meki River Watershed was 367.95 mm. As shown in Fig. 9, runoffs have no impact on sediment yield at some sub basin. For instance, in sub-basins (1-8), 10, 11,12,13,18, 20-26, 31 and 34 there was high runoff but less sediment yield. This was may be the response of LU/LC, soil resistance to erosion, slope and other management practice founded in the watershed. The sub-watersheds that produce moderate surface runoff were 9, 14, 19, 28, 32, 33 and 35. The sub-watersheds that produce slight surface runoff were 16, 17, 27 and 30 besides none to slight surface runoff were in 15 and 29. These simulation results show the relative variations of Runoff level within a sub-basin. Moreover, these results showed that Runoff to Meki River watershed was mainly from sub-basins of (1-8), 10, 11, 12, 13, 18, 20-26, 31 and 34. These sub-basin, which fall under high Runoff, was characterized by intensive cultivated land which leads to high Runoff susceptibility of the watershed.
The sediment yield distribution, for instance, sub-basins 9, 30 and 35 were high and characterized by maximum sediment yield distribution to Meki River watershed. The slight sediment yielding sub-basins were 12, 28, and 31. They deliver least sediment may be due to well-covered land use/cover. The erosion level was indicated as none to slight sediment in sub-basin 29. The sub-basins 9, 30 and 35, which fall under high erosion class, led to high sediment susceptibility of the watershed. The 25 years simulation result indicates that the simulated annual average suspended sediment yield and runoff of the Meki River watershed was 75.896 t/ha/yr. and 367.95mm respectively. The subwatersheds that produce moderate erosion level which were classi ed as moderate in sub-basin (1-8), 10, 11, (14-27) and (32-34) of Meki river watershed corresponds to moderate erosion level (22 -61 to/ha/yr.). The erosion level which were indicated as highest sediment yield in sub-basins 9, 30 and 35 were relative to remaining sub-basins and their erosion level (61 -109 t/yr.). The sub-watersheds that produce high surface runoff was (1-8), 10, 11,12,13,18, 20-26, 31 and 34. Following calibration and validation of SWAT model, also the model was applied to spatially distributed soil runoff and sedimentation processes at monthly time step. Generally, the SWAT model performed well in predicting both the ow and sediment yields from the study watershed and the results were acceptable.

Declarations
Ethical Approval: This article does not contain any studies with human participants or animals performed by any of the authors.   The Spatial Distribution of Annual Sediment Yield in Sub-Basins of Meki Watershed